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Resilience in adolescence during the COVID-19 crisis in Canada

2024· other· en· W6958764016 on OpenAlexaffabout

Bibliographic record

VenueFigshare · 2024
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicGenetic and Environmental Crop Studies
Canadian institutionsMcGill UniversityUniversity of CalgaryUniversity of TorontoMcMaster University
Fundersnot available
KeywordsMental healthPandemicPsychological resilienceFocus groupCoping (psychology)PerceptionQualitative researchQualitative property

Abstract

fetched live from OpenAlex

Abstract Background The COVID-19 pandemic constitutes a social crisis that will have long-term health consequences for much of the global population, especially for adolescents. Adolescents are triply affected as they: 1) are experiencing its immediate, direct effects, 2) will carry forward health habits they develop now into adulthood, and 3) as future parents, will shape the early life health of the next generation. It is therefore imperative to assess how the pandemic is influencing adolescent wellbeing, identify sources of resilience, and outline strategies for attenuating its negative impacts. Methods We report the results of longitudinal analyses of qualitative data from 28 focus group discussions (FGDs) with 39 Canadian adolescents and of cross-sectional analyses of survey data from 482 Canadian adolescents gathered between September 2020 and August 2021. FGD participants and survey respondents reported on their: socio-demographic characteristics; mental health and wellbeing before and during the pandemic; pre- and during-pandemic health behaviours; experiences living through a crisis; current perceptions of their school, work, social, media, and governmental environments; and ideas about pandemic coping and mutual aid. We plotted themes emerging from FGDs along a pandemic timeline, noting socio-demographic variations. Following assessment for internal reliability and dimension reduction, quantitative health/wellbeing indicators were analyzed as functions of composite socio-demographic, health-behavioural, and health-environmental indicators. Results Our mixed methods analyses indicate that adolescents faced considerable mental and physical health challenges due to the pandemic, and were generally in poorer health than expected in non-crisis times. Nevertheless, some participants showed significantly better outcomes than others, specifically those who: got more exercise; slept better; were food secure; had clearer routines; spent more time in nature, deep in-person social relationships, and leisure; and spent less time on social media. Conclusions Support for youth during times of crisis is essential to future population health because adolescence is a period in the life course which shapes the health behaviours, socio-economic capacities, and neurophysiology of these future parents/carers and leaders. Efforts to promote resilience in adolescents should leverage the factors identified above: helping them find structure and senses of purpose through strong social connections, well-supported work and leisure environments, and opportunities to engage with nature.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score0.399

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0140.003
Scholarly communication0.0030.001
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.026
GPT teacher head0.210
Teacher spread0.184 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2024
Admission routes2
Has abstractyes

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