Lynch et al. BMC Public Health 2014, 14:899
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RESEARCH ARTICLE

Open Access

Development and testing of a past year measureof sedentary behavior: the SIT-Q
Brigid M Lynch1,2*, Christine M Friedenreich3,4, Farah Khandwala3, Andrew Liu3, Joshua Nicholas3
and Ilona Csizmadi3,4

Abstract
Background: Most sedentary behavior measures focus on occupational or leisure-time sitting. Our aim was to develop
a comprehensive measure of adult sedentary behavior and establish its measurement properties.
Method: The SIT-Q was developed through expert review (n = 7), cognitive interviewing (n = 11) and pilot testing(n = 34). A convenience sample of 82 adults from Calgary, Alberta, Canada, participated in the measurement property
study. Test-retest reliability was assessed by intraclass correlation coefficients (ICCs) comparing two administrations of
the SIT-Q conducted one month apart. Convergent validity was established using Spearman’s rho, by comparing the
SIT-Q estimates of sedentary behaviour with values derived from a 7-Day Activity Diary.
Results: The SIT-Q exhibited good face validity and acceptability during pilot testing. Within the measurement property
study, the ICCs for test-retest reliability ranged from 0.31 for leisure-time computer use to 0.86 for occupational sitting.
Total daily sitting demonstrated substantial correlation (ICC = 0.65, 95% CI: 0.49, 0.78). In terms of convergent validity,
correlations varied from 0.19 for sitting during meals to 0.76 for occupational sitting. For total daily sitting, estimatesderived from the SIT-Q and 7 Day Activity Diaries were moderately correlated (ρ = 0.53, p < 0.01).
Conclusion: The SIT-Q has acceptable measurement properties for use in epidemiologic studies.
Keywords: Sedentary behavior, Sitting time, Questionnaire, Cognitive interviewing, Reliability, Validity

BackgroundA growing body of evidence suggests that sedentary behavior (time spent sitting or reclining) is independently
associated with all-cause and cardiovascular mortality[1-4], cardiovascular disease [5,6], type 2 diabetes [7,8],
and some cancers [9]. Sedentary behavior appears tohave physiological consequences, distinct from the effects associated with an absence of moderate- tovigorous-intensity physical activity, that may further
contribute to chronic disease risk [10,11].
Assessment of habitual patterns of physical activity
and sedentary behavior are necessary to study associations with health outcomes [12,13]. Measurement ofphysical activity and sedentary behavior by devices such
* Correspondence: brigid.lynch@bakeridi.edu.au
1
Physical Activity Laboratory, Baker IDI Heart and Diabetes Institute,
Melbourne, Australia
2
Melbourne School of Population and Global Health, Faculty of Medicine,
Dentistry and Health Sciences, The University of Melbourne, Melbourne,
Australia
Full list of author information is available at the end of the article

as accelerometers or heart rate monitors can objectively
measure duration, intensity and frequency. However, objective measures generally collect data over brief periodsof time necessitating serial measurements for the ascertainment of habitual patterns of behavior. Further, objective methods do not provide behavioral context, andthey may not be feasible for use with large, geographically dispersed samples. The cost of monitors, complexityof data processing and analysis, problems with compliance and burden on participants also limit their use inlarge population-based studies [14]. Hence, self-report
methods of data collection are likely to remain the primary methods whereby activity will be quantified in epidemiological studies, especially for studies with limited
economic resources [15,16].
Existing self-report measures of sedentary behavior typically focus on either occupational sitting, or leisure-time
pursuits such as television viewing and reading [17-21].
Additionally, some physical activity questionnaires, notably the International Physical Activity Questionnaire© 2014 Lynch et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative
Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, andreproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain
Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article,
unless otherwise stated.

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Page 2 of 12(IPAQ), include a global item that asks respondents to report their total sitting time [22]. Currently, few questionnaires attempt to assess adult sedentary behavior acrossmultiple domains [23]. Such measures are necessary inorder to determine whether the behavioral context is important in the associations between sedentary behavior
and chronic disease [11,24]. To address this need we developed the SIT-Q, a measure of habitual sedentary behaviors across occupation, transportation, household andleisure-time domains. Our aim was to develop a feasible
and cost-effective measure of usual sedentary behavior for
use in population cohort studies.

This report describes the development of the SIT-Q andthe measurement properties of the questionnaire, specifically the test-retest reliability and convergent validity.

Methods
This study was comprised of two distinct components:
the development of the SIT-Q through a three staged
approach of expert review, cognitive interviewing andpilot testing; and establishing the measurement properties of the SIT-Q (see Figure 1). The Alberta Cancer
Research Ethics Committee of Alberta Health Services
approved the procedures for all elements of this study.

DEVELOPMENT OF THE SIT-Q
EXPERT
REVIEW

Expert review (n = 7)
Revisions

COGNITIVE INTERVIEWS

Cognitive interviews (n = 3)
Revisions
Cognitive interviews (n = 3)
Revisions
Cognitive interviews (n = 5)

PILOT
TEST

Pilot testing (n = 34)

MEASUREMENT PROPERTY STUDYMAREE STUDYMEASUREMENT PROPERTY STUDY

Figure 1 Data collection protocol.

