A Police Guide to Surveying Citizens and Their Environment.


MENU TITLE: A Police Guide to Surveying Citizens
and Their Environment
Series: BJA 
Published: October 1993
108 pages
227,045 bytes

Bureau of Justice Assistance

A Police Guide to Surveying Citizens and Their
Environment Monograph

Acknowledgments 

The Bureau of Justice Assistance wishes to thank
the Police Executive Research Forum (PERF) for its
help and guidance in compiling this document, in
particular Nancy G. LaVigne and John E. Eck.

Table of Contents

EXECUTIVE SUMMARY

INTRODUCTION     

PART I: SURVEYING CITIZENS: A GUIDE FOR POLICE   

OF WHAT VALUE ARE SURVEYS?    
 The Uses of Surveys    
 Types of Questions To Be Addressed    
 Attitudes and Opinions    
 Behavior and Experience    
 Characteristics    
WHO WILL BE SURVEYED?   
 Simple Random Sampling  
 Nonrandom Sampling   
HOW MANY WILL BE SAMPLED?    
HOW WILL THE RESPONDENTS BE CONTACTED?    
 Mail Surveys   
 Telephone Surveys    
 Inperson Interviews  
 Summary   
WHAT QUESTIONS WILL BE ASKED?   
 General Considerations  
 How To Ask Questions  
 Open-Ended Questions  
 Designing the Questionnaire  
HOW TO MAKE SENSE OF THE DATA   
 Characteristics of the Sample  
 Representativeness of the Sample  
 Making Inferences About the Population  
 Estimating Relationships  
 Significance Testing  
CONCLUSIONS   

PART II: ENVIRONMENTAL SURVEYS FOR PROBLEM SOLVING:
A PRACTICAL GUIDE    

ENVIRONMENTAL SURVEYS AND PROBLEM SOLVING    
THE OFFENDER AND RATIONAL DECISIONMAKING 
 Defensible Space 
 Neighborhood Maintenance and Safety   
 Physical Defense and Target Hardening
ENVIRONMENTAL SURVEYS IN PRACTICE 
 Large-Scale Analysis 
 Assessing Situational Factors of Crime and        
  Disorder  
DEVELOPING AND USING A SURVEY INSTRUMENT   
 Designing an Approach  
 Defining the Area  
 Reliability and Validity  
 Survey Design 
 Layout of the Survey Instrument  
 Numbering Questions  
 Sampling and Pretesting Survey  
DRAWING ON OTHER DATA SOURCES   
 Police Calls for Service   
 Surveys of the Public  
 Official Land Use Data 
CONCLUSIONS   

GLOSSARY   

SOURCES FOR FURTHER INFORMATION   

BIBLIOGRAPHY   
FURTHER READING   

APPENDIX A: EXAMPLE OF A HOUSING COMPLEX           
 ENVIRONMENTAL SURVEY   

APPENDIX B: EXAMPLE OF A BLOCK ENVIRONMENTAL 
 PROBLEM IDENTIFICATION SURVEY    

APPENDIX C: EXAMPLE OF A DRUG "HOT SPOT" SURVEY   

APPENDIX D: EXAMPLE OF A SITUATIONAL ENVIRONMENTAL 
 SURVEY USED FOR ANALYZING CONVENIENCE STORE       
 PROBLEMS   

Executive Summary

"How are we doing?" How the public answers this
question can determine police strategies and,
ultimately, their success or failure. When a police 
department surveys public opinion it may well seek
to measure much more than citizen perceptions of
where police stand in public sentiment. Research
teaches that many popular yardsticks of police
performance-speedy response to calls for service,
for example-may tell little about law enforcement's
true effectiveness in reducing crime and the fear
of crime. Police survey teams may be probing deeper
questions: How do citizens feel about open-air drug
markets? Did that last crackdown make people feel
safer? How do the elderly feel about our efforts?
What do minority groups think? school children?
single female heads of households?

Some evidence suggests that door-to-door surveys by
police officers are enough by themselves to reduce
crime and fear and enhance citizen attitudes toward
police, independent of any information they gain or
what police do with it.

Surveys can also help measure the characteristics
of neighborhood residents, the background of crime
victims, or the background of offenders. They can
supplement and help interpret other, more readily
obtainable information such as census data, arrest
reports, or complaints of crime.

Selecting a Sample

Those conducting a survey must first determine from
what total group of individuals-called the
"population"-they want to obtain data. If it were
necessary to interview every member of this group,
surveys would be so expensive that few would ever
be conducted. Instead, one selects a group of
individuals from within the population that seems
statistically likely to reflect the views of the
whole. This is called a "sample."

For many reasons, the most popular manner of
selecting a representative sample is random
selection. It is mathematically simple to calculate
the (usually small) odds that a random sample is
not representative, and it is easy to "stratify" or
"weight" a random sample to ensure that it fairly
reflects the population on such matters as racial
or economic makeup.

Accident, coincidence, or a search for a particular
type of respondent will yield a sample that is less
likely to be unbiased. The next question is harder:
How large must the sample be? There's no simple
answer. The greater assurance of accuracy the
surveyor requires (the technical term is "level of
confidence"), the larger the sample must be-and
thus the more expensive the survey.  But unless the
population is itself very small, the size of the
population means little in terms of the size of the
sample. If the population is so small as to require
a larger sample, then one might as well interview
the total population.

How To Question Respondents

Generally one can question members of the chosen
sample in one of three ways: by sending a
questionnaire in the mail or questioning by
telephone or in person. Mail surveys tend to have a
lower response rate. Great skill is required to
avoid ambiguous questions, and great expense is
needed to make the survey instrument so impressive
looking that it's less likely to be thrown out with
the junk mail.

Telephone surveys have a much higher response rate,
but automatically exclude citizens without
telephones. Like inperson surveys, they require
questioners trained to administer them.
Face-to-face surveys, in person, are most
expensive, but usually most accurate.

Designing the questions to ask respondents requires
precision in wording, clarity of thought, and care
not to wear out the respondent's patience by taking
too much of his or her time. The reader is given
examples of good and bad questions and ways to
improve them, together with instructions on how to
code the questionnaire in advance for easy data
entry and how to test it in advance so as to
improve its clarity and ease of interpretation.

Making Sense of the Results

When all the results are in, some simple data
analysis is in order; as the survey technician
gains skill, he or she will learn of other works
that teach more advanced techniques. The "central
tendency" or typical response to a question can be
determined, the range of answers from one extreme
to the other, and even some good ideas of how well
one succeeded in drawing a representative sample.
All these together enable the analyst to make
inferences about the population as a whole.

Construction of numerical tables is one of the
simplest basic ways of drawing such inferences. The
reader also learns some simple ways of testing the
results for statistical significance.

How Surroundings Affect Behavior

Just as opinion surveys may themselves help deter
crime and quiet fears of crime, environmental
surveys help police quantify the physical
characteristics of neighborhoods and link them with
specific neighborhood problems. These surveys help
identify problems, determine what changes will help
solve them, and measure the effectiveness of those
efforts, once taken. 

Criminals may not be fully rational, but they can
read the environment well enough to reach the
conclusion that a crime target is likely to be a
successful or unsuccessful one. A drug dealer
recognizes a litter-strewn street with many
abandoned houses and cars as a likely place in
which to hide his wares and himself from police and
from his business rivals. If police or others clean
up that neighborhood and populate it more hours of
the day with working residents, the drug dealer's
haven disappears. 

A burglar, similarly, avoids crime targets that
have many physical barriers because those barriers
would increase the time required to escape. Other
types of barriers, however, might work to the
thief's advantage, making it harder for police or
law-abiding citizens to interrupt him in the midst
of his crime.

Tipping the Balance to the Good Guys

Through an environmental survey, police can
determine what environmental cues work for or
against the law-abiding resident. Then they try to
shift the balance in the good guys' favor.
One useful form of crime analysis is identifying
"hot spots"-locations with unusually high levels of
chronic crime and disorder. By using a survey to
zero in on physical features of such locations,
police can make suggestions to businesses,
residents, and government about physical changes
that can reduce or prevent problems.

Such a survey might begin by defining the area to
be surveyed. The survey instrument developed would
provide structured terms for recording and
validating the amount of lighting, the density of
population, and the behavior of residents at
various times of the day. In addition to data
developed by the survey, other sources of
information can help round out the picture of
environmental assets and problems.

Used both before and after implementing a
problem-solving effort, opinion surveys and
environmental surveys can enable police not only to
evaluate the effort just past but also to improve
on it when the effort moves on to new challenges
elsewhere.

A glossary and bibliography are provided as well as
examples of survey instruments used successfully in
several cities.

The Uses of Surveys

Part I: 

Surveying Citizens: A Guide for Police

Of What Value Are Surveys? 

Surveys can be used for a variety of purposes. For
example, they are useful in gathering data on how
police are perceived by the public and in helping
to determine police priorities. Regular surveys of
the general public are quite useful for the latter
purpose. The Reno (Nevada) Police Department
conducts such surveys every 6 months. The Madison
(Wisconsin) Police Department regularly surveys
individuals who have had contact with the police to
determine the quality of police-public encounters. 

Surveys can also be used to identify specific
problems in target neighborhoods or among special
populations. In Newport News, Virginia, a survey of
residents in an apartment complex revealed concerns
about the maintenance and physical structure of the
complex. In Maryland, Baltimore County police
officials routinely use surveys to diagnose
community problems confronted by special
problem-solving units. In other cities, community
surveys have been used to help define community
concerns about drug problems. Special populations--
the elderly, school children, women, minority
groups, and others--can also be surveyed to learn
their special concerns. Finally, multiple surveys
can be used to evaluate problem-solving efforts.
For example, before-and-after surveys can be used
to determine changes in citizens' fear of crime as
a result of a police intervention. Problem-solving
units of the Baltimore County Police Department
routinely use this technique to gauge their
effectiveness.

There is some evidence that door-to-door surveys by
uniformed police officers may reduce crime and fear
of crime, as well as enhance attitudes toward the
police, independent of any information collected by
the officers for the purpose of collecting that
information (Pate et al., 1986; Pate, 1989; Uchida,
Forst, and Annan, 1990). If true, then this may be
one of those "good news/bad news" situations. The
good news would be that surveys themselves could be
used as a tactic in the control of crime and fear;
although this is a resource-intensive tactic, it
requires neither coercion nor the use of force. The
bad news is that uniformed officers cannot conduct
before-and-after surveys and expect to obtain
genuinely unbiased answers to their problem-solving
questions. Most citizens are unlikely to criticize
police officers to their faces.  Civilian
interviewers are needed to make sure that effects
of the data collection are not interfering with the
effects of the problem-solving program.

In summary, surveys can be used to achieve four
goals:

o Gather information on the public's attitudes
toward police and neighborhood priorities.
o Detect and analyze problems in neighborhoods or
among special population groups.
o Evaluate problem-solving efforts and other
programs.
o Control crime and reduce fear of crime.

Except for the first goal cited, several
alternatives to surveys can achieve these
objectives. Whether surveys should be employed to
achieve these purposes depends on the types of
questions asked.

Types of Questions To Be Addressed

Police agencies collect a great deal of data during
their normal operations that can be used to detect
problems and judge anti-crime effectiveness. 
Because these data are a byproduct of routine
police activities, the only additional cost to
using them is the time needed for their analysis.
Surveys of the public, however, are seldom part of
routine police activity. These data are far more
costly because a special effort must be undertaken
to collect them. And surveys are not an appropriate
way to collect data if there is a cheaper
alternative of similar quality. Due to these
additional costs, police managers need to know when
it is worthwhile to conduct a survey and when it is
not.

Surveys can be used to address three types of
questions. They are the primary method of answering
questions about mental states--attitudes, beliefs,
fears, and perceptions--of large numbers of people.
They are useful for learning about people's
behaviors and experiences, and they can determine
group characteristics such as age, race, sex,
education, employment, income, and housing
conditions. 

Attitudes and Opinions

Data describing people's attitudes and opinions can
often be derived through surveys; it is impossible
to directly observe people's thought processes.
Surveys seeking information on mental states
frequently address issues such as:

o Attitudes toward police performance.
o Fear of crime.
o Future plans and intentions.
o Concerns about specific problems.
o Suggestions for police actions.

Although there are no alternative sources of this
type of information, surveys that seek information
on mental states are most useful when people
already have thought about the issue and can
express themselves honestly. Asking citizens about
their feelings concerning police actions they have
never experienced will yield less reliable
information than querying people who have already
interacted with officers. 

Additionally, individuals may not give their true
opinions but provide what they believe to be
socially acceptable answers. For example, if a
person is asked by a police officer whether he or
she thinks the police are doing a poor, adequate,
or good job, the respondent is more likely to rate
the police higher than if a civilian were asking
the question. 

Behavior and Experience 

Surveys are also useful for gathering data on
individuals' behaviors and experiences. Common
topics addressed in surveys of this type include:

o Crime-prevention actions taken.
o Experiences as victims of crime.
o Experiences with the police.
o Experiences with problems.

There are limitations to using surveys to obtain
accounts of behaviors and experiences: people
forget and they misrepresent. People often have
poor memories of experiences that occurred long
before a survey is administered. To overcome the
difficulties people have in remembering details of
crime experiences long past, the Bureau of Justice
Statistics queries people only about experiences
that occur during the 6 months preceding an
interview. People also have a tendency to
reinterpret the past based on more recent
experiences. For example, a citizen who has had
multiple police contacts over a period of time is
likely to base his or her opinion of the earliest
contacts partly on later experiences. Finally,
people may distort or downplay their responses when
asked to recall behaviors that embarrass them or,
alternatively, inflate and embellish a
victimization or heroic experience if they believe
this will make them look better. It is possible,
for example, that when drugs were considered "cool"
by teenagers, high school seniors interviewed about
drug use overreported their rates of drug use; once
drugs became socially unacceptable, high school
seniors may have underreported their drug use. 
Nevertheless, it may be worth some expense to
conduct surveys to learn about certain experiences.

If an event is unrecorded, a survey may be the only
way to learn about it. For example, to learn about
victimization experiences of people who do not
report crimes, one would have to interview them;
their experiences will not be found in a crime
report. Surveys have been used extensively to learn
about drug use by people who have not been arrested
(they represent the vast majority of illicit drug
users). Despite the limitations of poor memory
about victimization experiences or the current
tendency to downplay involvement in drugs, there
are few alternatives to conducting such surveys to
obtain these data.

Sometimes there are less expensive, alternative
sources of information than surveys; surveys should
not be used when better alternatives are available.
For example, officers might evaluate the need for a
project to control rowdy teenagers at a shopping
plaza by conducting surveys of store personnel and
customers, asking their perceptions of the problem.
Other approaches that might be cheaper and more
reliable would be to compare gross sales receipts
at stores before and after a control project, to
use traffic counters at entrances to the parking
lot, or to count people entering the stores. Such
measures provide direct evidence of behavior and
are not subject to memory lapses and other
distortions. However, if officers in the example
above did not care about shopping behavior, but
instead were concerned about how the merchants and
shoppers perceived the police, then surveys would
be the preferred tool. 

Characteristics 

A third way in which surveys are useful is in
revealing characteristics of groups of people. This
can include:

o The characteristics of people living in a
neighborhood.
o The background of victims of crimes.
o The personal history of offenders.

Often there are many alternative sources of this
type of information. Census data provide a great
deal of information about neighborhoods.
Characteristics of victims can be obtained from
offense reports. Offender background information
can be obtained from arrest reports. Police are
often interested in using this information in
conjunction with data on attitudes and opinions or
behaviors and experiences. As a result, questions
about the characteristics of a person answering a
survey are often included on survey forms. The
limitations that apply to experience and behavioral
questions also apply to these data: people may
forget or distort the answers. 

Limitations on the three types of survey data--the
attitudes and opinions of respondents, their
behavior and experience, and personal
characteristics, including personal history--can be
minimized through various survey methods. For
example, civilian interviewers may be substituted
for uniformed officers to obtain more accurate data
on people's attitudes toward the police. A variety
of questions may be asked on the same topic to
check consistency. Much of what follows in this
monograph are descriptions of techniques developed
to minimize problems of poor memory and distortion.

2. The research reports describing these findings
are not specific about what the officers actually
did with the information they gained from the
surveys. If they did little or nothing with the
information, then the reduction of crime and fear
of crime was a result only of the visibility of
police or the interaction of the officers with
members of the public during the survey. If,
however, the officers addressed the problems
revealed in the surveys, then the reduction of
crime and fear may have been caused by the
problem-solving efforts alone, the police-citizen
contacts alone, or a combination of the two.  

3. Police in one city asked residents of a housing
complex to rate their satisfaction with the police
and the public housing authority. The police
received good marks but the residents were very
critical of housing officials. Separately, the
housing officials had completed a similar survey in
which the police fared poorly (no questions were
asked about housing officials). Although the
questions in the two surveys and the methods of
administering the surveys were not the same, some
of the differences in the ratings of the police may
have been due to who asked the question.

Who Will Be Surveyed? 

Police officials often assume that they must
interview everyone in the community to obtain
useful information from a survey. If this were
true, surveys would be so expensive that few would
be conducted. In fact, survey research methods are
designed to get the maximum reliable information
from interviewing the fewest people. The procedure
for selecting people to be interviewed is called
sampling. This section discusses sampling
procedures.

A sample is a subgroup of the larger population
that interests the researcher. During presidential
campaigns the population of interest to pollsters
are those citizens who have registered to vote. The
pollster's goal is to interview only a portion of
this population--the sample. Members of the sample
who answer the survey questions are known as
respondents. Based on the respondents' answers, the
pollster will make inferences about the population.
For example, if 53 percent of the people
interviewed say they will vote for candidate X, the
pollster might assume that about 53 percent of the
registered voters (give or take a few percent)
intend to vote for candidate X. Political polling
and survey research is far more complex, but this
is the basic approach used.

A measurable characteristic of the population to be
studied is called a parameter. The investigator
defines a population sample and makes an estimate
of the parameter. The estimate is called a sample
statistic. For example, in estimating the
proportion of the voting public who would vote for
candidate X, this proportion of voters is a
parameter. (Other parameters might be the average
age of voters, how they have voted in the past, or
how they feel about other issues.) The estimate of
voters favoring candidate X, or 53 percent, is a
sample statistic.

To select a sample of respondents from a
population, the investigator needs a list of the
members of the population. The list from which the
sample is drawn is called the sampling frame. If
one is conducting a survey of sworn officers in a
police department (the population), a list of
department members could serve as the sampling
frame. Unfortunately, in many surveys, a list of
population members is seldom available to use as a
sampling frame. In these situations a sampling
frame must be created. The following example is
drawn from the experiences of a number of police
agencies that surveyed residents of public housing.
It illustrates the process they used to develop and
use a sampling frame.

Example: A number of police agencies have used
surveys to learn about the concerns and experiences
of people living in public housing complexes. The
residents of the housing complex comprise the
population. Officers wanted to interview adults
because children were less likely to give reliable
answers. Further, residents who were not named on
the lease were likely to avoid contacts with the
police for fear that they might be kicked out of
the complex. So the population was narrowed to
those adult leaseholders living in the complex. A
list of adult leaseholders is sometimes available
from the public housing authority. But drawing a
sample of respondents from this list could result
in households of several adults being
disproportionately represented in the sample. So
instead of using the list of adult leaseholders,
the police used a list of occupied apartments. The
sample was taken from this sampling frame, and
officers interviewed only the person who claimed to
be the head of the household. 

The example cited above was a rather
straightforward approach, and the sampling frame
was a reasonable approximation of the population of
interest. However, this is not always the case. To
conduct a victimization survey, for example, one
might start with a list of victims of crimes and
then draw a sample. Because crime reports may list
the names of victims, one might be tempted to start
there. There is a major problem with this approach:
some victims of crime never call the police, so no
incident report is created. Nonreporting victims
would be excluded from the sample, and these
individuals could have had very different
experiences from those persons who 
reported an offense. To overcome this difficulty,
researchers draw their sample from the entire
population of the area in question. During the
interview they ask several questions about
victimization experiences. When a respondent
indicates that he or she has been a victim of a
crime then a series of more detailed questions is
asked. Because most people have not been crime
victims, only a small percent of the total sample
are asked the special set of questions. Although
this is an expensive process, it is the only
reliable method of finding victims who do not
report crimes. 

The San Diego Police Department has been conducting
a study of the characteristics of drug-dealing
locations. This does not involve interviewing
individuals, but it does provide an illustration of
how a representative sample can be obtained without
having a list of respondents.

The study objective was to determine if the
physical characteristics of drug-dealing locations
were significantly different from locations in the
same neighborhood without drug dealing. Answering
this question could help determine what might be
done to prevent drug-dealing locations from
developing. A representative sample of drug-dealing
locations was needed, but no listing of such
locations was available. One option was to use
arrest, warrant, and raid information in police
records to identify all of the possible
drug-dealing locations in the area. This option was
eliminated as prohibitively expensive. Instead, a
list of all 340 census blocks in the area was used
as a sampling frame, and a random sample of 200
blocks was selected. For each address in the sample
of blocks, information from police records (citizen
calls about drugs, drug arrests, warrants, and
field interrogations) and from patrol officers and
narcotics investigators was used to list the
dealing and nondealing locations. A random
selection of dealing locations was made from this
sampling frame. Although there is some unknown
chance that a drug-dealing location may be missed
(or that a nondealing location may be mistaken for
a dealing location), the use of multiple indicators
minimizes this risk. The use of multiple indicators
of drug dealing is expensive, so a strategy of
limiting the number of addresses analyzed prior to
sampling was used. In this way, police achieved a
representative sample of dealing locations.

Simple Random Sampling

There is always a chance that the sample is not
representative of the population regardless of how
it is selected. But some sampling methods minimize
this risk and give the researcher the ability to
calculate the probability that the results from the
sample are very close to the results that would be
obtained if the entire population were surveyed. In
the preceding example, random selection was used to
choose blocks and then addresses within blocks.
Random selection is the most common way of
obtaining a representative sample. It is popular
for four reasons. 

