Can mindfulness play a role in building social-emotional capacities among youth exposed to screens?
Bibliographic record
Abstract
Introduction Increased screen time coupled with public safety restrictions may pose a serious challenge to adequate social-emotional development in youth during the pandemic. Social-emotional competence (resilience, self-esteem, and self-compassion) are essential for youth to adapt to the “new normal” in the prolonged pandemic timeline. The current study investigated the efficacy of a mindfulness-based intervention on youth social-emotional capacity while accounting for screen time. Methods One hundred and seventeen youth participated in a 12-week, online mindfulness-based program and completed pre-, post- and follow-up surveys across five cohorts during the COVID-19 pandemic (spring 2021 to spring 2022). Changes in youths’ resilience (RS), self-esteem (SE), and self-compassion (SC) between the three-time points were examined using linear regression analyses (unadjusted, partially adjusted for screen time, and fully adjusted for demographic and screen time variables). The regression models accounted for demographic (age, sex), baseline mental health status, and screen time (passive, social media, video games, and educational types of screen-based behaviours) factors. Results In an unadjusted regression model, resilience [β = 3.68, 95%CI = 1.78–5.50, p < 0.001], self-compassion [β = 0.50, 95%CI = 0.34–0.66, p < 0.001], and self-esteem [β = 2.16, 95%CI = 0.98–3.34, p < 0.001] significantly increased after the mindfulness program, and the effects were maintained in the follow-up. The efficacy of the mindfulness program persisted after controlling for five types of screen time [RS: β = 2.73, 95%CI = 0.89–4.57, p < 0.01; SC: β = 0.50, 95%CI = 0.32–0.67, p < 0.001; SE: β = 1.46, 95%CI = 0.34–2.59, p < 0.01] and in a fully adjusted model which additionally accounted for the baseline mental health status and demographic factors [RS: β = 3.01, 95%CI = 1.20, p < 0.01; SC: β = 0.51, 95%CI = 0.33–0.68, p < 0.001; SE: β = 1.64, 95%CI = 0.51–2.77, p < 0.01] and maintained its impact in the follow-up. Discussion Our findings reinforce the evidence base on the efficacy of mindfulness and support the use of online mindfulness programs in building social–emotional competencies (i.e., self-compassion, self-esteem, and resilience) among youth exposed to screens during the pandemic.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".