Retaining participants in community-based health research: a case example on standardized planning and reporting
Bibliographic record
Abstract
BACKGROUND: Effective strategies for participant retention are critical in health research to ensure validity, generalizability and efficient use of resources. Yet standardized guidelines for planning and reporting on retention efforts have been lacking. As with randomized controlled trial (RCT) and systematic review (SR) protocols, retention protocols are an opportunity to improve transparency and rigor. An RCT being conducted in British Columbia (BC), Canada provides a case example for developing a priori retention frameworks for use in protocol planning and reporting. METHODS: The BC Healthy Connections Project RCT is examining the effectiveness of a nurse home-visiting program in improving child and maternal outcomes compared with existing services. Participants (N = 739) were girls and young women preparing to parent for the first time and experiencing socioeconomic disadvantage. Quantitative data were collected upon trial entry during pregnancy and during five follow-up interviews until participants' children reached age 2 years. A framework was developed to guide retention of this study population throughout the RCT. We reviewed relevant literature and mapped essential retention activities across the study planning, recruitment and maintenance phases. Interview completion rates were tracked. RESULTS: Results from 3302 follow-up interviews (in-person/telephone) conducted over 4 years indicate high completion rates: 90% (n = 667) at 34 weeks gestation; and 91% (n = 676), 85% (n = 626), 80% (n = 594) and 83% (n = 613) at 2, 10, 18 and 24 months postpartum, respectively. Almost all participants (99%, n = 732) provided ongoing consent to access administrative health data. These results provide preliminary data on the success of the framework. CONCLUSIONS: Our retention results are encouraging given that participants were experiencing considerable socioeconomic disadvantage. Standardized retention planning and reporting may therefore be feasible for health research in general, using the framework we have developed. Use of standardized retention protocols should be encouraged in research to promote consistency across diverse studies, as now happens with RCT and SR protocols. Beyond this, successful retention approaches may help inform health policy-makers and practitioners who also need to better reach, engage and retain underserved populations. TRIAL REGISTRATION: ClinicalTrials.gov, NCT01672060. Registered on 24 August 2012.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.451 | 0.689 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.016 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".