First, random sampling removes the possibility that
the person selecting the respondents inadvertently
biased the sample; that is, selected a sample that
was not representative of the population. Note that
sampling bias has not necessarily been eliminated;
only the sampling bias due to conscious or
unconscious actions of the person doing the
selection has been removed. If the sampling frame
is biased, then the sample will not be
representative of the population, even if random
selection is used. 

Second, random sampling is simple to use. All one
needs to do is assign an identification number to
each member (person, address, etc.) on the sampling
frame. The members can be numbered in some sort of
sequence (alphabetically, for example) or in an
arbitrary manner. All that matters is that each
member has a unique number (not shared by another
member). A random numbers table (often found in
introductory statistics books) or a computer
program (most spreadsheet programs designed for
microcomputers have simple commands for selecting
random numbers) can be used to select the
respondents for the sample.

Third, statisticians can estimate the probability
that the results learned from the sample (for
example, the proportion of respondents who believe
drug dealing is the most important problem in their
neighborhood) are really characteristic of the
larger population and not due to chance. 
Fourth, there are many variations on random
sampling--generally referred to as probability
sampling--that fit the needs of most survey
efforts. For example, if a police chief is
interested in learning what problems are of
particular concern to certain ethnic and racial
groups in the city, a stratified random sample
might be useful, especially if the ethnic and
racial groups to be surveyed represent a small part
of the total population. If Hispanics make up 5
percent and blacks 15 percent of the population,
and the remaining 80 percent are whites, then a
simple random sample of the population would
reflect these proportions. This would mean that
relatively few Hispanics and blacks would be in the
sample. 

Either a large sample could be selected to make
sure enough Hispanics and blacks were in the sample
to draw valid conclusions, or the city could be
divided into three geographic areas corresponding
to the concentrations of the three groups. Three
random samples of equal sizes could then be drawn,
one from each area. Each sample would be
representative of the area from which it was drawn,
but in combination the three samples would not be
representative of the city population: blacks and
Hispanics would be overrepresented and whites
underrepresented. This is not a serious problem
because there are mathematical methods for
compensating for such distortion. If one can
calculate the probability of members of each area
being selected for the sample, then the responses
can be weighted by the number one divided by this
probability. 

The weighting process is easily explained by an
example. Suppose the city in a hypothetical example
has 100,000 adults. The census tracts comprising
contiguous black communities have an adult
population of 20,000. (Not all blacks live in these
census tracts; some whites and Hispanics live
there.) The adult population of the census tracts
that make up the Hispanic neighborhood numbers
6,000. The remaining 74,000 adults (primarily
whites but some blacks and Hispanics) live in the
other census tracts. A statistician has calculated
that an appropriate sample size is 300 adults from
each area. This means that the probability of
selecting a respondent of any race in the black
neighborhoods is 300/20,000 = 0.015; the
probability of selecting a respondent of any race
from the Hispanic neighborhood is 300/6,000 = 0.05;
and the probability of selecting a respondent of
any race from the other neighborhoods is 300/74,000
= 0.004. Another way of looking at these figures is
that every respondent selected from the black
neighborhood represents 66.67 ( = 1/.015 =
20,000/300) adults. Each respondent from the
Hispanic neighborhood represents 20 adults (1/.05 =
300/6,000) and each respondent from the other
neighborhoods represents 250 (=1/.004 = 300/74,000)
adults. Multiplying the answers from respondents
times the number of people they represent weights
the data so that the results of the survey analysis
reflect the proportions found in the population.
Data from respondents sampled from black
neighborhoods would be multiplied by 66.67, data
from Hispanic neighborhood respondents would be
multiplied by 20, and data from other neighborhoods
would be multiplied by 250.

This example of a stratified random sample is just
one of many types of probability sampling that can
be applied. Although these forms of sampling can be
very complicated to design, they often result in
substantial savings in data-collection resources,
and the findings that result from the data analysis
are often more definitive than the findings from
unstratified sample designs. In short, the benefits
of bringing in an expert in sampling may be far
less than the savings of a specially designed
survey. 

Nonrandom Sampling

Various nonrandom sampling procedures may be
simple, but they often leave open the possibility
of drawing a biased sample. Furthermore, one cannot
know how far the estimates obtained from sample
statistics differ from the true population
parameters. Nonrandom sampling procedures include:

o Convenience sampling--selecting respondents based
on how easy it is to get in touch with them. For
example, to get an estimate of residents' views of
community problems, an officer interviews everyone
who shows up at a meeting held to discuss community
problems. If the people who come to the meeting are
not representative of the general population of the
community--for instance, have higher incomes, show
greater willingness to get involved in community
affairs, have higher education, are less fearful of
retribution, or have different perspectives on
community problems--then the results of this
convenience sample will not reflect the views of
the community at large. This type of survey may
provide useful information on those attending the
meeting, but it is risky to generalize from such a
sample to a larger population.

o Accidental sampling--selecting respondents based
on some arbitrary characteristic. For example, to
learn how neighborhood residents feel about drug
problems, an officer talks to every pedestrian he
or she meets on a street during a tour of duty.
Here, again, the respondents are unlikely to be
representative of the population of the community.
The type of person an officer meets on the street
will depend on the time of day and where the
officer is patrolling. In the evening, relatively
few people may be on the street, and they are
likely to be disproportionately male and young.
During the day, more women may be present, but men
and women who work during the day will be absent.
People who are fearful of street behavior will also
be harder to find on the street, so the elderly may
be underrepresented. The location of the patrolling
will also have an effect. If the officer is
patrolling in front of bars on a Friday night, then
he or she will talk to a very different population
than when patrolling near a church on Sunday. There
may be good reasons to interview people in the
street, but these respondents are likely only to be
representative of others who have similar
lifestyles and are unlikely to represent the
general population of the community.

o Systematic sampling--selecting every nth person
or household from the sampling frame. For example,
to learn about community fears of crime, an officer
decides to talk to people in every fifth house.
This may yield a representative sample if there is
not a systematic layout of the neighborhood that
corresponds to the selection rate (every fifth
house). For example, if the 1st and 10th house on
every block is on a corner, then each house sampled
will be at the same relative position on its block.
Because corner houses may have a greater likelihood
of being burglarized, the closer a house is to a
corner the greater the chances that a household
member knows a burglary victim. This could bias the
level of fear estimated from the sample. However,
if there is no correspondence between the sampling
rate and the layout of the neighborhood, then this
strategy can be quite useful. For example, if some
blocks have 4 houses, some 10, and others 7 (in no
particular order), then systematic sampling may
provide a representative sample. Randomly selecting
the starting point--in this example, the first
house in the sample--removes the biases of the
person doing the sampling. Although systematic
sampling is clearly superior to accidental and
convenience sampling, a great deal of effort must
precede its application to ensure its suitability.
The Madison, Wisconsin, police department surveys
its "customers" weekly by sending a survey to
everyone mentioned in every 50th case report
(Couper and Lobitz, 1991).

o Purposive sampling--selecting members of the
sample to achieve a specific objective. For
example, to learn how drug users find out where
drugs are available, a group of arrestees is
interviewed after an undercover reverse buy (that
is, plainclothes investigators take over a dealing
location and sell real or fake drugs to customers,
who are then arrested). This group of suspected
users may not be representative of a larger
population of interest--and it is impossible to
determine whether or not they are--but the
information they provide may be potentially useful
for learning about drug markets. Often, purposive
samples are used to pretest survey questionnaires.
In these situations a draft questionnaire is given
to individuals especially selected because of some
concern as to how they would complete the form. For
example, a questionnaire to be read and filled out
later by respondents may be given to a few
individuals with little education to determine if
it is understandable. Or, a draft questionnaire
asking for information on criminal behavior may be
given to a number of known offenders whose
responses can be checked against official records
to determine if respondents are likely to fill it
out completely and honestly. In summary, the
objective in using a purposive sample is less to
make an estimate about some larger population than
to learn a specific set of facts about a few
hard-to-find individuals. One hopes the group
selected is representative of some larger group of
similar people, but because one cannot be certain,
no claim of representativeness is made. This
differs from accidental and convenience sampling in
that those strategies are associated with a claim--
usually insupportable--that the sample is
representative and no attempt is made to select
people with a special characteristic of interest.

This section discussed the rationale behind
sampling, introduced some standard terms common to
survey research, and reviewed some basic sampling
strategies. Random sampling, or one of its many
variants, is clearly the preferred method, although
systematic sampling is often useful if certain
conditions can be met. Purposive sampling is also
useful in answering some types of questions, but
inferences to larger populations are suspect or
unreliable when this strategy is followed. Finally,
accidental and convenience sampling should be
avoided because results based on these strategies
can be highly misleading.

The next section discusses how many respondents to
select for a sample. In that section and those that
follow, assume that some form of random sampling is
used unless specifically stated otherwise.  

How Many Will Be Sampled?

One of the questions most commonly asked by those
conducting a survey is, "How many respondents
should be in my sample?" This question is so
important and goes so close to the heart of the
rationale for sampling that it seems strange to
report that the question has no definitive answer.
Except for the simplest surveys, only ballpark
estimates can be made of optimal sample size--that
is, the smallest sample that will provide the most
valid and reliable results. Books have been written
on how to determine optimum sample sizes and the
many formulas that can be used, depending on the
sampling procedure and the known characteristics of
the population. In this brief primer on survey
methods, only the primary factors that must be
taken into account in determining sample sizes will
be described.  

There are two factors that are important in
determining the sample size: cost and confidence in
the findings. For any random (or systematic)
sampling procedure selected, the greater the
confidence desired in the results, the more the
survey will cost. This is because confidence
depends in large part on the size of the sample
once the sampling strategy has been selected. As
noted in the previous section, however, for any
given situation there are sampling strategies that
provide high confidence at relatively low cost,
other strategies that offer high confidence at a
high cost, and still other strategies that are
costly yet produce little confidence. For this
reason, it is worthwhile to discuss how various
factors influence sample sizes and how the
selection of a particular type of sampling strategy
can reduce the sample size needed for a desired
level of confidence.

Until now the term "confidence" has been used
without defining its meaning in statistics. As
stated in the previous section, the researcher's
objective is to estimate a population parameter
with a sample statistic. If 86 percent of the
adults in a sample of city residents believe that
the police are doing a good or very good job at
controlling drug abuse, then one might like to
conclude that 86 percent of all adults in the city
feel this way. In reality, it is highly unlikely
that exactly 86 percent of the adults in the
population feel this way, but the percentage should
be close--within a few percentage points. One might
claim to be very confident that the
police-approving population percent lies within a
range or interval, for example, between 83 percent
and 89 percent. Statisticians commonly express such
levels of confidence in percentage terms, so that
an investigator might report the results as
follows: "We are 95-percent certain that the
percentage of the adult population who believes the
police are doing a good or very good job is between
83 percent and 89 percent." Or alternatively,
"There is only a 5-percent chance that the true
population parameter is higher than 89 percent or
lower than 83 percent." Commonly, researchers
attempt to achieve 90-percent, 95-percent, or
99-percent confidence (with 95 percent and 99
percent more common than 90 percent).

Confidence, then, has two components: the size of
the interval in which the population parameter is
sought and the level of confidence that the
population parameter actually falls within the
interval. In the example above, the interval is 3
percent on either side of the sample statistic of
86 percent, and the level of confidence is 95
percent. As one narrows the confidence interval,
the larger the sample size needed for a given level
of confidence. In other words, the more precisely
the population parameter is defined, the more
respondents will be needed. Equally true, the
greater the level of confidence desired at a given
range or interval, the larger the sample size
needed. Therefore, a survey requiring a high level
of confidence in a very precise estimate will be
more costly than a survey designed to get a
ballpark estimate at a moderate level of
confidence. Levels of precision and confidence are
usually set early in the planning of a survey and
are adjusted as more details become known about the
sampling strategies available and the likely costs.

In the example above, the objective was to
determine the opinions held by the adult population
about the police. Included were all the adults and
all their views--pro and con. If concerns were
limited to the way a small portion of the
population felt about the police compared to the
larger group, a larger sample would have to be
selected for a given level of precision or
confidence. For example, to contrast the opinions
about police held by victims of crime with those
held by nonvictims, a very large sample is needed
because the experience of victimization is
relatively rare. Or to use another example, a
researcher plans identical surveys in two large
neighborhoods at opposite ends of town to determine
neighborhood problems. Of special interest are the
problems of the elderly. In neighborhood A, census
data show that half the adults are over age 65; in
neighborhood B, only about 10 percent of the
residents are in this age group. To obtain similar
levels of confidence and precision about problems
of the elderly in the two neighborhoods, a much
larger sample size will be needed in neighborhood B
(where the elderly are relatively scarce) than in
neighborhood A. In short, to calculate the
frequency of a rare attribute of respondents, a
larger sample size is needed than if the attribute
is common.

Stratified random sampling is well suited to this
type of situation. For example, if census data or
information from agencies that serve the elderly
indicate that in neighborhood B the elderly were
concentrated in a cluster of apartment buildings,
then neighborhood B could be stratified or
subdivided so that this cluster is in one study
area. Respondents could then be randomly selected
by areas within neighborhood B in such a way as to
assure that a large enough sample of elderly were
included. The sample could then be weighted to make
valid population parameter estimates. This could
result in a lower cost survey without sacrificing
precision and an acceptable level of confidence in
the results.

As a rule of thumb, if an attribute of interest is
held by fewer than 40 percent or more than 60
percent of the population to be studied, then
stratifying the sample may provide a cost savings.
Note, however, that the feasibility of stratifying
depends on the existence of a suitable sampling
frame. Without a sampling frame, stratification is
very difficult.

In the examples thus far, two population groups
have been compared, but the same logic applies to
multiple categories. Suppose that the population of
neighborhood X consists of equal members of adults
aged 18-30, 31-45, 46-60, and 61 and over (25
percent of the population in each group). By
contrast, neighborhood Y is overwhelmingly younger:
60 percent of persons are 18 to 30 years old; 20
percent are 31 to 45 years old; 15 percent are 45
to 60 years old; and 5 percent are aged 61 and
over. If the views of elderly persons are
particularly desired, then a larger sample would be
needed for neighborhood Y--unless a stratified
random sample can be used--to achieve the same
level of precision and confidence. But if the views
of the elderly are not a major focus of this
survey, it is possible that neighborhood X would
require the larger sample. Why? This would be
required if age appeared related to interviewee
responses (for example, their opinions about the
police). Neighborhood X is more heterogeneous than
neighborhood Y, or, in the terms of statisticians,
neighborhood X has a higher variance in age than
neighborhood Y. This suggests that the variance in
opinion about the police in neighborhood X is
higher than in Y. And the higher the variance in
the responses, the greater the sample size needed
to achieve a predetermined level of precision and
confidence. In this situation, stratifying on age
in neighborhood X might be useful to keep costs
down.

Finally, the greater the number of comparisons to
be made in subgroups within the sample, the greater
the sample size needed. In the previous examples,
comparisons were made only among different age
groups. In the first example, there were two groups
in question, in the second example there were four.
A sufficient number of respondents is needed in
each category so that the comparisons can be done
with a predetermined level of precision and
confidence. This suggests that larger sample sizes
will be required to answer the questions posed in
the second example (four groups) than to answer the
questions posed in the example with two groups.
Note that the number of groups compared is
determined by investigators conducting the survey,
based on their substantive concerns.

Note also that the number of groups can increase
rapidly. In addition to comparing the four age
groups in the second example, a researcher may want
to determine if female and male respondents at each
age view the police differently. That would require
eight groups. In addition, race may be a factor. If
three races are represented--white, black, and
other--then a comparison of age, gender, and race
categories would involve 24 groups (4 age x 2
genders x 3 races). Clearly, one needs to define
the most important comparisons prior to collecting
the data. Furthermore, one should determine if
certain comparisons are really needed. For example,
although there is interest in comparing the views
of whites, blacks, and others, is there a genuine
need to compare the views of young white males with
those of middle-aged black females? If such a need
actually exists, then a larger sample size is
required.

It is worth noting that unless the population is
small--fewer than 100, for example--the population
size has very little influence on the size of the
sample needed. The sample size needed to obtain a
desired level of precision and confidence in a
neighborhood of 800 residents will be about the
same as is needed to make the same estimates at the
same level of precision and confidence for a
neighborhood of 2,000 people, everything else being
equal. If the population is very small--perhaps 50
or fewer--there may be no point in sampling because
everyone could be interviewed.

How Will the Respondents Be Contacted?

The previous sections covered the tradeoff between
costs and quality and ways to keep costs down while
maximizing precision and level of confidence. It
was demonstrated how selection of a sampling
strategy and sample size can be chosen to get the
most "bang for the buck." This section will
continue the discussion by describing how various
methods of reaching respondents affect costs and
survey results and how a data collection strategy
that keeps costs down and achieves acceptable
results can be selected. 

There are three basic types of data collection
strategies: a questionnaire can be mailed to
everyone in the sample for them to complete and
mail back; the sampled respondents can be
interviewed by telephone; or the researcher can go
to the respondents (at home, in the office, on the
bus, or wherever they are) and interview them in
person.

Mail Surveys

Mail surveys are an inexpensive method of obtaining
large sample sizes. Instead of having to pay
someone to talk to respondents, the surveyor can
simply buy postage stamps and envelopes. As usual,
a person gets what he or she pays for. Mail surveys
are notorious for having low response rates. The
response rate is the proportion of sampled
respondents who provide information. Many sampled
respondents do not send back completed
questionnaires; this effectively lowers the sample
size. Low response rates have two problems. First,
by lowering the number of respondents whose answers
can be analyzed, the survey results will be less
precise and there will be less confidence in the
results. Second, if the nonresponses are not
systematic, then the sample of returned responses
can be treated as a random sample, but will be
representative of the population. Often, people who
do not respond have common characteristics related
to certain facts or opinions the survey is trying
to discern. For example, if nonresponders are 
uneducated, poor, and suspicious of the police,
then a mail survey soliciting public attitudes
toward the police will misleadingly overestimate
the confidence the public feels in the police; many
of those harboring negative feelings will not send
back the questionnaire. If the response rate is
high--about 90 percent, for example--the bias due
to selective responding is usually so minor it can
be ignored. But if 40 percent or more of the sample
do not respond, then there are serious questions
about how well the responses represent the larger
population. Unfortunately, mail surveys are more
likely to have response rates of 60 percent or
less; an 80 percent or greater response is rare. 

For example, a questionnaire mailed to 5,462
residents of Lansing, Michigan, by the police
department yielded 2,328 returned questionnaires, a
response rate of 42.6 percent (Trojanowicz et al.,
1987).

There are several approaches to raising the
response rate of mail surveys. First, publicizing
the mailing can sensitize the public, reminding
them to mail the questionnaire back. However,
because individuals are selective about the sources
of information they pay attention to, this also
could unbalance the sample. For example, if
publicity is made through press releases to the
local news media, only those persons who read the
paper, watch television news, or listen to radio
news will get the message; others will not. If
publicity is provided through local churches, then
churchgoers may be overrepresented in contrast to
adults who do not attend church. If publicity is to
be used, it must be conducted in a broad enough
manner--via multiple information outlets--so that
important groups of respondents are not missed.
However, one category of people will always be
missed by a mail survey: people without addresses
such as the homeless and those who move frequently
(members of the military and college students, for
example).

Another method of improving the response rate to
mail surveys is to send a followup letter to all
respondents within a short period of time--1 week
to 10 days after the mailing of the questionnaire.
The followup mailing reminds the recipients that
the survey is important and asks again for their
assistance. Because anonymity is important, the
letter should mention that the sender does not know
who already has and has not returned the
questionnaire; it should express thanks to those
who have already returned it. 

A well-designed questionnaire--easy to read,
appealing to the eye, and asking questions of
interest to respondents--is likely to get a higher
response rate than a poorly designed one. The
following section will discuss how to construct the
survey questions, but first the reader should
recognize the importance of nonsubstantive
considerations. Seemingly trivial considerations--
such as using colored paper and colored ink
(instead of black ink on white paper); employing a
larger, more impressive type face than is normally
produced by a typewriter or word processor;
generously providing white space instead of packing
questions tightly together; and choosing a good
quality reproduction and printing process--
influence the rate of returns. In other words, a
typewritten, photocopied questionnaire will, in all
likelihood, produce fewer responses than a version
with a more professional look. 

Finally, remember that it costs money to return
questionnaires by mail. To improve the response
rate, enclose an addressed, stamped envelope for
the purpose. Instead of pasting stamps on all the
return envelopes, check with the local post office
to see if a preprinted return stamp might be
cheaper and easier to use. Every week the Madison,
Wisconsin, police department sends out surveys to a
systematic sample of people who have contacted the
police that week. Enclosed with the survey
instrument is an addressed, stamped return
envelope. The mailing has a response rate of 35
percent to 40 percent (Couper and Lobitz, 1991).

Apart from the response rate, mail surveys have
another deficiency that may negate the cost
savings: there is no opportunity to assist
respondents who have trouble interpreting the
questions. If a question is ambiguous, respondents
will either make their own interpretations (which
may be inaccurate) or give up and leave the
question blank. Therefore, special attention needs
to be paid to ensuring that the wording is clear
and unambiguous. If many of the individuals in the
sample have limited education, the questionnaire
should be tested on a group of similar persons to
determine if they can read the text and understand
how to answer the questions. If a sizeable
proportion of the population sample is believed to
be illiterate, do not use a mail survey. It is also
important to determine whether a significant
proportion of the respondents are more conversant
in another language than English. If so, consider
translating the questionnaire into that language
and conducting a separate pretest of the translated
questionnaire to ensure that nothing was lost or
added in the translation.

Telephone Surveys 

Instead of mailing survey questionnaires to
determine the public's views about the police, the
Reno, Nevada, police department telephones a random
sample of citizens every 6 months. Calling
respondents by phone and asking them questions is
more expensive than sending them a questionnaire,
but response rates are usually higher, often 75
percent to 90 percent, and the quality of the
answers is usually higher. Remember, however, that
if many of the sampled respondents do not own
telephones, this strategy will not work. This is an
important consideration for surveys conducted in
public housing complexes and in low-income
neighborhoods.

