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Record W4403293684 · doi:10.1080/14927713.2024.2410163

Leisure activities, substance use and psychological health among Hungarian adolescents

2024· article· en· W4403293684 on OpenAlexvenueno aff
Bettina Pikó

Bibliographic record

VenueLeisure/Loisir · 2024
Typearticle
Languageen
FieldPsychology
TopicPsychological Well-being and Life Satisfaction
Canadian institutionsnot available
Fundersnot available
KeywordsSubstance usePsychologyClinical psychologyEnvironmental healthMedicine

Abstract

fetched live from OpenAlex

During the past several decades, adolescents’ leisure has undergone several important changes due to, for example, alternative modes of entertainment, such as video gaming and social media which have had a significant influence on their well-being. The aim of this study was to examine the relationships of adolescents’ leisure activities to their substance use and psychological health. Participants were middle and high school students (N = 2,239, aged between 12 and 18 years, M = 14.61 years, SD = 1.71; 51.8% females) using data drawn from the Szeged Youth Study 2022, Hungary. Peer-based leisure was positively associated with all types of substance use. Playing and gaming leisure showed a negative relationship with psychosomatic and depressive symptomatology. Aesthetic-sophisticated and family-based leisure proved the most beneficial for psychological health and health behaviour, and it was also the strongest predictor of adolescents’ life satisfaction. Arts, hobbies and internet use played a beneficial role.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.061
GPT teacher head0.345
Teacher spread0.284 · 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 teacher head, not a consensus.

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

Citations1
Published2024
Admission routes1
Has abstractyes

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