Recruitment to study (n = 106)
Baseline measures taken (n = 106)

Day 0

Day 7 Day Activity Diary begun (n = 104)

Day 15Declined to participate/did not respond (n = 24)
Recruited to SIT-Q study (n = 82)
7 Day Activity Diary completed (n = 76)

Month 9SIT-Q completed (n = 82)

Month 10

SIT-Q completed (n = 64)

Month 11

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Development of the SIT-Q

The first version of the SIT-Q comprised 18 items acrosssix different domains (sleeping and napping; transportation; employment and volunteer activities; meals; leisuretime; household chores and do-it-yourself tasks). Common sitting or reclining tasks were identified from theCompendium of Physical Activities [25], the American
Time Use Survey [26], and from a self-report measure ofactivity energy expenditure (the Sedentary Time and Activity Reporting Questionnaire; STAR-Q) developed by
one of our study team [27]. We also created items pertaining to whether or not more prolonged sedentary behaviors were interrupted by standing or walking breaks,
as patterns of sedentary behavioral accumulation havebeen shown to affect health outcomes [28,29]. The SITQ recall period was past 12 months, and participants
were instructed to estimate their usual activity pattern.
Sedentary behaviors were assessed separately for weekdays and weekends, to facilitate recall.
Expert review

The SIT-Q was reviewed for logical and face validity byinternationally recognized experts in sedentary behavior
conceptualization, measurement, analysis and interpretation. Nine experts were identified and sent an email
requesting their participation in the expert review; allagreed to participate and were sent the questionnaire.
Experts were asked to provide general feedback and to
specifically comment on: (i) the domains covered; (ii)whether the order items was logical and likely to help
minimize double-counting of time; (iii) the clarity of instructions; and (iv) whether the response formats wereappropriate for the data being collected.
Cognitive interviewing

Cognitive interviewing is an important, but often overlooked, step in questionnaire development [30,31]. Thismethod can identify misunderstandings of text that could
lead to response error and can provide insight into ways
in which respondents comprehend, retrieve and formulate
their answer [31]. The two main methods used in cognitive interviewing are think aloud and verbal probing.
When using the think aloud technique, the interviewee is
asked to answer a question and additionally to talk about
what he or she is thinking while reaching that answer.
Verbal probing is used by the interviewer to probe for
additional information relevant to the specific answer
given [31].
Cognitive interviews were conducted by an MSc trained
nurse-researcher to evaluate the feasibility of the SIT-Q as
a self-administered questionnaire. Participants were primarily drawn from members of the Alberta Tomorrow
Project (a province-wide longitudinal study) cohort, who
had volunteered, but been deemed ineligible for, thePage 3 of 12

Measuring Activity Related Energy Expenditure (MAREE)
study. Convenience sampling was used to ascertain additional participants. All participants provided informed,
signed consent prior to being interviewed.
The cognitive interviews were audio-taped and transcribed for analytic purposes. Based on these notes, theinterviewer identified key themes representing sourcesof difficulty or confusion after each interview. These
were summarized and discussed with the investigators
after a “round” of three interviews. The insights gained
from the interviews were used to revise the design of thequestionnaire and to re-word the text for another roundof cognitive interviewing.
Pilot testing

Convenience sampling was used to recruit participants
for the pilot study. Forty-five volunteers were sent a
copy of the SIT-Q (see Additional file 1), a consent form,a participant characteristics questionnaire, and a pilot
testing feedback questionnaire. The pilot testing feedback questionnaire was designed to elicit information on
the ease of the completion of the SIT-Q and on the clarity of the instructions and item wording. All questionnaires were completed by the participant in their own
time and returned in a provided postage-paid envelope.
Measurement property study

Participants of the MAREE Study (n = 106) were invited
to participate in the SIT-Q measurement property study.
The primary aim of the MAREE Study was to validate aself-report measure of activity energy expenditure (STARQ) against doubly-labeled water. As part of the MAREE
Study protocol, participants completed a 7-Day Activity
Diary two weeks after their recruitment (see Figure 1).
The SIT-Q measurement property study entailed a second
administration of the 7-Day Activity Diary, followed by two
administrations of the SIT-Q, one month apart (Figure 1).
The two administrations of the 7-Day Activity Diary
allowed us to generate mean estimates of sedentary behaviors from diaries completed at different times of theyear, but within the same reference period that wasassessed by the SIT-Q.
7-Day Activity Diary

The 7-Day Activity Diary involved recording the following details for each daily task: time task started; brief description of the task; position (recline, sit, stand, walk, inmotion); activity group (self-care, household, occupation,
walking for pleasure, care giving, transportation, yard
work, exercise and conditioning, light leisure activity,
sleeping, other); and physical effort (mainly sitting,mainly standing/no increase in heart rate, slight increasein heart rate, substantial increase in heart rate). The 7day activity diary was adapted from Conway et al. [32]

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and was designed to ascertain sleep time as well as all
activities (10 minutes or longer, or activities that caused
a noticeable change in physical effort) and posture while
awake. Participants were instructed to detail their activities in the 7-Day Activity Diary throughout the courseof each day, rather than completing the diary each evening or at the end of the week.
Time spent in sedentary behaviors was estimated by two
methods. The first estimated sedentary time from all tasks
performed in a reclining or sitting position (postural definition). The second method assigned a metabolic equivalent (MET) level from the Compendium of Physical
Activities [25] based on the brief description of the task
and physical effort indicated, and was operationalized as
behaviors ≤ 1.5 METs (MET definition). Sedentary behaviors were summarized into domains that matched those of
the SIT-Q: meals; transportation; work, study and volunteering; childcare and eldercare; and, leisure time. Severalof the activity group categories of the 7-Day Activity Diary
were directly comparable to SIT-Q domains (transportation, occupation, care giving, and light leisure activity).
We were not able to determine television viewing andcomputer use time separately from the 7-Day Activity
Diary data (these were often jointly reported and hence
amalgamated into leisure time sedentary behaviour).
The self-care activity grouping corresponded with themeals domain (although self-care also included a minimal amount of time spent sitting during personal
grooming activities), and a small amount of sitting time
recorded within the household activity group was reallocated to light leisure activity. There were no sedentary behaviors recorded within the walking for pleasure,yardwork or exercise and conditioning activity groups,
and sleeping was excluded from our analyses as this is
not considered a sedentary behavior.
SIT-Q

