A Robot-Delivered Training Program to Improve Children’s Mental Health and Resilience in Dutch Primary Schools: Pilot Intervention Study
Bibliographic record
Abstract
Background: Mental health problems often start at an early age and can persist into adulthood, leading to physical and mental health problems such as substance abuse, sleep problems, depressive disorders, and suicidal tendencies. Therefore, it is important to invest in the mental health of young people through, for example, initiatives focused on mental health promotion and prevention. The ePartners robot buddy offers children training modules focused on enhancing resilience and mental health, specifically targeting self-image and social skills and/or addressing unhelpful feelings and thinking patterns in children's daily life situations. Objective: The study primarily aims to assess the feasibility, acceptability, and usability of the intervention according to the children and their teachers and secondarily aims to evaluate its potential effects on the mental well-being (general mental well-being, quality of life [QoL], and self-efficacy) of children. Methods: A single-arm, 6-week, pre-post pilot intervention study involving children and their teachers was conducted in 3 primary schools in the Netherlands. Outcomes were assessed using questionnaires. Primary outcomes were assessed postintervention and included feasibility and acceptability for teachers and acceptability and usability for children. Secondary outcomes included self-reported general mental well-being and self-efficacy and teacher-reported general mental well-being and were assessed at baseline and postintervention. Results: Data showed that the intervention was generally perceived as moderately feasible according to the Feasibility of Intervention Measure (mean 17.3, SD 2.6; on a scale from 4 to 20) and showed relatively high acceptability (mean 16.9, SD 3.8; on a scale from 4 to 20) according to teachers (n=7). Additional feasibility questions showed that teachers found it generally feasible to guide children who had few questions about using the robot. Feasibility was moderate due to limited time for integration, many content-related questions from children, and the substantial learning needed to select themes. Children (n=73) reported high perceived usability of the intervention (mean 15.2, SD 2.4; on a scale from 4 to 20). The perceived acceptability of the intervention by children was also relatively high, with a mean of 12.0 (SD 2.3) on a scale from 3 to 15. Teacher-reported QoL of children improved significantly from baseline (mean 36.0, SD 4.6) to postintervention (mean 37.2, SD 3.8; t64=2.77; P=.01); however, the children's self-reported QoL did not significantly change over time. No significant changes in general mental well-being and self-efficacy scores were found. Conclusions: This study provides valuable insights into the feasibility, acceptability, and usability of a robot-delivered mental health-promoting intervention within a primary school setting. Further research is needed to fully understand its potential benefits and address existing limitations associated with the implementation of such interventions in the school setting.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".