Response rates for surveys by telephone are usually
higher than for mailed surveys because the
investigator can call back repeatedly until a
respondent answers, and people are less likely to
hang up on an interviewer than to throw a
questionnaire in the trash. In practice, a
researcher cannot continue to telephone people
indefinitely; a limit must be set on the number of
callbacks--two, three, or four--to be attempted.
The more callbacks the higher the response rate--
but the higher the cost.

An advantage of using telephone surveys is that if
respondents are unclear about the meaning of a
question they can seek clarification from the
interviewer. This means that all the interviewers
must provide the same answers to the same
questions, consistently. Obviously, it is better to
ask questions that do not require clarification.
Thus, as is the case with mail surveys, a great
deal of attention should be paid to how questions
are worded and how people may interpret certain
phrases. This is especially important when dealing
with different ethnic groups and people whose first
language is not English. If a significant
proportion of the population sample does not speak
English, the questionnaire should be translated,
and interviewers fluent in the other language
should be recruited.

Like the mail survey questionnaire, the phone
survey instrument should be pretested on a small
group of individuals believed to be similar to
persons in the sample.

Additionally, individuals conducting the interviews
need guidance and training. This should involve
standard scripts that interviewers follow when
introducing themselves to respondents and answering
questions they may have. Although some discretion
should be left to interviewers so that they do not
appear to be reading a script, a fair amount of
standardization is needed to ensure that the
interviewers are not influencing--intentionally or
unintentionally--the responses. 

Training should cover how to conduct telephone
interviews in general, as well as how to administer
the particular instrument to be used in the survey.
Such training usually involves some classroom time
for reviewing the questionnaire and answering
questions about it. Several rounds of rehearsals
should then be scheduled. The first round might
involve trainees interviewing each other to get
used to the questionnaire. A second round might
consist of the trainees interviewing various
department members by telephone. In both the first
and second rounds it is sometimes useful for the
person simulating the respondent to ask difficult
questions so that the trainee-interviewer learns
how to cope within the guidelines offered. Finally,
trainees should conduct the pretest. This will
suggest revisions in the questionnaire, or survey
instrument, and will reveal difficulties
interviewers may encounter.

Telephone interviewers can be either department
members or people especially recruited for this
purpose. With the collaboration of a local
university, the Reno police use both students and
volunteers. The only cost of their service to the
Reno Police Department is for the coffee and
doughnuts the volunteers consume.

Inperson Interviews

The highest response rates can usually be achieved
with personal interviews, which usually are more
costly to administer. Personal interviews allow
repeated followup and clarification of questions.
Particularly if a questionnaire is complex,
personal interviews may be required to ensure that
respondents can supply the answers. Inperson
interviews are particularly useful if many of those
in the sample have no telephone. In addition, an
interviewer can directly observe the respondent and
sometimes collect information without asking a
question. As with telephone surveys, training and
guidance need to be given to the interviewer.
Unlike phone and mail surveys, however, the
interviewers' safety in the field must be taken
into consideration if the questionnaire is to be
administered in high-crime areas.

When it comes to choosing who will actually
administer the survey, there are a number of
alternatives. Perhaps the most expensive
alternative is to have police officers conduct the
survey. This alternative has another drawback:
respondents may not give candid answers to some
questions. For example, questions about attitudes
toward the police will be inflated in the positive
direction, and questions about illegal activities
of respondents will produce underestimates of the
true level of these activities. 

However, officers may be very useful in getting
information about neighborhood problems. Not only
are respondents likely to welcome an officer's
asking about such problems, but officers will also
be able to ask followup questions and probe for
important details that an inexperienced, unsworn
interviewer might leave unexplored. In addition, as
a community relations tool, officer-interviewers
can be effective apart from the information they
gather. Surveys give officers a chance to meet
community members they seldom have a chance to talk
to, and the meeting is neither confrontational nor
an emergency. Finally, there is some evidence that
door-to-door interviews by officers may have a
crime suppression effect (Pate, 1986; Uchida,
Forst, and Annan, 1990). To the extent that
community relations and crime-suppression effects
are more important than information gathering, and
to the extent that these effects do not bias the
estimates of population parameters, then survey
interviews conducted by officers may be worthwhile.
The Baltimore County Police Department routinely
has officers assigned to special problem-solving
units conduct neighborhood surveys. The Newport
News, Virginia; Tampa, Florida; and Philadelphia,
Pennsylvania, police departments, among others,
have used uniformed officers to collect survey
information about neighborhood problems. In Tulsa,
Oklahoma, and Atlanta, Georgia, unsworn police
employees have been used to conduct surveys.

It is usually cheaper to use civilians to collect
survey data. They are often easier to schedule, and
the quality of their interviewing (assuming
competent training) is high. Furthermore, there is
less chance that their physical presence will
influence the responses of the respondents.
However, the community relations value of civilians
is lower, they probably have no crime-suppression
effect, and special measures may be needed to
provide security in high-crime areas.

Civilians can be recruited from a number of
sources. One might contract with a professional
survey research firm. The firm would assist with
all phases of the survey, from designing the
sampling strategy to analyzing and reporting the
data. Interviewers are usually well trained and
very professional. The out-of-pocket cost to the
police department is relatively high compared to
other alternatives.

If a number of civilians are employed by the police
department's crime prevention or community
relations units, these individuals may be good
interviewers and may be less expensive to use than
sworn officers. One might encounter many of the
same problems of biased data without some of the
benefits of using officers; nevertheless, this
approach can be useful. The Atlanta Bureau of
Police, for example, used civilian employees to
conduct a survey of public housing residents and
determine neighborhood problems.

Volunteers also can be used effectively for such
surveys. For one project, the San Diego,
California, police department gained the assistance
of a local university professor in recruiting
students to conduct a survey on drug problems in a
high-crime area. Several officers were assigned to
each city block while the interviewers were at
work. There were no incidents, and the information
was very useful.

It is also possible to recruit retirees or members
of citizens' groups to conduct surveys. For
example, a police department might interest a
neighborhood group in interviewing residents of its
own area. Care must be exercised to ensure that
these volunteers adhere to the interview protocol
and do not try to influence their neighbors'
responses.

Summary

There are a number of alternative data collection
strategies that can be used, depending on budget
and quality concerns. For ballpark estimates that
will not be used in critical decisionmaking, a
well-constructed mail survey may be useful. But if
relatively exact estimates of population parameters
are needed, or if the results will be used to make
decisions that will have major impacts on people's
lives, telephone and inperson surveys are more
appropriate.

Telephone and inperson surveys require that the
interviewers be trained and provided with guidance
on how to administer the survey questionnaire.
Regardless of the method of administering the
survey, a pretest should be conducted before a
final instrument is developed.

Whichever strategy is adopted, care must be taken
in the construction of the survey instrument to
ensure that respondents understand the questions
and can provide honest answers. This is the subject
of the next section.

What Questions Will Be Asked?

Until now, the construction and content of
questionnaires and data collection instruments have
not been considered. It should be clear from the
previous discussions, however, that the
questionnaire must be tailored to fit the needs of
the data collection strategy. For example, a survey
instrument suitable for a telephone interviewer
will not be suitable for a mail survey. 

General Considerations

There are a few key issues to resolve before
developing a questionnaire:

o What are the specific purposes of the survey and
what kinds of questions are most likely to yield
responses that are consistent with those purposes? 
It is important to clarify the goals of the survey
project to minimize the number of questions asked.
For example, a police department is planning a
survey of 200 city residents to examine their fears
of crime and their perceptions of the magnitude of
the drug problem. A police official asks whether
the survey should also include a question about
recent victimization experience because victims may
be more fearful. Victimization is relatively rare;
few respondents in a sample of 200 will report
having been victimized. Should such a question be
included? Probably not, unless a high-crime
neighborhood is being surveyed. Without clear
goals, the number of questions tends to mushroom.
This increases the time it takes to administer each
survey, which is a burden on the respondent and the
interviewer, and may reduce the response rate. With
too many questions asked, many of the responses are
not analyzed and the time expended to collect the
information is wasted. In short, fight the
temptation to include everyone's favorite question,
which is often prefaced by, "As long as we are
doing a survey, we might as well ask ..."

o How will the survey be administered--by mail,
phone, or in person--and how much opportunity will
the respondent have to seek clarification?
Self-administered questionnaires--either sent
through the mail or handed to the respondent by a
personal interviewer--need to be professional in
appearance, easy to read, and easy to complete.
Make sure that the lines and spaces for answers are
clearly marked and far enough apart that stray
marks do not confuse someone reading the completed
questionnaire. Instructions should be short, clear,
and polite. They should also be clearly marked so
that someone who rapidly reviews the questionnaire
does not accidently skip over them. If it is
impossible to ask a simple question, easily
understood by respondents who fill out the form by
themselves, consider eliminating the question or
using a different data collection strategy. Once
the questionnaire is completed and returned, assume
that the respondent answered the question that was
posed, not his or her own interpretation of the
question. If this assumption seems implausible,
then asking the question was a waste of time. If an
interviewer is administering the instrument, the
questionnaire does not have to have a professional
look, but it still should be easy to follow and be
designed to minimize errors when an interviewer
marks down the responses.

o Who will fill out the survey instrument--the
respondent or an interviewer--and what is his or
her educational level, training, and proficiency in
the language of the survey instrument? A
questionnaire that examines problems in a community
of college students will be very different from a
questionnaire developed for a similar study in a
low-income public housing project with a high
proportion of high school dropouts; this is true
even if the surveys are designed to obtain the same
basic information with the data collection
strategy. If the survey will cover an educationally
heterogeneous population, then a single
questionnaire should be developed that will be
understandable to all respondents. If an important
segment of the population does not understand
English, then separate, translated instruments need
to be developed.

o How much time will it take to complete the survey
and is this a reasonable amount of time to impose
on respondents? When persons are asked to complete
a questionnaire or answer some questions for a
survey, it is an intrusion into their lives; it
takes up their time and makes personal inquiries.
Most people are willing to allow such an intrusion
if it is for a good cause and the time burden is
not too onerous. Ten to fifteen minutes to complete
a questionnaire is reasonable, but if the subject
is important (concerns about crime, drugs, and
personal safety usually are considered important),
the survey instrument is designed well, and the
interviewer well trained, then survey times of 30
to 45 minutes may be possible. The time it takes to
complete a mail survey is only slightly linked to
the number of pages in the questionnaire. It is
better to have a multi-page, well-formatted
instrument than a short, cramped one. For telephone
and personal surveys, the interviewers' time as
well as the respondent's is consumed. It is a good
idea to make time estimates when the instrument is
pretested. Even at this late stage, the
questionnaire may be edited to make it more cost
effective.

How To Ask Questions

There are various ways of asking questions on a
survey instrument, depending on the issues explored
and the data collection strategy employed. Here are
a few of the most common methods. Remember,
however, as with other topics discussed in this
monograph, there is much more to the subject matter
than can be covered here. Consulting an expert and
reviewing survey instruments that are acknowledged
to be effective and well constructed is a highly
recommended course of action.
Asking about behavior or experiences 
Questions about behavior or experience generally
are framed in one of two ways: "In the last n time
period, have you done a specific action?" or (2)
"In the last n time period, have you been involved
in this specific type of event?" Note first that
there is a time period for reporting the behavior
or experience. Respondents will give very different
answers to the following questions:

A.  In the last 6 months, have you witnessed what
you believe to be drug dealing on the block in
front of your residence?
Yes   1
No    0
Do Not Recall    8

B.  Have you ever witnessed what you believe to be
drug dealing on the block in front of your
residence? 
Yes    1
No     0
Do Not Recall  q  8

With example A, there will be many fewer positive
responses than with B, but they will reflect more
recent experiences. Because example B has no time
boundaries, drug dealing witnessed years ago but no
longer occurring will be reported along with recent
drug dealing. In short, without time limits for
recalling behavior and experience, one can obtain
very unreliable estimates. If you are interested in
determining behavior or experience over a lifetime,
that should be explicitly stated in the question.

(Note: the coding numbers (1, 0, and 8) are used
here to key answers for data entry.) 

C.  Have you ever witnessed what you believe to be
drug dealing on the block in front of your place of
residence? 
Yes    1
No     0
Do Not Recall    8

Note that because people change residences often,
example C may be answered Yes even if the drug
dealing was witnessed in another neighborhood or
city.

The above examples carefully place the behavior in
question in a defined location with reference to
the respondent's home. This type of phrasing would
be useful for determining the prevalence and
concern about drug dealing for a community,
possibly as part of a problem-solving effort.
However, to determine how much drug dealing people
witness in their daily lives, a more general
question would probably be asked. 

D.  In the last 6 months, have you witnessed what
you believe to be drug dealing in the city of
Pheasant Hills?              
Yes    1
No     0
Do Not Recall  q  8

Example D provides a larger area for the respondent
to report drug dealing, yet drug dealing witnessed
outside the city is purposely excluded. However,
there is an implied assumption that respondents
know when they are inside the city of Pheasant
Hills' boundaries. This may be plausible if there
is very little or no drug dealing in adjacent
communities or if the border of the city is clearly
delineated. However, in a dense urban cluster of
cities and towns, municipal boundaries may be hard
to recognize. In such a setting, one would want to
specify some other geographic delimiter that is
obvious and well recognized. If it cannot be
identified, the researcher has the choice of
dropping the question or retaining it while
recognizing that the respondents' answers will be
difficult to interpret.

Finally, notice that the definition of drug dealing
is unclear in these examples. If the investigator
is interested in learning about citizens'
perceptions of drug dealing, these questions are
reasonable. But if a more precise count of drug
dealing in neighborhoods is needed, answers to
these questions can overcount or undercount the
number of times citizens see such behavior.
Behavior that appears suspicious to respondents but
does not constitute drug dealing is likely to be
reported in the survey. On the other hand, street
dealing that is extremely subtle or drug exchanges
that take place in private settings will not be
reported. To obtain more precise estimates of
actual drug dealing on the street, a more precise
question or set of questions needs to be asked.

In example E, a series of questions have been asked
about specific behaviors that have been witnessed
and how often they have been witnessed. If a strict
definition of witnessing drug dealing were
employed, only affirmative answers to question E2.1
would be used as an indicator. Alternatively, an
investigator might decide that a reasonable
indicator of witnessing drug dealing is witnessing
an exchange of money on more than one occasion (E1)
and seeing the same people involved (an affirmative
answer to E1.1). 

E.  In the last 6 months, have you witnessed people
exchanging money on the block in front of this
residence?
Yes    1  (If "yes", please go to E1)
No     0  (Go to F)         
Do Not Recall    8  (Go to F)         
 
E1.  In the last 6 months, how many times have you
witnessed the exchanging of money in the block in
front of your residence?
One Time  q 1 (If "one time", please go to E2)
2 or 3 Times    2                 
4 or 5 Times    3                 
6 to 10 Times   4  If two or more times   
11 to 20 Times  5  Go to E1.1     
More Than 20 Times    6

E1.1.  Have you seen the same people making
exchanges on different occasions during this
6-month period?               
Yes    1
No     0
Don't Know    8

E2.  During any of the exchange(s) you witnessed,
did you see an exchange of things other than money? 
  
Yes    1  (If "yes", please go to E2.1)         
No    0  (Go to F)                
Don't Know    8  (Go to F)           

E2.1.Did you see what you thought were drugs being
exchanged?               
Yes    1
No    0
Don't Know    8

There are other criteria for witnessing drug
dealing that could be selected from these
questions, and there are many other questions that
could be asked. What is important about this
example is that it adds specificity to the
definition of drug dealing.

In fact, in this example, the definition of drug
dealing is not left to the respondent. The survey's
developer defines drug dealing based on the pattern
of multiple-choice answers provided. For example,
drug dealing might be defined broadly by accepting
any answer of Yes to question E as evidence of
dealing. More restrictive definitions can be
developed from E1 by establishing a number of
exchanges witnessed (2+, 4+, 6+, 10+, or 20+) as
the definition, or the investigator might decide
that a Yes to question E1.1 would define drug
dealing. More strictly, a Yes to question E2.1
might be required to define drug dealing. Other
definitions could be used as well, and one need not
be bound by a single definition. When the data are
analyzed, the researcher might compare results from
using different definitions to determine whether
the results change dramatically with the definition
selected. A high level of specificity comes with a
cost, however. What was once a single question is
now a series of questions. More time will be needed
to administer the survey, and more time will be
needed to analyze the results. In some
circumstances, one may be able to find a more
specific single question, but often more questions
will need to be asked. 

This example uses what is called a skip pattern.
The respondent is directed to specific questions,
depending on how he or she answered previous
questions. If question E was answered No, then the
respondent would have skipped over all of the
questions in the example and answered some other
questions that followed later. By answering Yes the
respondent is directed to a set of questions that
probes for more details. Skip patterns are quite
useful when there are a series of questions that
only some of the respondents will be asked.
Researchers must ensure that respondents understand
which questions they are and are not supposed to
answer. In this example, written instructions
follow an answer, along with directional arrows and
a graphic design that directs the respondent to a
box containing the next set of questions to be
answered. Care must be taken when editing and
revising questionnaires with skip patterns: moving
just one question in a survey may create a need for
adjustments in the instructions to a number of skip
patterns. It is important to test all the possible
alternative patterns prior to the actual survey to
ensure that the questions make sense and are easy
to follow.

Asking about opinions and attitudes 

There are a number of ways to elicit opinions and
attitudes in surveys. One common way is to ask
respondents how much they agree or disagree with a
series of statements.
F.  I feel safe walking around my neighborhood
after dark.
1   Strongly agree
2   Agree     
3   Neutral
4   Disagree
5   Strongly disagree

G.  Open-air drug dealing is a serious problem in
my neighborhood.
 Strongly agree   
 Agree       
 Neutral
 Disagree
 Strongly disagree

H.  Police in Pheasant Hills are discourteous and
rude. 
 Strongly agree   
 Agree       
 Neutral
 Disagree
 Strongly disagree

Notice that one has a choice of how to present the
statement. Compare examples F, G, and H to I, J,
and K below.

I.  I do not feel safe walking around my
neighborhood after dark. 
 Strongly agree   
 Agree       
 Neutral
 Disagree
 Strongly disagree

J.  Open-air drug dealing is not a serious problem
in my neighborhood. 
 Strongly agree   
 Agree       
 Neutral
 Disagree
 Strongly disagree

K.  Police in Pheasant Hills are courteous and well
mannered. 
 Strongly agree   
 Agree       
 Neutral
 Disagree
 Strongly disagree

Because the statements are designed to provoke
agreement or disagreement, they cannot be phrased
in a neutral manner. However, the statements should
not all be written with a positive (or a negative)
slant; the slant of question should be alternated
between negative and positive. Accordingly, in
answering four questions that explore fear, a very
fearful respondent should agree with two and
disagree with two.

Another approach is to ask a question and provide a
series of answers from which a respondent selects.

L.  How safe is it to walk around your neighborhood
after dark?
 Very safe
 Safe 
 Somewhat safe 
 Unsafe 
 Very unsafe 
 
M.  How serious a problem is open-air drug dealing
in your neighborhood?
 Not a problem 
 Minor problem 
 Moderate problem 
 Major problem

N.   How courteous are police in Pheasant Hills? 
 Very courteous 
 Courteous 
 Not very courteous 
 Discourteous 
 Very discourteous

Instead of placing multiple-choice answers below a
question, as in examples L, M, and N, a scale could
be provided and respondents asked to circle the
most appropriate value in the scale, as in the
examples below.

INSTRUCTIONS: For the following questions, circle
the score that matches your views most closely.
O.  How safe is it to walk around your neighborhood
after dark?
1  2  3  4  5
very        very
safe        unsafe

P.  How serious a problem is open-air drug dealing
in your neighborhood?
1  2  3  4  5
no        very
problem   serious

Q.  How courteous are police in Pheasant Hills? 
1  2  3  4  5
very        very
courteous   discourteous

A third way to elicit opinions and attitudes is to
pose a hypothetical situation and ask respondents 
to give the outcome they think is most likely.

R.  If you were driving through your neighborhood
and a police officer stopped your car for a minor
traffic infraction, the officer would be:
1  2  3  4  5
very        very
courteous      discourteous

S.  Suppose your apartment were broken into while
you were not at home. If your neighbors saw the
burglar break in, what do you think they would do?
1. They would call the police.
2. They would call the apartment manager.
3. They would call someone else.
4. They would try to stop the burglar 
themselves.
5. They would watch the burglary and 
investigate.
6. They would wait until you got home and tell you
who did it.
7. They would not do anything about the burglary.
8. Other. Please describe  
9. Do not know.

Note that with this last question respondents can
give multiple answers. A neighbor could call the
police and watch the burglary and investigate, for
example. During the analysis of this question,
items S.1 through S.9 should be treated as nine
separate Yes/No questions.  

Asking about characteristics of respondents 

An investigator often wants to ask some basic
questions about attributes and characteristics of
the respondents: age, sex, race, income, marital
status, welfare benefits, and so on. For questions
of this type, the researcher should list
alternatives and allow the respondent to check the
alternative that fits best.

T.  Sex of the person answering this questionnaire.
Male     Female 

U.  Age of the person answering this questionnaire.
 17-19 years old
 20-25 years old
 26-30 years old
 31-40 years old
 41-50 years old
 51-60 years old
 61+ years old

V.  Please mark the race or ethnic group that most
closely describes you.
 White
 African-American
 Hispanic
 Asian
 Other

The categories presented should reflect the
characteristics of the respondents to be
interviewed and the issues the survey will try to
address. For example, if the survey inquires about
a person's area of origin and many of the
respondents are from Southeast Asia, the researcher
may want to subdivide the term Asian into several
categories, such as Korean, Japanese, Vietnamese. 
If a fine gradation of ages is not needed, the
questionnaire might employ only four age groupings,
such as 17-25, 26-40, 41-60, and 61+ years old. Two
important considerations must be taken into account
when creating categories. First, a respondent must
fit into only one group (note, for example, how the
age groups in example U do not overlap). Second,
all respondents must be classifiable into one group
or another; no one should be left out. In example
V, the category "other" was added for this purpose.
The categories in example U are appropriate if the
questionnaire is directed only to adults, that is,
those aged 17 or older. If this were a mail survey,
and a researcher could not be certain that only
adults would complete the questionnaire, a category
for ages 16 and younger should be added.

