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Record W2762057980 · doi:10.1093/pch/9.suppl_a.41ab

74 Understanding the Influence of Indirect Relationships between Adolescents' Extrinsic and Intrinsic Resiliency Factors to their Engagement in Risk Behaviour Patterns

2004· article· en· W2762057980 on OpenAlexaffabout
TL Donnon, JF Lemay

Bibliographic record

VenuePaediatrics & Child Health · 2004
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPsychologyConfirmatory factor analysisDevelopmental psychologyStructural equation modelingVariance (accounting)Clinical psychology

Abstract

fetched live from OpenAlex

Youth resiliency can be defined as the capacity of children and adolescents to adapt successfully in the face of high stress or adversarial conditions. The Youth Resiliency: Assessing Developmental Strengths (YR:ADS) questionnaire is a reliable assessment tool that supports a protective-protective model of resiliency and demonstrates the additive effect of extrinsic and intrinsic resiliency factors to determine whether adolescents engage in various risk behaviour patterns. To determine the patterns of relationships between adolescents' resiliency factors and their corresponding direct and indirect influence on whether or not they engage in risk behaviour patterns. A sample of 2991 adolescents from 5 junior and 2 senior high schools in a major Canadian urban centre completed the self-reported YR:ADS questionnaire: males (51.5%) and females (48.5%) with an average age of 14.0 (SD=1.69) and 13.7 (SD=1.64) respectively. The relationships between the 10 factor resiliency framework and risk behaviour patterns were evaluated using correlation and confirmatory factor analyses. The direct influence of extrinsic factors on adolescents' engagement in risk behaviour patterns is less important (e.g. variance of families influence on the youths' risk behaviour index=12%) when compared to the multiple effects that occur through indirect strength-based approaches to youth development (e.g. variance of families influence on self-concept=41%, commitment to learning=37%, peer relations/influence=29%). Confirmatory factor analysis provides strong support for a theoretically purported three factor model of resiliency (comparative fit index=0.9). The extension of the intrinsic and extrinsic resiliency factors to incorporate a latent factor that encompasses an overarching youth resiliency profile highlights the importance of having a comprehensive overview of adolescents' resiliency factors in understanding and identifying potential approaches for risk behaviour prevention and intervention. Although adolescents with strong resiliency profiles are able to cope with adversity more effectively, the intervention or treatment of risk behaviour pattern engagement is multifaceted. In particular, a direct approach to risk behaviour prevention detriments of risk will be less effective then the indirect and additive effects of many intrinsic and extrinsic resiliency factors in collaboration.

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)0.003
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 score0.028
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.060
GPT teacher head0.340
Teacher spread0.280 · 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
Published2004
Admission routes2
Has abstractyes

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