Participants were sent a copy of the SIT-Q one monthafter the 7-Day Activity Diary, and a second copy of the
SIT-Q one month after the first (see Figure 1 for data collection overview; see Additional file 1 for SIT-Q). Allquestionnaires were returned by mail, and participants received up to three telephone calls to follow-up unreturned
questionnaires. Importantly, all measures were completed
within a 12-month period, commensurate with the 12month recall period of the SIT-Q.
Data were manually entered into a database and any
outlying responses were checked against the original questionnaires. Sedentary behaviors were assessed separately
for weekdays and weekends within each domain except
work, study and volunteering. Sedentary behavior during
work, study and volunteering was reported based on
weeks per year, days per week and hours per day. Given
that most individuals did not work on a daily basis, thePage 4 of 12

descriptive statistics for each type of “job” (work, study or
volunteering) were summarized as hours or minutes ofsedentary behavior in this domain per week. To facilitate
estimation of total sedentary time, average minutes per
day were calculated for each sedentary behavior.
Statistical analyses

Analyses were conducted using StataSE 12.0 (StataCorp
LP, College Station, TX) and SAS/STAT® software (version
9.2) SAS System for PC. None of the sedentary behavior
variables were normally distributed, except for total sedentary time. We therefore summarized sedentary behavior
variables as median (interquartile range median; IQR) for
all variables except for total sitting time, which was summarized as mean (standard deviation).
Test-retest reliability was assessed by intraclass correlation coefficients (ICCs) comparing two administrationsof the SIT-Q, conducted one month apart. The ICCs formeals, transportation, work (incorporating study andvolunteering), caring duties and leisure-time domains
were estimated overall and separately for weekday andweekend days. We also examined the ICCs for televisionviewing and computer time, as these behaviours havefrequently been assessed in sedentary behaviour measurement studies. ICCs were interpreted as follows: <0.40
indicated poor agreement; 0.40–0.74 fair to good agreement; ≥0.75 excellent agreement [21,33]. Mean differences and 95% confidence intervals (CIs) between thefirst and second administrations of the SIT-Q were estimated. A Bland-Altman plot [34] of differences against
means for each domain of sedentary behaviour was used
to describe agreement at the individual level. Finally, theconsistency with which participants rated how frequently
they interrupted their prolonged sitting was assessed bypercent agreement (%) and a weighted kappa statistic(wκ) [35] with the default weights matrix in Stata 12.0.
Landis and Koch’s guide for interpreting agreement for
categorical data was utilised: ≤0.20 slight; 0.21–0.40 fair;
0.41–0.60 moderate; 0.61-0.80 substantial; >0.80 almost
perfect [36]. Statistical significance was set at P < 0.05.
Convergent validity was established using Spearman’srank correlation coefficient (ρ), by comparing domainspecific estimates of sedentary behaviour from the firstadministration of the SIT-Q with the mean values derived from two administrations of the 7-Day Activity
Diary, completed eight months apart. Comparisons weremade across the activity group categories of the 7-Day
Activity Diaries that corresponded closely with domainsof the SIT-Q, namely self-care (this section included
time sitting for meals and grooming); transportation; occupation; care giving; and light leisure activity. All sedentary behaviors were incorporated into these domains,and each domain was considered overall and separately
for weekdays and weekend days. The strength of theLynch et al. BMC Public Health 2014, 14:899
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correlations between the SIT-Q and the 7-Day Activity
Diary was interpreted using the following: weak (<0.30);
low (0.30–0.49); moderate (0.50–0.69); strong (0.70–0.89); very strong (≥0.90) [37]. Mean differences and
95% confidence intervals (CIs) between the SIT-Q and
7-Day Activity Diary estimates of sedentary behaviour
were also estimated.

Results
Development of the SITQ
Expert review

The initial version of the SIT-Q contained 20 items
grouped within six domains: sleeping and napping; transportation; employment and volunteer activities; meals;
leisure-time; and, household chores and do-it-yourself.
Formal review was completed by seven of the nine invited
sedentary behavior experts. Overall, the feedback received
was positive and few substantial changes were suggested.
Experts had been asked to respond specifically to four
points. With regard to the domains covered by the SIT-Q,
there was broad agreement that the questionnaire hadcovered the major domains. In relation to the order of the
SIT-Q items, the expert reviewers all agreed that a logicalflow is important for minimizing double-counting of time,
and they concurred that the order of the SIT-Q items was
sensible. One expert made the recommendation that atable of contents be included inside the front cover of thequestionnaire: providing participants with an understanding of where and when they can report time spent invarious seated tasks might also help to prevent somedouble-counting of time. Two of the reviewers recommended including driving to and from work in the transportation section, rather than within the Employment andVolunteer Activities domain, to prevent respondents from
reporting this travel time twice. While most of the reviewers indicated that the clarity of instructions was good,
two suggested that some of the instructions may be too
lengthy, encouraging respondents to skim over or not readthem at all. The difficulty in striking a balance between
being comprehensive and parsimonious was acknowledged, and the two reviewers concluded that many ofthese issues would be resolved through the cognitive interview phase. A suggestion was made regarding the response
format of the SIT-Q that, for some items, it would be
helpful to provide options of “hours per day” in addition
to “hours per week” because some participants might notengage in this behavior on a daily basis.
A number of additional recommendations arose fromthe expert review, including a suggestion to add an itemon snacking behavior while watching television. The expert who suggested this inclusion thought it would provide useful insight for disentangling the contributions of
television time and high energy snacks to outcomes suchas adiposity and metabolic dysfunction. Refinements

