Patients as teachers: a within-subjects randomized pilot experiment of patient-led online learning modules for health professionals.

PURPOSE: Many health professions education programs involve people with lived experience as expert speakers. Such presentations may help learners better understand the realities of living with chronic illness or experiencing an acute health problem. However, lectures from only one or a small number of people may not adequately illustrate the perspectives and experiences of a diverse patient cohort. Additionally, logistical constraints such as public health restrictions or travel barriers may impede in-person presentations, particularly among people who have more restrictions on their time. Health professions education programs may benefit from understanding the potential effects of online patient-led presentations with a diverse set of speakers. We aimed to explore whether patient-led online learning modules about diabetes care would influence learners' responses to clinical scenarios and to collect learners' feedback about the modules. METHOD: This within-subjects randomized experiment involved 26 third-year medical students at Université Laval in Quebec, Canada. Participation in the experiment was an optional component within a required course. Prior to the intervention, participating learners responded to three clinical scenarios randomly selected from a set of six such scenarios. Each participant responded to the other three scenarios after the intervention. The intervention consisted of patient-led online learning modules incorporating segments of narratives from 21 patient partners (11 racialized or Indigenous) describing why and how clinicians could provide patient-centered care. Working with clinical teachers and psychometric experts, we developed a scoring grid based on the biopsychosocial model and set 0.6 as a passing score. Independent evaluators, blinded to whether each response was collected before or after the intervention, then scored learners' responses to scenarios using the grid. We used Fisher's Exact test to compare proportions of passing scores before and after the intervention. RESULTS: Learners' overall percentage of passing scores prior to the intervention was 66%. Following the intervention, the percentage of passing scores was 76% (p = 0.002). Overall, learners expressed appreciation and other positive feedback regarding the patient-led online learning modules. DISCUSSION: Findings from this experiment suggest that learners can learn to provide better patient-centered care by watching patient-led online learning modules created in collaboration with a diversity of patient partners.

Prediction models of diabetes complications: a scoping review.

BACKGROUND: Diabetes often places a large burden on people with diabetes (hereafter 'patients') and the society, that is, in part attributable to its complications. However, evidence from models predicting diabetes complications in patients remains unclear. With the collaboration of patient partners, we aimed to describe existing prediction models of physical and mental health complications of diabetes. METHODS: Building on existing frameworks, we systematically searched for studies in Ovid-Medline and Embase. We included studies describing prognostic prediction models that used data from patients with pre-diabetes or any type of diabetes, published between 2000 and 2020. Independent reviewers screened articles, extracted data and narratively synthesised findings using established reporting standards. RESULTS: Overall, 78 studies reported 260 risk prediction models of cardiovascular complications (n=42 studies), mortality (n=16), kidney complications (n=14), eye complications (n=10), hypoglycaemia (n=8), nerve complications (n=3), cancer (n=2), fracture (n=2) and dementia (n=1). Prevalent complications deemed important by patients such as amputation and mental health were poorly or not at all represented. Studies primarily analysed data from older people with type 2 diabetes (n=54), with little focus on pre-diabetes (n=0), type 1 diabetes (n=8), younger (n=1) and racialised people (n=10). Per complication, predictors vary substantially between models. Studies with details of calibration and discrimination mostly exhibited good model performance. CONCLUSION: This rigorous knowledge synthesis provides evidence of gaps in the landscape of diabetes complication prediction models. Future studies should address unmet needs for analyses of complications n> and among patient groups currently under-represented in the literature and should consistently report relevant statistics. SCOPING REVIEW REGISTRATION: https://osf.io/fjubt/.

Clarifying Values: An Updated and Expanded Systematic Review and Meta-Analysis.

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 (χ2 = 9.25, P = 0.01). There were no differences between different values clarification methods regarding decisional conflict (χ2 = 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.

Systematic Development of Patient Decision Aids: An Update from the IPDAS Collaboration.

BACKGROUND: The 2013 update of the evidence informing the quality dimensions behind the International Patient Decision Aid Standards (IPDAS) offered a model process for developers of patient decision aids. OBJECTIVE: To summarize and update the evidence used to inform the systematic development of patient decision aids from the IPDAS Collaboration. METHODS: To provide further details about design and development methods, we summarized findings from a subgroup (n = 283 patient decision aid projects) in a recent systematic review of user involvement by Vaisson et al. Using a new measure of user-centeredness (UCD-11), we then rated the degree of user-centeredness reported in 66 articles describing patient decision aid development and citing the 2013 IPDAS update on systematic development. We contacted the 66 articles' authors to request their self-reports of UCD-11 items. RESULTS: The 283 development processes varied substantially from minimal iteration cycles to more complex processes, with multiple iterations, needs assessments, and extensive involvement of end users. We summarized minimal, medium, and maximal processes from the data. Authors of 54 of 66 articles (82%) provided self-reported UCD-11 ratings. Self-reported scores were significantly higher than reviewer ratings (reviewers: mean [SD] = 6.45 [3.10]; authors: mean [SD] = 9.62 [1.16], P < 0.001). CONCLUSIONS: Decision aid developers have embraced principles of user-centered design in the development of patient decision aids while also underreporting aspects of user involvement in publications about their tools. Templates may reduce the need for extensive development, and new approaches for rapid development of aids have been proposed when a more detailed approach is not feasible. We provide empirically derived benchmark processes and a reporting checklist to support developers in more fully describing their development processes.[Box: see text].