Evaluation of a prenatal screening decision aid: A mixed methods pilot study.

BACKGROUND: We developed a decision aid (DA) to help pregnant women and their partners make informed decisions about prenatal screening for trisomy. We aimed to determine its usefulness for preparing for decision-making and its acceptability among end-users. METHODS: In this mixed-methods pilot study, we recruited participants in three prenatal care settings in Quebec City. Eligible women were over 18 and more than 16 weeks pregnant or had given birth recently. We asked them about the usefulness of the DA using an interview grid based on the Technology Acceptance Model. We performed descriptive statistics and deductive analysis. RESULTS: Thirty-nine dyads or individuals participated in the study. Mean usefulness score was 86.2 ± 13. Most participants found the amount of information in the DA just right (79.5%), balanced (89.7%), and very useful (61.5%). They were less satisfied with the presentation and the values worksheet and suggested different values clarification methods. CONCLUSION: Rigorous pilot tests of DAs with patients are an important stage in their development before the more formal assessments that precede scaling up the DA in clinical practice. PRACTICE IMPLICATIONS: The next version of the DA will integrate the suggestions of end-users for better decision-making processes about prenatal screening for trisomy.

Decision Regret among Informal Caregivers Making Housing Decisions for Older Adults with Cognitive Impairment: A Cross-sectional Analysis.

Background. Informal caregivers are regularly faced with difficult housing decisions for older adults with cognitive impairment. They often regret the decision they made. We aimed to identify factors associated with decision regret among informal caregivers engaging in housing decisions for cognitively impaired older adults. Methods. We performed a secondary analysis of cross-sectional data collected from a cluster-randomized trial. Eligible participants were informal caregivers involved in making housing decisions for cognitively impaired older adults. Decision regret was assessed after caregivers' enrollment in the study using the Decision Regret Scale (DRS), scored from 0 to 100. We used a conceptual framework of potential predictors of regret to identify independent variables. We performed multilevel analyses using a mixed linear model by estimating fixed effects (ß) and 95% confidence intervals (CIs). Results. The mean (SD) DRS score of 296 informal caregivers (mean [SD] age, 62 [12] years) was 12.4 (18.4). Factors associated with less decision regret were having a college degree compared to primary education (ß [95% CI]: -11.14 [-18.36, -3.92]), being married compared to being single (-5.60 [-10.05, -1.15]), informal caregivers' perception that a joint process occurred (-0.14 [-0.25, -0.02]), and older adults' not having a specific housing preference compared to preferring to stay at home (-4.13 [-7.40, -0.86]). Factors associated with more decision regret were being retired compared to being a homemaker (7.74 [1.32, 14.16]), higher burden of care (0.14 [0.05, 0.22]), and higher decisional conflict (0.51 [0.34, 0.67]). Limitations. Our analysis may not illustrate all predictors of decision regret among informal caregivers. Conclusions. Our findings will allow risk-mitigation strategies for informal caregivers at risk of experiencing regret.

Towards a taxonomy of behavior change techniques for promoting shared decision making.

BACKGROUND: There is little information about the functions and behavior change techniques (BCTs) needed to implement shared decision making (SDM) in clinical practice. To guide future implementation initiatives, we sought to develop a BCT taxonomy for SDM implementation interventions. METHODS: This study is a secondary analysis of a 2018 Cochrane review on interventions for increasing the use of shared decision making by healthcare professionals. We examined all 87 studies included in the review. We extracted relevant information on each study intervention into a spreadsheet. Coders had undergone a training workshop on intervention functions and online training on BCT Taxonomy version 1 (BCTTv1). We performed functions and BCTs coding trials, and identified coding rules. We used Michie's guide for designing behavior change interventions to code the functions and BCTs used in the interventions. Coders met to compare coding and discrepancies were discussed until consensus was reached. Data was analyzed using simple descriptive statistics. RESULTS: Overall, 7 functions, 24 combinations of functions and 32 BCTs were used in the 87 SDM implementation interventions. The mean of functions per intervention was 2.5 and the mean of BCTs per intervention was 3.7. The functions Coercion and Restriction were not found. The most common function was Education (73 studies). Three combinations of functions were most common (e.g: Education + Persuasion, used in 10 studies). The functions associated with more effective SDM implementation interventions were Modeling and Training. The most effective combination of functions was Education + Training + Modeling + Enablement. The most commonly used BCT was Instruction on how to perform the behavior (43 studies). BCTs associated with more effective SDM implementation interventions were: Instruction on how to perform the behavior, Demonstration of the behavior, Feedback on behavior, Pharmacological support, Material reward, and Biofeedback. Twenty-five BCTs were associated with less effective SDM implementation interventions. Four new BCTs were identified: General information to support the behavior, Tailoring, Exercises to conceptually prepare for the behavior, and Experience sharing and learning. CONCLUSIONS: We established a BCT taxonomy specific to the field of SDM to guide future SDM implementation interventions. Four new BCTs should be added to BCTTv1.

Extent and Predictors of Decision Regret among Informal Caregivers Making Decisions for a Loved One: A Systematic Review.

BACKGROUND: Informal caregivers often serve as decision makers for dependent or vulnerable individuals facing health care decisions. Decision regret is one of the most prevalent outcomes reported by informal caregivers who have made such decisions. OBJECTIVE: To examine levels of decision regret and its predictors among informal caregivers who have made health-related decisions for a loved one. DATA SOURCES: We performed a systematic search of Embase, MEDLINE, Web of Science, and Google Scholar up to November 2018. Participants were informal caregivers, and the outcome was decision regret as measured using the Decision Regret Scale (DRS). REVIEW METHODS: Two reviewers independently selected eligible studies, extracted data, and assessed the methodological quality of studies using the Mixed Methods Appraisal Tool. We performed a narrative synthesis and presented predictors of decision regret using a conceptual framework, dividing the predictors into decision antecedents, decision-making process, and decision outcomes. RESULTS: We included 16 of 3003 studies identified. Most studies (n = 13) reported a mean DRS score ranging from 7.0 to 32.3 out of 100 (median = 14.3). The methodological quality of studies was acceptable. We organized predictors and their estimated effects (ß) or odds ratio (OR) with 95% confidence interval (CI) as follows: decision antecedents (e.g., caregivers' desire to avoid the decision, OR 2.07, 95% CI [1.04-4.12], P = 0.04), decision-making process (e.g., caregivers' perception of effective decision making, ß = 0.49 [0.05, 0.93], P < 0.01), and decision outcomes (e.g., incontinence, OR = 4.4 [1.1, 18.1], P < 0.001). CONCLUSIONS: This review shows that informal caregivers' level of decision regret is generally low but is high for some decisions. We also identified predictors of regret during different stages of the decision-making process. These findings may guide future research on improving caregivers' experiences.