Evaluating a Social-Emotional Training Program for Refugee Families and Service Providers: Pilot Study
Bibliographic record
Abstract
BACKGROUND: Refugee children are often exposed to adversities that present a threat to their healthy development. Promoting refugee children's social-emotional capacities may be an opportune, strengths-based avenue to nurture their resilience, coping strategies, and mental health outcomes amid these risks. Furthermore, supporting caregivers' and service providers' capacities to provide strengths-based care may result in more sustainable, caring environments for refugee children. However, culturally adapted initiatives that aim to promote social-emotional capacities and mental health in refugee children, caregivers, and service providers are limited. OBJECTIVE: In this pilot study, we aimed to assess the feasibility and efficacy of a brief, 3-week social-emotional training program for refugee caregivers of children aged between 2 and 12 years and service providers who support refugees. This study had 3 central objectives. First, we examined whether refugee caregivers' and service providers' knowledge of core social-emotional concepts increased from pre- to posttraining, whether these increases were maintained 2 months later, and whether caregivers and service providers reported a high use of training-based strategies after the training. Second, we assessed if refugee caregivers reported any improvements in their children's social-emotional capacities and mental health from pre- to posttraining and 2 months later. Finally, we evaluated whether caregivers and service providers experienced any improvements in their own mental health symptoms from pre- to posttraining and 2 months later. METHODS: A total of 50 Middle Eastern refugee caregivers of children (n=26) aged between 2 and 12 years and service providers (n=24) were recruited using convenience sampling and participated in a 3-week training program. Training sessions were delivered via a web-based learning management system and involved a combination of asynchronous (video-based) and synchronous (web-based live group) sessions. The training was evaluated using an uncontrolled pre-, post-, and 2-month follow-up design. Caregivers and service providers reported their understanding of social-emotional concepts and mental health at pre-, post-, and 2 months after training and reported their use of training strategies after training. Caregivers reported their children's social-emotional capacities and mental health through a presurvey, a series of postsurveys (after each module session and 1 week after the training), and a 2-month follow-up survey. The participants also reported their demographic information. RESULTS: Caregivers' and service providers' knowledge of social-emotional concepts increased significantly from pre- to posttraining, and the service providers' knowledge increase was sustained at the 2-month follow-up. Both caregivers and service providers reported high levels of strategy use. Furthermore, 2 markers of children's social-emotional development (ie, emotion regulation and sadness over wrongdoing) improved after training. CONCLUSIONS: The findings highlight the potential of strengths-based, culturally adapted social-emotional initiatives to support refugee caregivers' and service providers' abilities to provide high-quality social-emotional care to refugee children.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 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) | 0.003 | 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".