TY - JOUR
T1 - Clarifying Values: An Updated and Expanded Systematic Review and Meta-Analysis
AU - Witteman, H.O.
AU - Ndjaboue, R.
AU - Vaisson, G.
AU - Dansokho, S.C.
AU - Arnold, B.
AU - Bridges, J.F.P.
AU - Comeau, S.
AU - Fagerlin, A.
AU - Gavaruzzi, T.
AU - Marcoux, M.
AU - Pieterse, A.
AU - Pignone, M.
AU - Provencher, T.
AU - Racine, C.
AU - Regier, D.
AU - Rochefort-Brihay, C.
AU - Thokala, P.
AU - Weernink, M.
AU - White, D.B.
AU - Wills, C.E.
AU - Jansen, J.
N1 - Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Financial support for this study was provided in part by the Canadian Institutes of Health Research (CIHR) FDN-148426 (principal investigator: HOW). HOW receives salary support from Tier 2 Canada Research Chair in Human-Centred Digital Health and received salary support during this study from a Fonds de Recherche du Québec-Santé (FRQS) Research Scholar Junior 2 Career Award. The funding agreements ensured the authors’ independence in designing the study, interpreting the data, writing, and publishing the article.
Funding Information:
We thank Fr?d?ric Bergeron, MLIS, for assistance with search strategy, Caroline Beaudoin for assistance in resolving article counts, and all authors of the original articles who generously gave their time to provide missing data when we were unable to extract the data needed from their papers. The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Financial support for this study was provided in part by the Canadian Institutes of Health Research (CIHR) FDN-148426 (principal investigator: HOW). HOW receives salary support from Tier 2 Canada Research Chair in Human-Centred Digital Health and received salary support during this study from a Fonds de Recherche du Qu?bec-Sant? (FRQS) Research Scholar Junior 2 Career Award. The funding agreements ensured the authors? independence in designing the study, interpreting the data, writing, and publishing the article.
Publisher Copyright:
© The Author(s) 2021.
PY - 2021/10/1
Y1 - 2021/10/1
N2 - Background Patient decision aids should help people make evidence-informed decisions aligned with their values. There is limited guidance about how to achieve such alignment. Purpose To describe the range of values clarification methods available to patient decision aid developers, synthesize evidence regarding their relative merits, and foster collection of evidence by offering researchers a proposed set of outcomes to report when evaluating the effects of values clarification methods. Data Sources MEDLINE, EMBASE, PubMed, Web of Science, the Cochrane Library, and CINAHL. Study Selection We included articles that described randomized trials of 1 or more explicit values clarification methods. From 30,648 records screened, we identified 33 articles describing trials of 43 values clarification methods. Data Extraction Two independent reviewers extracted details about each values clarification method and its evaluation. Data Synthesis Compared to control conditions or to implicit values clarification methods, explicit values clarification methods decreased the frequency of values-incongruent choices (risk difference, -0.04; 95% confidence interval [CI], -0.06 to -0.02; P < 0.001) and decisional conflict (standardized mean difference, -0.20; 95% CI, -0.29 to -0.11; P < 0.001). Multicriteria decision analysis led to more values-congruent decisions than other values clarification methods (chi(2) = 9.25, P = 0.01). There were no differences between different values clarification methods regarding decisional conflict (chi(2) = 6.08, P = 0.05). Limitations Some meta-analyses had high heterogeneity. We grouped values clarification methods into broad categories. Conclusions Current evidence suggests patient decision aids should include an explicit values clarification method. Developers may wish to specifically consider multicriteria decision analysis. Future evaluations of values clarification methods should report their effects on decisional conflict, decisions made, values congruence, and decisional regret.
AB - Background Patient decision aids should help people make evidence-informed decisions aligned with their values. There is limited guidance about how to achieve such alignment. Purpose To describe the range of values clarification methods available to patient decision aid developers, synthesize evidence regarding their relative merits, and foster collection of evidence by offering researchers a proposed set of outcomes to report when evaluating the effects of values clarification methods. Data Sources MEDLINE, EMBASE, PubMed, Web of Science, the Cochrane Library, and CINAHL. Study Selection We included articles that described randomized trials of 1 or more explicit values clarification methods. From 30,648 records screened, we identified 33 articles describing trials of 43 values clarification methods. Data Extraction Two independent reviewers extracted details about each values clarification method and its evaluation. Data Synthesis Compared to control conditions or to implicit values clarification methods, explicit values clarification methods decreased the frequency of values-incongruent choices (risk difference, -0.04; 95% confidence interval [CI], -0.06 to -0.02; P < 0.001) and decisional conflict (standardized mean difference, -0.20; 95% CI, -0.29 to -0.11; P < 0.001). Multicriteria decision analysis led to more values-congruent decisions than other values clarification methods (chi(2) = 9.25, P = 0.01). There were no differences between different values clarification methods regarding decisional conflict (chi(2) = 6.08, P = 0.05). Limitations Some meta-analyses had high heterogeneity. We grouped values clarification methods into broad categories. Conclusions Current evidence suggests patient decision aids should include an explicit values clarification method. Developers may wish to specifically consider multicriteria decision analysis. Future evaluations of values clarification methods should report their effects on decisional conflict, decisions made, values congruence, and decisional regret.
KW - decision making
KW - values clarification
KW - shared decision making
KW - preference elicitation
KW - RANDOMIZED CONTROLLED-TRIAL
KW - INFORMED DECISION-MAKING
KW - CLARIFICATION METHODS
KW - CONJOINT-ANALYSIS
KW - PATIENTS PREFERENCES
KW - DESIGN-FEATURES
KW - PATIENT
KW - CARE
KW - AIDS
KW - PROSTATE
U2 - 10.1177/0272989X211037946
DO - 10.1177/0272989X211037946
M3 - (Systematic) Review article
C2 - 34565196
SN - 0272-989X
VL - 41
SP - 801
EP - 820
JO - Medical Decision Making
JF - Medical Decision Making
IS - 7
ER -