For some queries, regarding age or income, for
example, the question might just ask for a number,
as below.   

W.  What is your age in years?  

X.  What is your annual gross household income?

Open-Ended Questions

To this point, with the exception of examples W and
X, only questions for which a range of potential
responses were provided have been discussed. 
Questions for which the responses are predetermined
are called close ended. In contrast to close-ended
questions, one may ask open-ended questions.
Open-ended questions allow respondents to provide
an answer in their own way. Consider example Y.

Y.  Describe the most serious problems in your
neighborhood.  
  
Here the respondent can write (or dictate, if an
interviewer is administering the questionnaire)
whatever response he or she feels appropriate.
Obviously, many different responses are possible.
The advantage of open-ended questions is that
respondents can tell their own story in their own
words. This also allows for responses that a
survey's developer may not have considered when
preparing the questionnaire. The disadvantage of
open-ended responses is that it is difficult to
enter the data into a computer and analyze the
responses. Because people use their own words, it
is difficult to compare responses. For example,
consider the following two possible replies to 
example Y.

1.  "There are not many problems on this block. On
Saturdays a few of the men get together and drink
some in the park over there, but they don't bother
anyone. I suppose I worry most about having my
house robbed. The biggest problem is that a lot of
these kids get out of school and cannot get a job."

2.  "There is a lot of drinking and carrying on in
the park. People are always having their houses
broken into, and it is not safe to walk on the
streets at night."

Is drinking in the park a problem for both of these
respondents? Is having one's house robbed the same
as having one's house broken into, or are these two
different problems? How would you classify the
problems of job scarcity and street safety at
night? While open-ended questions give much richer
responses, it is not clear what should be done with
this information. If the responses to the
questionnaire are to be tabulated, the researcher
will have to classify them and provide numerical
codes for each type of response. This means that
for open-ended questions, the investigator will
have to read all the responses and develop
categories. This is a time-consuming process. For
this reason, it is sometimes useful to ask an
open-ended question and follow it by a close-ended
question that lists the responses of greatest
interest. The open-ended question allows
respondents to tell their own story and nominate
responses the researcher may not have thought of.
At the same time, the close-ended questionnaire
focuses attention on issues the survey is designed
to address. An advantage of this strategy is that
when the results are reported, they can be
supplemented with tables, charts, and figures and
direct quotes.

Designing the Questionnaire

There are many other types of questions and formats
for eliciting valid answers. Readers should examine
and compare professionally constructed survey
questionnaires to appreciate how questions can be
asked. Here are a few tips on how to elicit valid
responses from respondents, encourage respondents
to complete a questionnaire, and reduce errors when
collecting the data.

Ask value-neutral questions 

Honest responses are needed from respondents to
reach sound conclusions, so it is important that
the questions and the array of multiple-choice
answers allow respondents to express their true
opinions, as happens in examples F, G, and H.
Although the questions are phrased as statements,
respondents may agree or disagree in a format
offering equal potential for agreement and
disagreement. Contrast the range of responses
allowed in example H with those listed in example
Z.

Z.  Police in Pheasant Hills are courteous and well
mannered. 
 Strongly agree   
 Agree   
 Neutral
 no opinion

In example Z, respondents who disagree with the
statement will either mark "neutral," "no opinion,"
or what is more likely, skip the question. They may
feel that the questionnaire is not designed to
allow them to express an honest opinion, so they
will refuse to complete the survey. The results of
the survey will show views strongly favorable to
the police, but these results will not be valid.

Make sure that the allowed responses measure the
same thing 

The examples given above rate the responses along
some continuum (for example, from observing
something frequently to observing it infrequently,
from strongly agreeing to strongly disagreeing,
from feeling very safe to feeling very unsafe) or
they provide categories for responses (for example,
male/female or race). Example AA illustrates a
poorly constructed question. It tries to evaluate
fear of crime in a neighborhood but mixes up
several measures of fear in the response
categories.

AA. How often do you walk around your neighborhood
after dark?
 Every night
 Only with someone else 
 Occasionally
 Never 

The example has several problems. For example, a
respondent could legitimately mark two boxes ("only
with someone else," and "occasionally").  This
immediately suggests that the second possible
response is unlike the other three and should be
dropped. But there is another problem. "Every
night" is a relatively specific response whereas
"occasionally" is more vague. One should either
pose the question with defined timeframes such as
"every night," "once a week," "once a month," "less
often than once a month," or offer general time
terms--"often," "occasionally," "seldom," "never."
Depending on the choice of scale, the question may
need to be revised to fit the possible answers more
closely.

Ask only one question at a time 

If only one question is asked at a time, there will
be little problem interpreting the answers. If a
survey item contains two questions then the
investigator will not know which question the
respondents answered. Consider a questionnaire in
which the following question about drug dealing is
asked: 

BB. When does drug dealing take place in your
neighborhood?
 During the day only
 At night only
 Night and day
 Have not seen drug dealing

Because this query was not preceded by a question
asking whether the respondent notices drug dealing
in the neighborhood, it contains the implicit
question, "Is there drug dealing in your
neighborhood?" Therefore, an investigator will not
be able to tell if persons choosing the last
response in the series are saying that they know of
drug dealing but have not seen it, or that they
believe no drug dealing is taking place. Both are
legitimate but very different responses. Survey
questions must be unambiguous, and the responses
must allow only for one interpretation. 

Ask what you mean 

Example BB illustrates another problem. Presumably
the person asking the question wants to know what
time of day respondents have seen drug dealing and
believes that the most meaningful categories are
day, night, or both. If this is the question, then
once it has been established in a previous question
that drug dealing has been noticed by the
respondent, the survey questions should read: "When
have you seen drug dealing in your neighborhood?" 

Pay attention to packaging and details 

Make the questionnaire easy to follow; decide
whether it will be self-administered as part of a
mail survey or whether a trained interviewer will
complete it for the respondent. The following
guidelines should be considered when designing a
survey instrument:

o Give clear and concise instructions. If the
instructions must be complex, give visual clues (as
were used to show the skip pattern in example E) to
aid the interviewer or respondent.

o Provide enough space between questions to make it
obvious that they are distinct and separate.

o When a respondent is expected to check or mark a
category, provide respondents with brackets q or,
better yet, a box to hold the check mark.

o Group the questions by topic or by question
style. For example, questions dealing with
perceptions of neighborhood safety could be placed
in one area of the survey instrument, and questions
on attitudes about the police department in
another. Alternatively, all questions using a
five-point scale (see examples O, P, and Q) should
be grouped, and all statements for agreement or
disagreement (see examples F, G, and H) should be
grouped. 

o Place sensitive questions toward the end of the
survey, if possible. This minimizes the chances
that a respondent will skip the entire
questionnaire because of a sensitive question early
in the document.

Precode the questionnaire 

To analyze information obtained in the survey, a
computer may be helpful. If the questionnaire
contains many questions, if the sample size is
large, or if there are many comparisons to be made
among different types of respondents, the
researcher will almost certainly need to use a
computer. 

To enter the data on a computer, codes must be
established for each response to a question. Codes
translate the answer into a number. For some
questions, this is not a problem. For example, the
codes for the answers to examples W and X are the
answers themselves because the answers are specific
numbers. Similarly, the codes for questions O, P,
Q, and R are obvious from the question. For other
questions codes will have to be created. In
examples A through E, codes have been provided--0
for No, 1 for Yes, and 8 for Don't Know. In
question F, codes of 1 through 5 have been assigned
to the answers. In question S, codes 1 through 9
are shown. Assigning codes is very simple. If there
is some natural order or rank to the responses
(more to less, high to low, stronger to weaker),
then the codes should reflect this. If there is no
natural order, the assignment of a number to a
response is arbitrary--0 is assigned to No and 1 to
Yes because they are easy to remember. Alternative
codes are always possible--1 to No and 2 to Yes,
for example. It is important to use the same coding
scheme for all questions with the same format to
reduce the chance of error.

Special codes for missing data are useful. In
examples A through E, the response Don't Know was
assigned an 8. If a respondent does not answer a
question, the investigator may want to code this as
well. All codes should be developed prior to
administering the survey; the investigator has a
choice of whether or not to show the codes on the
questionnaire itself. Their appearance on the
survey instrument is helpful when the data are
entered into a computer file. The person doing data
entry does not have to look up the codes, and this
can reduce data entry errors. On the other hand,
placing the codes on the questionnaire can clutter
it up and may be confusing to the respondents. If
the survey is self-administered, relatively simple,
and contains only a small number of codes, then
coding should not be shown on the survey
instrument. 

Pretest the survey instrument 

The precise wording and format of a questionnaire
may have been the subject of much thought, but
until it is tested on people like those in the
population sample, an investigator cannot predict
whether respondents will interpret the questions
correctly. Some revisions in the content and
wording of the questions and in the instructions,
format, and organization of the questionnaire will
be inevitable. It is useful to ask probing
questions of those who pretest the questionnaire
("Were any questions hard to understand?" "Was the
time needed to complete the questionnaire
excessive?" "Were the instructions clear?"). A
pretest may be time consuming, but it 
can eliminate many problems before they become
serious.

How To Make Sense of the Data

Once the data are collected, they require analysis.
For large sets of data--many questions or many
respondents--a computer will probably be needed.
Someone will have to read each questionnaire, note
how each question was answered, determine the code
for each answer, and enter the codes into a data
file. This must be done with care to minimize data
entry errors (for example, typing a 0 when a 1 is
intended or skipping a question). Having an
easy-to-follow questionnaire, established codes,
and trained data entry people will help minimize
these errors, but someone should check the data
that were entered to determine if mistakes have
been made. Randomly comparing a sample of
questionnaires to data entered from them will
provide an estimate of the frequency of errors.

Although analysis techniques are discussed here 
only in the most basic manner, a more detailed
introduction to analyzing data in policing can be
found in Using Research: A Primer for Law
Enforcement Managers (Eck, 1984). As in all stages
of a survey project, more advanced texts and
experts should be consulted while conducting the
analysis of survey data.

Once the data have been entered, there are four
types of analyses to be performed. First, the
characteristics of the sample must be determined.
Second, a determination is needed of how
representative the sample really is of the
population being studied. Third, an investigator
may want to make inferences from the sample to the
population it represents. And fourth, the
investigator may want to determine if there are
relationships among the attitudes, behaviors, and
characteristics identified in the sample
population.

Characteristics of the Sample

During this most basic stage of data analysis, the
frequency, central tendency, and dispersion of
responses to each question will be calculated. The
frequency of responses to a question is the number
of people in the sample who answered the question
in each of the possible ways. With a Yes/No
question, for example, the number of persons
answering Yes, the number answering No, and the
number who did not answer show the frequency of
responses for this question. If the numbers of
responses are used, this is called the absolute
frequency. If the percentage of respondents
answering each way is used, this is called the
relative frequency. Both the absolute and the
relative frequency should be calculated.

The central tendency is the average, or typical,
response to a question. There are three types of
measures for central tendency. The most common
measure of central tendency is the mean, the sum of
all the responses divided by the number of
individuals responding to the question. For
example, to determine the mean income of persons in
a sample, reported incomes of all respondents would
be added, and that total then divided by the number
of respondents reporting incomes. (Some respondents
may have ignored this question, so they would be
excluded from the calculation.) Although the mean
is the most commonly used measure of the average
response, it is inappropriate for many types of
questions. (A detailed explanation of situations in
which the mean is the appropriate measure is found
in Eck, 1984.)

When the codes for a response have an order (for
example, smallest to greatest, or least agreement
to most agreement), but the responses cannot be
added numerically (for example, adding "strongly
agree" to "disagree" has no meaning), then the
median is the most appropriate measure of central
tendency. The median is the number that divides the
number of responses in half. For example, if half
of 100 respondents answered question R by circling
4 or 5, another 35 circled 3, and the remaining 15
circled 2, the median would be 3.5 because 50
percent of the respondents are above this score,
and 50 percent are below. Or, if the ages of
persons in this sample of 100 respondents had been
recorded by categories (as in question U), then
summing the categories and dividing by 100 would be
meaningless. Instead, one would examine the
frequency data for the question and determine the
age category of the 50th and 51st respondents. The
median age of respondents in a category is the age
category between two answers; half of the
respondents will have ages below the median, and
half will have ages above the median.

For questions with answers that have no order (for
example, sex, race, or religion of the
respondents), the mode is the measure of central
tendency to be used. The mode is the answer given
most often. If 73 of the 100 respondents answered
No to question E, another 20 answered Yes, and 7
marked, "Don't Know," then No is the modal
response.

Measures of dispersion show how spread out the
responses are. If all responses gave the same
answer to a question, there would be no dispersion.
If each response was selected by a similar number
of people, there would be a great deal of
dispersion. As with the central tendency, there are
a number of ways of obtaining a measurement. If the
mean is the most appropriate central tendency
measure, the standard deviation or variance of the
responses is the statistical method to be used. The
method for calculating standard deviations and
variances is beyond the scope of this monograph,
but every statistical program will calculate these
for a user, as will many hand calculators. They can
be calculated from common microcomputer spreadsheet
programs. Another measure of dispersion, useful
when using medians to measure central tendency, is
the range of the data. The range is the lowest and
highest score for a question.

Standard statistical programs will calculate all of
these measures easily. More important than the
mechanics of the calculations, however, is how the
information will be used. The first step in using
this information is to do an error check, looking
for questions that have higher-than-expected
missing cases or whose frequency of responses is
very different from that expected. Before
proceeding with the analysis, these matters should
be checked to ensure that the data were entered
correctly.  Second, one begins to find answers to
some of the substantive questions: Are respondents
concerned about drugs? Do they have positive
attitudes about the police? Are they fearful of
crime? 

Representativeness of the Sample

Regardless of the sampling strategy followed, the
data must be checked to determine whether they are
representative of the population. Random samples do
not guarantee a representative sample; they merely
make it likely. Furthermore, nonresponses can make
the sample unrepresentative. The principal method
for checking representativeness is by comparing
answers to a few of the questions with information
known about the population from other sources. For
example, when members of the Newport News Police
Department conducted a personal survey of residents
in an apartment complex, they collected information
on the income, age, race, and education of
respondents along with other information. Because
this apartment complex made up an entire census
tract, these data could be compared with census
data for the same area. Police analysts found no
substantial differences between the proportions
found in the sample and those found in the census
information (for example, the percentage of blacks
was similar in both data sets, as was the average
income). This result suggested that the sample was
likely to be representative of the entire adult
population of the complex.

It may not always be possible to make such a
comparison, either because there are no data from a
source other than the survey or because comparative
data exist but are organized in a way that makes it
difficult to achieve comparisons. For example, a
survey may be for a single neighborhood, and the
most comparable data are aggregated for several
neighborhoods.

This text has assumed that the sample was drawn
using simple random sampling that did not involve
stratification. If a stratified or other more
complex random sampling procedure was used, then
direct comparisons could not be made until the
sample data were weighted to reflect the
probabilities of selecting each respondent.  

Making Inferences About the Population

There are two types of inferences that can be made
about the population, based on sample data. First,
characteristics of the population can be determined
from what is learned from the sample. Second, one
can determine whether or not there are
relationships among the characteristics of members
of the population, for example, whether the age and
sex of a person have an influence on fear of crime.
Such relationships will be discussed in the
following section.

The simplest method of determining characteristics
of the population is to use the characteristics of
the sample as the best estimate of the
characteristics of the population; that is, one
assumes that the relative frequencies, central
tendencies, and dispersions found in the sample are
very similar to the relative frequencies, central
tendencies, and dispersions that would be found if
everyone in the population had been surveyed. 

To make estimates of absolute frequencies in the
population, the data must be weighted to reflect
the probability of selecting each respondent. Each
case is weighted by the inverse of chance of
selection. For example, if a simple random sample
of 200 households were selected out of a population
of 560, the chances of selection are 200/560 or
.357, so each case would be weighted by 560/200 or
2.8. In other words, each sampled case represents
2.8 households in the population. If 150 of the 200
respondents had seen drug dealing outside their
residences in the last 6 months, then the best
estimate of the total number of residents in the
population who had seen drug dealing would be 150 x
2.8 = 420. In this example, all respondents are
weighted the same because each had the same chance
of being selected. If a stratified random sample
had been used, respondents in each stratum, or
subpopulation, would have different weights. For
example, instead of a simple random sample,
residents on the north side of the neighborhood had
a 50 percent chance of selection, and those on the
south side had a 30 percent chance of selection,
and 100 respondents were selected from each part of
the neighborhood. If 75 respondents from the north
side and 10 respondents from the south side saw
drug dealing in the last 6 months, then the best
estimate of the number of residents in the entire
neighborhood who witnessed drug dealing during this
period is 183 (2 x 75 + 3.33 x 10 = 183.33).

These are estimates of the population parameter,
not exact figures. The true parameter will vary
somewhat from the sample statistic. The question
is, how much will it vary? A statistician can
calculate the probability that the population
parameter lies within set limits around the sample
statistic. The broader the limits, the greater the
probability that the parameter is within them, but
the less precise the measurement. As discussed
above, the greater the sample size, the narrower
these limits can be drawn for some preset level of
confidence. Commonly, a survey analyst will want to
be 95-percent or 99-percent confident that the
parameter is within certain limits (that is, that
there is only a 5-percent or 1-percent chance that
it lies outside these limits). Knowing the
statistic of interest from the survey, the
confidence limits desired, and other information
available from statistical analysis of the data,
the analyst will be able to calculate the bounds
that provide this level of confidence. These
calculations are beyond the scope of this basic
overview of survey methods; however, most
introductory survey research books discuss how
these estimates can be made. What is important to
remember here is that the estimates of population
parameters are not guaranteed to be the precise
figure found in the population; they will vary from
advance estimates, and there are methods for
learning how much they are likely to vary.

Estimating Relationships

Often the purpose behind a survey is to determine
if people with certain characteristics or attitudes
are likely to have another, specified attitude or
to behave in a particular manner. When analyzing
relationships, social scientists usually talk about
variables. A variable is something that has
different values in different circumstances.
Because questions in a survey can be answered in
different ways--that is, take on different values
depending on the respondent's attitudes, behavior,
or characteristics--questions are often treated as
variables. Two variables are positively related if
when one changes (increases or decreases) the other
changes in the same direction. Two variables are
negatively or inversely related when one changes
and the other changes in the opposite direction.
If, for example, respondents who are highly
concerned about drugs also rate the police highly,
then these two variables are positively related. If
nonwhites rate the police lower than whites, then
the variable "race" is negatively related to
"rating the police highly."

Two variables may be causally related or
noncausally related. A noncausal relationship means
that neither variable causes the other, they merely
happen to be associated, perhaps because a third
variable is causing both of them. For example, one
might discover that in a sample of respondents,
race is related to gender--that if the respondent
is African-American, the respondent is more likely
to be female. Race does not cause gender or vice
versa. However, some other process may have created
this relationship, perhaps the sampling process
itself. In a causal relationship one variable is
causing the other, almost always as a partial
cause. In statistical analysis, the causes are
called independent variables, and the effects are
the dependent variables. In a noncausal
relationship, there is no distinction between
dependent and independent variables. Whether the
investigation is of a causal relationship or a
noncausal relationship depends on the theory and
hypotheses of the analyst; the data do not specify
whether the relationship is causal or not. Previous
research, theories of human behavior, logic, and
common sense dictate whether the relationship is
causal. The data can suggest whether the
relationship is real or not, how big it is, and
whether it is positive or negative, but not the
type of relationship.

There are many methods for establishing
relationships, but only the most basic method, the
use of tables, is described here. First a general
case is examined to show how calculations are made.
Next a specific example is used to illustrate the
calculations. To analyze a relationship using a
table, one places the values of a variable to be
evaluated at the head of the columns and places the
values of the other variable at the head of the
rows, as in exhibit 1. Each cell--lettered a
through y--would contain the number of respondents
who have the value of X corresponding to the column
and the value of variable Y corresponding to the
row. So q will equal the number of respondents who
gave a value of 2 to question X and the value of 4
to question Y. The sum of columns or rows are
called marginals, and the sum of the column
marginals equals the sum of the row marginals and
the sum of all the cells, the grand total. If the
cells along the diagonal a, g, m, s, and y contain
most of the respondents, then there is evidence of
a strong positive relationship. If the diagonal
cells u, q, m, i, and e contain most of the
respondents, then there is evidence for a strong
negative relationship. The more spread out or
varied the respondents are from the diagonals, the
weaker the positive or negative relationships.
Although exhibit 1 shows a five-by-five table,
these concepts apply to tables of any 
dimension.

When analyzing a causal relationship, one
calculates only the marginals for the independent
variable (X) and divides each cell by its
corresponding marginal to obtain a percent of the
marginal. Then one compares these percents in the
direction of the dependent variable (Y). Using
exhibit 1, one would divide cells a, f, k, p, and u
each by its sum to have the column percent for each
of these cells. The same would also be done for the
other four columns. Then one would compare along
the rows to see if the percents varied from column
to column.

Suppose an investigator wanted to determine if
respondents who were concerned about drugs were
more likely than those unconcerned to participate
in a neighborhood anti-drug effort. The
investigator might include the following two
questions in a survey:

Drug selling and use are problems in my 
neighborhood.
 Strongly agree   
 Agree       
 Neutral
 Disagree
 Strongly disagree

I would participate in a neighborhood anti-drug
group if one were formed.
 Strongly agree   
 Agree       
 Neutral
 Disagree
 Strongly disagree

After looking at the frequency of responses for
each question separately, the investigator decides
to collapse, or consolidate, the two "agree"
categories into one and to collapse the two
"disagree" categories. The table analyzed will have
three columns for each variable and nine cells.
Exhibit 2 displays the row percents (with numbers
of respondents in parentheses) for this
hypothetical example. 

