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Record W4416368116 · doi:10.1371/journal.pone.0337188

A mediation model explaining the impact of fear of COVID-19 and COVID-19- induced changes in multiple life domains on adolescents’ subjective well-being in sub-Saharan Africa

2025· article· en· W4416368116 on OpenAlexaff
Evelyn Aboagye Addae, Moses Adjei, Uchechi Shirley Anaduaka, David Kyetuo Wuollah-Dire, Regobert Bondong

Bibliographic record

VenuePLoS ONE · 2025
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsUniversity of AlbertaMemorial University of Newfoundland
FundersLingnan University
KeywordsHappinessLife satisfactionFeelingAffect (linguistics)MediationSubjective well-beingQuality of life (healthcare)

Abstract

fetched live from OpenAlex

Though the impact of COVID-19 pandemic's effects on individuals' life domains and quality of life has been widely researched, there remains unanswered questions on the mechanisms that explain the impact of fear of COVID-19 on different measurements of adolescents' subjective well-being (SWB) particularly in the sub-Saharan African context. In a mediation model, we employed data collected during the pandemic to examine the mediating mechanisms that links fear of COVID-19 and COVID-19-induced changes in multiple life domains (subjective feelings of unsafety, positive affect and peer relationships) to different measurements of adolescents' SWB (overall life satisfaction, overall happiness, subjective happiness, and composite SWB). Findings revealed significant negative correlations between fear of COVID-19 and all employed measurements of SWB as well as between the proposed mediating variables - changes in peer relationship, positive affect, subjective feelings of unsafety and the different measurements of SWB. Adolescents who reported negative changes in peer relationship, positive affect and subjective feelings of unsafety were more likely to report poorer SWB including lower life satisfaction and happiness. For instance, adolescents who experienced increase in peer relationship were more likely to experience higher overall life satisfaction (B = .169, p < .005) compared to those who experienced a decrease in peer relationship. Also, adolescents who reported an increase in positive affect were more likely to report higher overall life satisfaction (B = .172, p < .005), overall happiness (B = .056, p < .005), composite SWB (B = .416, p < .005) and subjective happiness (B = .381, p < .001) while adolescents who reported a decrease in perceived safety were more likely to report lower composite SWB (B = -1.350, p < .001) compared to those who experienced an increase in perceived safety. While there was a significant direct negative effect of fear of COVID-19 on SWB in the absence of the mediators, there was no significant negative effect of fear of COVID-19 on SWB after adjusting for the mediators in the model. Consequently, the direct effect of fear of COVID-19 on all the measurements of SWB including overall life satisfaction and happiness were completely mediated by changes in peer relationship, positive affect and subjective feelings of unsafety; suggesting indirect effects of fear of COVID-19 on the adolescents' SWB. For example, change in peer relationship and positive affect mediated the relationship between fear of COVID-19 and overall life satisfaction. Again, change in positive affect and change in subjective feeling of unsafety significantly mediated the effect of fear of COVID-19 on composite SWB and only change in positive affect mediated the effect of fear of COVID-19 on subjective happiness. The mechanism explaining the relationship between fear of COVID-19 and COVID-19-induced changes in multiple life domains and adolescents SWB and the implications for public health policy are discussed.

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)0.004
metaresearch head score (Gemma)0.011
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0130.001

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 head0.125
GPT teacher head0.380
Teacher spread0.255 · 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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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