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Record W2793326136 · doi:10.1017/prp.2017.18

The Mediation Role of Self-Esteem for Self-Stigma on Quality of Life for People With Schizophrenia: A Retrospectively Longitudinal Study

2018· article· en· W2793326136 on OpenAlexaff
Wen‐Yi Huang, Shu‐Ping Chen, Amir H. Pakpour, Chung‐Ying Lin

Bibliographic record

VenueJournal of Pacific Rim Psychology · 2018
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMediationSelf-esteemSchizophrenia (object-oriented programming)PsychologyClinical psychologyLongitudinal studyQuality of life (healthcare)Stigma (botany)Mental healthDiagnosis of schizophreniaSocial stigmaPsychiatryPositive and Negative Syndrome ScalePsychosisMedicinePsychotherapist

Abstract

fetched live from OpenAlex

Background: Among patients with schizophrenia, there is evidence of a negative association between self-stigma and subjective quality of life (SQoL), and self-esteem was an important mediator in the association. We attempted to use a longitudinal study to investigate the aforementioned mediation on a sample with schizophrenia. Methods: We used longitudinal data retrieved from medical records of a psychiatric centre between June 2014 and December 2015. In the data, we retrieved information of self-stigma using the Self-Stigma Scale — Short; SQoL, using the WHO questionnaire on the Quality of Life — Short Form; and self-esteem, using the Rosenberg Self-Esteem Scale. All the measures were evaluated five times. Linear mixed-effect models accompanied by Sobel tests were used to tackle the mediating effects. Results: Data from 74 patients (57 males) with schizophrenia were eligible for analysis; their mean ( SD) age was 39.53 (10.67); mean age of onset was 22.95 (8.38). Self-esteem was a mediator for patients in physical ( p = .039), psychological ( p = .003), and social SQoL ( p = .004), but not in environment SQoL ( p = .051). Conclusion: Based on our findings, mental health professionals could tailor different programs to patients with schizophrenia, such as self-stigma reduction and self-esteem improvement programs. However, treatment as a whole should be sensitive to both self-stigma and self-esteem. Also, we should consider individuals’ health and wellbeing from social perspectives of disability rather than the medical model of disability emphasising symptoms and medications.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.523

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.050
GPT teacher head0.413
Teacher spread0.363 · 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

Citations32
Published2018
Admission routes1
Has abstractyes

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