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Record W2034445004 · doi:10.1080/10509670801940987

Assessment of the Long-Term Benefits of Life Skills Programming on Psychosocial Adjustment

2008· article· en· W2034445004 on OpenAlexaff
Ruby Sharma, John R. Reddon, Brenda Hoglin, Mary-Ann Woodman

Bibliographic record

VenueJournal of Offender Rehabilitation · 2008
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsAlberta Hospital Edmonton
Fundersnot available
KeywordsPsychosocialPsychiatryPsychologyMental healthMedicineClinical psychology

Abstract

fetched live from OpenAlex

ABSTRACT The durability of the psychosocial benefits of Life Skills programming on outpatient adults with mental health/forensic issues was examined. Participants were 52 adults (28 males, 24 females) who completed 16 weeks of Life Skills at a psychiatric outpatient clinic and were re-assessed between six months and six years following treatment. Psychosocial adjustment was assessed using the three scales of the Holden Psychological Screening Inventory (HPSI). Two groups of participants were compared, based on time since completion of treatment. There were no significant differences between time-based groups on the HPSI, but there was a significant gender effect for psychiatric symptoms, with females scoring higher on this scale than males (p = .028). When current HPSI scores were compared to HPSI scores that were assessed upon completion of Life Skills in a recent pre-post study on the same clientele (Reddon, Hoglin, & Woodman, 2008), analyses produced no statistically significant differences between follow-up HPSI scores and the post-treatment scores. The immediate psychosocial gains reported by Reddon et al. (2008) are evidently durable. The results of this study provide support for Life Skills as an effective treatment with persistent benefits for psychiatric outpatients.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.376

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 studies0.0000.000
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 head0.029
GPT teacher head0.316
Teacher spread0.287 · 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 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

Citations2
Published2008
Admission routes1
Has abstractyes

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