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Record W2886021959 · doi:10.3329/bjpsy.v29i2.37851

Factors associated with relapse of schizophrenia

2018· article· en· W2886021959 on OpenAlexaff
AKM Akramul Haque, AHM Kazi Mostofa Kamal, Zinat De Laila, Luna Laila, Helal Uddin Ahmed, Niaz Mohammad Khan

Bibliographic record

VenueBangladesh Journal of Psychiatry · 2018
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsChild, Adolescent and Family Mental Health
Fundersnot available
KeywordsMarital statusSchizophrenia (object-oriented programming)PsychiatryMedicineInternal medicineResidencePsychologyClinical psychologyDemographyPopulation

Abstract

fetched live from OpenAlex

Schizophrenia is a chronic psychiatric illness with high rate of relapse which is commonly associated with noncompliance of medicine, as well as stress and high expressed emotions. The objective of the study was to determine the factors of relapse among the schizophrenic patients attending in outpatient departments of three tertiary level psychiatric facilities in Bangladesh. This was a cross sectional study conducted from July, 2001 to June, 2002. Two hundred patients including both relapse and nonrelapse cases of schizophrenia and their key relatives were included by purposive sampling. The results showed no statistically significant difference in terms of relapse with age, sex, religion, residence, occupation and level of education (p>0.05), but statistically significant difference was found with marital status and economic status (p<0.01). The proportion of non-compliance was found to be 80% and 14%, of high expressed emotion was 17% and 2% and of the occurrence of stressful life events was 10% and 1% in relapse and non-relapse cases respectively which were statistically significant (p<0.001). The study indicated that stressful life events, high expressed emotion, and noncompliance with medication had a role in schizophrenic patients for its relapse.Bang J Psychiatry December 2015; 29(2): 59-63

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 score0.008
Threshold uncertainty score0.435

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 head0.034
GPT teacher head0.294
Teacher spread0.261 · 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

Citations10
Published2018
Admission routes1
Has abstractyes

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