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Record W2005608407 · doi:10.5539/ass.v10n9p144

The Use of Expressive Arts Therapy in Understanding Psychological Issues of Juvenile Delinquency

2014· article· en· W2005608407 on OpenAlexvenueno aff
Sh Marzety Adibah Al Sayed Mohamad, Zakaria Mohamad

Bibliographic record

VenueAsian Social Science · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologySadnessNonprobability samplingAffectionJuvenile delinquencyMeaning (existential)HappinessSocial psychologyAngerFeelingRegretDevelopmental psychologyPsychotherapist

Abstract

fetched live from OpenAlex

This phenomenological research design of qualitative study was conducted to understand the experiences of creative relationship during Expressive Arts Therapy group counseling session. A total of seven girls between the ages of 12-18 years who have been involved in juvenile delinquent behaviors were selected using purposive sampling groups. Interviews, observations and document analysis were conducted for data collection. Validity and reliability of the process were done through triangulation, peer review and audit trail. Data analysis was made to give overall meaning, meaning of discrimination unit, initial transfer of meaning units, transfer units psychological meaning, structure of individual psychology, and general psychological structure. The results showed that there are some psychological issues that have to be shared and expressed by all subjects in the study. The study participants shared their feelings such as anger, revenge, hatred, guilt and regret, disappointment and sadness, rebellious, begging for affection, looking for happiness, satisfaction and enjoyment of life, issues of low self-esteem and other issues concerning trauma and emotional disorders that have been experienced in their lives. In conclusion, this study provides some implications in terms of techniques and practices of counseling in Malaysia and the need for further research.

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)0.000
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.436
Threshold uncertainty score0.639

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
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 head0.252
GPT teacher head0.384
Teacher spread0.132 · 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

Citations12
Published2014
Admission routes1
Has abstractyes

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