Clarifying & Expressing Values
2012 UPDATED CHAPTER D:
CLARIFYING AND EXPRESSING VALUESSECTION 1:
AUTHORS/AFFILIATIONSAngela Fagerlin (co-lead)
Michael Pignone(co-lead)
Purva Abhyankar
Nananda Col
Deb Feldman-Stewart
Teresa Gavaruzzi

University of Michigan
University of North Carolina

USA
USA
UK
USA
CanadaItaly & UK

Jennifer Kryworuchko
Carrie A. Levin
Arwen Pieterse

University of Stirling
University of New England
Queen’s University, Ontario
University of Padova & University of
Leeds
University of Saskatchewan
Informed Medical Decisions Foundation
Leiden University Medical Center

Valerie Reyna
Anne Stiggelbout

Cornell University, New York
Leiden University Medical Center

Laura Scherer
Celia Wills
Holly Witteman

University of Michigan
Ohio State University
University of Michigan

CanadaUSA
The
Netherlands
USA
The
Netherlands
USA
USA
USA

SECTION 2:
CHAPTER SUMMARY
What is this dimension?
Values clarification methods (VCMs) are best defined as methods to help patients think about
the desirability of options or attributes of options within a specific decision context, in order
to identify which option he/she prefers.
What is the theoretical rationale for including this dimension?
Several decision making process theories were identified that can inform the design ofvalues clarification methods, but no single “best” practice for how such methods should beconstructed was determined.

Suggested Citation:
Pignone M, Fagerlin A, Abhyankar P, Col N, Feldman-Stewart D, Gavaruzzi T, Kryworuchko J, Levin CA, Pieterse A, Reyna V,
Scherer L, Stiggelbout A, Wills C, Witteman H. (2012). Clarifying and expressing values. In Volk R & Llewellyn-Thomas H(editors). 2012 Update of the International Patient Decision Aids Standards (IPDAS) Collaboration's Background Document.
Chapter D. http://ipdas.ohri.ca/resources.html.

Clarifying & Expressing Values
What is the evidence to support including or excluding this dimension?
Our evidence review found that existing VCMs were used for a variety of different decisions,rarely referenced underlying theory for their design, but generally were well described inregard to their development process. Listing the pros and cons of a decision was the mostcommon method used. The 13 trials that compared decision support with or without VCMs
reached mixed results: some found that VCMs improved some decision-making processes,
while others found no effect.
SECTION 3:
DEFINITION (CONCEPTUAL/OPERATIONAL) OF THIS QUALITY DIMENSIONa)

Updated Definition

Values clarification methods (VCMs) include any methods that are intended to help patientsevaluate the desirability of options or attributes of options within a specific decision context,
in order to identify which option he/she prefers. Although the methods can be either implicit
and non-interactive (e.g., the patient thinks about what’s important to his decision) or explicit
and interactive (e.g., the patient sets a rating scale for each attribute to reflect the importanceof each to his decision) (O’Connor 2005; Llewellyn-Thomas 2009), this chapter is focused on
the more studied and better understood explicit values clarification methods.
b)Changes from Original Definition

Our revised definition differs somewhat from the previous chapter’s definition, whichreferred to “values clarification exercises”: “[Exercises to] help patients to clarify andcommunicate the personal value of options, in order to improve the match between what is
personally most desirable and which option is actually selected.” (O’Connor 2005)
The rationale for our new definition of VCMs is as follows:• It focuses on attributes of the situation (e.g., the option that the doctor recommends, theoption that my partner/children prefer), attributes of options (e.g., the probability of cure,
impact on bladder functioning) and of options as a whole (e.g. holistic comparison ofsurgery to radiotherapy), because VCMs are intended to ultimately help clarify which
option an individual prefers and any of the above aspects of the situation may be helpful
in that process.
• It does not include the communication of values to others- this is considered to be adifferent aspect of decision support interventions.
• It employs the more general term “methods” rather than “exercises.”c)Emerging Issues with Definitions
See Section 6.

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Clarifying & Expressing Values
SECTION 4:
THEORETICAL RATIONALE FOR INCLUDING THIS QUALITY DIMENSIONa) Original Theoretical Rationale
In the original chapter (see Appendix), different types of VCMs were described,
including the mechanisms by which these methods may help patients to clarify theirvalues. These descriptions did not refer to underlying theories. The mechanisms that were
described in the original chapter include clarifying values by:•••

Considering detailed information about the options and their outcomes, which helps topromote understanding of what it means to undergo the procedures involved and to face
the physical, emotional, and social consequences;
Considering how others value features of options and whether the participant is similar toothers (social matching);
Rating or ranking features of options or trading off features of options, which may giveinsight into one’s personal values and/or the tradeoffs underlying the choice for one
versus other options.

b) Updated Theoretical Rationale
Considerable evidence suggests that individuals facing new and complex decisions often
do not have stable or clear preferences (Fischhoff 1991; Simon 2008). For example,
Feldman-Stewart et al. (2004) showed that almost all early-stage prostate cancer patients
who made use of a decision aid made changes to the attributes that they identified asaffecting their decision. Importantly, these were patients who had already talked to theirurologist and their radiation oncologist, and may have become clearer about what was
important to them during those discussions.
Values clarification methods are deemed to be helpful to patients because they provide
assistance with particular decision processes. Decision-making process theories imply
that those processes can include:
•
•
•
•
•
•

Identifying options, which can include either the narrowing down of options, or thegeneration of options that were not offered at the outset
Identifying attributes of the situation and/or the options which ultimately affect thepatient’s preference in a specific decision context
Reasoning about options or attributes of options
Integrating attributes of options using either compensatory or both compensatory andnon-compensatory decision rules
Making holistic comparisonsHelping decision makers retrieve relevant values from long-term memory

A specific VCM need not aim to address all of the above decision-making processes, butshould aim to facilitate, explicitly or implicitly, at least one or more of these decision-making
processes.
The theories presented in Table 1 (and described in greater detail in Table 2) were selected
because they specify particular decision-making processes, and hence provide the basis fromwhich the subset of processes that VCMs may be able to assist were derived. (Because sometheories, such as Expected Utility Theory (EUT) and theories of behavioral change (e.g.,3Clarifying & Expressing Values
Transtheoretical Model), do not specify particular decision processes, they cannot guideidentification of the processes that VCMs might be able to help.)
Table 3 uses the context of decision making about prostate cancer treatment to provide
examples of these decision-making processes, and to indicate which theories address theseprocesses.
c)Emerging Issues/Research Areas in Theory/Rationale
See Section 6.