By reviewing and comparing each column in turn, it
becomes clear that concern about drugs increases
willingness to participate. A total of 61 percent
of the respondents who disagree with the statement
that drugs are a neighborhood problem also disagree
with the statement that they would be willing to
participate in a neighborhood campaign against
drugs. Only 24 percent of the neutral respondents
and 3 percent of those respondents agreeing that
drugs are a problem disagree with the idea of
participating in a neighborhood organization.

Twenty-four percent of the respondents who disagree
with the statement that drugs are a problem were
neutral about their willingness to participate. A
total of 36 percent of those neutral on drug
problems were neutral on participation, while less
than 16 percent of those who felt drugs were a
major problem were neutral on participation.
Finally, 15 percent of the respondents who did not
feel that drugs were a neighborhood problem agreed
that they would participate. Of those neutral on
drug problems, 39 percent would participate. And
more than half the respondents who felt drugs were
a major problem were willing to participate in a
neighborhood anti-drug group. Clearly, the more
that respondents in this example felt that drugs
were a problem in their neighborhood, the more
willingness they expressed to get involved to do
something about it.

Suppose an investigator had reason to believe that
this relationship was not universal. In particular,
he or she believed that apartment dwellers were
less willing to participate in anti-drug campaigns
than owner-occupants of single-family homes (in
this neighborhood, there are no renters of
single-family homes and no condominium owners).
Because some neighborhoods have many apartment
buildings, determining the validity of this
assumption was important for developing a
neighborhood-based anti-drug program.

To determine if home ownership makes a difference
in willingness to participate, the same analysis as
above was conducted, but it controlled for whether
the respondents were renters or owners (information
presumably collected in the survey), meaning that
separate analyses were conducted for renters and
owners. In other words, the variable owner/renter
was held constant; it did not vary. These results
were then compared with the initial, uncontrolled
results.

When the owners' responses are evaluated, the same
basic relationship emerges, increasing concern
about drugs leads to increased willingness to
participate in a neighborhood anti-drug program.
Furthermore, the relationship seems also to apply
to renters. The major difference between renters
and owners seems to be the greater willingness of
owners to participate in a neighborhood drug
program, given their perception of the drug
problem. Note that ownership is treated as the
independent variable; the perception of drug
problems is treated as the dependent variable. This
exhibit is calculated from the marginals of the
independent variable shown in exhibit 3, panels A
and B. It shows that fewer renters seem to agree
with the statement that there is a drug problem in
their neighborhood. From this analysis, we have
evidence that among respondents in this
hypothetical example, ownership influences
perceptions of a drug problem; this in turn
influences willingness to participate in a
neighborhood anti-drug program.

In a causal analysis, control variables are always
independent variables. They are introduced into the
analysis to test whether they would change the
relationship between the initial independent and
dependent variables. In the above example, the
relationship did not change because it turned out
that the control variable did not directly affect
the dependent variable, but affected only the
independent variable. But this is not the only
possible result of introducing a control variable. 
It is also possible to discover the following: 

o The control variable directly affects the
dependent variable, but the independent variable
has no direct effect on the dependent variable and
instead directly affects the control variable.

o The control variable causes both the dependent
and the independent variable, but the independent
variable has no impact on the dependent variable.

o The independent variable has a different effect
on the dependent variable depending on the value of
the control variable. (This is what was expected
when the control variable was introduced in the
example above.)

o The independent variable and the control variable
are noncausally related, and both have a direct
effect on the dependent variable.

Two conditions must be met in order to introduce a
control variable into an analysis. First, there
must be a sound reason to believe that it could
change the relationship. The reason could be based
on prior theory or the investigator's experience.
Second, the control variable must be separately
related to the independent variable and the
dependent variable. While the first condition
cannot be tested for with the data, the
relationship of a prospective control variable to
the independent and dependent variable can be
analyzed separately, prior to introducing it as a
control.

Significance Testing

This text has discussed relationships among
variables without discussing criteria for accepting
the presence of a relationship. It is possible that
a researcher may observe a relationship in the data
that is due to random chance and not to a true
relationship in the population. There are
statistical tests that determine the probability
that an observed relationship is due to chance. The
use of these tests is called significance testing.
To construct a significance test, an investigator
first establishes two competing hypotheses: the
null hypothesis and the alternative hypothesis. 

The null hypothesis states that there is no
relationship between two variables in the
population and that the observed relationship is
due to chance. The alternative hypothesis states
that the relationship in the population is as shown
in the data.

The investigator then picks a maximum probability
that the observed relationship is due to chance. 
This is called the significance level. Typical
significance levels are .01, .05, and .10. That is,
there is a 1-percent, 5-percent, or 10-percent
chance, respectively, that if there were no
relationship in the population, the observed
relationship could arise by chance. The lower the
significance level, the greater the confidence one
has that the results are not due to chance. Note
that significance levels are interpreted in the
same way as confidence levels.

The mathematical formula to be used in the test
depends on a host of factors, including the sample
size, the type of data being used, and how the
relationship is being analyzed. A great variety of
significance tests can be applied, too many to
permit examination here of the formulas that can be
used. Suffice it to say that the test indicates
whether the probability of the relationship's being
due to chance--when there is no real relationship--
is greater or less than the significance level
selected.

If this probability is equal to or greater than the
significance level, then the null hypothesis cannot
be rejected. This means that the possibility that
there is no relationship in the population cannot
be ruled out. Notice that there is no claim that a
relationship does not exist, only that this
possibility cannot be ruled out.

If the probability is less than the significance
level, then the null hypothesis can be rejected in
favor of the alternative hypothesis. This means
that the chances of there being no relationship in
the population are so remote that the investigator
will act as if the alternative hypothesis is true.
While the test provides evidence that the
alternative hypothesis is true, it is not proof
that it is true. There is still a small, but real,
probability that the observed relationship did
arise by chance.

Conclusions 

In this introduction to survey research for
policing, this text has focused on the costs and
benefits of various decisions about neighborhood
surveys. For example, the text has discussed how
increasing sample sizes provides greater precision
and confidence, yet results in a more
time-consuming and costly study. Techniques have
been described that improve the information gained
from a survey while keeping costs down. For
example, often a researcher may choose among
different sampling strategies that can provide
equally precise results at the same level of
confidence, yet one strategy permits interviewing
of fewer respondents. 

The basic choice is between using survey research
methods or using other methods that have no basis
in science such as a convenience sample or an
accidental sample. It might be argued that because
survey research methods are so complex, the expense
of gaining the expertise and carrying out the
needed steps makes them cost-ineffective. This may
be the case in certain circumstances, but the
careful researcher knows that the validity of
results may suffer greatly from a convenience
sample, although there is no way of knowing by how
much. Selecting a convenience sample of a few
citizens and asking them questions that have clear,
socially desirable responses may provide some
information about community needs and problems, but
there is no way of determining whether the opinions
expressed are representative of the population
under study.

Policing is now acknowledging the value of social
science methods for informed decisionmaking. An
increasing interest in the application of survey
research methods to community and police problems
is evidence of this trend. Consistent and diligent
application of survey methods to police work will
lead to more informed decisions and improved
collaboration with community members. This book is
only a starting point; police leaders who want to
make surveys part of their operations should tap
the expertise of the many college-educated officers
and other employees with advanced degrees who are
already in policing. For additional help they
should seek out local experts in survey methods at
nearby universities, marketing research firms, and
other corporations, and consult more advanced texts
on the subject.

Part II:

Environmental Surveys for Problem Solving: 
A Practical Guide

Environmental Surveys and Problem Solving

These surveys seek to assess, as systematically and
objectively as possible, the overall physical
environment of an area. That physical environment
comprises the buildings, parks, streets,
transportation facilities, and overall landscaping
of an area as well as the functions and conditions
of these entities. Although this guide focuses on
the physical environment, police are concerned
about how the physical environment affects the
social environment. In other words, they want to
find out how features of the physical environment
contribute to crime and disorder by facilitating
offenders and inhibiting nonoffenders. Therefore,
environmental surveys are a component of a larger
problem-solving process. 

The problem-solving process can be divided into
four stages: scanning, analysis, response, and
assessment. In the scanning stage, officers
identify problems by grouping similar calls and
incidents together. During the analysis stage,
officers systematically analyze problems by
collecting a wide variety of information, from
inside and outside the police department, about
factors or conditions that may be contributing to
the problem. This information is used in the
response stage to develop specific strategies to
resolve the problem. Finally, in the assessment
stage, officers evaluate the effectiveness of their
response. The first letters of these four stages
are often combined to refer to "the SARA model" for
the problem-solving approach. Results from the
evaluation may be used to revise the response,
collect additional information, or redefine the
problem.

Environmental surveys can prove useful in each of
the four stages of problem solving. Periodic
environmental surveys can help identify problems
that are just beginning to develop. For example, a
citizens group trained in the use of environmental
surveys conducts a biannual survey of its
neighborhood. The group detects an increase in
street litter (and among it, empty spray paint
cans) in a one-block area. Further investigation
reveals that an alley off the block is being used
by a group of young men who sniff paint fumes.
Early intervention by the police, the citizens
group, the department of sanitation, and the
department of health head off a major outbreak in
substance abuse.

In the analysis stage, officers can use
environmental surveys along with other information
sources to gain understanding of conditions
contributing to a problem. By measuring the
physical environment of the drug-ridden area, for
example, a survey may illustrate a connection
between low lighting and overgrown bushes and an
inability of local residents to keep watch over the
area. Likewise, a litter-strewn environment might
provide dealers a place to hide their drugs, or
perhaps neighborhood "junkies" use nearby abandoned
houses to use their drugs.

Information collected from an environmental survey
can guide responses to crime problems. A survey may
shed light on activities within an open-air drug
market, for example, by drawing attention to the
market's street design. A one-way loop, for
example, would offer maximum control of traffic in
and out of the market. In this case, the response
could be to work with city planners on redesigning
the street to change traffic flow and
accessibility.

Environmental surveys can also be used in the
assessment stage. By testing for changes in the
environment before and after police intervention,
police can evaluate the effectiveness of their
responses. Following the example above, police and
the citizens group that detected the spray cans
could compare the amount and content of litter on
the problem block after their intervention to the
amount and content prior to intervention.
Comparisons of the litter and its content on
surrounding blocks would provide stronger evidence
of the impact of intervention and would also help
detect any displacement of the problem.

Offender and Rational Decisionmaking

Environmental surveys are useful in tackling
problems because people good and bad make rational
decisions about when and where to act--and how.
Burglars and drug dealers, for example, make
decisions that maximize the gains and profit of
their crimes and minimize their losses, including
the possibility of getting caught or cheated by
other dealers. Though most people may not be fully
rational, they are rational enough to look for
indications that an act is likely to be beneficial
and to learn from their mistakes. Criminal
offenders are well practiced at reading
environmental circumstances and reaching the
conclusion that a crime target is a good or bad one
(Harries, 1990). Even nonoffenders whose behavior
contributes to an atmosphere conducive to crime
take note of environmental indicators in
determining when and where their acts will be
tolerated. An example might be teenagers who spend
their weekends cruising downtown or riding on dirt
bikes. 

Some types of crime fit the assumption of rational
criminal behavior more neatly than others. With
crimes of violence, for instance, rewards are not
as easily identified as with property crimes.
Violent crimes tend to have an element of
spontaneity that challenges the notion that
criminals behave rationally; the violent offender
may find it more difficult to weigh potential costs
and benefits. On average, however, offenders will
behave in a manner that minimizes the risk of
getting caught. Even drug users, a group that would
seem more influenced by chemicals than by rational
thought, have been found to behave in a rational
manner (Bennett, 1986).

Decisions are based, in part, on cues picked up
from the physical environment that serve as
evidence of the social environment. Wilson and
Kelling (1982) suggest, for example, that the
appearance of neglect in a neighborhood
(garbage-filled lots, unrepaired buildings,
graffiti-marked walls) gives strong cues to
would-be predatory criminals that residents may be
unwilling to protect themselves and each other.
Skogan (1990) describes how the physical
environment can reinforce citizen fears and how
these fears of crime can impair citizens' abilities
in collective crime prevention. 

A dirty, litter-strewn street with many abandoned
automobiles and houses provides many places for a
drug dealer to hide his wares, thus protecting
himself not only from the police but also from
rivals who may want to steal his inventory. An
apartment building with many uncontrolled access
points presents an attractive set of targets for
burglars. 

Defensible Space

What does the rational criminal look for when
choosing a crime target? First, offenders usually
try to avoid being seen while they are committing
their crimes. Not only the police but also the
public serve as deterrents to crime by providing
neighborhood surveillance. Criminals, however, are
not deterred by the mere possibility of being seen,
but rather the possibility that those who see them
will take action against them. 

Offenders avoid being seen by those who know them
(or can distinguish legitimate and illegitimate
users of an area) and by those committed to
defending property or persons under threat
(Brantingham and Brantingham, 1991; Mayhew, 1991).
Offenders are most often deterred by the police, by
residents with a vested interest in their
neighborhood, and by employees who have a general
responsibility for security of an area such as bus
drivers, parking lot attendants, and receptionists
(Cohen and Felson, 1979). This is the basis for
defensible space theory, which contends that crime
control cannot be implemented through physical
design alone, but must rely on the strength of the
neighborhood social organization (Newman, 1972).

Neighborhood Maintenance and Safety

The appearance of a neighborhood expresses the
behaviors and attitudes of residents and what they
are likely to do to control behavior in their
community. The maintenance of a neighborhood sends
a message to would-be offenders that their behavior
will either be tolerated or resisted. 

Wilson and Kelling (1982) use the example of broken
windows to make this point. If a broken window is
not replaced, they claim, more windows will soon be
shattered. The message to vandals is that
destruction is tolerated. Soon graffiti appear on
public property, and undesirables begin to
congregate on street corners. The deteriorated
conditions and strange behavior of street people
create public perceptions of crime even if few
predatory crimes occur.

Social problems of disorder such as loitering and
graffiti may not be serious offenses in themselves,
but they nonetheless raise the level of fear in the
neighborhood. When people no longer feel
comfortable strolling the streets after dark, drug
dealers can attend to their business without being
observed. Like falling dominos, the initial results
of environmental deterioration lead to more
deterioration. 

Criminals look for these kinds of neighborhoods
when choosing targets, because the message is that
residents do not care enough to maintain their
environment and, therefore, do not care enough to
protect each other. Skogan (1990) tested this
theory in 40 neighborhoods and 6 cities and found
general support for this process of neighborhood
deterioration and crime.

Physical Defense and Target Hardening

When deciding when and where to commit a crime,
criminals tend to follow the principle of least
complexity: avoid crime targets that have many
barriers, because these barriers increase the time
it takes to escape. Physical barriers come in the
form of landscaping such as bushes and hedges
blocking off properties, other buildings blocking
the crime target, and areas closed off by fences or
walls. 

Physical defense manifests itself in the form of
street patterns and traffic flow. Physical barriers
make it difficult for offenders to minimize their
retreat distance, the time and effort it takes to
retreat from the crime scene. However, such
barriers can also work in the criminal's favor,
preventing visibility and providing places of
concealment. Likewise, legitimate users of an area
may avoid a location that does not offer them the
ability to see potential threats at a distance or
avoid people who appear threatening (Felson et al.,
1990).

The character and substance of physical barriers
are equally important. While the presence and
design of physical barriers minimize retreat
distance, the strength and resistance to damage of
physical barriers are important if the barriers are
to serve the purpose of preventing entrance to
buildings or grounds. The most obvious and commonly
used crime prevention tactic is called target
hardening, which includes the use of stronger locks
and doors to deter burglaries and more
damage-resistant materials to prevent vandalism.
Again, criminals generally do not look for targets
that present a challenge in gaining entry; rather,
they seek the most easily accessible crime targets.

A principal purpose of an environmental survey is
to determine what environmental cues might affect a
specific problem and then find ways of altering
them so that people change their behaviors. 

Environmental surveys also are sometimes useful for
detecting the physical evidence of a problem. An
earlier example concerned paint spray cans found in
litter, thus pointing to the presence of people
sniffing paint fumes. The tactics taken by local
residents and merchants to protect themselves from
harm often can be seen in the environment. Bars on
windows, the lack of pedestrian traffic, and other
characteristics can be used to assess community
members' responses to a perception of crime.

To summarize, offenders observe the physical
environment to determine whether their actions will
have a net payoff. The environment suggests the
degree to which people in the area will interfere
with the offender's activities and the barriers
that the offender will have to surmount. Finally,
just as criminals often leave behind physical
evidence of a crime, offenders and potential
victims sometimes alter the physical environment
and leave physical evidence of a problem.
Environmental surveys can be designed to detect all
three of these aspects of a problem--citizen
resistance through target hardening, physical
barriers, and physical evidence of a problem.

Environmental Surveys in Practice

Environmental surveys can be developed to gather
different types of information for different areas
and problems. An environmental survey can make
comparisons between counties and States, measure
spatial distributions of crime in subunits of a
city from large areas such as boroughs down to
precincts or census tracts, or analyze a specific
crime site such as a drug "hot spot" or a
particular business or housing complex.

Large-Scale Analysis

One form of specific crime site analysis is to
identify crime hot spots (Sherman, Gartin, and
Buerger, 1989). Hot spots are particular locations
with high levels of crime or disorder. An
environmental survey can systematically appraise
the features of a hot spot. For example, a drug hot
spot includes the physical area in which buyers and
sellers make contact, and this is usually defined
by physical barriers such as buildings, wooded
lots, and fences. The area is normally one that
enables buyers to meet sellers and one where
sellers can easily monitor the approach of police
and other threats. An environmental survey would
document lighting, pedestrian and auto access
routes, windows that overlook the area, locations
of public telephones, bars and convenience stores,
and places where young people congregate.

An environmental survey of several neighborhoods
was conducted by the Tulsa Police Department in
1988 as part of BJA's Problem-Oriented Approach to
Drug Enforcement project. Tulsa officers identified
four public housing units that had high incidences
of drug-related crime. 

Trained in problem-solving techniques, foot patrol
officers conducted environmental surveys in each of
these four complexes to measure the amount of
deterioration, graffiti, litter, and overall lack
of good maintenance. The officers noted a direct
correlation between the degree of environmental
decay and the number of drug-related calls for
service. Appendixes A and B give examples of
environmental surveys used to analyze neighborhood
problems.

Assessing Situational Factors of Crime and Disorder

An environmental analysis does not have to focus on
a particular facet of a problem. Analysis is useful
when a problem occurs at similar businesses or
locations throughout a jurisdiction (appendix C
gives an example of an environmental survey
analyzing drug-dealing locations). By zeroing in on
physical features of the locations, officers can
make suggestions to businesses, government, and
residents about changes in the environment that can
reduce or prevent problems. The San Diego Police
Department has used an environmental survey to
study features common to 200 separate drug-dealing
locations and contrasting these with common
features of 200 separate nondealing locations.

Convenience store robberies are another example of
a problem, spread throughout the city, that can
benefit from the same type of analysis applied to
drug hot spots. In 1985, Gainesville, Florida,
experienced a rash of convenience store robberies.
Convenience stores, police found, had twice as many
robberies in a 5-year period as gas stations and
fast food restaurants combined (Clifton, 1986). 

Police officers began an indepth study of
convenience store crime, making contacts all over
the country to determine if other jurisdictions had
successfully combated the problem. Based on what
they knew about convenience store robbers and their
methods, officers designed an environmental survey
to measure business practices in each such store in
Gainesville. They wanted to learn why some stores
had many robberies and others had few or none. 
Officers rated the lighting of each store and its
premises, any visual obstruction to cashiers, and
the number of clerks on duty (see appendix D for an
example of a convenience store survey instrument
used in another study). Police found that the more
brightly lit the convenience store, with fewer
obstructions, the lower the robbery rate. An even
stronger correlation was found between the number
of clerks on duty and the amount of crime. When the
environment rated high in terms of good lighting
and few obstructions and two clerks were working,
no robberies were reported at all. Convenience
store crime, then, was in part a function of the
environment controlled by the business.

Developing and Using a Survey Instrument

The previous examples show how environmental
surveys can address specific problems. In each
case, officers had ideas based on experience and
previous research about the types of environmental
features most likely to contribute to the problem
they faced. They used this knowledge to construct
the survey. They did not list every environmental
condition conceivable and go on a fishing
expedition to find the most salient factors.
Instead they took an informed approach that tapped
the expertise most officers already have about the
problems in their beats. 

The most important rule in obtaining useful results
from a survey is to identify the general nature of
the problem area to be studied.

Designing an Approach

In a well-executed environmental study, the officer
outlines the objectives of his or her inquiry and
determines the tasks and resources required. What
method will produce the kind of data needed? Who
will conduct the site observations, interviews, or
both? What level of detail is needed and what
resources are available? These questions must be
explored and answered at the outset of the study. 

One useful approach for exploring objectives is to
create an outline allowing the officer to visualize
the goals he or she wants to accomplish. Table 1.1
outlines the basic theory and processes behind an
environmental survey conducted on a specific
problem housing unit.

Defining the Area

Surveying a physical environment requires that the
environment first be defined. What are its bounds?
If surveying a single neighborhood, the survey
leader would need carefully to specify the exact
area the neighborhood covers. The survey team might
want to survey a particular block. If so, it must
define the block so that observers know the
complete set of addresses of interest. In another
case, the survey might be conducted around a
specific location. Then the type of location would
need to be clearly defined as well as the limits of
the surrounding area. The instructions might, for
example, tell observers to report only on features
within sight of the location, or that only features
within half a block in either direction will be
taken into account. No matter what the definition,
it needs to be precise and unambiguous. If the
location is on a corner, will the observer go half
a block in all possible directions, or only in one
specific direction?

Example of a definition: For the questions below,
"block" is defined as the areas on both sides of
the street separated by the nearest cross streets
or street endings on each side. A corner building
is part of the block only if its street address
corresponds with the name of the street analyzed.

