An Observational Study of the Progression of Patients’ Mental Health Symptoms Six Weeks Following Discharge From the Hospital
Bibliographic record
Abstract
Introduction Transitioning from mental health inpatient care to community care is often a vulnerable time in the treatment process where additional risks and anxiety may arise. Objectives The objective of this paper was to evaluate the progression of mental health symptoms in patients six weeks after their discharge from the hospital as the first phase of an ongoing innovative supportive program. In this study, factors that may contribute to the presence or absence of anxiety and depression symptoms, and the quality of life following a return to the community were examined. The results of this study provide evidence and baseline data for future phases of the project. Methods An observational design was used in this study. We collected sociodemographic and clinical data using REDCap at discharge and six weeks later. Anxiety, depression, and well-being symptoms were assessed using the Generalized Anxiety Disorder (GAD-7) questionnaire, the Patient Health Questionnaire-9 (PHQ-9), and the World Health Organization-Five Well-Being Index (WHO-5) respectively. Descriptive, Chi-square, independent T-test, and multivariate regression analyses were conducted. Results The survey was completed by 88 participants out of 144 (61.1% response rate). A statistically non-significant reduction in anxiety and depression symptoms was found six weeks after returning to the community based on the Chi-squared/Fisher exact test and independent t-test. As well, the mean anxiety and depression scores showed a non-significant marginal reduction after discharge compared to baseline. In the period following discharge, a non-significant increase in participants experiencing low well-being symptoms was observed, as well as a decline in the mean well-being scores. Based on logistic regression models, only baseline symptoms were significant predictors of symptoms six weeks after inpatient discharge. Image: Image 2: Image 3: Conclusions In the short term following hospital discharge, no significant changes were observed in mental health conditions. A collaboration between researchers and policymakers is essential for the implementation and maintenance of effective interventions to support and maintain the mental health of patients following discharge. Disclosure of Interest None Declared
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".