SECTION 5:
EVIDENCE BASE UNDERLYING THIS QUALITY DIMENSIONa)

Original Evidence BaseIn the original version of this chapter, the authors found 19 studies that employed VCMs.
(O’Connor 2005) They noted that most (72%) offered examples of how others’ values ledthem to make different choices, and almost half (42%) incorporated some explicit means ofmeasuring one’s values (e.g. rating, trade-offs, balance scales). Few studies examined thespecific effects of VCMs: the trial by O’Connor and colleagues (O’Connor 1999) did not
find important effects of VCMs compared with a listing of the features of the decision. (SeeAppendix for further details).
b)

Updated Evidence Base

We organized our review into 2 major areas: A. Characteristics; and B. Evaluation
A. Characteristics
Witteman et al. conducted a rigorous systematic review of the characteristics of values
clarification exercises, and identified 61 studies that included an explicit VCM within adecision aid (Witteman 2012). In their review, Witteman and colleagues examined a large
number of characteristics of the values clarification methods and of the decision aids inwhich they were embedded.
We present a sub-set of these data here. Our goal was to describe the state of the science ofstudies that include values clarification methods. Thus, the factors we ultimately decided tohighlight were based on the following principles:1) characteristics of the studies in which the VCMs were presented (e.g., decision context),2) characteristics influencing the design of the VCMs (e.g., development process),3) characteristics of the VCMs (e.g., type of VCM utilized).
Our review is therefore limited to “higher level” characteristics of the VCMs and the studies
in which they were included. These key characteristics are summarized below and in Table
2. (Witteman and colleagues’ full paper provides additional details on these—and other—characteristics.)
1. Characteristics of Studies in Which Values Clarification Methods were Presented

4Clarifying & Expressing Values• What was the decision context?
Types of decisions were catalogued by the decision context: whether the decision addressed
1) treatment, 2) prevention, 3) screening (other than genetic screening), or 4) genetic testing.
Forty-six percent of VCMs focused on treatment decisions, 25% on prevention decisions,
33% on screening behaviors (not including genetic testing), and 10% on decisions about
genetic testing. Three VCMs addressed two of the above decision contexts; one addressed
three contexts, and one addressed all four.

• What medium was the VCM designed for?
The values clarification methods reviewed were designed to be completed on paper (49%),
using a computer (38%), or verbally (15%); two VCMs used two different media, thus
numbers do not sum to 100%.

• Where was the VCM located within the larger decision aid?
Values clarification methods can be placed before or after the presentation of the relevant
information needed to make a decision. The vast majority (85%) of the VCMs were presented
after the information section.

• Were decision intentions measured?
Over a third of the tools (38%) did not ask participants any questions about their decisions(intentions or actual). Thirty-four percent of the tools asked participants which way they wereleaning, while 28% asked for their actual decision.
2. Characteristics Influencing The Design of The VCM• What theory, framework, model, or mechanism underlie the development of the VCM?
The theory, framework, model, or mechanism underlying the development of the VCM wasreported or apparent in only 36% of publications. Some theoretical framework was presented
in the description of the underlying decision aid for 64% of studies. Twenty-five percent
did not report any theory, framework, model, or mechanism. It should be noted that somestudies reported theory for both the VCM and the overarching decision aid, thus the numberspresented in Table 2 do not sum to 100%. The most common theory was expected utility
theory (18%), even though this theory makes no predictions about how VCMs can improve
the process of medical decision making.

• Was the development process described and what was the development process?
Most of the articles (74%) described, in some way, the development process of either
the decision aid or the values clarification method. Of those that did include details, thedevelopment process used included literature reviews (42%), expert reviews (51%), and/or testing (80%). Those involved in the development process included health professionals(53%), academic experts (31%), and patients who have previously faced the decision (38%).
Because many of the articles used multiple processes and participants in their developmentof the tool, the numbers in Table 2 do not sum to 100%. Less than half (39%) of the VCMs
in decision aids were developed and evaluated using established guidelines, most often the
IPDAS standards (28% of VCMs).

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Clarifying & Expressing Values
3. Characteristics of the VCM• What type of VCM was used?
Ten categories of VCMs were utilized. The most common types were considering the prosvs. cons (46%), utility assessment with or without decision analysis (18%), prioritization(11%), and rating scales (11%). See Table 4.

• Were the results of the VCM presented to participants?
Thirty-nine percent explicitly showed participants the result of the VCM, most of which
occurred before the patient was asked to indicate their decision. Fifty-seven percent did not
explicitly provide feedback to participants.
B. Evaluation
The committee reviewed 13 studies that compared the effects of decision support with andwithout VCMs (see Table 5). The selected articles were derived from the Witteman et al.
review. However, only studies that included VCMs within the context of a decision aid areincluded here.
The identified studies examined a range of health conditions, with cancer-related topics being
the most common (6 of 13). Sample sizes ranged from small (5 of 13 with less than 100
participants) to moderately large (4 with 400 or more participants). Most examined actual
patients facing decisions but 3 studies asked participants to evaluate hypothetical decisions.
Several different types of VCMs were employed. Available studies examined a wide rangeof outcomes, and no outcomes were assessed in the same manner across all or most studies.
Reported outcomes included likeability of the VCM, knowledge, decision making processes,
decisional conflict, uncertainty, satisfaction, decision preference, treatment intent, actual
health behaviors, regret and, in a few cases, health outcomes or cost.
The effects of VCMs were mixed: decision processes were improved in 5 of 8 studies, butother outcomes were not measured frequently enough to reach conclusions about whether
VCM had mainly positive or mainly neutral effects; no trials, however, suggested VCMs led
to worse outcomes. See Table 6.
c)Emerging Issues/Research Areas in Evidence BaseSee Section 6.

