Interventions to improve well-being among children and youth aged 6–17 years during the COVID-19 pandemic: a systematic review
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic is an example of a global infectious disease outbreak that poses a threat to the well-being of children and youth (e.g., physical infection, psychological impacts). The consequences of challenges faced during COVID-19 may be longstanding and newly developed interventions are being deployed. We present a narrative synthesis of available evidence from the first 2 years of the COVID-19 pandemic on the feasibility, accessibility, and effects of interventions to improve well-being among children and youth to inform the development and refinement of interventions relevant to post-pandemic recovery. METHODS: Six databases were searched from inception to August 2022. A total of 5484 records were screened, 39 were reviewed in full text, and 19 studies were included. The definition of well-being and the five domains of well-being as defined by the Partnership for Maternal, Newborn & Child Health and the World Health Organization in collaboration with the United Nations H6 + Technical Working Group on Adolescent Health and Well-Being were used. RESULTS: Nineteen studies (74% randomized controlled trials) from 10 countries were identified, involving a total of 7492 children and youth (age range: 8.2-17.2 years; 27.8-75.2% males) and 954 parents that occurred during the COVID-19 pandemic (March 2020 to March 2021). Nearly all interventions (n = 18, 95%) targeted health and nutrition, followed by connectedness (n = 6, 32%), while fewer studies targeted agency and resilience (n = 5, 23%), learning and competence (n = 2, 11%), or safety and support (n = 1, 3%). Five interventions (26%) were self-guided while 13 interventions (68%) were guided synchronous by a trained professional, all of which targeted physical and mental health subdomains within health and nutrition; one intervention (5%) was unclear. CONCLUSIONS: Studies deploying synchronous interventions most often reported improved well-being among children and youth largely in the domain of health and nutrition, specifically physical and mental health. Targeted approaches will be crucial to reach sub-groups of children and youth who are most at risk of negative well-being outcomes. Further research is needed to determine how interventions that best supported children and youth early in the pandemic are different from interventions that are required now as we enter into the post-pandemic phase.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".