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based on the suggestions provided by expert reviewers
were made to the SIT-Q accordingly.
Cognitive interviewing

Eleven cognitive interviews were conducted, each one lasting between one and a half and two hours. Three males(mean age = 51.0 years, SD = 13.9 years) and eight females(mean age = 44.9 years, SD = 7.5 years) participated. Further details on the characteristics of participants in the
cognitive interviews and pilot testing can be found in
Additional file 2. Three rounds of testing were conducteduntil, during the final round, five successive interviews did
not identify any new sources of misunderstanding.
Table 1 outlines key sources of difficulty or confusion
identified by the cognitive interviews, and the resultant
changes made to the SIT-Q. In the final round of interviews, all changes that had been made due to reported
issues in rounds 1 and 2 were well received and appeared to make comprehension easier for participants.
Other, more general, issues raised during the cognitive
interviews included difficulty with the concept of ‘usual’time, particularly if participants had a varied routine. For
example, one participant, a health professional, worked
four days per week on a hospital ward and one day per
week in her office. Other participants had shared custody of their children. Their usual routine varied substantially depending on whether or not their children
were staying with them. Seasonal variation also made itdifficult for participants to define their usual sedentary
behavior, particularly within the leisure-time domain. A
number of participants indicated that they were moresedentary during the winter months than in summer.
The feedback received during the cognitive interviews
regarding the breaks in sedentary time items was positive.
Participants indicated that the questions were clearlystated and did not create any confusion. Feedback fromparticipants also led to changes in the order of domains,
so as to improve the logical flow of questioning from one
topic to the next. The initial SIT-Q assessed by the cognitive interviews was ordered: (1) sleeping and napping;(2) transportation; (3) work, study and volunteering; (4)meals; (5) leisure-time; and, (6) household chores and doit-yourself. The revised version of the SIT-Q (to be pilot
tested) was ordered: (1) sleeping and napping; (2) meals;(3) transportation; (4) work, study and volunteering; (5)childcare and elder care; (6) light leisure and relaxing; and,(7) final questions. The revised SIT-Q incorporated ‘finalquestions’, an additional section with open-ended responses to allow participants to record any additional sedentary behaviors not covered by the questionnaire.
Pilot testing

The pilot study phase was completed by 34 participants(76% response rate), of whom 14 were male (mean age =Lynch et al. BMC Public Health 2014, 14:899
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Table 1 Sources of misunderstanding or difficulty identified during the cognitive interviews (n = 11)
Sources of misunderstanding/confusion

Initial wording of SIT-Q

Revised wording of SIT-Q• Confusion about use of ‘activity’ todescribe time spent sitting or lying down.

• Do your best to estimate your usual activity
pattern.

• The amount of time you spent sitting or
lying down may have varied over the past
12 months. Do your best to estimate yourusual pattern over the past 12 months.

• Uncertainty about the concept of‘double-counting’.

• Do not double-count time. For each of theactivities only count the time where this wasyour main activity. The total hours should
not add up to more than 24 hours.

• For each of the sitting tasks only count thetime where this was your main focus. For
example, if you spent one hour sitting on
the sofa reading a book while you had a CD
on in the background, count this time as
one hour reading (do not also ‘double
count’ as one hour listening to music).

• Uncertainty whether to include timespent lying in bed before falling asleep assleep time.

• Please record the usual number of hours of
sleep for weekdays and weekends.

• Please record how long you usually slept on
weekdays and weekends. This may include
time you spent lying quietly while waiting tofall asleep, or after awakening.

• Understanding what was meant by‘usually take a daily nap’ was difficult forsome.

• If you did not usually take a daily nap on
weekdays or weekends over the past
12 months, please write “0” in the response
section. How long did you usually nap per day?

• Did you take a nap each day, on either
weekdays or weekends, over the past
12 months? How long did you usually nap
per day (do not include occasional naps)?

• Difficulty incorporating semi-regulardriving that is neither usual daily trips nora holiday.

• Please record the usual amount of time you
spent sitting during transportation over the
past 12 months. Do not include one-off trips
like holidays. Record the usual hours per day
for weekdays and weekends.

Note: no change was made in this instance;
response will be dependent on participant’s
perception of “usual”.

• Participants indicated that separate
questions for driving a car and being apassenger were not necessary.

• Record the usual hours per day for weekdays
and weekends (a) driving a car (b) sitting asa passenger in a car, bus, train etc.

• How long did you usually spend sitting
during transport per day?

• Some misunderstanding about instruction
regarding ‘transportation while at work’.

• Do not include time sitting in an automobile
while at work.

• Do not report time spent sitting duringtransportation as part of your job (you will
be asked about this later).

• One participant recorded 52 weeks spentin her job, even though she verbally said
she only worked 48 weeks, with fourweeks vacation.

• Weeks per year? Note: no instruction otherthan a heading for the response section• Do not include holiday time here, even if it
is paid vacation.

• Difficulty in separating out times spent
doing light office tasks like typing or
reading, as these were done at the sametime as talking to others. Participants
reported multi-tasking was frequent, andhence it would be easier to provide an
overall estimate of sitting time at work,
rather than for separate work tasks.

• Record the amount of time you spent doing
the following sitting tasks as part of your job
over the past 12 months:

Instructions

Sleeping and Napping

Transportation

Work, study and volunteering• How many weeks in the past 12 months did
you do job # 1?

(a) driving or travelling in a car (do notinclude operating heavy machinery)• How much time per day did you spend
sitting for your job? (include driving andtravelling while doing this job; do not include
time commuting to and from this job).

