Pattern of attendance and predictors of default among Nigerian outpatients with schizophrenia
Bibliographic record
Abstract
OBJECTIVE: To assess the pattern of and factors associated with outpatient clinic attendance among patients diagnosed with schizophrenia at a Nigerian psychiatric hospital. METHODS: This was a cross-sectional descriptive study of 313 consecutive outpatients with diagnosis of schizophrenia confirmed with the Structured Clinical Interview for Diagnosis (SCID). Data was collected on sociodemographics, clinic attendance, perceived social support, perceived satisfaction with hospital care and illness severity (assessed using the Brief Psychiatric Rating Scale, BPRS). Logistic regression analysis was used to identify factors associated with outpatient clinic default. RESULTS: Overall, 20.4% respondents were defaulters, with a median duration of clinic non-attendance of 8 weeks. Outpatient clinic defaulters had significantly higher BPRS scores and had missed more outpatient clinic appointments compared with non-defaulters. A significantly higher proportion of defaulters resided more than 20 km away from the hospital and reported "not satisfied" with their outpatient care. Being financially constrained was the commonest reason given by defaulters for missing their clinic appointments. The significant predictors of outpatient clinic default included residing more than 20 km from the hospital, missing previous appointments and dissatisfaction with outpatient care. CONCLUSION: Outpatient clinic non-attendance is common among patients with schizophrenia, and is significantly associated with demographic, clinical and service related factors. Interventions targeted at addressing the risk factors for defaulting peculiar to developing country settings similar to the location of this study, could significantly improve treatment outcome.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".