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Clarifying & Expressing Values
SECTION 6:
EMERGING ISSUES / RESEARCH AREAS IN DEFINITION, THEORY, AND
EVIDENCE BASE
Although the number of studies of values clarification methods (VCMs) and decision aids
is growing rapidly, our review highlights that many questions about the effects of VCMs
remain unanswered. We outline several such issues here.
1. Proposed Theories
A number of decision-making process theories were suggested without intending to establish
agreement about a single theory, or a set of theories, that should be viewed as most promisingin providing guidance for the design and evaluation of VCMs. More research is needed
across contexts (e.g., healthcare settings) and cultures to better understand how VCMs
might be designed to contribute to decision-making. Such understanding requires testing
VCMs based on specific theory, including theory-based predictions of anticipated effects
on outcomes and consideration of how such VCMs might contribute to effective decisionmaking.
2. Intuitive Processes
There is a debate currently about the value of intuitive processes in decision making.
Intuitive processing is typically characterized by a lack of overt cognitive effort and theimplicit integration of available information. In contrast, deliberative processing generally
involves effortful, conscious and analytical thought (Betsch 2010). Importantly, intuitive anddeliberative processes should not be conflated with implicit versus explicit VCMs. Althoughexplicit VCMs are often effortful, and thereby require deliberative thought, an implicit VCM
may also be quite effortful and activate analytical thought processes.
From research outside of health care (Wilson & Schooler 1991), deliberative reasoning
about pros and cons may cause people to focus on attributes that are obvious, accessible,
and easy to articulate, and these attributes may not be the ones that are actually the mostimportant factors in the decision. Therefore, in contexts outside of health care, there isevidence to suggest that deliberation can cause people to ignore attributes that lead to longterm satisfaction. There is also evidence to suggest that intuitions can accurately reflect the
integration of a large amount of information (Betsch 2010). However, the decisions that havebeen studied in the psychology literature are typically hypothetical and/or familiar decisions.
There is little research yet to assess to what extent these results are expected to hold for users
facing new, complex, preference-sensitive health related decisions. Until more research isavailable on the value of intuitive processes in such decision contexts, it is unclear to what
extent a VCM that encourages intuitive processing of options would be effective to help
people sort out what is most important to them, in comparison to a VCM that encourages
explicit processing or no VCM.
An increasing number of theories of decision making assume both intuitive and deliberativedecision making processes. Importantly, intuition and deliberation are not mutually
exclusive. A given decision may employ extensive use of both.

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Clarifying & Expressing Values
3. How VCMs Fit with Patient-Provider Shared Decision Making
Researchers and practitioners need to better understand how values clarification relates toshared decision making (SDM). Is values clarification a pre-requisite to, or an element of,
SDM? Does it improve SDM? Through the process of SDM, health care providers may elicit
patients’ and their families’ values. Patients and their families may not necessarily be clear
about their own values before the conversation with the health care team and may, on thecontrary, be guided to become clear in the SDM process. Whether a VCM should precede
the consultation with the health care provider, be used within the consultation, follow thatconversation, or even used at all requires further study.
4. Use of VCMs with Surrogate Decision Makers
More evidence is needed to determine whether VCMs would also be helpful for others
involved in decision making processes. That is, what is the impact of VCMs designed tosupport the clarification of values of those who influence the treatment decision and whoare affected by the outcome of the decision (e.g., caregivers or partners of patients), or of
surrogate decision makers, such as family members deciding on behalf of the patient andtrying to construct that patient’s values from their past experience with that patient and theirknowledge about the patient?
5. Use of VCMs to Reach a Decision Involving Multiple People
More research is needed to examine how VCMs can be used to help multiple people (such as
health care providers and family members) who are working together to support the patient’s
decision. Specifically, little is known about how VCMs can help clarify the values that
influence the advice of others to patients, as well as how VCMs could be used in a process
leading to consensus about the choice (when consensus does not violate the autonomy of thepatient).
6. The Role of Distal Outcomes
Attempts to develop measures of the effectiveness of VCMs have often focused on decision
making processes, likely because such processes are directly affected by the VCMs. Moredistal outcomes, including effects on regret, satisfaction, behaviors, actual decisions, andmeasures of health may also be important measures of the effect of VCMs, but are often
affected by many other factors. How best to incorporate these more distal outcomes into
evaluation of VCMs warrants further study.
7. Implicit versus Explicit VCM
More research is needed to ascertain the "active ingredients" of VCMs -- that is, thecomponents that make independent contributions to facilitating good decision making
processes that the VCMs aim to facilitate. In particular, more research is needed to clarify(a) what is required for implicit values clarification, and (b) if the use of strategies toencourage implicit values clarification is helpful, compared with explicit VCMs and also
compared with no VCM.

