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Record W4317212375 · doi:10.2196/35669

Predictors of Adolescents’ Response to a Web-Based Intervention to Improve Psychosocial Adjustment to Having an Appearance-Affecting Condition (Young Person’s Face IT): Prospective Study

2023· article· en· W4317212375 on OpenAlexvenueno aff
Deniz Zelihić, Kristin Billaud Feragen, Are Hugo Pripp, Tine Nordgreen, Heidi Williamson, Johanna Kling

Bibliographic record

VenueJMIR Formative Research · 2023
Typearticle
Languageen
FieldPsychology
TopicBody Image and Dysmorphia Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPsychosocialPsychological interventionDistressAnxietyClinical psychologyRandomized controlled trialIntervention (counseling)PsychologyDisengagement theoryNorwegianMedicineGerontologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Adolescents with a condition affecting their appearance that results in a visible difference can be at risk of psychosocial distress and impaired adjustment. Evidence for the effectiveness of existing interventions in improving psychosocial outcomes is limited, and relevant treatment can be difficult to access. Young Person's Face IT (YPF), a self-guided web-based intervention, has demonstrated potential in reducing social anxiety in adolescents with a visible difference. However, more knowledge is needed about the variables that contribute to variations in intervention effects to identify those who may benefit most from YPF. OBJECTIVE: This study aimed to investigate demographic, psychosocial, and intervention-related variables as predictors of overall intervention effects after adolescents' use of YPF. METHODS: We used longitudinal data collected as part of a larger, ongoing mixed methods project and randomized controlled trial (ClinicalTrials.gov NCT03165331) investigating the effectiveness of the Norwegian version of YPF. Participants were 71 adolescents (mean age 13.98, SD 1.74 years; range 11-18 years; 43/71, 61% girls) with a wide range of visible differences. The adolescents completed primary (body esteem and social anxiety symptoms) and secondary (perceived stigmatization, life disengagement, and self-rated health satisfaction) outcome measures at baseline and postintervention measurement. The predictor variables were demographic (age and gender), psychosocial (frequency of teasing experiences related to aspects of the body and appearance as well as depressive and anxiety symptoms), and intervention-related (time spent on YPF) variables. RESULTS: Two-thirds (47/71, 66%) of the adolescents completed all YPF sessions and spent an average of 265 (SD 125) minutes on the intervention. Backward multiple regression analyses with a 2-tailed P-value threshold of .20 revealed that several variables were retained in the final models and predicted postintervention outcome changes. Body esteem was predicted by age (P=.14) and frequency of teasing experiences (P=.09). Social anxiety symptoms were predicted by gender (P=.12), frequency of teasing experiences (P=.03), depressive and anxiety symptoms (P=.08), and time spent on YPF (P=.06). Perceived stigmatization was predicted by age (P=.09), gender (P=.09), frequency of teasing experiences (P=.19), and depressive and anxiety symptoms (P=.06). Life disengagement was predicted by gender (P=.03), depressive and anxiety symptoms (P=.001), and time spent on YPF (P=.14). Self-rated health satisfaction was predicted by age (P=.008). However, the results were limited by relatively low explained postintervention variance, ranging from 1.6% to 24.1%. CONCLUSIONS: This study suggests that adolescent boys, adolescents who experience higher levels of psychosocial distress related to their visible difference, and adolescents who spend sufficient time on YPF may obtain better overall intervention effects.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.581
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.053
GPT teacher head0.444
Teacher spread0.391 · 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 designQualitative
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

Citations2
Published2023
Admission routes1
Has abstractyes

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