Notice that in addition to providing a specific
definition, the designer of the survey instrument
has taken special pains to accurately define how
the observer should account for difficult
situations: corner buildings. If the block is not
defined precisely, some observers would count all
corner houses and others would only count some,
resulting in inconsistencies and, therefore,
inaccuracies.

Reliability and Validity

To be as consistent and objective as possible when
conducting environmental surveys, instructions must
include specific questions about the presence and
absence of the environmental features of interest.
For example, how would one go about measuring the
lighting in a particular public housing complex?
One could simply ask officers to describe the
situation. In this case, however, one officer might
write, "I could not see the numbers on the
apartments at night," while another, viewing the
same situation, might write, "I needed a flashlight
to see where I was going." Still another might
write, "Though dark, there is sufficient light to
see other people in the hallways."

To make sense out of diverse observations, the
survey instrument must provide a structured form
that guides the observations and provides an easy
place to record them. 

A standardized form will require specific
responses. So instead of letting each officer
describe the lighting conditions, the instrument
might provide a standardized scale like this: 

On a scale of 1 to 5, with 1 being completely dark
and 5 being fully illuminated, circle the number
that most closely corresponds to the level of
lighting in the common entryways after sunset.
  1  2  3  4  5

Even with such a standardized scale, this kind of
questioning is very subjective. One observer may
have a different idea from another of what the
level of lighting is. When different observers of
the same situation record different answers, we
call the answers unreliable. A more reliable
measure in this example would be to give each
officer a standard handheld photographic light
meter from which he or she would simply record the
reading. Light meters can be purchased at a camera
supply store, and it may even be possible for the
store to loan them to the department for the short
time needed to carry out the study. 

Care must be taken that researchers understand
exactly where they should take the reading, but 
this is nonetheless a much more reliable approach 
to measurement. A reliable measure is one that 
will repeatedly give the same results under the 
same circumstances regardless of who makes the
observation.

Another reason reliability is so important is that
the survey may need to compare the environmental
characteristics of different places (one apartment
complex to another) and circumstances (a park at
night and the same park during the day).
Replicability requires using the same measurement
instrument in a number of different situations and
environments. This permits comparing relationships
found in one set of circumstances to another. It is
most useful in measuring the effectiveness of a
problem-solving strategy.

A survey also needs to be concerned with the
validity of measures of the environment. A valid
measure is one that measures the concept its
planners had in mind. For example, if one is
interested in measuring the density of dwelling
units on a block, a valid measure might be the
number of buildings on the block. This measure may
be valid in a block of single-family detached
homes, but not for blocks with many apartment
buildings. Note that in both circumstances the
measure of density is probably reliable, even
though validity changes. 

Validity is always a concern, but it is more likely
to be a concern when the environmental survey is
collecting data on people's behavior--use of the
physical environment--rather than on the
environment itself.

Recording how people act within the environment is
often useful. An officer can, for example, record
the types of people using a park (children and
adults, men and women, young adults and elderly)
and what they are doing (sitting in groups, playing
sports, playing board games, drinking). The
presence of observers can change the behavior
observed, reducing the validity of the measure.
Police officers in uniform can affect people's
behaviors. People using the area for illegitimate
purposes will tend to move away, for example.
Legitimate users of the area may become curious
about what the police are up to and try to satisfy
their curiosity, thus changing their behavior. The
use of officers in plainclothes or civilian
interviewers, such as local residents, college
students, or volunteers, may improve the validity
of the survey.

An alternative to observing behavior is to record
the effects of behavior. For example, dirt paths
through a public housing complex reveal frequently
used pedestrian routes. Disposable diapers in trash
containers near a play area suggests that mothers
and very young children use the area. Drug
paraphernalia in a gutter suggests that drug use
takes place nearby. These unobtrusive measures of
behavior can be used to supplement direct
observations or as substitutes for observations.
Unobtrusive measures do not influence the behavior
measured either because they are done secretly (for
example, with a surveillance van or from a hidden
observation point) or because they involve looking
at the effects of the behavior on the environment
(much like physical evidence is an unobtrusive
measure of criminal behavior at a crime scene).
Though unobtrusive measures are often indirect--
requiring some logical deductions--they have the
advantage that the process of data gathering does
not change the behavior observers seek to record. 

Survey Design

Designing questions for a survey is easy once the
data one hopes to measure and collect are defined.
Limit the number of questions to those that
directly apply to your study and minimize the
number of open-ended questions in your survey
instrument. Open-ended questions are those that
allow the observer to provide the answer in any way
he or she chooses. An example above showed how
inconsistent answers might result from an
open-ended question about lighting within an
apartment complex. Another example is:

"What kind of houses are on this block?"

This gives little guidance to the type of answers
required. Should the officer describe architectural
styles, the number of occupants, the material of
which they are built? Not only hard to answer,
open-ended questions are very difficult to
translate into numbers for computer analysis. They
do have one advantage: They can provide a wealth of
qualitative information about specific details that
could not have been anticipated when the survey
instrument was constructed. One or two open-ended
questions in a survey will usually provide that
kind of information, however. A more reliable
method of obtaining information for the above
question is to offer a number of responses:

Which of the following best describes the type of
housing on the block?

1.  Mostly single-family homes
2.  Mostly two-family homes
3.  Mostly apartments/condominiums
4.  Mostly public housing
5.  Mixed (enter that combination)  

This example still provides room for observers to
give different responses to the same situation. A
still more reliable question might be:

Count the number of residential buildings of each
type on the block and enter the numbers in the
appropriate spaces below.

Single-family homes
Two-family homes
Apartment/condominium buildings
Public housing
Other residential buildings

This question is unambiguous, though it will
require much more time to make the required
observation.

In addition to providing the expected responses in
a survey instrument, including an "other" category
is recommended when appropriate:

Are any of the following features adjacent to the
apartment complex (directly across the street, next
door, or behind unit)? Check as many as apply:

1.  School
2.  Park/playground
3.  Wooded area
4.  Liquor store
5.  Porn shop/X-rated theater/massage parlor
6.  Police precinct or substation
7.  24-hour establishment
8.  Abandoned houses or stores
9.  Other  

The "other" category serves as a catchall for
unanticipated responses. Depending on the variety
of "other" answers received, they can simply be
combined into another category or left as "other."

Layout of the Survey Instrument

The physical form of the survey is just as
important as the placement and content of the
questions. The form should be attractive and easy
to read, fill out, and code. Different typefaces
should be used if it helps to clarify the content
of the survey. Whenever possible, questions should
be precoded to facilitate data entry. Codes are
numbers assigned to responses that can be entered
into a computer file. The example above assigned
nine codes to the possible responses. The example
below gives five possible responses, each with its
own code.

How much litter is in the parking lot and directly
in front of the store?
a.  No litter  
b.  Few pieces 
c.  Several pieces  
d.  Small piles  
e.  Other  

Since the observer marked "few pieces," the number
2 will be entered into the computer as the answer
for this question.

In general, each question should be coded so that a
single numerical code is entered for each question.
But coding schemes can be developed for questions
that can have more than one response. In the next
example, the question actually comprises seven
separate yes/no questions. The observer has
indicated "no" 24-hour business, "yes" liquor
store, "yes" wooded area/park, "yes" school, "no"
police station, "yes" bar/nightclub, and "no"
other.

Are any of the following adjacent to the building?
Check as many as apply:

a.  24-hour business
b.  Liquor store
c.  Wooded area/park
d.  School
e.  Police precinct
f.  Bar/nightclub
g.  Other

Numbering Questions

Each question should be numbered consecutively with
its own unique identifying number, and each survey
form must have its own number to avoid confusion in
the field and during analysis. Along with designing
the survey questions, care should be taken in
ordering the sequence of questions to make it easy
for the site observer to record his or her
information. 

Sampling and Pretesting Survey

After designing the survey instrument, the next
step is to test it in an area similar to the one to
be surveyed. Have several people, preferably the
observers to be used in the full survey, observe
the pretest area and complete the survey
instrument. If they have difficulty completing the
instrument, revisions are required. One can also
have several observers record the features of the
same area and compare the responses. If the
instruments are filled out in the same way, it is
reliable. If there are major discrepancies,
something must be done to increase reliability.
This might include revising the questions to make
them more precise, providing clearer instructions,
or providing more detailed training to observers.

Drawing on Other Data Sources

Other sources of information can help in a study of
the physical environment. In addition, the physical
environment is only one part of most problems and
there are data sources useful for linking these
other aspects of problems to the physical
environment. This section will highlight some of
the most common and useful sources of information.

Police Calls for Service

An important source of information for use with
environmental surveys are the calls-for-service
data that most police departments collect and
maintain. Sherman and his colleagues have shown how
useful these are for identifying problems (Sherman,
Gartin, and Buerger, 1989). Repeat call analysis
requires that the calls-for-service data be
organized by address and that a problem analysis
unit be able to obtain a list of addresses in
decreasing order of the number of calls received. 
The top addresses on this list have a
disproportionate number of calls, symptomatic of a
community problem. Further investigation by patrol
officers or specialist problem-solvers is required
to determine if a problem really exists and, if it
does, its nature and extent.

Some addresses will appear high on the list because
they are normal places from which to report crimes
and other complaints, not because they are problem
locations themselves. For example, police stations
and hospitals will usually be high on the list.
These addresses should be deleted. 

Environmental surveys can help in the analysis of
locations with high numbers of calls for service. A
single survey can be used for one location, but it
is sometimes worthwhile to conduct environmental
surveys around several similar such locations. If
similar environmental features are found, it may
reduce the problem in several locations and help
develop preventive measures.

Surveys of the Public

People behave within the physical environment,
changing it and responding to its features. How
people react to the environment can be learned from
observation or from unobtrusive measures. In
addition, however, interviews of people can shed
some light on the links between problem behavior
and the environment. For example, interviewing
residents of a neighborhood can determine what
areas of their community they find fear inducing.
Environmental surveys of these areas can then help
find the features that create the problem. 
Interviewing offenders can reveal what physical
features they look for when planning a crime--those
that indicate an offense is worthwhile and those
that indicate an offense is too risky. (Part I of
this monograph describes how police can conduct
surveys of the public.) 

Official Land Use Data

Cities and counties maintain extensive records on
land use, zoning, buildings, roads, and other
environmental features. These records, often in map
form, can be very helpful for the analysis of
problem areas. Planning departments or other
government agencies, for example, usually have
detailed maps of streets and buildings on blocks
and block clusters. These maps help make zoning
decisions and plan street changes, approve building
plans, and establish tax rates. Analysis of these
maps can reveal how the configurations of buildings
and streets influence problems. Topographical maps,
showing elevations and other natural and man-made
features, can also help address public behavior
problems. Maps of public housing complexes can be
particularly helpful to police officers, especially
if the complexes are large and the streets are not
laid out in a grid. 

Data from regulatory agencies (for example,
alcoholic beverage control agencies) or private
companies can point to the geographic distribution
of particular businesses (for example, bars, liquor
stores, and convenience stores) or amenities (for
example, outside phone booths). This distribution
can be mapped and compared to calls for service
data, crime reports, drug arrests, public surveys,
and environmental surveys.

Local governments vary in their capacity to
collect, organize, and retrieve data that can be
used for assessing the impact of the physical
environment on problems of citizen life. In some
cities and counties, the agencies that regulate
building and construction maintain automated files
on the interior configuration, utility hookups, and
other details of many of the structures. In other
cities, such data may be harder to come by. The
important thing is to make inquiries as to what is
available and in what form.

Conclusions

Police officers make it their business to take note
of the environmental characteristics of their
beats. Officers notice some of the obvious
relationships between, for example, poor
maintenance in a neighborhood and the number of car
thefts. Environmental surveys used in problem
solving can confirm some of these relationships,
thereby revealing some solutions to the problem.
Not all obvious relationships, however, are real.
An environmental survey can show that some features
are not related to the problem. Further,
environmental surveys can point to relationships 
that might not be so obvious by nonsystematic
observation.

By recording and analyzing the environmental
characteristics of a problem area, environmental
surveys can be used at each stage of the
problem-solving process, from scanning through
assessment. They help an officer analyze the nature
of a problem by identifying what factors contribute
to the crime and pointing to incivilities in the
problem area. Used before and after implementing a
problem-solving effort, environmental surveys
enable the officer to measure the effectiveness of
that effort.

Though environmental surveys appear to be time
consuming, they need not be. Simple surveys can be
constructed to highlight a few important, easily
observable features and may take only 1 or 2
minutes of an officer's time to conduct. Further,
because officers are deployed around the clock and
7 days a week, low workload times can be used to
conduct lengthier surveys. For example, in some
cities, or parts of cities, few calls for police
assistance are reported on Sunday mornings. This
time period could be used to conduct surveys. 
Finally, time required to conduct surveys can be
turned to an advantage. Instead of taking on the
surveys as part of police activities, citizens'
groups can be encouraged to conduct them as part of
their routine monitoring of their neighborhood.
This would directly involve citizens in problem
solving and bring to the attention of residents
some environmental conditions over which they may
have direct control. 

Police officers throughout North America are
becoming more effective in their responses to
public concerns, using more sophisticated
techniques and innovative tactics. Careful
environmental analysis can make a substantial
contribution to improving the effectiveness of
police.

Glossary

access routes: pedestrian and automobile street
patterns and outlets for traffic flow into and out
of a neighborhood. Access routes help determine how
criminals judge their ability to retreat or escape.

codes: numbers assigned to possible responses to a
survey question for ease in entering the responses
into computer files.

confidence interval: in estimating or measuring
results, the interval or range within which the
true or actual number is most likely to be found.

consistency: quality of a survey question that
directs responses into easily compared terms.
Examples might be directing the use of a light
meter to measure brightness or an audiometer to
measure sound. Another method for creating
consistency is the use of a standardized scale,
"from 1 to 5" or whatever number the survey
designer selects. 

defensible space: a residential or other
environment for living whose physical attributes
make it possible for residents to defend it, toward
which its residents or workers take a protective
territorial attitude, and in which an intruder
perceives its residents are in control. 

definition: the unambiguous description or
restriction within describable boundaries that a
survey instrument makes of a location, area, or
other subject of the survey.

displacement: process by which criminal activity or
a neighborhood problem, being quelled at one
location by police or citizen action, resumes at
another location.

Hawthorne effect: theoretical principle that
observation of a population's behavior tends to
change that behavior.

hot spots: locations at which a disproportionate
number of crimes occur or from which an excessive
number of calls for police service originate.

hypothesis: an unproven assumption that is not yet
conclusively tested.

intervention: literally, "coming between"; any
beginning of an action or interference with an
action by which police or other agencies of social
change seek to affect the behavior of others.

marginal(s): related to or being a function of a
random variable that is obtained from a function of
several random variables by integrating or summing
over all possible values of the other variables.

mean: the arithmetic average; that is, a middle
point between two extremes. It is obtained by
totaling all the individual values and dividing
that sum by the number of individual values
studied.

null hypothesis: an approach to testing a favored
hypothesis in which a scientist assumes that his or
her hypothesis is worthless, then proceeds to
collect data in a scrupulous effort to disprove it. 

open-air drug market: outdoor location where
dealers and users of unlawful drugs gather to
bargain and make transactions.

open-ended question: a question on a survey (or a
police interview) that is so unstructured as to
allow the observer to answer in any way he or she
sees fit. "What did you see?" is an open-ended
question. Responses to such questions usually lack 

consistency (see above). Even a structured question
may permit, in addition to structured answers, the
unstructured reply "other," providing space for the
respondent to detail the response.

parameter: an arbitrary constant, or a measurable
characteristic, that defines or distinguishes a
member of a system, entity, or population.

physical barriers: physical attributes that help
define a location such as a drug market or,
conversely, a gathering place for neighborhood
citizens. These barriers may effect either bad or
good, on the one hand helping criminals to hide or
escape, on the other making it difficult to take
poorly lighted escape routes. Examples might be
buildings blocking the crime target, bushes and
hedges, fences or walls, and landscaping.

physical defense: physical barriers, street
patterns, traffic flow, and other factors that
maximize (or minimize) offender's opportunity for
concealment or retreat.

physical environment: comprises the buildings,
parks, streets, transportation facilities, and
overall landscaping of an area as well as the
functions and conditions of these entities. Police
are concerned about how the physical environment
affects the social environment. 

physical evidence: evidence furnished by tangible
things themselves as opposed to descriptions of
them.

problem-oriented policing: the process of
approaching persistent community problems that need
police response with detailed research into the
underlying causes and formulation of unconventional
police responses, often drawing on a variety of
police agency, private-sector, and community
resources.

problems of disorder: symptoms of poor neighborhood
maintenance that tend to increase fear of crime and
attract undesirable persons. Wilson and Kelling
(1982) identified "Broken Windows" (the title of
their article) and graffiti, loitering, strange
behavior by street people, prostitution, begging,
and other danger signals.

random: not part of an established or expected
pattern; occurring by chance. Describes events,
numbers, or circumstances.

randomization: the arrangement of a population
sample into two or more comparable groups using a
method designed to eliminate bias in selection and
simulate chance in the arrangement to reduce
interference by irrelevant variables.

reliability: characteristic describing a survey
measure or measuring tool that will repeatedly give
the same results under the same circumstances no
matter who makes the measurement.

replicability: a survey characteristic denoting
that the same measure or measuring tool may be used
to measure comparable things in different
environments and circumstances while still
attaining comparable results.

respondents: individuals in a population sample who
respond to a survey questionnaire or agree to be
interviewed or polled by a researcher.

retreat distance: the path, time, and effort an
offender needs to retreat from a crime scene.

sampling: the process of choosing a representative
segment of a population to determine
characteristics of the entire population.  

significance: a condition, factor, or outcome that
appears to be important, which is probably caused
by something other than mere chance. Only a small
statistical probability exists that the
circumstance or event could have developed
accidentally. 

situational crime prevention strategies: strategies
for deterring or preventing crime in a given
location based on the physical features of the
location that make crime likely there. Similar to
the theoretical applications formerly called "crime
prevention through environmental design" and, more
recently, "security by design."

skip pattern: the arrangement of queries in a
survey questionnaire by which a respondent is
directed to additional questions based upon
previous answers. At the same time, the respondent
is directed to skip certain questions based upon
those answers.

standard deviation: a calculation that takes
account of all values in a distribution to indicate
how spread out or dispersed the values are.

standardized instrument: a questionnaire (also
called "survey instrument") by which a survey
designer ensures that comparable data are gathered
on comparable phenomena throughout a defined survey
area.

target hardening: making a building, dwelling, or
area less accessible to potential criminals by use
of "hardware" such as locks, gates, bars, or
fortifications.

unobtrusive observation: gathering of survey data
by an observer who is unseen or is not identified
with the survey, such an observer being chosen so
as to avoid the loss of validity created by the
Hawthorne effect.

validity: relevant and meaningful to the particular
aspect of an area or problem that a survey seeks to
measure.

variable: A factor, condition, or number that may
vary or change; as it changes it may affect the
outcome.

variance: the square of the standard deviation.

weighting: the assignment of a statistical weight.
Sources for Further Information

Bibliography

Bennett, Trevor (1986). "A Decision-Making Approach
to Opioid Addiction," in Derek B. Cornish and
Ronald V. Clarke, eds., The Reasoning Criminal:
Rational Choice Perspectives on Offending. New
York: Springer-Verlag.

Brantingham, Paul J., and Patricia L. Brantingham
(1991). "Notes on the Geometry of Crime," in Paul
J. Brantingham and Patricia L. Brantingham, eds.,
Environmental Criminology. Prospect Heights, IL:
Waveland Press.

Clarke, Ronald V. (1990). "Deterring Obscene Phone
Callers: Preliminary Results of the New Jersey
Experience," Security Journal, 1, pp. 143-148.
----- (1983). "Situational Crime Prevention: Its
Theoretical Basis and Practical Scope," in Michael
Tonry and Norval Morris, eds., Crime and Justice:
An Annual Review of Research, vol. 4. Chicago:
University of Chicago Press.

Clarke, Ronald V., and Gerry McGrath (1990). "Cash
Reduction and Robbery Prevention in Australian
Betting Shops," Security Journal, 1, pp. 160-163.
Clifton, Wayland, Jr. (1987). Convenience Store
Robberies in Gainesville, Florida: An Intervention
Strategy by the Gainesville Police Department.
Gainesville, FL: Gainesville Police Department.
Cohen, Lawrence E., and Marcus Felson (1979).
"Social Change and Crime Rate Trends: A Routine
Activity Approach," American Sociological Review,
44, pp. 588-605.

Couper, David C., and Sabine A. Lobitz (1991).
Quality Policing: The Madison Experience.
Washington, D.C.: Police Executive Research Forum.

Eck, John E. (1984). Using Research: A Primer for
Law Enforcement Managers, Washington, D.C.: Police
Executive Research Forum.

Eck, John E., and William Spelman (1987). Problem
Solving: Problem-Oriented Policing in Newport News.
Washington, D.C.: Police Executive Research Forum.

Ekblom, Paul (1988). "Preventing Post Office
Robberies in London: Effects and Side Effects."
Journal of Security Administration, 11, pp. 36-43.

Farmer, Michael T. (1981). Differential Police
Response Strategies. Washington, D.C.: Police
Executive Research Forum.

Felson, Marcus, Dory E. Dickman, Denise E. Glenn,
Linda M. Kelly, Gregory A. Lambard, Lisa S. Maher,
Laura L. Nelson-Green, Craig S. Ortega, Thomas J.
Preiser, A. Rajendran, Trini E. Ross, Lourdes Tous,
and James M. Veil (1990). "Preventing Crime in
Newark Subway Stations," Security Journal, 1, pp.
137-142.

Goldstein, Herman (1990). Problem-Oriented
Policing. New York: McGraw-Hill.

Grandjean, Christian (1990). "Bank Robberies and
Physical Security in Switzerland: A Case Study of
the Escalation and Displacement Phenomena,"
Security Journal, 1, pp. 155-160.

Harries, Keith D. (1980). Crime and the
Environment. Springfield, IL: Charles C. Thomas.
Hunter, Ronald D., and C. Ray Jeffrey (1991).
"Environmental Crime Prevention: An Analysis of
Convenience Store Robberies," Security Journal, 2,
pp. 78-83.