(b) non-strenuous tasks while sitting (typing,reading, light assembly)(c) sitting while talking to others (on thetelephone, during meetings).

• Need for response option of “never” for theitems about breaking up sedentary time.

• How often do you ‘break up’ the time you
spend sitting in job # 1?

• How often did you ‘break up’ the time you
spent sitting in job # 1?

(a) less than hourly(a) less than hourly(b) hourly(b) hourly(c) half hourly(c) half hourly(d) every 10 minutes(d) every 10 minutes(e) every 5 minutes.

(d) every 5 minutes(f) I did not sit for more than 30 minutes ina day.

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Table 1 Sources of misunderstanding or difficulty identified during the cognitive interviews (n = 11) (Continued)
Household chores and childcare• Participants spent almost no time sitting
for any household chores. All such tasks
were done from a standing position.
Participants could not identify with theexample tasks provided.

• Chores done sitting down on weekdays andweekends (examples: food preparation,folding clean clothes, household accounts,
polishing silver).

Note: household chores section removed
from SIT-Q.

• Participants felt that the question andexamples about childcare in this section
could also apply for looking after elderly
parents or other family members withdisabilities.

• Child-care tasks while sitting down on
weekdays and weekends (examples: nursing
a baby, feeding a child, reading to a child).

• How long did you usually spend sitting or
lying down while caring for your child perday? (examples: nursing baby, helping childwith homework).

38.0 years, SD = 19.5 years) and 20 were female (meanage = 44.1 years, SD = 10.8 years). The total time spent
in sedentary behaviors (excluding sleeping and napping)was 12.0 hours per day (SD = 3.9), representing 73% ofparticipants’ waking time. There was no significant difference between the total hours of sitting time for men(mean = 12.8, SD = 4.0) and women (mean = 11.5, SD =3.9). Each SIT-Q returned was completed correctly;
none of the responses were outside of expected parameters. Whilst there were no true missing data, approximately half of the pilot study sample simply left sections
blank that did not apply to them, rather than entering“0” as instructed by the questionnaire. Participants rated
the SIT-Q highly in terms of ease of use: on a scale of 1
(not at all easy) to 5 (very easy) the mean rating was 4.3,
and 50% of the pilot study sample gave a rating of 5.
There was considerable variation in the SIT-Q domains
considered the easiest to complete: 36% reported sleeping and napping was the easiest section to complete,
while 24% reported meals and 12% reported transportation. All participants indicated that their usual sedentary behavior was covered by the SIT-Q items, and no
additional tasks were suggested for inclusion in thequestionnaire.
Measurement property study

Eighty-two (77%) participants enrolled in the MAREE
Study agreed to take part in the SIT-Q measurement
property study. Of these, 34 were male (mean age =51.2 years, SD = 6.7 years; mean BMI = 25.6 kg/m2, SD =3.2 kg/m2) and 47 were female (mean age = 45.9 years,
SD = 8.6 years; mean BMI = 23.7 kg/m2, SD = 2.8 kg/m2).
For further details on the characteristics of the sample,
see Additional file 3. The second administration of the
7-Day Activity Diary was completed by 76 participants.
Mean values of the summary variables were calculated
from the two different administrations of the 7-Day• How long did you usually spend sitting
down while caring for elderly family member
per day? (examples: reading aloud, assistancewith eating meals).

Activity Diary; 74 complete records were available foranalysis. All 82 participants completed the first administration of the SIT-Q; 64 completed the second administration of the SIT-Q.
Overall, there was a mean difference of 52 minutes between the first and second administrations of the SIT-Q.
There was little mean difference noted across the meals,
transportation or childcare and eldercare domains, however the second administration saw an overall decreaseof approximately half an hour for the work, study andvolunteering, and leisure time domains. In terms of testretest reliability, the ICCs ranged from 0.31 (poor) forcomputer use during leisure time to 0.86 (excellent) for
occupational sitting (see Table 2). Total daily sitting
demonstrated fair to good correlation (ICC = 0.65, 95%
CI: 0.49, 0.78). Figure 2 shows the Bland-Altman plot
for total sitting time (h/day), with wide 95% limits ofagreement (-3.62, 4.69). Overall, participants tended
to report shorter periods of sedentary behaviour inthe second administration of the SIT-Q. However theplot demonstrates that there was little systematic variability in reporting, although there were a few outliers
indicating some instances of high variability at theupper end.
In response to the question How often did you “breakup” the time you spent sitting during their primary “job”(response options: I did not sit for more than 30 minutes
in a day; less than hourly; half hourly, every 10 minutes;
every 5 minutes), participants’ absolute agreement between the two administrations of the SIT-Q was 55%,
and the weighted kappa was 0.49. Similar results wereobtained for the item pertaining to breaking up timespent sitting whilst watching television (percent agreement = 61%; wκ = 0.50) and for the item assessing how
often participants ate snack foods whilst watching television (percent agreement = 56%; wκ = 0.48). Hence, thetwo items referring to breaks in sitting time, and theLynch et al. BMC Public Health 2014, 14:899
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Table 2 Results comparing sitting time (h/day) measured by two administrations of the SIT-Q, one month apart(n = 64)
SIT-Q

SIT-Q

First administration

Second administration

Mean difference (95% CI)

ICC (95% CI)

Meals (h/day)

1.07 (0.52)

1.00 (0.56)

0.06 (-0.03, 0.16)

0.60 (0.42, 0.74)

weekday only

1.00 (0.50)

1.00 (0.63)

0.03 (-0.06, 0.12)

0.65 (0.48, 0.77)

weekend only

1.25 (0.75)

1.00 (0.71)

0.14 (0, 0.29)