8. How to Handle More Than Two Options
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Clarifying & Expressing Values

More research is needed to examine whether, in the case of multiple options, it isnecessary to present all of the options and whether multiple options should be consideredsimultaneously or in series. For example, it may be more helpful to identify attributes andthen present only the options that match the attributes the individual who faces the decisionconsiders most important. Or rather, it may be more helpful to present all options prior to
the VCM and then identify preferred option(s) for further consideration. However, patientsrequire sufficient knowledge of options to realize that certain attributes or values are relevant(Reyna 2008).
9. Assessing Capacity of The Patient For VCMs
More research is needed to identify which types of patients are able to benefit from VCMs,
how cognitive deficits (e.g. age-related loss of executive functioning) and/or mental illness orother conditions might adversely affect the use of VCMs, and which types of VCMs are best
suited for these populations.
10. Empirical Evidence BaseOur systematic review found that the research questions and outcome variables being tested
vary widely across studies. It may be helpful for studies to use at least a subset of standard
measures so that study results can be more easily compared. We found that reportingof results is quite consistent, with the exception of the development process for values
clarification methods. We recommend succinct reporting of: 1) the rationale for the designused (theory, previous designs, literature), 2) who was involved in its development (e.g.,clinical experts, patients, advisory panel, etc.), and 3) how was stakeholder input incorporated(focus groups, individual interview, pilot testing, etc.). We also refer authors of reports
of VCMs to Witteman et al.’s systematic review where we report a more thorough set of
categories for reporting.
We chose to include studies that used either hypothetical or actual clinical decisions. It
is unclear whether and how differences in the population used will affect results whencomparing decision aids with and without VCM. Hypothetical samples may be preferredin early developmental work to reduce the possibility of causing harm to actual patients;
conversely, actual patient populations are needed for evaluating more distal outcomes and toincrease generalizability.
As described above, the theoretical and empirical basis for values clarifications research haschanged significantly since the last IPDAS Background Document. Yet, there are still many
areas that need considerable research before we can make strong conclusions about the use of
VCM in decision aids.

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Clarifying & Expressing Values
Table 1: Decision Process Theories: Extent to Which They Address Specific Decision-Making Processes

TheoryBehavioral Decision
Framework(BDF)
Fischhoff, 2008

Conflict Model ofDecision Making(CM)
Janis & Mann, 1977

10

Ident
ifyingOptions

Ident
ifyingAttributes ofSituation
And/OrOptionsyes

yes

Brief Description(Descriptive & Prescriptive
theory): Good decisionmaking is characterized by:a) focusing on the consequencesof options; b) identifying all
options and assessing theirconsequences and desirability;
and c) making trade-offs toselect the alternative with thehighest overall evaluation
on a set of choice criteria(compensatory).
(Prescriptive theory): Decisions
create stress which can interferewith good decision making
process, characterized by: a)systematic information search;b) thorough consideration of allalternatives; c) sufficient timeto evaluate each alternative; andd) reexamining and reviewing
data in an unbiased manner

Reasoning About
Optionsor
Attributes ofOptionsInteg
ratingAttributes ofOptions

MakingHolistic
Compari
sons

yes

yes

yes

Helping
Retrieve
Relevant
ValuesClarifying & Expressing Values

Differentiation
and Consolidation
Theory(Diff Con)
Svenson,1992

Fuzzy Trace Theory(FTT)
Reyna, 2008

Image Theory(IT)
Beach & Mitchell,
1987

11

(Descriptive theory): Decision
making involves a processof gradually identifying
differences between options(differentiation); theseprocesses continue after thedecision is made (consolidation)
to minimize cognitive
dissonance and future regret.
(Descriptive & Prescriptive
theory): People encode bothverbatim and gist representations(“traces”) of information.
However, decision making
is mainly determined by thegist (basic meaning for that
individual) and by the social andmoral values that are retrieved incontext, a highly cue-dependent
process.
(Descriptive theory): Decision
making includes two stages:a) pre-choice screening using
rapid, simple, emotionallymediated and non-compensatory
strategies; followed by b) the
choice, using more deliberateand compensatory strategies
with the goal to pick the option
with the most attractive expectedconsequences.

yes

yes

yes

yes

yes

yes

yes

yes

yes

yes

yes

yes

yes

Clarifying & Expressing Values(Descriptive theory): Decision
making involves: a) deliberative
Parallel Constraint
processes for information
Satisfaction Modelsearch and production focused(PCS)
on actively constructing
the decision problem using
Glockner and Betsch different decision rules for2008
searching, editing and changing
information; and b) automatic
processes for integrating
information using an allpurpose, parallel constraint
satisfaction rule.
(Descriptive theory): Decision
making involves a search for
Search for Dominance a perspective that leads toStructure Model
optimal differences between(SDS)
a to-be-chosen option andother available options, in fourMontgomery, 1983
stages: a) identifying important
attributes and options;b) selecting an initiallyfavored option; c) identifying
disadvantages of the initiallyfavored option; andd) neutralizing disadvantages of
the initially favored option.

12

yes

yes

yes

yes

yes

yes

yes

Clarifying & Expressing Values
Table 2: Detailed Descriptions of Selected Decision Processing Theories

