Non-time-varying characteristics at enrolment.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<div><p>Background</p><p>All longitudinal cohort studies strive for high participant retention, although attrition is common. Understanding determinants of attrition is important to inform and develop targeted strategies to improve study participation. We aimed to identify factors associated with research participation in a large children’s primary care cohort study.</p><p>Methods</p><p>In this longitudinal cohort study between 2008 and 2020, all children who participated in the Applied Research Group for Kids (TARGet Kids!) were included. TARGet Kids! is a large primary care practice-based pediatric research network in Canada with ongoing data collection at well-child visits. Several sociodemographic, health, and study design factors were examined for their associations with research participation. The primary outcome was attendance of eligible research follow-up visits. The secondary outcome was time to withdrawal from the TARGet Kids! study. Generalized linear mixed effects models and Cox proportional hazard models were fitted. We have engaged parent partners in all stages of this study.</p><p>Results</p><p>A total 10,412 children with 62,655 total eligible research follow-up visits were included. Mean age at enrolment was 22 months, 52% were male, and 52% had mothers of European ethnicity. 68.4% of the participants attended at least 1 research follow-up visit. Since 2008, 6.4% of the participants have submitted a withdrawal request. Key factors associated with research participation included child age, ethnicity, maternal age, maternal education level, family income, parental employment, child diagnosis of chronic health conditions, certain study sites, and missingness in questionnaire data.</p><p>Conclusions</p><p>Socioeconomic status, demographic factors, chronic conditions, and missingness in questionnaire data were associated with research participation in this large primary care practice-based cohort study of children. Results from this analysis and input from our parent partners suggested that retention strategies could include continued parent engagement, creating brand identity and communication tools, using multiple languages and avoiding redundancy in the questionnaires.</p></div>
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.237 | 0.183 |
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 it