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Record W4417019762 · doi:10.1186/s40900-025-00806-z

Patient engagement and shared decision-making in trial recruitment intervention studies: a systematic review

2025· review· en· W4417019762 on OpenAlexafffund
Tamara L. Morgan, Natasha Hudek, Kelly Carroll, Mei-Lin Yee, Juliette Inglis, Dean Fergusson, Katie Gillies, Dawn P. Richards, Seana N. Semchishen, Justin Presseau, Jeremy Grimshaw, Ian D. Graham, Marc Rodger, Monica Taljaard, Susan Marlin, Charles Weijer, Graeme MacLennan

Bibliographic record

VenueResearch Involvement and Engagement · 2025
Typereview
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsWestern UniversityRobarts Clinical TrialsMcGill UniversityOttawa HospitalUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsPsychological interventionIntervention (counseling)Equity (law)Patient participationRandomized controlled trialClinical trialSystematic review

Abstract

fetched live from OpenAlex

Supporting participation decisions and experiences in clinical trials is a persistent challenge that could be improved by two areas: patient engagement (PE), which involves actively collaborating with patients to enhance research relevance and value, and shared decision-making (SDM), which involves helping individuals make evidence-informed, values-based decisions about participation. The extent to which PE and SDM have informed trial recruitment interventions has not been synthesized. We aimed to explore (1) how PE informed recruitment interventions, both in general and among equity-deserving populations, and whether demographic differences existed between studies using and not using PE, and (2) how SDM has informed recruitment interventions, both in general and among equity-deserving populations. We identified randomized and quasi-randomized recruitment intervention studies from a prior Cochrane review and the Online Resource for Research in Clinical triAls database. We assessed recruitment interventions for reporting of PE and coded the level at which PE occurred (‘substantive engagement’, ‘limited engagement’, ‘both’, ‘unclear’, or ‘no engagement’) and the areas in which PE occurred (development of the research question, intervention design, selecting outcomes, dissemination/implementation, or ‘other’). We coded SDM across six domains: providing information about options, probabilities, clarifying outcomes, guidance in deliberation, using evidence, and disclosure and transparency. Of the 122 recruitment intervention studies included, 37 (30.3%) reported PE, although limited engagement was most common (n = 22; 59.5%). PE was most often used in designing the recruitment intervention (n = 32; 86.5%) followed by ‘other’ (n = 11; 29.7%; e.g., PE supporting participant recruitment efforts), developing the research question (n = 2; 5.4%), selecting outcomes (n = 3; 8.1%), and dissemination/implementation (n = 3; 8.1%). SDM was occasionally reported (n = 25; 20.5%), most commonly as ‘providing information about options’ (n = 11; 9.0%). Equity-deserving populations were the focus of 24 studies (19.7%); 11 of these also used PE (9.0%). Efforts to improve trial participation have not been informed by literature around patient lived experiences. Recruitment interventions infrequently reported any PE and occasionally mentioned SDM. When PE was mentioned, it was usually limited. These results hold among studies involving equity-deserving populations. Greater consideration of PE and SDM could enhance trial recruitment, research impact, trial participation experiences, and equity in trial recruitment. Getting people to participate in clinical trials is challenging. Two approaches that can help are working closely with patients to ensure the research is important to them (called patient engagement, or PE) and helping them understand their options to make informed choices about whether to participate (called shared decision-making, or SDM). We wanted to find out how PE and SDM are used when recruiting people for trials in general and when recruiting populations that are often left out of trials. We also wanted to find out the differences between studies that use PE and those that do not. We reviewed studies about how people are recruited into trials. We checked whether these studies used PE, how engaged patients were (ranging from very engaged to not engaged at all), and where they were engaged, such as helping to choose the research question or sharing results. We also reviewed how SDM was used, such as providing information about options or using evidence to help people decide. Of 122 studies, only 37 mentioned PE, mostly at low levels of engagement. PE was mostly used to help design the recruitment strategy. Only 25 studies mentioned SDM, mainly by providing people with information. Only 24 studies focused on groups that are often overlooked, and only 11 of these used PE. Most efforts to ask people to join trials have not reflected patients’ real-life experiences. Using PE and SDM more effectively could help more people participate and lead to fairer recruitment.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.043
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.296
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0430.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0020.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.004
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.814
GPT teacher head0.648
Teacher spread0.166 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations1
Published2025
Admission routes2
Has abstractyes

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