The Behavioral Decision Framework (BDF, Frisch & Clemen, 1994; Fischhoff, 2008;
Payne et al, 1992; Payne et al, 1998) describes the foundations of a model of a good decision
making process (for an early precursor of this model, see Janis & Mann, 1977). That is, gooddecision making can be characterized by the following three basic features:
1. Consequentialist decision strategies: i.e., explicitly focussing on consequences of different
options/actions as opposed to non-consequentialist ones such as imitation, habit or otherheuristic processing (e.g. I prefer option A because my good friend had it or my doctor seems
to prefer it).
2. Thorough structuring: Identifying possible options (option generation), anticipating theconsequences of options accurately (beliefs about probabilities), and determining thepersonal desirability of those consequences (value structuring).
3. Using compensatory decision rules: Making trade-offs using compensatory rules (e.g., trading
off probabilities and consequences) rather than non-compensatory rules.
The Conflict Model (CM, Janis & Mann, 1977) of decision making assumes that the mostthorough and ideal way of coming to a decision is by way of vigilant information processing.
It is characterized by (a) systematically searching information, (b) thoroughly considering
all available alternatives, (c) devoting sufficient time to evaluate each alternative, and (d)reexamining and reviewing data in an unbiased manner before making a decision.
Differentiation and Consolidation (Diff Con, Svenson, 2003) theory views decision making as
a process over time in which one option is gradually differentiated from competing alternatives
until one alternative is sufficiently superior. A preliminary option is selected. The differentiationof alternatives subsequently occurs through structural differentiation, that is, changing mental
representations of options in support of the preliminary choice, and process differentiation,that is, applying one or more compensatory or non-compensatory decision rules. The theory
suggests that the goals of decision makers’ processing are to protect themselves against cognitive
dissonance and later regret. It suggests that differentiating processes continue after the decision is
made, called consolidation. That is, after a decision has been made the relative attractiveness ofthe chosen alternative is further altered in an attempt to consolidate the choice’s superiority.
Fuzzy Trace Theory (FTT, Kuhberger & Tanner, 2010; Reyna, 2008) proposes that people
simultaneously encode mental representations (traces) of information that vary in precision.
Verbatim traces preserve precise detail, but ‘gist’ traces preserve basic meaning and are theanswer to the question “What does this information mean?” to an individual. Essential elementsof a decision consist of knowledge, gist of information, retrieval (how knowledge and values
are accessed when needed), and processing (how what is perceived is put together with what
is retrieved to make a decision). In processing, values and principles are retrieved that are thenapplied to mental representations of gist. However, retrieval is highly cue-dependent (i.e.,
sensitive to reminders in the immediate environment), even when values and principles arestrongly endorsed (Bartels, Bauman, Skitka, & Medin, 2009). Main implications of FTT forvalues clarification would be to (a) ensure that patients understand the essential meaning of
information (because different gists cue different values) (b) remind patients of an array of13

Clarifying & Expressing Values
values, some of which might be contradictory; and (c) assist patients in applying their values totheir mental representations by disentangling overlapping sets (Reyna, 2008; Reyna & Lloyd,2006).
Image Theory (IT, Beach & Mitchell, 1987) assumes two stages in making decisions: prechoice screening of options to narrow the pool of options, followed by the choice. In screening,
unacceptable options are eliminated based on their incompatibility with the decision maker’s
guiding principles, which underlie the adoption of goals to pursue for a specific decision.
It is a rapid, simple, emotionally mediated and non-compensatory strategy that does notnecessarily take place consciously. Choice of an option is accomplished by a more deliberate andcompensatory strategy that evaluates both the positive and negative attributes of options. It will
select the option which potentially offers the most attractive consequences. Depending on thenumber of options, the decision strategy will be non-compensatory followed by compensatory orcompensatory alone.
The Parallel Constraint Satisfaction model (PCS, Glöckner and Betsch, 2008) proposes thatdecision making involves deliberative processes for information search and production, andautomatic processes for integrating information and making choices. Processes of deliberationin decision making are mainly concerned with actively constructing the decision problem using
different decision rules for search, editing and changing information regarding the decisionsituation. These rules are under individuals’ deliberate control, can be verbalized and giveindividuals the feeling that they are deciding based on reasoning. The model further assumes that
individuals integrate and structure information using an automatic all-purpose decision rule, theparallel constraint satisfaction rule.
The Search for Dominance Structure (SDS) model (Montgomery, 1994, 2006) proposes thatwhen available options carry both advantages and disadvantages, decision making involves asearch for a perspective that leads to an optimal differentiation between a to-be-chosen option
and other available options, that is, the search for dominance. A dominance structure is achieved
when the individual perceives one option to be superior to all other options on at least one
attribute and is not inferior to any other option on any attribute. The search for dominanceincludes four stages: selecting important attributes and options (i.e., pre-editing); finding an
initially favored option for the final choice; checking disadvantages of the initially favored
option (dominance testing); and neutralizing disadvantages of the initially favored option(dominance structuring).

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Clarifying & Expressing Values
Table 3: Examples of Decision-Making Processes in Choosing Prostate Cancer Treatment
Decision-Making
Processes

Example Using The Clinical Context ofTreatment of Early Stage Prostate Cancer

Theories
Utilized

Identifying options

Recognizing active surveillance, surgery, andradiation as potential options

IT, SDS, Diff
Con, BDF

Identifying attributesof the situation and/or the options

Identifying effectiveness of the treatments; risk ofadverse effects such as impotence or incontinence;anxiety related to potential for cancer progression ormetastasis
Evaluating the potential distress of not having
immediate treatment in the context of other life
stresses. Recognizing the patient can change his
mind about active surveillance at any time and opt
for active treatment, whereas the converse is notpossible.
Trading off fear of living with cancer vs. how
important it may be to avoid adverse effects such asincontinence.

IT, SDS, Diff
Con, BDF

Making holisticcomparisons

Desiring to avoid surgery or radiation per se;
valuing an “active” approach vs. one that feels
reactive or passive

CM, Diff Con,
FTT

Helping retrieve
relevant values

A value that is often retrieved initially concerns
survival (life is better than death) and having cancer
is often equated to death. A patient retrieving only
this value would likely choose immediate surgery.
However, a decision aid could elicit retrieval of
additional values, such as values concerning sexual
health (e.g., “How important is sexual functioning
to you?”) that are sometimes not easily retrieved,
despite their relevance.