0.41 (0.18, 0.59)

Transportation (h/day)

0.82 (0.61)

0.83 (0.75)-0.05 (-0.15, 0.06)

0.59 (0.41, 0.73)

weekday only

0.75 (0.50)

0.75 (0.50)-0.04 (-0.14, 0.06)

0.65 (0.48, 0.77)

weekend only

1.00 (1.00)

1.00 (1.00)-0.06 (-0.26, 0.13)

0.51 (0.30, 0.67)

Work, study and volunteering (h/day)

2.83 (4.22)

2.36 (4.42)-0.25 (-0.54, 0.04)

0.86 (0.78, 0.91)

Childcare and elder care (h/day)

0 (0)

0 (0)

0.13 (0.01, 0.24)

0.59 (0.40, 0.73)

weekday only

0 (0)

0 (0)

0.12 (0.01, 0.24)

0.60 (0.41, 0.73)

weekend only

0 (0)

0 (0)

0.13 (-0.01, 0.28)

0.59 (0.40, 0.73)

Television viewing time (h/day)

1.73 (1.29)

1.50 (1.39)

0.12 (-0.03, 0.28)

0.84 (0.75, 0.90)

weekday only

1.50 (1.50)

1.50 (1.50)

0.07 (-0.11, 0.24)

0.82 (0.72, 0.89)

weekend only

2.00 (1.67)

2.00 (2.00)

0.27 (-0.01, 0.55)

0.69 (0.53, 0.80)

Computer use at home (h/day)

1.00 (1.00)

0.64 (0.64)

0.12 (-0.03, 0.28)

0.31 (0.07, 0.52)

weekday only

1.00 (1.00)

0.50 (0.50)

0.31 (0.06, 0.56)

0.25 (0, 0.47)

weekend only

1.00 (1.00)

0.50 (0.71)

0.23 (0.04, 0.43)

0.42 (0.19, 0.60)

Leisure time (h/day)

4.50 (2.69)

3.82 (2.39)

0.65 (0.29, 1.02)

0.61 (0.43, 0.74)

weekday only

3.71 (3.08)

3.00 (2.00)

0.58 (0.21, 0.95)

0.63 (0.45, 0.76)

weekend only

6.00 (3.50)

4.71 (3.42)

0.79 (0.21, 1.36)

0.51 (0.31, 0.68)

Total sitting time (h/day)

9.48 (2.82)

8.59 (2.36)

0.54 (0.01, 1.07)

0.65 (0.49, 0.78)

First and second administration results presented are median (IQR) for all variables except for total sitting time, which is presented as mean (standard deviation).

item referring to frequency of snack food consumption,
demonstrated moderate agreement.
There were 69 participants with mean diary and first
SIT-Q data. Overall, there was less than ten minutes difference between the SIT-Q and 7-Day Activity Diary estimates of total daily sedentary behavior. Compared withthe 7-Day Activity Diary, the SIT-Q estimated over half
an hour less within the meals and transportation domains. There was relatively little difference between the
different methods of sedentary behavior assessment for
the work, study and volunteering or childcare and eldercare domains. A substantial difference was noted within
the leisure time domain; the SIT-Q estimated nearly twohours per day more leisure time sedentary behavior.
Correlations representing the convergent validity varied
from 0.19 (weak) for sitting during meals to 0.76 (strong)for occupational sitting (see Table 3). For total daily sitting,estimates derived from the SIT-Q and 7- Day Activity
Diaries were moderately correlated (ρ = 0.53, p < 0.01).
There were only minor differences in the estimates of timespent in sedentary behaviours based on postural or
MET-based definitions from the 7-Day Activity Diaries.
The correlations were somewhat lower for sitting during

meals (postural definition) in comparison to the METbased definition; however the correlation coefficients wereequivalent across other categories and for total sedentarytime. The Bland-Altman plot for total sitting time (h/day)is shown in Figure 2. This plot also shows wide confidence
intervals but little systematic variability in reporting.

Discussion
We adopted a three-staged approach to the development
and refinement of the SIT-Q: expert review, cognitive
interviewing and pilot-testing. Broadly, our findings suggest that the SIT-Q exhibits good face validity and ishighly acceptable to questionnaire respondents. Whilst
helpful suggestions were provided through the process
of expert review, it was encouraging that no substantialchanges to the SIT-Q were recommended: this finding
indicated consistency in the understanding of these behaviors between the authors and content experts. Findings from the cognitive interviews lead to significant
restructuring of questions and changes in wording, as
participants’ perception of the meaning of questions was
sometimes quite different from what had been intended.
Improvement in participant comprehension was achieved

Page 9 of 12

Difference of Total Sitting Estimates

Lynch et al. BMC Public Health 2014, 14:899
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Mean of Total Sitting Estimates

A. Bland-Altman plot comparing total sitting time from the first and second administrations

Difference of Total Sitting Estimatesof the SIT-Q

Mean of Total Sitting Estimates

B. Bland-Altman plot comparing total sitting time from the SIT-Q and the 7 Day Activity
Diary

Figure 2 Bland-Altman plots for test-retest reliability and convergent validity of the SIT-Q. A. Bland-Altman plots of total sitting time (h/day)
estimated by the SIT-Q during two administrations, one month apart, with means (solid lines) and limits of agreement (dashed lines). B. Bland-Altman
plot of total sitting time (h/day) estimated by the first administration of the SIT-Q and the 7-Day Activity Diary.

