Determinants of Drop-Out from a Healthy Lifestyle Intervention: Experience from the Centre Pediatrique d'Intervention en Prevention et en Readaptation Cardiovasculaires ( Circuit) Program
Bibliographic record
Abstract
<p>Background: CIRCUIT (CHU Sainte-Justine, Montréal) is a lifestyle intervention focused on increasing physical activity among youth aged 5 to18 y at risk of cardiovascular disease. Over a 2-year period, a personalized strategy is delivered by a team comprising a kinesiologist, dietician and psychologist. Obesity intervention programs typically report high attrition rates.</p> \n \n<p>Objectives: Estimate the prevalence and identify the determinants of drop-out among CIRCUIT participants.</p> \n \n<p>Methods: Anthropometrics and socioeconomic characteristics were collected at baseline. Drop out was defined as ceasing attendance prior to the 1-year follow-up. Differences in baseline characteristics between those who dropped out (n=261) and those who pursued (n=226) CIRCUIT were analyzed using chi-square-, Fisher’s exact-, and t-tests. Logistic regression models adjusted for age, sex, body mass index (BMI) z-score and socio-demographic characteristics.</p> \n \n<p>Results: The drop-out rate for CIRCUIT was 54%. Youth who dropped out were older (mean age 12.6 vs. 11.3 y; p&#60;0.001), less likely to live with both parents (59% vs. 69%, p=0.03), and spent less time living with their mother (69% vs 82%, p&#60;0.001). Their mothers were also less likely to complete high school (81% vs. 89%, p=0.015). No group differences were observed for sex, ethnicity, zBMI, fathers’ education and % of time spent living with the father. In logistic regression models, only older age at initiation of the intervention (OR: 1.1, p&#60;0.001) and lower maternal education (OR: 1.98, p=0.032) predicted drop out.</p> \n \n<p>Conclusion: Although comparable to other programs, attrition was high. Promoting earlier initiation and tailoring the program to parental level of education may improve retention to CIRCUIT.</p>
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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 | 0.002 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; a candidate call from one teacher head, 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".