FTT

Reasoning about
attributes of options

Integrating attributesof options

Abbreviations:
BDF: Behavioral Decision Framework
CM: Conflict Model of Decision Making
Diff Con: Differentiation and Consolidation theory
FTT: Fuzzy Trace Theory
IT: Image Theory
PCS : Parallel Constraint Satisfaction model
SDS: Search for Dominance Structure model

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CM, IT, SDS,
Diff Con, FTT

BDF, IT, SDS,
Diff Con, PCS,FTTClarifying & Expressing Values
Table 4: Characteristics of Values Clarification Methods and the Studies in Which They
Were Presented*This table was adapted with permission from Witteman et al.
1. Characteristics of Studies
In Which VCMs Were Presented

Decision Context

Treatment

Overlapping(Note: Three VCMs address two decisioncontexts; one addresses three contexts; and one
addresses all four.)28 (46%)

Prevention

15 (25%)

Screening (non-genetic)

20 (33%)

Genetic testing

6 (10%)

MediumComputer-based

Overlapping(Note: Two VCMs used two different media.)23 (38%)

Online/Web

9 (15%)

CD-ROM

1 (2%)

With Multimedia

8 (13%)Audio

3 (5%)

Video

6 (10%)Other

2 (3%)

Decision board

1 (2%)Paper

30 (49%)With Audiotape

5 (8%)

With Verbal component

5 (8%)

Verbal16

N (%)

9 (15%)

Clarifying & Expressing Values
With Visual Aids

6 (10%)

With Paper Exercises

1 (2%)

With Personal Data Assistant

1 (2%)

Position in Larger Decision Aid
After information section

52 (85%)

Before information section

2 (3%)

Between information sections

1 (2%)

Throughout: As add-on to DA

3 (5%)

Throughout: VCM formed the entirety ofthe tool

3 (5%)

Unclear from article

1 (2%)

Measurement of Decision Intentions
Asked which way leaning

21 (34%)

Asked which decision taken

17 (28%)

Not asked

23 (38%)

2. Characteristics Influencing The
Design of The VCMs

N (%)

Theory, Framework, Model, or
Mechanism
None

15 (25%)

Underlying the VCM
Expected utility theory

11 (18%)

Conjoint Analysis

1 (2%)

17

Clarifying & Expressing Values
Differentiation and Consolidation Theory

2 (3%)

Multiattribute Utility Theory

2 (3%)Other

6 (10%)

Underlying the Overall Decision Aid
Ottawa Decision Support Framework(ODSF)

19 (31%)

Precaution Adoption Model

3 (5%)

Edutainment Decision Aid Model(EDAM)

2 (3%)

Elaboration Likelihood Model

2 (3%)

Stages of Change

2 (3%)Other

11 (18%)Development Process
Development Process Described in
ArticleYes

45 (74%)No

16 (26%)

What Aspect of Development Process was
Described

N.B. Percentages out of 45 with descriptions

Literature review

19 (42%)Modification, adaptation, translation oftool

5 (11%)

Model validation

2 (4%)

Needs assessment

9 (20%)

Observation of existing processes

1 (2%)

18

Clarifying & Expressing Values
Individual sessions, interviews

9 (20%)

Focus groups

13 (29%)Consultations, expert review

23 (51%)

Feasibility testing

2 (4%)

Iterative process, iterative steps

9 (20%)

Prototype testing, usability testing, pilot
testing

36 (80%)

Who was Involved in the Development
Process

N.B. Percentages out of 45 with descriptions

Clinical experts, health care professionals

24 (53%)

Experts in counseling, patient education,
patient advocates

9 (20%)

Experts from relevant academic fields(e.g., epidemiology, decision-making,health communication)

14 (31%)

Plain language experts

3 (7%)

Technical experts, design experts

2 (4%)

Policymakers

1 (2%)

Consumer representatives, people from
community-based groups, advocacy
groups

6 (13%)

Patient experts (those who havepreviously faced decision)

17 (38%)Prospective users

22 (49%)Healthy volunteers, people recruited from
community

6 (13%)

Patient advisory groups

1 (2%)

Committees, steering committees,
advisory panels, multidisciplinary teams

6 (13%)

19

Clarifying & Expressing Values

What Development Guidelines were Used
CREDIBLE

3 (5%)IPDAS

17 (28%)IPDAS cited, but not used

2 (3%)

National Health and Medical ResearchCouncil guidelines for presenting
information to consumers

2 (3%)

American College of Physicians
Guideline for counselling postmenopausal
women about preventive hormone
therapy

1 (2%)None

37 (61%)

3. Characteristics of the VCMs

N (%)

Type of VCM
Decision analysis

11 (18%)

Conjoint analysis

1 (2%)

Analytic hierarchy process

1 (2%)

Tradeoffs

4 (7%)

Probability

1 (2%)Time

1 (2%)

Attributes

2 (3%)

Pros vs. cons

28 (46%)20

With weighting

23 (38%)With binary response

4 (7%)

Viewing or listing only

1 (2%)

Clarifying & Expressing Values
Prioritization

7 (11%)

Rating scales

7 (11%)

Lists of concerns

5 (8%)

List only

2 (3%)

List and discuss

3 (5%)

Social matching

1 (2%)Other

1 (2%)

Presentation of ResultsYes

24 (39%)Yes, after decision intention

3 (5%)

Yes, prior to decision intention

21 (34%)

Possibly shown explicitly (depends on
options selected)

1 (2%)

No

35 (57%)
No, not at all

10 (16%)

No, not explicitly, though it may beinferred25 (41%)

Unclear from article

2 (3%)

21

Clarifying & Expressing Values
Table 5: Trials Examining Effect of VCM Versus No VCM Within Decision Aids
Reference
Abhyankar
2010(n = 30)
hypothetical decision

Clancy1988(n = 1280)

VCM used
Pros andCons withweightings

Decisionanalysiswith visual
analogue scale

Feldman-Stewart
2006(n = 90)
hypothetical decision

Rating(sliders)

Feldman-Stewart
2012(n = 156)

Ratingattributes

Fraenkel2007(n = 87)

Conjoint
analysis

22

Decision orContext
Choice between
standard
adjuvant
chemotherapy
for early stage
breast cancer
and clinical
trial testing new
chemotherapy
Choicebetween being
immunized for
Hepatitis B,
screened for
antibodies andimmunized if
negative, or
not immunized
unless exposed
Choice between
four main
options forearly stage
prostate cancer(watchful
waiting,surgery,
external beam
radiation andbrachytherapy)
Treatment ofearly stage
prostate cancer
Choice between
treatments forknee pain

Summary of Results
Relevant to VCM
VCM resulted in more use of
personal values when evaluating
attributes of options, somewhat lessambivalence, less uncertainty, anddid not change decision preference.

