Understanding levels of engagement and readiness for change in an eHealth sleep program for children with neurodevelopmental disorders
Bibliographic record
Abstract
Background Children with neurodevelopmental disorders (NDD) experience high rates of sleep problems. The Better Nights, Better Days for Children with Neurodevelopmental DisordersTM(BNBD-NDDTM) program is an online intervention for parents of children with NDD who have insomnia/insomnia symptoms. The program has recently undergone a national implementation study (recruitment completed; data collection and analysis ongoing), where parental adherence and engagement are being evaluated. Preliminary results have shown that despite high levels of recruitment, there is less utilization of the program than the research team expected. Parental engagement may have been impacted by participants' motivation and readiness for change, as well as indirectly by the COVID-19 pandemic. The objective of the current study is to better understand engagement with the BNBD-NDDTM program concerning parental motivation and readiness for change, while considering the possible impacts of COVID-19. Methods Parents of children with NDD (n = 18) who were enrolled in the BNBD-NDDTM program for a minimum of 4 months completed exit interviews using a researcher-generated, semi-structured interview guide. During the interview, participants were asked about their engagement in the program, perspectives on their own readiness for changing their children's sleep, and the impact of COVID-19 on their engagement. Data were analyzed following an inductive content analysis approach. Results Several categories of data were generated that explain levels of engagement, including: (1) severity of sleep problems; (2) motivation for change; (3) previous strategies for sleep; (4) confidence in the program; (5) sacrifices made to change sleep; (6) maintenance of change; (7) experience with levels of support provided; and (8) impact of the COVID-19 pandemic. Conclusion Parents identified several factors related to their readiness for change as contributors to their engagement level in the BNBD-NDDTM program. The COVID-19 pandemic had varied impacts on engagement for participants in this sample. Understanding parents' engagement levels within the BNBD-NDDTM eHealth program related to their motivation and readiness for change is crucial to optimize uptake and adherence to the program, improve the program's implementation and sustainability, and continue to help children with NDD to sleep better.
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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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".