Factors Affecting Participant Recruitment and Retention in Borderline Personality Disorder Research: A Feasibility Study
Bibliographic record
Abstract
Abstract Background Previous studies have shown that stigma is a major barrier to participation in psychiatric research, and that individuals who participate in psychiatric research may differ clinically from non-participants. However, no previous study has explored research recruitment and retention challenges in the context of personality disorders. Aim To provide an analysis of the factors affecting participant recruitment and retention in a study of borderline personality disorder. Methods Adult inpatients in a tertiary psychiatric hospital were approached about participating in a cross-sectional study of borderline personality disorder. Recruitment rates, retention rates, and reasons for declining participation or withdrawing from the study were collected. Demographic characteristics were compared between participants and non-participants, and between patients who remained in the study and those who withdrew. Results A total of 70 participants were recruited into the study between January 2018 and February 2020. Recruitment and retention rates were 46% and 70%, respectively. Lack of interest was the most commonly cited reason for non-participation, followed by scheduling conflicts and concerns regarding mental/physical well-being. Age and sex were not predictors of study participation or retention. Conclusions More research is needed to explore patients’ perspectives and attitudes towards borderline personality disorder diagnosis and research; determine effects of different recruitment strategies; and identify clinical predictors of recruitment and retention in personality disorder research. Trial registration: The study was not registered as it did not involve the provision of a health care intervention to human participants.
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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 | 0.130 | 0.165 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".