VCM increased action-taking(screening or vaccination).

Participants preferred VCM design
with summary over VCM withoutsummary and no VCM.

VCM users reported higher
preparation for decision making
retrospectively and had reduced
regret at 1 year.
VCM resulted in higher scores on
decisional self-efficacy, preparation
for decision making, and arthritis
self-efficacy.

Clarifying & Expressing Values

23

Frosch2008(n = 611)

Time Tradeoff and Visual
Analogue
Scale

Kennedy2002(n = 894)

List ofconcerns anddiscussion

Labrecque2010(n = 63)
Lerman1997(n = 400)

Rating Scales

List ofconcerns withdiscussion

Whether or not
to have prostate
specific antigen(PSA) testingto screen for
prostate cancer
Choice between
treatment
options formenorrhagia(advice andreassurance,
addressing
possible
iatrogenic
causes, drug
therapy, or
surgery such as
hysterectomy
or endometrial
destruction)
Whether or
not to have avasectomy
Whether or not
to have genetic
testing for
BRCA1

VCM had no effect on preferences
for PSA testing, preference forwatchful waiting, knowledge ordecisional conflict.

VCM resulted in minimal
improvements in self-reported
health status, lower use of a moreinvasive treatment, higher patientsatisfaction, more frequent clinician
perceptions of "longer than usual"consultations, and lower overall
costs.

VCM had no effect on decisional
conflict, knowledge, decisionpreferences or certainty.
VCM with education resulted inincreased perceptions of risks andlimitations of BRCA1 testing,but knowledge was no better
than education alone. Perceived
personal risk decreased morewith education alone, and neither
VCM and education nor education
alone influenced perceptions ofbenefits of BRCA1 testing, decision
intentions, or decisions.

Clarifying & Expressing Values
Montgomery
2003(n = 217)

Decisionanalysis withstandard
gambleO'Connor 1999
(n = 201)

Balance Scale(Pros andCons)

Sheridan2010(n = 137)
hypothetical decision

Rating andranking tasks(prioritization)

van Roosmalen
2004(n = 88)

Time Tradeoff

24

Whether or not
to start drug
therapy for
hypertension

VCM increased knowledge andreduced total decisional conflictby significantly reducing scoreson uninformed, unclear values
and unsupported subscales andsomewhat reducing scores on
uncertainty subscale. VCM did
not influence scores on decisionquality subscale, nor did it change
state anxiety, decision intention, or
ultimate decision.
Whether or not VCM had no effect on clarity
to take hormone of values, concordance between
replacement
values and decision, total decisional
therapy after
conflict, other subscales ofmenopause
Decisional Conflict Scale, nor
acceptability of intervention.
Whether or
VCM increased time spent withnot to initiate
online tool, but did not affectbehaviors
decisional conflict, clarity ofto prevent
values, behavioral intentions,coronary heart
perceptions that decision was indisease (CHD), line with values, self-efficacy for
and, if so,
reducing coronary risk, decision
which behaviors intentions (including numberof treatments intended), norperceptions of tool.
Choice between VCM resulted in lower scores on
intensive
depression and intrusive thoughts,
screening andhigher self-rated health, stronger
prophylactic
treatment preferences for breasts,
surgery forincreased perceptions of having
breasts and/or
weighed pros and cons for breast
ovariestreatments, and perceptions thatspecialists had a strong preference
about breast treatments 9 months
post-intervention. There were no
significant differences observed
for any outcomes at 3 months postintervention.

Clarifying & Expressing Values
Table 6: Outcomes of VCM Trials

Study

Abhyankar
2010(n = 30)
Clancy1988(n = 1280)
FeldmanStewart 2006
(n = 90)
FeldmanStewart 2012(n = 156)
Fraenkel2007(n = 87)
Frosch2008(n = 611)

25

Likeab
ility

Knowl
edge

Deci
sion
Ma
king
Process
es

Decis
ional
Conflict

Improved

Improved

Decision
Satisfa
ction

RegretPreferenceIntentBehavior

No effect

Increased

Improved

Improved

Improved

Improved

No effect

No effect

No effect

HealthOutcomeClarifying & Expressing Values
Likeab
ility

Knowl
edge

Study

Deci
sion
Ma
king
Process
es

Decis
ional
ConflictKennedy2002(n = 894)

RegretPreferenceIntentImproved

Labrecque2010(n = 63)
Lerman1997(n = 400)Montgomery
2003(n = 217)

No effect

No effect

No effect

Improved

Improved

No effect

Improved

O'Connor
1999(n = 201)

No effect

No effect(concordance)

Sheridan2010(n = 137)
van
Roosmalen
2004(n = 88)

No effect

No effect

26

Satisfa
ction

Improved

Behavior

HealthOutcomeReducedNo effect(reducedcosts)

No effect

No effect

No effect

No effect

No effect

No effect

No effect

No effect

No effect

Changed

Improved

Clarifying & Expressing Values
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Clarifying & Expressing Values
APPENDIX:
ORIGINAL CHAPTER D
Original Authors
Annette O’Connor(co-lead)
Hilary Llewellyn-Thomas(co-lead)