Kansas City Police Department (1980). Response Time
Analysis: Volume II--Part I Crime Analysis.
Washington, D.C.: U.S. Government Printing Office.
Kelling, George L., Tony Pate, Duane Dieckman, and
Charles E. Brown (1974). The Kansas City Preventive
Patrol Experiment: A Technical Report. Washington,
D.C.: Police Foundation.

Matthews, Roger (1990). "Developing More Effective
Strategies for Curbing Prostitution," Security
Journal, 1, pp. 182-187.

Mayhew, Pat (1991). "Crime in Public View: 
Surveillance and Crime Prevention," in Paul J.
Brantingham and Patricia L. Brantingham, eds.,
Environmental Criminology. Prospect Heights, IL:
Waveland Press.

Mayhew, P., R.V.G. Clarke, A. Sturman, and J.M.
Hough (1976). Crime as Opportunity, Home Office
Research Study No. 34. London: Her Majesty's
Stationery Office.

McEwen, J. Thomas, Edward F. Connors III, and
Marcia I. Cohen (1986). Evaluation of the
Differential Police Response Field Test.
Washington, D.C.: U.S. Government Printing Office.

Newman, Oscar (1972). Defensible Space: Crime
Prevention Through Urban Design. New York:
Macmillan.

Pate, Antony M. (1989). "Community-Oriented
Policing in Baltimore," Police and Policing:
Contemporary Issues. New York: Praeger.

Pate, Antony M., Mary Ann Wycoff, Wesley G. Skogan,
and Lawrence W. Sherman (1986). Reducing Fear of
Crime in Houston and Newark: A Summary Report.
Washington, D.C.: Police Foundation.

Pate, Antony M., Amy Ferrara, Robert A. Bowers, and
Jon Lorence (1976). Police Response Time: Its
Determinants and Effects. Washington, D.C.: Police
Foundation.

Perkins, Douglas D., John W. Meeks and Ralph Taylor
(1987). "The Physical Environment of Street Blocks
and Resident Perceptions of Crime and Disorder:
Implications for Theory and Measurement," paper
presented at the annual meeting of the American
Society of Criminology, Montreal.

Police Foundation (1981). The Newark Foot Patrol
Experiment. Washington, D.C.

Poyner, Barry (1983). Design Against Crime: Beyond
Defensible Space. London: Butterworths.
Sherman, Lawrence W., Patrick R. Gartin, and
Michael E. Buerger. (1989). "Hot Spots of Predatory
Crime: Routine Activities and the Criminology of
Place," Criminology, 27, pp. 27-55.

Skogan, Wesley G. (1990). Disorder and Decline:
Crime and the Spiral of Decay in American
Neighborhoods. New York: Free Press.

Spelman, William, and Dale K. Brown (1984). Calling
the Police: Citizen Reporting of Serious Crime.
Washington, D.C.: U.S. Government Printing Office.

Taub, Richard, D. Garth Taylor, and Jan Dunham
(1984). Patterns of Neighborhood Change: Race and
Crime in Urban America. Chicago: University of
Chicago Press.

Tien, James M., James W. Simon, and Richard C.
Larson (1978). An Alternative Approach in Police
Patrol: The Wilmington Split-Force Experiment.
Washington, D.C.: U.S. Government Printing Office.

Trojanowicz, Robert, Richard Gleason, Bonnie
Pollard, and David Sinclair (1987). Community
Policing: Community Input Into Police
Policy-Making. Community Policing Series No. 12.
East Lansing: National Neighborhood Foot Patrol
Center, Michigan State University.

Uchida, Craig D., Brian Forst, and Sampson O. Annan
(1990). Modern Policing and the Control of Illegal
Drugs: Testing New Strategies in Two Cities.
Unpublished summary report, Washington, D.C.:
National Institute of Justice.

Wilson, James Q., and George L. Kelling (1982).
"Broken Windows: The Police and Neighborhood
Safety." The Atlantic Monthly (March), pp. 29-38.

Further Reading

Converse, Jean M., and Stanley Presser (1986).
Survey Questions: Handcrafting the Standardized
Questionnaire. Sage University Paper series on
Quantitative Applications in the Social Sciences,
07-063. Newbury Park, California: Sage
Publications.
Discusses question development

Eck, John E. (1984). Using Research: A Primer for
Law Enforcement Managers. Washington, D.C.: Police
Executive Research Forum.
General introduction to research methods of police

Fowler, Floyd J., Jr. (1984). Survey Research
Methods. Newbury Park, CA: Sage Publications.
Basic introduction to survey research

Harries, Keith (1990). Geographical Factors in
Policing. Washington, D.C.: Police Executive
Research Forum.
Contains discussion of significance testing and
dispersion

Henkel, Ramon E. (1976). Tests of Significance.
Sage University Paper series on Quantitative
Applications in the Social Sciences, 07-004.
Newbury Park, California: Sage Publications.
Discusses the use of significance tests

Henry, Gary T. (1990). Practical Sampling. Newbury
Park, California: Sage Publications.
Basic introduction to sampling strategies

Kalton, Graham (1983). Introduction to Survey
Sampling. Sage University Paper series on
Quantitative Applications in the Social Sciences,
07-035. Newbury Park, California: Sage
Publications.
Basic introduction to sampling strategies

Lavrakas, Paul J. (1987). Telephone Survey Methods:
Sampling, Selection, and Supervision. Newbury Park,
California: Sage Publications.
A very thorough discussion of telephone surveys
with many pointers that can be applied to other
types of surveys

Lipsey, Mark W. (1990). Design Sensitivity:
Statistical Power for Experimental Research.
Newbury Park, California: Sage Publications.
Discusses the number of respondents needed for a
study

Mohr, Lawrence B. (1990). Understanding
Significance Testing. Sage University Paper series
on Quantitative Applications in the Social
Sciences, 
07-073. Newbury Park, California: Sage
Publications. Basic introduction to significance
testing

Two standard texts for survey research that require
some analytical and mathematical sophistication on
the part of the reader are:

Kish, Leslie (1965). Survey Research. New York:
John Wiley.

Rosenberg, Morris (1968). The Logic of Survey
Analysis. New York: Basic Books.
----------------------------------------

WITHIN THE FOLLOWING APPENDIXES ARE TEXTUALLY
COMPLETE, BUT UNFORMATTED, FORMS.

Appendix A: 

Example of a Housing Complex Environmental Survey

This instrument was developed for analyzing drug
problems in apartment housing complexes, public
housing complexes in particular, as part of the
Problem-Oriented Approach to Drug Enforcement.
Designed by John Meeks of the Police Executive
Research Forum as part of a set of instruments (see
appendixes B and C), it was used in Philadelphia. A
map of the neighborhood being surveyed was attached
as part of the instrument. However, as the map is
particular to the community being surveyed, it is
not included here.

Overview

The purpose of the Housing Complex Rating
Instrument is to rate, as systematically and
objectively as possible, the overall physical and
social environment of housing complexes. The
procedure involves making onsite observations and
ratings of the physical and social incivilities
that may be contributing to area crime and
residents' fear of crime. Physical incivilities
include such things as litter, graffiti, broken
windows, unkempt lots, vacant or dilapidated
housing, and abandoned automobiles. Social
incivilities include such behaviors as people
"hanging out," being noisy, drinking, and selling
or using drugs. 

This rating instrument will allow police officers
to identify incivilities that may need problem
solving. In addition, ratings may be used to
explain living conditions, crime problems, and fear
levels. The presence of incivilities indicates a
breakdown in social order. Area residents and
criminals may perceive the police as being unable
to prevent or control such problems. Thus, it
becomes important to identify and respond to
incivilities.

Before conducting the actual rating, it would be
beneficial to divide the housing complex into
smaller areas or zones. It will make rating the
physical environment much easier. Since there are
no established methods for dividing housing
complexes, any of the methods described below will
suffice. One method is to create artificial blocks
within the housing complex and rate each block.
Another method is to use existing boundaries or
markers such as fences, open spaces, building
types, building numbers, foot beats, or compass
directions. The key is identifying smaller,
geographically defined areas within the housing
complex. Each smaller community may have its own
set of problems.

The idea for this rating instrument comes from the
earlier works of Richard P. Taub, D. Garth Taylor,
and Jan D. Dunham (1984), and Douglas D. Perkins,
John Meeks, and Ralph Taylor (1987). This rating
instrument, however, is different in design and
purpose. This instrument is designed to provide
police officers with a specific practical tool for
problem solving, whereas these earlier studies used
rating instruments for conducting basic social
science research.

General Rating Instructions

Although the instrument is designed to facilitate
rating the social and physical environment
objectively, problems with coding and classifying
information are bound to arise. When questions or
problems do arise, it is important that the rater
does the following:

1.  Check the specific item instructions for coding
procedures.

2.  If checking the instructions does not help,
write down the problem and the way the question is
coded. Be sure to inform your supervisor as soon as
possible so that the problem can be resolved before
it reoccurs.

Ideally, two raters should rate each area or zone
at the same time. However, it is important that
they do not discuss their ratings with each other.
Their ratings are to be independent of each other.
This will allow the department to determine the
reliability of the raters and the instrument. Prior
studies have shown similar rating instruments to be
very reliable.

Specific Item Instructions

First, fill in the data (month, day, year), day of
week, and the time started. For day of the week,
code Monday=1, Tuesday=2, Wednesday=3, Thursday=4,
Friday=5, Saturday=6, and Sunday=7. For time, use
24-hour numbers (example: 8:30 p.m. = 2030 hrs.).
For rater, put your name and badge number. For
location, put the name of the complex and the area
or zone within the complex.

I.  TYPE OF HOUSING STRUCTURE

Check the category that best describes the units.
1.  Single units are units such as single homes.
They may be attached like duplexes or row houses,
or detached individual homes.
2.  Multiple-unit buildings are best described when
several dwelling units are located in a single
building. For example, each building in the complex
may contain four apartments.

II.  CONDITIONS OF BUILDINGS/UNITS--EXTERIOR

The objective here is to do a quick scan of the
front of the buildings to get an overall feel for
the appearance and condition of the buildings. You
do not need to examine the buildings too closely.
You do not need to examine all sides of the
buildings/units. You should only rate the front of
the buildings/units. This is the part most people
see.
3.  Structural problems: the objective here is to
determine the overall condition of the
building/units. Count buildings/units that are
leaning or bulging as having structural problems as
well.
4.  Broken fixtures: if it is part of the
building/unit and broken, count it.
5.  Graffiti: do not count murals as graffiti.
6.  General lack of maintenance: this question is a
composite of the first three questions. So consider
structural problems, fixtures, and graffiti as
evidence of a general lack of maintenance.
7.  Vacant buildings/units: it may be difficult at
times to determine if a unit is vacant. Check all
the signs that could indicate vacancy such as old
mail and newspapers piling up, uncut grass, windows
without curtains/blinds, or boarded up windows,
etc.
8.  Overall appearance and condition of buildings:
this question is intended to give an overall feel
for the buildings/units in the zone. To make rating
this question easier, you can consider the five
choices as a scale from 1 to 5, with very poor
being 1 and very good being 5, or as a grading
system with very poor being an F and very good
being an A.
9.  Identify on the map buildings/units that need
special or immediate attention: you should identify
buildings/units by marking the location and
describing the problem.

III. CONDITIONS OF GROUNDS/LANDSCAPING

Again you are only to scan the area. The objective
is to rate the overall appearance and condition of
the area.
10.  Litter, trash, broken glass: only count litter
and trash bigger than 2" by 2". Do count cans and
old newspapers. Only count broken glass if it
covers more than a 2-square- foot area. Do not
count trash that is placed outside for disposal.
11.  Large pieces of junk: do not count junk that
is placed in the trash for immediate disposal.
12.  Unkempt lawns: count both private and public
lawns in the zone. If the grass or weeds are higher
that 10", count them overgrown. Count bushes and
trees overgrown if they are clearly in need of
trimming or are blocking walkways or pathways.
13.  Missing, cracked, or sunken sidewalks: count
both private and public sidewalks in the zone.
14.  Open spaces: include places to sit, talk, or
play outside. Only count litter bigger that 2" by
2", and broken glass if it covers more than 2
square feet.
15.  Abandoned automobiles: count one abandoned if
it appears nondrivable (i.e., it has shattered
windows, more than one flat tire, missing tires or
body parts, or a missing license plate). 
16.  Recreational equipment: only include the
equipment outdoors such as a jungle-gym,
merry-go-round, basketball court, etc.
17.  Regular use: does it appear that the equipment
is used often?
18.  Condition and appearance of equipment:
consider the physical condition and overall
appearance.
19.  Lighting conditions: consider whether there is
ample private and overhead lighting.
20.  Overall appearance and conditions: the
objective here is to give a feeling for the overall
appearance and conditions of the zone.
21.  Unusual characteristics: the objective is to
identify any features that show a sense of
community or organization.
22.  Identify on the map any specific problem areas
that need special attention because of health and
safety concerns.  Be sure to label the problems on
the map.

IV. INTELLIGENCE INFORMATION

23.  Problem locations: count places where
troublemakers or criminals "hang out" and/or live.
Include a brief description of those "hanging out."
Include such items as age, sex, and race or
ethnicity.
24.  Drug locations: include those locations that
have received complaints or are suspected of being
drug locations.

I.  TYPE OF HOUSING STRUCTURE

1.  Single units
a.   Attached
b.   Detached
2.  Multiple unit buildings
a.   Number of units per building
b.   Number of stories

II.   CONDITIONS OF BUILDINGS/UNITS--EXTERIOR

Note: Code percentages in increments of 10: 0%=0,
10%=1, 20%=2, 30%=3, 40%=4, 50%=5, 60%=6, 70%=7,
80%=8, 90%=9, 100%=10.

3.  What percentage of the buildings/units in the
zone have a structural problems such as missing
brick, stone, stucco, siding, etc.? Missing
material must be greater than 1 foot.
4.  What percentage of the buildings/units have
broken fixtures such as windows, doors, outdoor
lights, awnings, railings, etc.?
5.  What percentage of the buildings/units have
graffiti?
6.  What percentage of the buildings/units show an
overall lack of general maintenance by residents
and housing management?
7.  What percentage of the buildings/units are
vacant? 
8.  Rate the overall appearance and condition of
the buildings/units in the zone according to
structural soundness, neatness, and cleanliness.
Very Good
Good
Poor
Very Poor

9.  Indicate on the map any buildings/units that
need special or immediate attention because of
structural problems, health, safety, or security
concerns.

III. CONDITIONS OF GROUNDS/LANDSCAPING

Note: Code percentages in increments of 10: 0%=0,
10%=1, 20%=2, 30%=3, 40%=4, 50%=5, 60%=6, 70%=7,
80%=8, 90%=9, 100%=10.

10.  What percent of the buildings/units have a
litter, trash, or broken glass problem?
11.  What percent of the buildings/units have large
pieces of junk such as old tires, bicycles,
furniture, and appliances?
12.  What percent of the buildings/units have
problems with unkempt lawns such as overgrown grass
and weeds (more than 10" high), bushes, and trees?
13.  What percent of the buildings/units have
missing, cracked, or sunken sidewalks?
14.  Are the open spaces for sitting or playing
clean of litter, trash, and broken glass?
Yes      No
  
15.  Are abandoned automobiles in the zone?
Yes    Number         No

16.  Any recreational equipment in the zone?
Yes      No (if no, skip questions 17 and 18)

17.  Is the recreational equipment used regularly?
Yes       No

18.  Is the recreational equipment in good
condition?   Yes      No

19.  Is there adequate lighting in the zone?
Yes       No

20.  Rate the overall condition and appearance of
the grounds landscaping in terms of cleanliness,
beautification, health, and safety concerns.
Very Good        Good
Poor             Very Poor

21.  Describe any other unusual physical
characteristics such as distinctive topography,
housing style, conditions, ornamentation (e.g.,
identical lamps, planters, railings, awnings, paint
designs), anything that might show a sense of
community or organization within the zone.

22.  Indicate on the map any buildings/units or
open spaces that need special or immediate
attention for cleanups, extra lighting, or extra
patrol.

IV.   INTELLIGENCE INFORMATION

23.  Are there any problem locations in the zone
where people tend to "hang out" and cause problems?
Provide a brief description of those people
"hanging out," their activities, and the problems
at that location. Indicate on the map any problem
locations.

24.  Are there any drug locations in the zone? Mark
on the map any drug locations or suspected drug
locations.
Yes    Number                   No

25.  Any other comments or observations about the
zone:
  
Appendix B: 

Example of a Block Environmental Problem
Identification Survey

This survey was constructed by John Meeks for the
Philadelphia Police Department as part of the 
Problem-Oriented Approach to Drug Enforcement
project. This instrument is an example of a survey
form useful for assessing physical environmental
conditions in small areas. Such an instrument could
be used routinely to code block conditions and
compare them over time, or as part of a single
period problem-solving effort in a community.
Usually, several blocks would be coded. One form is
completed for each block for each survey wave. This
instrument is based on similar survey instruments
used in previous studies (see the citations listed
in appendix A) and is related to the instruments
shown in appendixes A and C.

General Instructions

1.  Be sure to fill in the date (month, day, year),
day of week, and time started. For day of week:
Monday=1, Tuesday=2, Wednesday=3, Thursday=4,
Friday=5, Saturday=6, Sunday=7. For time started,
be sure to circle AM or PM. For rater, put your
name.

2.  Check the street signs to make sure that you
are at the block that is supposed to be rated.
Check the block number. Rate only that particular
block selected for the survey even though the
street may continue for several more blocks.

3.  Be sure to write down all cross streets that
intersect that particular block being surveyed.
Again, keep in mind the block number before writing
down the cross street(s).

4.  For purposes of this survey, a street block is
defined as having two facing sides of the street,
extending between and bounded by cross streets.
Check to make sure that both sides of the street
have address numbers.  Corner properties should
only be included as part of the block if their
address is listed on the block being surveyed.

Specific Item Instructions

1.  Type of street layout: use the diagram provided
below to code the type of street layout. Again, the
focus is on the type of street layout for the block
being surveyed, not the entire street. If the block
does not match one of the street layouts in the
diagram, check "other" and draw the street layout
in the space to the right of it.                   
   
2.  Street width: it is important here that you do
not count the same lanes in more than one category.
Drivable lanes refer to designated driving lanes
(not turning lanes or shoulders). Parking lanes are
strictly for parking only. A median includes a
turning lane or raised divider.

3.  Traffic flow: be sure to count both overhead
and low traffic signals.

4.  Traffic volume: this may be a tough question
because the volume of traffic may vary depending on
the time of the day. Based on your observations and
knowledge of the street, rate it according to the
category that best describes the traffic volume
overall. For example, if it has a light volume of
traffic during the day or week and a heavy traffic
volume at nights or on weekends, you might want to
adjust your rating accordingly.

5 & 6.  Street lighting: be sure to count both high
overhead street lights and pedestrian lights. Do
not count light poles on someone's property. In
daylight it will be difficult to determine whether
a street light is broken. Assume that it works
unless you see broken glass (e.g., a broken bulb or
cover).

7.  Abandoned automobiles: count one abandoned if
it appears nondrivable (i.e., has shattered
windows, dismantled body parts, missing tires,
missing tags). For our purposes here, consider it
abandoned if it appears that it has not been driven
in some time, and it appears that it is not going
to be for some time to come.

8.  Public property with graffiti: public property
refers to property owned by the city or major
utilities such as signs, light poles, telephone
poles, and statues. Count spray paint, posters, and
flyers as graffiti. Consider posters or flyers as a
problem if there are more than three in any one
spot. Do not count murals as graffiti.

9.  Private property with graffiti: private
property includes houses, apartment buildings,
businesses. Again, count spray paint, posters and
flyers as graffiti. Consider posters and flyers as
a problem if there are more than three in any one
spot. Do not count murals as graffiti.

10.  Based on your observations, do you feel that
there is a graffiti or flyer problem on the block?
You might want to write down any specifics, or ways
that may help solve the problem.

11.  Number and type of people visible on the
block: be sure to count and categorize everyone
visible outside on the block. "Hanging" should
include those standing around and/or socializing.
"Working" should include those who are working on
their houses, yards, or cars. If someone else is
working on the block (such as a street sweeper, gas
or water repairperson, meterperson, phone or
electric person, mailperson) count them as "other."
Try to do the best you can in estimating the ages.
If there are two raters doing the same block, both
should take a head count at the same time to avoid
large discrepancies. Also try to describe the
locations of these people. For example, if you see
10 young males playing, indicate whether they are
playing in a park, playground, or alley, etc.

12.  In determining whether the block has a litter
problem, rate sidewalks and property fronts as one
separate unit and curbs and streets as another.
Count something as litter if it is bigger than your
shoe. Do not count rolled newspapers, gum wrappers,
cigarette butts, etc. Do count bottles and cans. In
trying to determine the extent of the litter
problem, consider a rating of no litter to a few
pieces as "acceptable," and several pieces to small
piles as "unacceptable." If unacceptable, the block
could use some organized cleaning.

13.  Number and type of open land use: just count
up the number of each type that appears on the
block. Keep in mind the boundaries of the block. If
a vacant lot is used as a parking lot, code as
"other" and give a brief description of how the
vacant lot is being used. To distinguish between
"playgrounds" and "public courts" or "park," code
as a playground if there is playground equipment.
Otherwise, code it as a park or court. "Parking
lots" refer to official or actual parking lots. For
each type of open land use, indicate whether it has
a litter/trash/junk and/or graffiti problem. Use
one column for each land use. There is enough space
to rate up to four different vacant lots, 
playgrounds, etc.

14.  Type of street block: the objective here is to
determine the makeup of the street block.
"Residential" includes apartments, condominiums,
townhouses, rowhouses, and single homes.
"Commercial" includes stores, bars, restaurants,
and other service businesses.
"Industrial-manufacturing" includes any factories
or manufacturing plants on the block.
"Institutional" includes schools and churches.
"Abandoned-vacant" buildings include both empty
shells and buildings that may be temporarily
vacant. If the block is mixed, indicate what type
predominates (i.e., commercial, residential, etc.).

