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Record W2301701492

The role of self-presentation in adolescent health risk behaviours

2006· dissertation· en· W2301701492 on OpenAlexaboutno aff
Kelly A. Roth

Bibliographic record

VenueBrock University Digital Repository (Brock University) · 2006
Typedissertation
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsnot available
Fundersnot available
KeywordsPresentation (obstetrics)PsychologyMedicineDevelopmental psychologyEnvironmental healthSurgery
DOInot available

Abstract

fetched live from OpenAlex

Self-presentation has been identified as playing a key role in the perfonnance of
\nvarious potentially hazardous health behaviours such as substance abuse, eating disorders
\nand reckless behaviours (Leary, Tchividjian, & Kraxberger, 1994; Martin & Leary, 2001;
\nMartin, Leary, & O'Brien, 2001). The present study investigated the role of selfpresentation
\non adolescent health-risk behaviours. Specifically, this study examined the
\nprevalence of adolescent identified health-risk behaviours rooted in self-presentational
\nmotives in youths aged 13-18 years. The current study also identified the specific images
\nassociated with these behaviours desired by youth, and the targets of these behaviours.
\nAlso, the relationship between these behaviours, and several trait measures (social
\nphysique anxiety, public-self consciousness, fear of negative evaluations, selfpresentational
\nefficacy) of self-presentation were examined. Finally, the gender
\ndifferences in health risk behaviours and self-presentational concerns were examined.
\nParticipants in the present study were 96 adolescent students, 34 male and 62
\nfemale, recruited from various private schools across Southern Ontario. Students ranged
\nin age from 13 to 18 years for both males (M age = 15.81 years, SD = 1.49) and females
\n(M age = 14.89 years, SD = 1.17) and ranged from grades 8 through 13. Results of the
\ncurrent study suggested that Canadian adolescents between the ages of 13 and 18 years
\nparticipated in health risk behaviours for self-presentational purposes. Drinking alcohol,
\nskipping school, and performing stunts and dares were identified as the most common
\nhealth risk behaviours performed for self-presentational purposes by both males and
\nfemales. Appearing fun and cool were the most commonly reported desired images while
\nappearing brave and mature were the least reported. The most desired target group cited
\nwas same sex friends, followed by other sex friends. Trait measures of self-presentational
\nconcerns identified females as being higher in public self-consciousness, and social
\nphysique anxiety than males. Males were found to be higher in self-presentational
\nefficacy than females. The total number of health risk behaviours was predicted by selfpresentational
\nefficacy and social physique anxiety for males, and social physique anxiety
\nfor females.
\nFindings of the current study suggest that Canadian adolescents' health risk
\nbehaviours are rooted, in part, in self-presentational motives. Thus far, an educational
\napproach to health interventions has been favoured and/or adopted by teachers, health
\npromoters, and educators (Jessor, 1992). Implications of the current study suggest that
\nalthough educational interventions are beneficial in presenting the associated risks with
\ncertain activities and/or behaviours, one reason this type of approach may be ineffective
\nin changing adolescent behaviour over the long run is that it does not address the strong
\nand prominent influences of interpersonal motives on health damaging behaviour. It is
\nevident that social acceptance and public image are of importance to adolescents, and the
\ndesire to make the "right" impression and to achieve peer approval and acceptance often
\noverride health and safety concerns (Jessor, 1992). Thus, a self-presentational approach
\nfocusing on changing the images associated with the behaviours may be more successful
\nat deterring adolescent health risk behaviours.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.472
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.007
GPT teacher head0.236
Teacher spread0.229 · 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

Citations0
Published2006
Admission routes1
Has abstractyes

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