University of Ottawa, Ontario

CanadaDartmouth Medical School, DartmouthCollege, New Hampshire

USA

James Dolan

University of Rochester, New YorkUSA

Miriam Kupperman

University of California at San Francisco

USA

Celia Wills

Michigan State University

USA

Original Rationale / Theory
A key objective of patient decision aids is to help patients to clarify and communicate thepersonal value of options, in order to improve the match between what is personally mostdesirable and which option is actually selected. Several mechanisms explain how patientdecision aids may accomplish this goal.
Most patient decision aids describe the options and outcomes in sufficient detail for decision
making (O’Connor et al., 2003). This helps patients understand what it is like to undergo theprocedures involved and to face the physical, emotional, and social consequences. Fishhoffand colleagues (1980) found that patients are better able to judge the value of consequences
when they are familiar, simple, and directly experienced. Providing detailed descriptions ofexperiences makes the features of an option more vivid for individuals.
Some patient decision aids use balanced examples of how others value the features of each
option, in order to illustrate how different values may lead to different choices. Patients may beable to sort through their personal values by considering which examples most closely match
their own and which do not.
Some patient decision aids explicitly measure values. They guide patients to rate or trade-off
different features of options. This engaging process may increase awareness of personal values
and provide insight into the trade-offs that need to be made in choosing one option over another.
Some patient decision aids not only encourage patients to clarify their values, but also to sharethem with others involved in the decision. Strategies may range from recording values, guiding/coaching patients in values communication, training practitioners in values communication, or
sending recorded values to providers. Strategies that facilitate communication may increase thechances that they are discussed in counseling sessions and that patients receive the most valued
option (Dodin et al., 2001; Guimond et al., 2003; Holmes-Rovner et al., 1999; O’Connor et al.,31Clarifying & Expressing Values
1999; Rothert et al., 1997)
Original Evidence
RCTs Involving Patients Facing Actual Choices (O’Connor, et al., 2003).
Data were obtained from the Cochrane Systematic Review of patient decision aids in which
29 different patient decision aids were evaluated in 34 trials. Of these 19, 11 measured thematch between personal values and choices (n = 3), and self-reports about feeling clear about
the personal importance of benefits versus harms (n = 10). One trial explored the effects onpractitioner’s discussion of values.
Ways To Clarify Values
The most frequently used values clarification techniques in patient decision aids are:Describing features: 100% (19 of 19) patient decision aids described the features of
options and their outcomes. However, there was considerable variability in the levelof detail about what it is like to undergo the procedures and to live with the physical,
emotional, and social consequences. Some used detailed scenarios or testimonials; others
briefly described key features.
Examples of others’ values: 72% (13 of 18) provided examples of how other patients’values led them to make different choices;
Measuring values of features: 42% (8 of 19) explicitly guided patients to rate or tradeoff different features of options using: personal balance scales (4 of 8); non-directive
counseling with standardized questions (2 of 8); relevance charts (1 of 8); and theanalytic hierarchy process (1 of 8).
Communicating values: 47% (9 of 19) of patient decision aids used strategies to facilitate
the communication of values, such as personal worksheets (5 of 9); and personalcoaching or encouragement to communicate values (4 of 9).
Primary Endpoints
Match between values and choices
3 randomized trials (Dodin et al., 2001; O’Connor, Wells et al., 1999; Rothert et al., 1997), allfocused on menopause hormone decisions, evaluated the effects of a basic method of clarifying
values in a DA (feature description) compared to DAs with multiple methods (feature description+ examples; feature description + examples + rating, feature description +examples + rating +guidance in communicating values). All three studies measured the match between values andchoices differently.

32Clarifying & Expressing Values
Are more values clarification methods better than the single method of featuredescription?
All three trials found that more methods are usually better than a single method. When the single
method of describing experience with options was brief, there was an overall benefit of adding
one other method (examples) or several other methods (examples, rating values, guidance incommunicating values). However, when the single method of describing consequences wasa detailed description of physical, emotional, and social consequences, the benefit was large
but of borderline statistical significance (p = 0.06), and was confined only to those who wereconsidering changing from not taking hormones to taking them. In those who were not on
hormones and would remain that way, there was no added benefit from having more than one
method.
Feeling clear about personal values
Ten trials used a subscale of the Decisional Conflict Scale (O’Connor, 1995) to measure theextent to which patients feel clear about personal values (Davison et al., 1999; Dodin et al.,
2001; Dolan et al., 2002; Goel et al., 2001; Man-Son Hing et al., 1999; Morgan, 1997; Murray
et al., 2001a; 2001b, O’Connor et al., 1998; O’Connor et al., 1999). Scores that combine 3
items (e.g., “I am clear about the personal importance of positive versus negative features of theoptions”) in the subscale can range from 0 (“strongly agree”) to 100 (“strongly disagree”).
Are values clarification methods better than usual practices? 6 trials compared patientdecision aids with one or more values clarification methods to usual practices (Davison et al.,
1999; Dolan et al., 2002; Man-Son Hing et al., 1999; Morgan et al., 1997; Murray et al., 2001a;
2001b). In 3 of these 6 trials, there were statistically significant differences in favor of patientdecision aids. The overall improvement, combining results from all 6 trials, was statisticallysignificant (the weighted average difference in favor of patient decision aids was 5.48 points outof 100; we are confident that if this study were repeated several times, 95% of the time theimprovement would fall between 1.44 and 9.53 points). The importance of this small
improvement in scores needs to be evaluated further.
Are more methods or more detailed methods better than fewer or less detailed methods?
Of the 4 trials making this comparison (O’Connor et al., 1999; Dodin et al., 2001; Goel et al.,2001), 3 showed no significant differences and one showed differences in favor of more methods(O’Connor et al., 1998). When the results of all 4 trials were combined, the overall improvement
was not statistically significant. The one trial that did show improvement (7.5 points out of 100)
had feature descriptions that were very brief. In three trials whose basic feature descriptions weremore detailed, there was no significant improvement.
Communication of values in discussions with others
One trial (Guimond et al., 2003) involved tape recording the dialogue between patients anddoctors after patients were either prepared with: 1) a patient decision aid with brief information
about consequences (n = 18); or 2) a patient decision aid with detailed information about
consequences, examples of others’ values, rating of values, and guidance in recording andcommunicating values (n = 16). The group prepared using the simpler patient decision aid
had less discussion of values (median = 16) than did the group prepared using the moredetailed patient decision aid with a written record of values (n = 22), but the difference was notstatistically significant from 0 (p=0.10).

33

Clarifying & Expressing Values
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