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Record W2609529704 · doi:10.1002/mpr.1566

Psychometric properties of the Mental Health and Social Inadaptation Assessment for Adolescents (MIA) in a population‐based sample

2017· article· en· W2609529704 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

VenueInternational Journal of Methods in Psychiatric Research · 2017
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsMcGill UniversityDouglas Mental Health University InstituteUniversité LavalUniversité du Québec à MontréalUniversité de Montréal
Fundersnot available
KeywordsPsychologyPsychosocialDiscriminant validityClinical psychologyMental healthPopulationConvergent validityConfirmatory factor analysisAnxietyPsychiatryStructural equation modelingPsychometricsMedicineInternal consistency

Abstract

fetched live from OpenAlex

We report on the psychometric properties of the Mental Health and Social Inadaptation Assessment for Adolescents (MIA), a self-report instrument for quantifying the frequency of mental health and psychosocial adaptation problems using a dimensional approach and based on the DSM-5. The instrument includes 113 questions, takes 20-25 minutes to answer, and covers the past 12 months. A population-based cohort of adolescents (n = 1443, age = 15 years; 48% males) rated the frequency at which they experienced symptoms of Attention Deficit Hyperactivity Disorder (ADHD), Conduct Disorder, Oppositional Defiant Disorder, Depression, Generalized Anxiety, Social Phobia, Eating Disorders (i.e. DSM disorders), Self-harm, Delinquency, Psychopathy as well as social adaptation problems (e.g. aggression). They also rated interference with functioning in four contexts (family, friends, school, daily life). Reliability analyses indicated good to excellent internal consistency for most scales (alpha = 0.70-0.97) except Psychopathy (alpha = 0.46). The hypothesized structure of the instrument showed acceptable fit according to confirmatory factor analysis (CFA) [Chi-square (4155) = 9776.2, p = 0.000; Chi-square/DF = 2.35; root mean square error of approximation (RMSEA) = 0.031; Comparative Fit Index (CFI) = 0.864], and good convergent and discriminant validity according to multitrait-multimethods analysis. This initial study showed adequate internal validity and reliability of the MIA. Our findings open the way for further studies investigating other validity aspects, which are necessary before recommending the wide use of the MIA in research and clinical settings.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.131
Threshold uncertainty score0.287

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.216
GPT teacher head0.546
Teacher spread0.329 · 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