Some but not all dyadic measures in shared decision making research have satisfactory psychometric properties

Turcotte, Stéphane; Robitaille, Hubert; Stewart, Moira; Frosch, Dominick L.; Grimshaw, Jeremy; Labrecque, Michel; Ouimet, Mathieu; Rousseau, Michel; Stacey, Dawn; Elwyn, Glyn

doi:10.1016/j.jclinepi.2012.06.019

Cited by 30 publications

(35 citation statements)

References 42 publications

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“…We performed a secondary analysis of all data collected between January 2009 and April 2010 for the EXACKTE2 (EXploiting clinicAl Consultations as a Knowledge Transfer and Exchange environment) study [15, 22]. The EXACKTE2 study assessed how patients and physicians influence each other in consultations, based on a shared decision-making (SDM) model but in the absence of SDM interventions.…”

Section: Methodsmentioning

confidence: 99%

“…The EXACKTE2 study assessed how patients and physicians influence each other in consultations, based on a shared decision-making (SDM) model but in the absence of SDM interventions. The study was conducted in 17 primary care clinics in two Canadian provinces [15, 22]. French-speaking pairs of patients and physicians were recruited in a practice-based research network (PBRN) in the Province of Quebec consisting of twelve family practice teaching units with a total of about 250 family physicians, including residents, and over 300,000 consultations per year.…”

Section: Methodsmentioning

confidence: 99%

“…The measures included in this secondary analysis were selected from a systematic literature review conducted by the research team [8] and for the potential of their variables to predict decision regret as suggested by EXACKTE’s theoretical framework [15, 22]. …”

Section: Methodsmentioning

confidence: 99%

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More primary care patients regret health decisions if they experienced decisional conflict in the consultation: a secondary analysis of a multicenter descriptive study

et al. 2016

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BackgroundWe sought to estimate the extent of decision regret among primary care patients and identify risk factors associated with regret.MethodsSecondary analysis of an observational descriptive study conducted in two Canadian provinces. Unique patient-physician dyads were recruited from 17 primary care clinics and data on patient, physician and consultation characteristics were collected before, during and immediately after consultations, as well as two weeks post-consultation, when patients completed the Decision Regret Scale (DRS). We examined the DRS score distribution and performed ordinal logistic regression analysis to identify predictors of regret.ResultsAmong 258 unique patient-physicians dyads, mean ± standard deviation of decision regret scores was 11.7 ± 15.1 out of 100. Overall, 43 % of patients reported no regret, 45 % reported mild regret and 12 % reported moderate to strong regret. In multivariate analyses, higher decision regret was strongly associated with increased decisional conflict and less significantly associated with patient age and education, as well with male (vs. female) physicians and residents (vs. teachers).ConclusionAfter consulting family physicians, most primary care patients experience little decision regret, but some experience more regret if there is decisional conflict. Strategies for reducing decisional conflict in primary care, such as shared decision-making with decision aids, seem warranted.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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More primary care patients regret health decisions if they experienced decisional conflict in the consultation: a secondary analysis of a multicenter descriptive study

et al. 2016

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“…The tool was only in pilot stage in the studies included in this review, but appears to offer a reasonable tool for patient participation measurement 54 55. A second dyadic-SDM model in trial stages57 also shows promise, but its length currently reduces utility.…”

Section: Discussionmentioning

confidence: 99%

A systematic review of reliable and valid tools for the measurement of patient participation in healthcare

2015

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Few reliable and valid tools for measurement of patient participation in healthcare have been recently developed. Of those reported in this review, the dyadic Observing Patient Involvement in Decision Making (dyadic-OPTION) tool presents the most promise for measuring core components of patient participation. There remains a need for further study into valid, reliable and feasible strategies for measuring patient participation as part of continuous quality improvement.

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“…SDM is a collaborative communication process in which health decisions are made jointly by health care providers and consumers of health care services (Légaré, Turcotte, Robitaille et al 2012). This practice is particularly desirable for preference-sensitive decisions (where there is more than one viable option for a given consumer that should be tailored to his/her preferences) requiring expertise from both parties: providers’ scientific- and clinically-based knowledge and consumers’ values and personal experiences with treatment options (Légaré and Witteman 2013; Veroff, Marr, Wennberg 2013).…”

Section: Introductionmentioning

confidence: 99%

Core Domains of Shared Decision-Making During Psychiatric Visits: Scientific and Preference-Based Discussions

Fukui

Matthias

Salyers

2014

Adm Policy Ment Health

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Shared decision-making (SDM) is imperative to person-centered care, yet little is known about what aspects of SDM are targeted during psychiatric visits. This secondary data analysis (191 psychiatric visits with 11 providers, coded with a validated SDM coding system) revealed two factors (scientific and preference-based discussions) underlying SDM communication. Preference-based discussion occurred less. Both provider and consumer initiation of SDM elements and decision complexity were associated with greater discussions in both factors, but were more strongly associated with scientific discussion. Longer visit length correlated with only scientific discussion. Providers’ understanding of core domains could facilitate engaging consumers in SDM.

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Some but not all dyadic measures in shared decision making research have satisfactory psychometric properties

Abstract: The subscales for values clarification, perceived behavioral control, information verifying, and uncertainty are appropriate dyadic measures for SDM research and can be used to derive dyadic indices.

Cited by 30 publications

References 42 publications

More primary care patients regret health decisions if they experienced decisional conflict in the consultation: a secondary analysis of a multicenter descriptive study

More primary care patients regret health decisions if they experienced decisional conflict in the consultation: a secondary analysis of a multicenter descriptive study

A systematic review of reliable and valid tools for the measurement of patient participation in healthcare

Core Domains of Shared Decision-Making During Psychiatric Visits: Scientific and Preference-Based Discussions

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