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The effect of social support and gender on depression and quality of life in patients with schizophrenia

2015· article· en· W2807728253 on OpenAlexaboutno aff
Mariam Unwala

Bibliographic record

VenueIndian Journal of Mental Health(IJMH) · 2015
Typearticle
Languageen
FieldPsychology
TopicFamily Caregiving in Mental Illness
Canadian institutionsnot available
Fundersnot available
KeywordsSchizophrenia (object-oriented programming)Depression (economics)PsychologyQuality of life (healthcare)Social supportPsychiatryClinical psychologyPsychotherapist

Abstract

fetched live from OpenAlex

Social support buffers against stressful life events, increases adherence to medical treatments and improves recovery from medical illness.The quality of life of patients suffering from schizophrenia is dependent on amount of social support to a great extent.Also rates of depression are high in schizophrenia patients.So we undertook this study among 68 patients to understand the relationship of social support and gender with depression and quality of life amongst the patients of schizophrenia.The scales used were the Multidimensional Scale of Perceived Social Support (MSPSS), Calgary Depression Scale for Schizophrenia and the WHO Quality of Life-Bref Scale.It is observed that means score of depression was higher in low social support group and amongst females.Similarly QOL was poorer amongst low social support groups and females.The difference was statistically significant only in QOL scores in social support group and depression scores in gender group.Thus the study concludes that social support has an impact on depression and quality of life amongst the patients of schizophrenia.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0020.000

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 head0.032
GPT teacher head0.352
Teacher spread0.320 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2015
Admission routes1
Has abstractyes

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