Assessments of Depression Anxiety and Stress among Volunteers Health Workers in Lagos, Nigeria
Bibliographic record
Abstract
This study aimed at investigating the prevalence and factors associated with depression, anxiety, and stress symptoms among volunteers who volunteered to carry out free health services in Lagos, Nigeria. It was a cross-sectional survey. The secondary objective was to determine whether there were differences between individuals who were experiencing depression, anxiety, or stress and those who were not. One hundred and sixty-three consecutive health workers were invited to take part in the study. Sociodemographic and clinical data were gathered using a semi-structured proforma. Assessments were further done using the Depression, Anxiety, and Stress Scale. According to the DASS-21 scale, 30.3% had various levels of depression, and various levels of anxiety were detected in 47.5% of participants. Similarly, various levels of stress were detected in 29.5% of the participants. There were significant associations between the sub-domains of depression anxiety and stress. High levels of depression, anxiety and stress were detected among the participants. The higher degree was evident, particularly among the single, female participants. The results will serve as supporting evidence for the timely intervention of further planning of preventative mental health services by the supervising ministry for volunteer health workers within the public and private health sectors. This implicates the need for mental health training. Hospital management and medical policymakers should continue to provide various types of therapies to increase the emotional resilience and coping skills of healthcare workers.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".