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Record W1970377262 · doi:10.1177/082957350001600107

Validity and Reliability of the Draw A Person: Screening Procedure for Emotional Disturbance with Adolescent Students

2000· article· en· W1970377262 on OpenAlexaff
Linda Wrightson, Donald H. Saklofske

Bibliographic record

VenueCanadian Journal of School Psychology · 2000
Typearticle
Languageen
FieldPsychology
TopicBehavioral and Psychological Studies
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsPsychologyChecklistChild Behavior ChecklistClinical psychologyReliability (semiconductor)Rating scaleTest (biology)Test validityDevelopmental psychologyPredictive validityDisturbance (geology)Psychometrics

Abstract

fetched live from OpenAlex

The Draw A Person: Screening Procedure for Emotional Disturbance (DAP:SPED; Naglieri, 1991) was developed to provide a quick screening measure for the identification of children and adolescents who may have emotional disorders. The present study examined the test-retest reliability and validity of the DAP:SPED with three groups of adolescents: mainstream students, alternate education students, and students manifesting behavior problems. Significant score differences were found only between the regular and the alternate and behavior class students on the DAP:SPED scores. In contrast, significant score differences between all three groups were found on the Devereux Behavior Rating Scale and the Child Behavior Checklist. Test-retest reliability over 23-27 weeks was relatively low. Results of the present study suggest that the DAP:SPED may have limited utility in the identification of adolescents with behavior disorders.

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)0.008
metaresearch head score (Gemma)0.024
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 score0.008
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.141
GPT teacher head0.352
Teacher spread0.211 · 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

Citations11
Published2000
Admission routes1
Has abstractyes

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