15.  Housing style: indicate which type
predominates on the block.

16.  Number of abandoned buildings: count only
empty shells or places that are going to take some
rehabilitation before someone could move in.

17.  Number of vacant buildings: count one vacant
if it appears to be usable or between owners or
rents.

18.  Type of businesses on the block: this may also
be difficult at times to code. Do the best that you
can to code the businesses. When coding one, think
of its primary activity (i.e., does it sell food,
liquor, clothing, services, etc.).

19.  Identifying possible drug locations: check
whether the drug location has been reported to you
or is suspected as a result of your onsite rater
observations. For those blocks that are thought to
be a control (i.e., without a drug location), it is
important to make sure that they are in fact drug
free.

20.  General comments and observations: if you have
questions about how to code something (i.e., that a
question is unclear, or the categories are
inadequate), indicate how you coded it here. You
may also want to write down an observation that is
not captured by the survey instrument.

21.  Address listing: list all the addresses on the
block corresponding to a building.

22.  Number of occupied residential units per
address: this is very important. This is important
because when we do the residential survey, a
criteria for block selection will be the total
number of occupied units. That is, there must be at
least 10 occupied residential units on that block.
Check for the number of doorbells and mailboxes.
Under each address, write the number of occupied
residential units. If an address is a business,
write "B" in the box for occupied units. Unless the
business has some occupied units above it, in which
case count them. For example:

Addresses  300  301  302  303  304  305  310  311 
312  314  315

No. of  occupied resident units   1  1  2  2  4  B 
1  4  2  B  2

BLOCK ENVIRONMENTAL PROBLEM IDENTIFICATION SURVEY
Date:
Day of Week:
Time:    
Rater:  
Street Name:  
Cross Streets:  

1.  Type of street layout:
Through street  0
Through curved  1
H-layout  2
T-layout  3  Number:  
L-layout  4
Court/circle  5
Dead end  6
Other  7

2.  Street width:
Number of drivable lanes.  
Number of parking lanes.  
Is there a median (Yes=1, No=0)  .  

3.  Traffic flow:
Is there a traffic signal on the block? (Yes=1,
No=0).  
Is there a stop sign on the block? (Yes=1, No=0).  
Is there a one-way street? (Yes=1, No=0).  

4.  Volume of traffic flow:
very light  1
light  2
moderate  3  Number:  
heavy  4
very heavy  5

5.  Number of overhead street lights on the block 

6.  Number of broken street lights on the block 

7.  Number of abandoned (nondrivable) automobiles
on the block 

8.  Number of public property (including signs,
light poles, telephone poles, statues) that have
graffiti, posters, or flyers on them. 

9.  Number of privately owned property (includes
houses, and businesses) that have graffiti,
posters, or flyers on them. 

10.  Based on your observations, do you feel there
is a graffiti or poster-flyer problem on this
block? (Yes=1, No=0) 

Any comments or observations:  

11.  List all the people on the block and their
activities (hanging, playing, working, other). Also
be sure to write any comments and descriptions of
your observations describing the location of the
activity (vacant lots, playground, schoolyard,
churchyard, parking lot, public court, alley,
corner, other).

Describe the locations of the activities:  

12.  Does the block have a litter or trash problem?
(Check the appropriate box)
Property Fronts
Curbs and Sidewalks
Streets
No litter  0
Few pieces  1
Several pieces  2
Small piles  3  

13.  Open land use (public land use): for each
category, indicate whether it has a
litter/trash/junk or graffiti problem.
Code Yes=1 No=0
Litter/Trash/Junk
Graffiti
1  2  3  4  1  2  3  4
Vacant lots
Public playgrounds
Schoolyard
Churchyard
Parking lot
Public court/garden
Alleys
Other (specify)

14.  Primary type of block:
Residential  1
Commercial  2
Industrial/manufacturing  3
Institutional  4  Number:   
Abandoned buildings  5
Vacant lots  6
Playgrounds or parks  7
Mixed  8  (specify)  
  
15.  Primary type of housing style:
Apartments  1
Condominiums  2
Row houses  3  Number:   
Townhouses  4
Mixed  5  (specify)  
  
16.  Abandoned buildings (empty shells) on the
block:  

17.  Vacant buildings on the block:  

18.  Types of businesses on the block (check all
that apply):

Grocery, deli, convenience, or food retail store.  
Bar, liquor store, or primarily selling liquor.  
Restaurants, carry outs, or selling ready-to-eat
food.  
Retail, furniture, souvenir shops, or goods sales. 
Services--barber, cleaners, parking garage, etc.   
Support agencies--mental health or medical clinics,
etc.  
Pharmacy/drug stores.  
Other (specify).  

19.  Are there any possible drug houses on the
block? 
(Yes=1, No=0)  

20.  Any comment or observations about the block:  

21.  List all addresses

22.  No. of occupied residential units/address

Addresses and occupied residential units
continued...
21.
22.

Addresses and occupied residential units
continued...
21.
22.

Addresses and occupied residential units
continued...
21.
22.

Addresses and occupied residential units
continued...
21.
22.

Appendix C: 

Example of a Drug "Hot Spot" Survey

This instrument was developed to help analyze the
physical conditions around businesses that may
contribute to drug dealing. It was developed by
John Meeks as part of a set of environmental survey
instruments (see appendixes A and B) to help police
understand drug problems in communities. Though
this instrument is designed to guide observations
of drug dealing around business locations, with
modifications this instrument can be adapted for
analyzing drug (or other problems) in and around
residential and recreational areas. Coding
instructions can be found in appendixes A and B.

DRUG "HOT SPOT" RATING INSTRUMENT: BUSINESSES
Date:
Day of Week:
Time:    
Rater:  
Location:  
Name of Business:  

I.  TYPE OF BUSINESS
Check most appropriate description:
a.  Food stores: grocery, supermarket, convenience
store
b.  Restaurants, fast-food, carry-outs, deli
c.  Bar, liquor store
d.  Retail stores: department, clothing, shoes,
sporting goods, jewelry, music, hardware, pharmacy
e.  Service: barber shop, beauty salon, cleaners,
automotive, post office, printing shop, travel
agency
f.  Support agencies: Salvation Army, United Way,
mental health clinic, alcohol or drug abuse
treatment clinic, medical facility, unemployment
agency
g.  Undesirables: porno shop, pawn shop, massage
parlor, amusement arcades
h.  Recreation: gyms, clubs, spas
i.  Wholesale warehouses, distributors
j.  Financial: banks, check cashing, finance
company
k.  Other (specify)  

II.  CONDITIONS OF BUSINESS
Note:  For items 1 through 3, code all remaining
items as
No=0, Yes=1, Not visible (NV)=2, Not applicable
(NA)=3

1.  Any missing front wall material such as brick,
stone, stucco, siding, or other signs of a
structural problem? (Count wall material missing if
the hole (or gap) is bigger than 1 foot.)

2.  Any broken fixtures such as doors, windows,
awnings, neon signs, or lights?

3.  Any graffiti?

4.  Any other signs of a general lack of
maintenance?

5.    Rate the overall conditions and appearance of
the building in terms of structural soundness,
neatness, and cleanliness:
Very Good
Good
Fair
Poor
Very Poor

III. CONDITIONS OF GROUNDS
Note:  For items 1 through 3, code all remaining
items as No=0, Yes=1, Not visible (NV)=2, Not
applicable (NA)=3

1.  Any litter (more than five pieces bigger than
2" x 2")?

2.  Any broken glass or bottles (more than
2-square-foot area)?

3.  Any junk such as appliances, furniture, tires,
abandoned automobiles?

4.  Rate the overall conditions and appearance of
the premise in terms of cleanliness,
beautification, health, and safety:
    Very Good
    Good
    Fair
    Poor
    Very Poor

IV.   CHARACTERISTICS OF BUSINESS

Note:  For items 1 through 3, code all remaining
items as No=0, Yes=1, Not visible (NV)=2, Not
applicable (NA)=3
1.  Any security bars or gates over windows?
2.  Any windows sealed with bricks?
3.  Any windows boarded up?
4.  Is the entrance used for drug sales in plain
view from the street or public walkway?
5.  Is the entrance used for drug sales easily
accessible from the street or walkway?
6.  Is there any security alarm sticker, "beware of
dog" sign, or surveillance camera?
7.  Is the business located next to another
business?
8.  Is the business located next to a vacant or
abandoned building?
9.  Is the business located next to or in the
immediate vicinity of an open land use such as a
street corner, vacant lot, public playground, park,
schoolyard, churchyard, parking lot, or alley?
10.  Is the business a mixed unit with an apartment
overhead?
11.  List business hours:  

V.  INTELLIGENCE INFORMATION

1.   What types of drugs are sold at the drug
location?

a.  Powder cocaine.    d.  Methadone.
b.  Crack cocaine.    e.  Marijuana.
c.  Heroin.    f.  Pills.
g.  Other.
  
Note:  For items 1 through 3, code all remaining
items as No=0, Yes=1, Not visible (NV)=2, Not
applicable (NA)=3

2.  Any unusual kinds of activity such as excessive
foot or vehicular traffic?

3.  Any people sitting outside or "hanging out" at
the drug location or immediate vicinity?

4.  List and describe all people at the drug
location or immediate vicinity, including such
items as age, sex, race, and car make or model.
  
5.  Any other unusual characteristics, activities,
or impressions at the drug location? Does the drug
activity vary by time of day or day of week?
  
VI.  BLOCK CHARACTERISTICS

1. Type of street layout: Mark the drug location on
the matching street layout. If the street does not
match any in the diagram, draw the street and mark
the drug location.
  
2. Type of street:
  a.  Main thoroughfare
  b.  Residential street block
  c.  Side street of alley
  d.  Business complex
  e.  Apartment complex road

3.    Traffic flow:
  a.  One-way street
  b.  A stop sign or traffic signal at the drug
location or immediate vicinity

4.  Street width:
  a.  Number of drivable lanes
  b.  Number of parking lanes
  c.  Median (Yes=1, No=0)

5.  Number of overhead street lights at drug
location or immediate vicinity         

6.  Number of broken overhead street lights 

7.  Number of public fixtures such as street signs,
light poles, bridges, statues at the drug location
or immediate vicinity marked with graffiti 

8.  Number of privately owned structures such as
houses or businesses at the drug location or
immediate vicinity marked with graffiti 
  
9.  Type and number of open land use at the drug
location or immediate vicinity. Place the total
number of each in the blank.
  a.  Vacant lots
  b.  Public playgrounds  
  c.  Schoolyard      
  d.  Churchyard      
  e.  Parking lot      
  f.  Public court/garden   
  g.  Alleys         
  h.  Other (specify) 

10.  Type of drug location/vicinity:
  a.  Residential
  b.  Commercial
  c.  Industrial/manufacturing
  d.  Institutional
  e.  Abandoned buildings
  f.  Vacant lots
  g.  Playgrounds or parks
  h.  Mixed (specify)  

11.  Primary type of housing style:
  a.  Single-family--detached or attached
  b.  Apartments or condominiums
  c.  Businesses with apartments overhead
  d.  No housing at drug location
  e.  Other (specify)  

12.  Types of businesses on the block (check all
that apply):
  a.  Grocery, deli, convenience, or food retail
store
  b.  Bar, liquor store, or primarily selling
liquor 
  c.  Restaurants, carry outs, or selling
ready-to-eat food
  d.  Retail, furniture, souvenir shops, or goods
sales
  e.   Services--barber, cleaners, parking garage,
etc.
  f.  Support agencies--mental health or medical
clinics, etc.
  g.  Pharmacy/drug stores
  h.  Recreation: gyms, clubs, spas
  i.  Wholesale warehouses, distributors
  j.  Financial--banks, check-cashing
establishments, finance company
  k.  Other (specify)  

13.  Street signs identifying area as part of a
block or neighborhood watch or other citizen anti- 
crime group    
  
14.  Describe any other unusual physical
characteristics such as distinctive topography,
housing style, conditions, ornamentation (e.g.,
identical lamps, planters, railings, awnings, paint
designs), anything that might show a sense of
community or organization within the zone.
      
15.  Any other comments or observations  
      
Appendix D:

Example of a Situational Environmental Survey Used
for Analyzing Convenience Store Problems

This instrument is slightly edited from one
developed by the author for analyzing problems in
and around convenience stores. It was applied to a
sample of such stores in Austin, Texas.

CONVENIENCE STORE SITE OBSERVATION SURVEY
Survey No.  
Date:
Day of Week:
Time:    

Store Name  
Street Address  

PART I--INTRODUCTION/QUESTIONS FOR CLERK

Hi, my name is      and I'm with the University of
Texas. I'm conducting a survey of crimes that take
place at convenience stores and how we can go about
preventing these crimes. I'd like to ask you a few
questions and then take a look around the store.
First, I should tell you that your answers will be
held in the strictest confidence and your name will
not be used in my study. If you want to end the
interview at any time, please say so, and if you do
not want to answer a particular question, just tell
me and I'll move on to the next one, okay?

1.  How long have you been working at this
particular store?
  a.  Less than a month
  b.  One to six months
  c.  Six months to a year
  d.  More than a year

2.  What is your job title?
  a.  Clerk
  b.  Manager
  c.  Owner
  d.  Other (specify)   

3.  Who owns this store?
  a.  Store chain
  b.  Privately owned
  c.  Franchised
  d.  Other (specify)   

4.  Has the store ever been robbed to your
knowledge?
  a.  Yes
  b.  No
  c.  Do not know
If yes,
  d.  How many times?
  e.  Were you present at the scene of any of these
crimes? (Yes=1, No=0)
If yes,
  f.  How many other employees, in addition to
yourself, were in the store at the time of each
crime?
  g.  How many customers, not including the
offender, were in the store at the time of the
crime?

5.    a.  Does your store have a robbery-prevention
training program for its employees? (Yes=1, No=0)
    If yes,
  b.  Have you participated in this program?
(Yes=1, No=0)

6.  How frequent are shoplifting incidents?
  a.  Once a day or more
  b.  Once a week
  c.  Once or twice a month
  d.  Once a year or less

7.  What do shoplifters usually take?  

8.  Do you have an automatic lock button by the
counter to keep out customers? (Yes=1, No=0)

9.  Do you have a robbery alarm? (Yes=1, No=0)
    If yes,
    Is the store directly connected to the police
department? (Yes=1, No=0)

10.  Is there a group of people that consistently
hangs around the store?
 a.  Yes
 b.  No
 c.  Do not know
If yes,
 d.  What is the approximate age of the group?
  i.  Under age 13
  ii.  13 to 17 years old
  iii.  18 to 25 years old
  iv.  26 to 50 years old
  v.  Over 50 years old
 e.  How would you describe the character of the
group?  
        
11.  Does your store have a policy of giving coffee
to police officers free of charge?
 a.  Yes
 b.  No
 c.  Do not know

12.  Of the following list of crimes, how often do
you think each of these have occurred at this store
or in the   store parking lot within the last 30
days? (Fill in 0 or number of times.)
 a.  Shoplifting
 b.  Beer runs
 c.  Robbery
 d.  Drug dealing
 e.  Underage purchase or consumption of alcohol
 f.  Gasoline drive-offs (if applicable)
 g.  Physical assault
 h.  Vandalism
 i.  Burglaries/break-ins
 j.  Other (specify)   
      
13.  Can you tell me your impressions of the level
of security in this store and what you think can be
done to discourage the crime that goes on here  
      
14.  How many clerks do you normally have on duty
during the night shifts?
 a.  One clerk
 b.  Two clerks
 c.  Other (specify)   

15.  On a scale of 1 to 5, with 1 being the lowest
and 5 being the highest, how fearful are you about
your personal safety when:
a.  You are working alone during the night shifts?
1  2  3  4  5  Do not know (0)  N/A (9)

b.  You are working with another clerk during the
night shifts?
1  2  3  4  5  Do not know (0)  N/A (9)

PART II--DETAILS OF OPERATIONS

16. Is the store open 24 hours? (Yes=1, No=0)
If not, what are hours of operation? 

17. Types of surveillance? (place total number of
each in appropriate box)
a. Closed-circuit TV(s)?
b. Parabolic mirror(s)?
c. Regular mirror(s)?
d. Private security guard(s)?
If yes,
e. Off-duty police officer(s)? (Yes=1, No=0)
f. Is guard armed? (Yes=1, No=0)

18. Video games in store? (Yes=1, No=0)

19. ATM machine in or right outside store? (Yes=1,
No=0)

20.  a. Cold beer/wine sold? (Yes=1, No=0)
If yes,
b. Single beer/wine sold? (Yes=1, No=0)

21. Interior lighting
How brightly lit is inside of store? (use light
meter)

22. Cash register
a. Type of register (check one)
 i. Raised register
 ii. Deep register
 iii. Other (specify)  
b. Height of register counter (approximate footage)
c. Location of register in store (check one)
 i. To immediate right or left of door
 ii. In center of store
 iii. In back of store
d. Number of entrances/exits to store

23. What percentage of the windows are covered with
posters/advertisements or blocked by stacked boxes?
a. Less than 25 percent
b. 25 percent to 50 percent
c. More than 50 percent

24. Obstacles to surveillance
a. Number of interior blind spots (places where
customer is not in view of register or door)
b. Height of shelves (approximate, in feet)

25. Size of store (approximate square footage) 

26.  a. Number of clerks on duty
b. Age of clerk No. 1
c. Age of clerk No. 2
d. Sex of clerk No. 1 (Male=1, Female=0)
e. Sex of clerk No. 2 (Male=1, Female=0)

27.  Is there a back room or bathroom in the store?
(Yes=1, No=0)

28. Sign indicating robbery alarm system? (Yes=1,
No=0)

29. Sign indicating limited cash on hand? (Yes=1,
No=0)

30. Sign indicating safe is inaccessible to clerks?
(Yes=1, No=0)

31. Sign indicating closed-circuit TV? (Yes=1,
No=0)

PART III--SURROUNDINGS

Survey No. 
Store Name 
Street Address 

32. Area (check only one)
a. Primarily retail/commercial area
b. Primarily residential area
c. Primarily industrial area
d. Primarily institutional area
e. Primarily office buildings
f. Mixed  

33. Are any of these adjacent to store? (directly
across, next door, or behind store)
a. School
b. Park/playground
c. Wooded area
d. Liquor store
e. Pornography shop/x-rated movie house/massage
parlor
f. Bar
g. Restaurant
h. Police precinct or substation
i. Other 24-hour establishment. List type 
j. Abandoned houses or stores
k. Other (specify)   

34. Sketch location of store in relation to streets
and parking lot (on corner, in middle of street,
etc.). Include names of cross streets and where
entrances/exits to parking lots are located.

35. How far is store set back from street? (Check
category that most closely applies.)
a. 25 feet
b. 50 feet
c. 100 feet
d. Other (specify)  

36. Check type of street store is on:
a. Through street
b. Through curved
c. T-layout
d. L-layout
e. Court, circle, or cul-de-sac
f. U-shaped
g. Dead end
h. Other (specify)  

37. Is store located on a corner? (Yes=1, No=0)
Note:  For the questions to follow, "block" is
defined as the areas on both sides of the street on
which the store is located, separated by the
nearest cross streets or street endings on each
side. A corner building is part of the block only
if its street address corresponds with the name of
the street on the convenience store is located.

38. What is the speed limit on the block?

39. Street width (count for both sides of street
and count only the street that the front of the
store is facing):
a. Number of drivable lanes
b. Number of parking lanes
c. Is there a median? (Yes=1, No=0)
d. Is there a "chicken lane" (for turning)? (Yes=1,
No=0)

40.  a. Number of overhead streetlights (only on
side of street facing store)
b. Number of broken overhead streetlights (only on
side of street facing store) 

41. Number of abandoned (nondrivable) automobiles
on block (look for absence of tags, missing tires,
shattered windows)

42. On a scale of 1 to 5, with 1 being the least
and 5 being the most, how much graffiti is visible
on the block?
1 2 3 4 5

43.  a. Is there a parking lot for the store?
(Yes=1, No=0)
If so,
b. How many spaces in parking lot? (count only
those that have lines indicating spaces)
c. How many street exits?
d. Is cash register visible from lot? (Yes=1, No=0)
e. How many cars parked in lot?
f. How brightly lit is the parking lot?
i. Light meter reading under entrance to store
ii. Light meter reading at farthest end of parking
lot

44. On a scale of 1 to 5, with 1 being the least
and 5 being the most, how littered is the area
immediately adjacent to (next to, in front of, or
behind) the store?  1 2 3 4 5

45. How much litter is on curbs, in street, and in
parking lot surrounding store? (check only one)
a. No litter
b. Few pieces
c. Several pieces
d. Small piles

46. Is there a bus stop on the block? (Yes=1, No=0)

47. How many pay phones?
a. Inside and directly outside of store?
If number is greater than 0,
b. How many phones show phone numbers so people can
call in? (enter number of phones with numbers) 
c. How many phones are in working order? (enter
number)

48. Are there bars on store's windows, doors, or
both? (Yes=1, No=0)

49. Double-plated or bullet-resistant glass for
store windows? (Yes=1, No=0) 

50.  a. Number of people congregating for more than
5 minutes on the block.
If number is greater than 2, 
b. Average age of people congregating.
c. Is group mostly male (1) or mostly female (0)?

51. Volume of traffic flow:
a. Very light
b. Light
c. Moderate
d. Heavy
e. Very heavy

52. How many gasoline pumps? (count handles) 
If number greater than 0, 

53. Is there a prepay gas policy? (Yes=1, No=0)

54. Is a clerk normally in view of pumps? (Yes=1,
No=0)

PART IV--OTHER FACTORS

55. Is there a neighborhood crime prevention
program?

56. What is traffic density and flow by time of
day? (Get from city traffic department)

57. What is income level of neighborhood? (Get from
census tract data) 

58. Type of sales in store.

59. Total dollars in tax receipts for last fiscal
year?

60. Police calls for service by type: 

NCJ 143711