through revisions to the wording of instructions and questions. However, some factors such as seasonal differencesand variable work or family routines remained limitationsin the context of past 12-month recall. The pilot study
confirmed that the SIT-Q was acceptable to respondents,
and that most common sedentary behaviors were includedin the questionnaire.
The second administration of the SIT-Q generated an
estimate of total sedentary behavior that was 52 less thanderived by the first administration. Whilst the difference
between total sedentary behavior estimates from the firstadministration of the SIT-Q and the 7-Day Activity
Diary were small, we noted substantial differences between methods in relation to leisure-time sedentary

behavior. The first administration of the SIT-Q appears
likely to have over-estimated leisure time sitting, possibly
due to concurrent computer and television use. These
two behaviors could not be disentangled from the diarydata, as many participants reported these as occurring at
the same time. We note that leisure-time sedentary behavior was over 40 minutes less in the second administration of the SIT-Q; perhaps familiarity with methodsof recalling and reporting sitting time resulted in less ofthe ‘double counting’ that had been identified as an issue
in the cognitive interviewing process.
The psychometric properties of the SIT-Q are comparable to the test-retest reliability and convergent validity
established for other sedentary behavior questionnaires.

Lynch et al. BMC Public Health 2014, 14:899
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Page 10 of 12

Table 3 Results comparing sitting time measured by the SIT-Q to estimates derived from Seven-Day Activity Diaries(both postural and MET-based definitions of sedentary) (n = 69)
Diary – postural definition

Diary – MET-based definition

Mean difference (95% CI)

Spearman’s ρMean difference (95% CI)

Spearman’s ρ

Meals (h/day)

1.52 (0.79)-0.58 (-0.75, -0.42)

0.19 (p = 0.11)

1.55 (0.74)-0.65 (-0.83, -0.48)

0.29 (p = 0.01)

weekday only

1.47 (0.81)-0.63 (-0.81, -0.44)

0.07 (p = 0.58)

1.47 (0.80)-0.69 (-0.88, -0.50)

0.23 (p = 0.07)

weekend only

1.52 (1.03)-0.45 (-0.66, -0.25)

0.36 (p < 0.01)

1.61 (0.95)-0.52 (-0.75, -0.28)

0.37 (p < 0.01)

Transportation (h/day)

1.34 (0.91)-0.53 (-0.67, -0.38)

0.37 (p < 0.01)

1.37 (0.92)-0.54 (-0.69, -0.39)

0.34 (p < 0.01)

weekday only

1.21 (0.93)-0.60 (-0.77, -0.43)

0.39 (p < 0.01)

1.27 (0.92)-0.62 (-0.79, -0.45)

0.37 (p < 0.01)

weekend only

1.29 (1.27)-0.38 (-0.64, -0.11)

0.11 (p = 0.38)

1.26 (1.27)-0.38 (-0.64, -0.12

0.11 (p = 0.37)

Work, Study andVolunteering (h/day)

2.64 (3.48)-0.17 (-0.51, 0.16)

0.76 (p < 0.01)

2.72 (3.30)-0.24 (-0.59, 0.11)

0.75 (p < 0.01)

Childcare and eldercare (h/day)

0 (0)0.11 (-0.01, 0.23)

0.49 (p < 0.01)

0 (0.02)0.15 (0.03, 0.27)

0.46 (p < 0.01)

weekday only

0 (0)0.11 (-0.03, 0.24)

0.47 (p < 0.01)

0 (0.03)0.16 (0.01, 0.29)

0.36 (p < 0.01)

weekend only

0 (0)0.15 (-0.01, 0.30)

0.61 (p < 0.01)

0 (0)0.18 (0.03, 0.34)

0.53 (p < 0.01)

Leisure time (h/day)

2.57 (2.01)

1.93 (1.38, 2.48)

0.26 (p = 0.03)

2.61 (2.12)

1.94 (1.39, 2.49)

0.26 (p = 0.03)

weekday only

2.33 (2.28)

1.68 (1.08, 2.29)

0.31 (p = 0.01)

2.33 (2.35)

1.68 (1.08, 2.28)

0.32 (p = 0.01)

weekend only

3.24 (2.89)

2.44 (1.68, 3.20)

0.14 (p = 0.26)

2.75 (3.50)

3.01 (2.17, 3.86)

0.09 (p = 0.45)

Total sitting time (h/day)

9.50 (2.36)-0.15 (-0.78, 0.47)

0.53 (p < 0.01)

9.26 (2.25)

0.09 (-0.50, 0.68)

0.52 (p < 0.01)

The test-retest reliability for total sitting time (ICC =0.65) was somewhat higher than the ICC presented for
total sitting time by Gardiner et al. (0.52) [38], andsomewhat lower than the ICCs reported by Salmon
et al. (0.79) [20] and Rosenberg et al. (weekday = 0.85;
weekend = 0.77) [19]. However, the estimates of total sitting time generated by other questionnaires did not encompass the variety of domains, or number of different
sedentary behaviors covered by the SIT-Q. The SIT-Q
performed favorably when measuring television viewing
time (ICC = 0.84), compared to findings from Gardineret al. (ICC = 0.76) [39], Marshall et al. (ICC for men,
weekdays = 0.65; weekends = 0.62, Pearson’s r for women,
weekdays = 0.79, weekends = 0.57) [18], Salmon et al.
(ICC = 0.82) [20] and Rosenberg et al. (ICC weekdays =0.86; weekends = 0.84) [19]. Only Marshall et al. reported the test-retest properties for occupational sitting (ICC for men, weekdays = 0.86, ICC for women,
weekdays = 0.79); their results were similar to the SIT-Q
results (ICC = 0.86) [18].
The SIT-Q demonstrated moderate validity overall. In
terms of the validity of other sedentary behavior measures,
only Salmon et al. [20] and Marshall et al. [18] compared
their sedentary behavior questionnaires against activity
logs or diaries, however neither of these studies determined the convergent validity for their measured estimateof total sitting time. The SIT-Q’s estimate of occupational
sitting (ρ = 0.76) compared favorably to the item examinedby Marshall et al. (r for men, weekdays = 0.74, for women,
weekdays = 0.69) [18]. Sitting whilst driving in the Salmon
et al. scale demonstrated low correlation (ρ = 0.30)

