Building Emotional Awareness and Mental Health (BEAM): A Pilot Randomized Controlled Trial of an App-Based Program for Mothers of Toddlers
Bibliographic record
Abstract
Background: Families have faced unprecedented challenges during the COVID-19 pandemic, leading to increased maternal mental health problems and barriers to accessing care. Innovative programs are needed to support both maternal mental health and parenting, and to buffer the long-term impacts of stress on young children. Using a patient-oriented approach, our research team aimed to co-develop and pilot test an App-based psychoeducation and social-connection platform: Building Emotional Awareness and Mental Health (BEAM). Methods: The co-development process involved a parent advisory board from conceptualization and design, through to direct participation in the program delivery. The BEAM program includes weekly videos and activities based on Unified Protocol therapy modules and emotion-focused parenting strategies, a weekly telehealth group review session, and access to a private online forum for support from other mothers and clinical coaches. A parallel randomized control trial was conducted across two provinces in Canada. Mothers of preschool children (aged 18-36 months old), with moderate-to-severe depression (Patient Health Questionaire-9 ≥ 10), were recruited online and randomized to either the 10-week BEAM intervention or treatment as usual (TAU) control group. Online surveys (ensuring researcher blinding) included questions about feasibility and acceptability of the program and pre/post self-report measures of mental health, parenting, positive coping and child behavior outcomes. The primary outcome measures were symptoms of depression and parenting stress. Data were analyzed using mixed models and an intention-to-treat approach. Results: = 32) groups. Engagement was relatively high at the beginning of the program, with 78.8% starting the BEAM App and 70.6% attending ≥1 telehealth session. Most respondents felt socially supported, satisfied with the App, and found it easy to use. Pre-post results indicated interaction effects with greater reductions in overall mental health problems, and specifically anxiety and sleep symptoms, among BEAM vs. control participants. There were also time effects with reductions in depression symptoms across both groups. No significant treatment effects emerged for the other mental health symptoms, parenting problems, positive coping, or child behavior outcomes. Descriptive data are included to highlight possible areas of promise for future large efficacy trials. Technological difficulties and other challenges that may have led to attrition and impacted outcomes are discussed. There were no adverse events related to study participation. Conclusions: The BEAM program has promise as a novel, feasible and acceptable intervention for improving mental health among mothers of young children. Clinical Trial Registration: [www.ClinicalTrials.gov], identifier [NCT04772677].
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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".