Predictors of Study Attrition in a Randomized Controlled Trial Evaluating a Perinatal Home-Visiting Program with Mothers with Psychosocial Vulnerabilities
Bibliographic record
Abstract
OBJECTIVE: Randomised controlled trials evaluating perinatal home-visiting programs are frequently confronted with the problem of high attrition rates. The aim of the present study is to identify predictors of study attrition in a trial evaluating a perinatal home-visiting program in France. MATERIALS AND METHODS: CAPEDP is a French randomized trial comparing a perinatal home-visiting program using psychologists versus usual care (N = 440). The first assessment was at inclusion into the trial at the 27th week of pregnancy and the final assessment when the child reached the age of two. Attrition rates were calculated at 3 and 24 months postpartum. Stepwise logistic regression was used to identify predictors of early (between inclusion and 3 months postpartum) and later (between 3 and 24 months postpartum) attrition among social, psychological and parenting factors. RESULTS: Attrition rates were 17% and 63% at 3 and 24 months respectively. At 24 months, there was significantly more attrition in the control arm (70.6%) compared to the intervention arm (55.2%). Five independent predictors of early attrition were identified: having already had an abortion; having greater attachment insecurity as measured with the Vulnerable Attachment Style Questionnaire (VASQ); having lower global severity of psychiatric symptoms as assessed with the Symptom Check-List (SCL-90) at inclusion, being neither currently employed nor studying; and declaring no tobacco consumption during pregnancy. Being randomized into the control arm, having undergone early parental loss before age 11 and having lower global severity of psychiatric symptoms (SCL-90) at 3 months postpartum were the only variables associated with later attrition. CONCLUSION: This study provides key information for identifying mothers who may require specific support to avoid study attrition in trials evaluating a home-visiting program.
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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 | 0.037 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".