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Record W4408906736 · doi:10.23977/aetp.2025.090201

Strategies and Practice of Mental Health Education for Primary and Secondary School Students from the Perspective of Positive Psychology

2025· article· en· W4408906736 on OpenAlexvenueno aff

Bibliographic record

VenueAdvances in Educational Technology and Psychology · 2025
Typearticle
Languageen
FieldMedicine
TopicMedical Research and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsPerspective (graphical)Mental healthPsychologySchool psychologyPedagogyApplied psychologyMedical educationMedicinePsychotherapist

Abstract

fetched live from OpenAlex

This study is devoted to the in-depth analysis of the application and concrete practice of positive psychology in the field of mental health education in primary and secondary schools. In the introduction, the article expounds the necessity and urgency of the research, points out the increasingly serious mental health problems of primary and secondary school students, and emphasizes the urgent need to find efficient educational strategies to improve the present situation. This paper discusses the challenges that may be encountered in the process of implementing the mental health education strategy for primary and secondary school students, including the shortage of teachers, the lack of educational resources and the cognitive deviation of parents and society. In order to meet these challenges, the article puts forward a series of measures. These include strengthening teacher training to improve teachers' professional quality and educational ability, striving for more educational resources to provide material guarantee for mental health education, and raising parents' and society's awareness and attention to mental health education through publicity and education. The article emphasizes that only by taking effective measures to meet the challenges can we ensure the effective implementation of the strategy and provide a strong guarantee for the healthy psychological growth of primary and secondary school students.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.438
Threshold uncertainty score0.309

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.015
GPT teacher head0.500
Teacher spread0.486 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

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