061 Patient involvement in decision making: an updated systematic review of studies using the option-12 instrument
Bibliographic record
Abstract
Introduction A decade has passed since Couët et al. (2013)1 provided the first comprehensive exploration of the extent to which healthcare providers involve patients in decision- making. The evolving nature of patient involvement practices emphasizes the imperative for an updated review of studies using the OPTION-12 scale2 to identify the state of the knowledge and remaining gaps. Methods An updated systematic review was conducted, following the PRISMA statement. Four electronic databases (MEDLINE, Embase, Cochrane Library and Web of Science) were consulted, from 2012 to September 2023. Observational and experimental studies were included. Data extraction covered study details, patients, providers and consultations’ characteristics and OPTION-12 scores. Two reviewers independently conducted screening and extraction. Descriptive statistics were used to summarize the studies’ characteristics, and the mean OPTION-12 score was calculated. Preliminary Results One hundred and four eligible studies were identified, with 75 of them published after Couët’s review.1 Most studies were conducted in the United States (n = 31, 30%), the United Kingdom (n = 14, 13%), and The Netherlands (n = 13, 13%). A substantial proportion of studies (27%) addressed multiple health conditions, and the most represented specific areas were oncological (16%), mental health (12%) and cardiovascular care (11%). Mean total scores ranged from 3 to 74 on a 0–100 scale, with an overall mean of 28. Discussion A decade after the first systematic review in this field, our preliminary results reveal persistently low levels of patient-involvement behaviors, with only a marginal increase in the overall OPTION-12 mean score. Conclusions These findings set the stage for a more in-depth exploration of patient involvement trends and variations. The forthcoming phase involves a meta- analysis for a weighted average score, exploring how various factors might influence total scores through subgroup analyses and metaregression. References Couët N, Desroches S, Robitaille H, Vaillancourt H, Leblanc A, Turcotte S, Elwyn G, Légaré F. Assessments of the extent to which health-care providers involve patients in decision making: a systematic review of studies using the OPTION instrument. Health Expect. 2013;18(4):542–61. Elwyn G, Hutchings H, Edwards A. et al. The OPTION scale: measuring the extent that clinicians involve patients in decision-making tasks. Health Expect. 2005;8(1):34–42.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.061 | 0.159 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.011 |
| Bibliometrics | 0.025 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".