compared to a 3-Day Log; [20] a similar correlation
was found for sitting during transportation in the SIT-Q(ρ = 0.37).
A major strength of the SIT-Q is the rigorous methodological approach used to develop the instrument. The
three-stage process of expert review, cognitive interviewing and pilot testing was critical for minimizing future
participant reporting errors by ensuring that items and instructions were worded in a manner appropriate for thetarget population. However, it is important that the SIT-Q
is used within the context for which it was designed. The
SIT-Q was developed for use in epidemiological studies
where habitual patterns of sedentary behavior are of interest in relation to chronic disease development and progression; it may not be a sensitive measure of change insedentary behavior. Using the 7-Day Activity Diary as ourcriterion measure enabled us to estimate the validity of
domain-specific estimates of sedentary behavior. Further,incorporating two administrations of the diaries and using
the mean of these estimates likely reduced intra-individual
variation in the criterion measure.
The study has a number of limitations that must be considered. The convenience samples drawn for both the cognitive interviews and pilot testing were comprised ofindividuals from Calgary, Canada, whose lifestyle may differ significantly from residents of other countries, particularly with regards to outdoor pursuits. Further, all study
participants were urban residents, and hence the experiences of adults who live and work in rural areas were notincorporated into the development of the SIT-Q. Men andmembers of non-white ethnicities were under-represented,

Lynch et al. BMC Public Health 2014, 14:899
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and study participants tended to be well educated and havesedentary, white-collar jobs. Whilst estimates of sedentary
behavior derived from the 7-Day Activity Diaries may
be more accurate than a seven day recall questionnaire
because of careful daily accounting of time spent invarious activities, they will still be subject to reporting
errors and biases. In future work we will determine thecriterion validity of the SIT-Q by comparing estimatesof sedentary behavior against data collected using theactivPAL® inclinometer (PAL Technologies, Glasgow,
Scotland).

Conclusion
The SIT-Q was developed to fill a need for a rigorously
tested, comprehensive measure of habitual adult sedentary behavior. It is the first sedentary behavior questionnaire to be developed and refined using expert review,
cognitive interviewing and pilot-testing. Overall, the
SIT-Q demonstrated fair to good test-retest reliability
and moderate validity. Items pertaining to behaviors that
occur in more structured contexts, such as televisionviewing or occupational sitting, displayed the strongest
psychometric properties [23]. These findings, coupledwith the high acceptability of the questionnaire from respondents in the pilot study, suggest that our aim to develop a feasible measure of usual sedentary behavior for
use in population cohort studies has been achieved.
Given the emerging evidence suggesting that sedentary
behavior is a modifiable lifestyle risk factor for numerous
chronic diseases, the SIT-Q should be a useful addition
to available methods of sedentary behavior assessment.
Additional files
Additional file 1: SIT-Q: this is the version of the SIT-Q used in themeasurement properties study.
Additional file 2: Sociodemographic characteristics of cognitive
interview and pilot study participants.
Additional file 3: Sociodemographic characteristics of measurement
property study participants.
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
BML, CMF and IC conceptualised the study and its design; BML, FK, AL, JN
and IC planned and performed the data collection and cleaning; BML, FK, AL
and IC planned and performed the statistical analyses; BML, CMF and IC
contributed to writing of the manuscript. All authors were involved in theinterpretation of the findings, and have read and approved the final
manuscript.
Acknowledgements
The authors thank Ruth Ullman (Alberta Health Services) for conducting the
cognitive interviews; Wendy Brown and Genevieve Healy (The University of
Queensland, Australia), Neville Owen and David Dunstan (Baker IDI Heart andDiabetes Institute, Australia), Charles Matthews (National Cancer Institute,USA), Jo Salmon (Deakin University, Australia), and Katrien Wijndaele (Medical
Research Council Epidemiology Unit, UK) for their participation in the expert

Page 11 of 12

review component of this study. This study was funded by the Canadian
Institutes of Health Research Grant # MOP-86632 (Ilona Csizmadi, Principal
Investigator) and the Alberta Cancer Foundation # 24265 (Ilona Csizmadi,
Principal Investigator). Brigid M. Lynch was supported by a Research Fellowshipfrom Alberta Innovates – Health Solutions, an Early Career Fellowship from the
National Health and Medical Research Council # 586727 and the Victorian
Government’s Operational Infrastructure Support Program. Christine M.
Friedenreich is funded by an Alberta Innovates-Health Solutions Health Senior
Scholar Award, and is the Alberta Cancer Foundation Weekend to End
Women’s Cancers Breast Cancer Chair.
Author details
1
Physical Activity Laboratory, Baker IDI Heart and Diabetes Institute,
Melbourne, Australia. 2Melbourne School of Population and Global Health,
Faculty of Medicine, Dentistry and Health Sciences, The University of
Melbourne, Melbourne, Australia. 3Department of Population HealthResearch, Alberta Health Services - CancerControl Alberta, Calgary, Canada.
4
Department of Oncology, Faculty of Medicine, University of Calgary, Calgary,
Canada.
Received: 30 November 2013 Accepted: 15 August 2014
Published: 1 September 2014
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doi:10.1186/1471-2458-14-899
Cite this article as: Lynch et al.: Development and testing of a past year
measure of sedentary behavior: the SIT-Q. BMC Public Health 2014 14:899.

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