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Are media literacy interventions effective at changing attitudes and intentions towards risky health behaviors in adolescents? A meta‐analytic review

2018· review· en· W2810765674 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Adolescence · 2018
Typereview
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMedia literacyPsychologyPsychological interventionIntervention (counseling)LiteracyDevelopmental psychologyHealth literacyMeta-analysisSocial psychologyClinical psychologyMedicinePedagogyHealth carePsychiatry

Abstract

fetched live from OpenAlex

Youth are inundated with media products promoting risky health behaviors (RHBs), including substance use and risky sexual activity. Media literacy interventions emphasize critical media consumption to decrease RHBs. However, it is unclear whether they positively influence attitudes and behavioral intentions towards RHBs. We conducted meta-analyses of 15 studies (N = 5000) testing intervention effectiveness on media literacy skills and 20 studies (N = 9177) testing effectiveness on attitudes and intentions towards RHBs. We found positive effects on media literacy skills (Hedge's g = .417, [95% CI, .29-.54]) and attitudes and intentions (Hedge's g = .100 [95% CI, .01-.19]). Intervention medium and target behavior moderated intervention success on attitudes and intentions, but no moderators emerged for media literacy skills. These interventions produce positive effects on media literacy skills and positive but smaller effects on attitudes and behavioral intentions, depending on medium and target behaviour. Implications for adolescent health initiatives 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.

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)0.007
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.765
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.002
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 head0.102
GPT teacher head0.466
Teacher spread0.364 · 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