MétaCan
Menu
Back to cohort
Record W7112782142

EVALUATING SCHOOL-BASED INTERVENTIONS AND PROGRAMS IN TREATING CHILDREN MENTAL HEALTH DISORDERS

2025· article· W7112782142 on OpenAlexaboutno aff

Bibliographic record

VenueCSUSB ScholarWorks (California State University, San Bernardino) · 2025
Typearticle
Language
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsnot available
Fundersnot available
KeywordsPsychological interventionMental healthNonprobability samplingChecklistIntervention (counseling)Sampling (signal processing)Interpersonal communication
DOInot available

Abstract

fetched live from OpenAlex

Background: The implementation of mental health services such as school-based interventions and programs have been well established within schools. However, it is uncertain how effective school-based interventions and programs are in treating children who are diagnosed with a mental health disorder specifically for children who are younger than 11 years old as it has not been explored. Objective: This proposed quasi-experimental study aims to determine the effectiveness of school-based mental health intervention programs in supporting and treating children (ages 6 to 11) who are diagnosed with a mental health disorder by evaluating their symptoms. Method: The proposed study would collect quantitative data from 200 participants recruited using a probability sampling strategy known as cluster sampling coupled with purposive sampling from Ontario-Montclair School District and Pomona Unified School District. Out of the 200 participants, 100 of the participants will be from OMSD and receive the school-based intervention and the other 100 participants will be from PUSD and not receive the school-based intervention. This study proposes the use of the Pediatric Symptom Checklist (PSC-35) pretreatment and posttreatment to measure changes in their symptoms, behaviors, interpersonal functioning, and emotions.

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)0.002
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 score0.289
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.325
Teacher spread0.290 · 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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueCSUSB ScholarWorks (California State University, San Bernardino)Same topicChild and Adolescent Psychosocial and Emotional DevelopmentFrench-language works237,207