Insomnia, excessive daytime sleepiness, anxiety, depression and socioeconomic status among customer service employees in Canada.
Bibliographic record
Abstract
OBJECTIVE: It is the first study investigating deeply symptoms of neuropsychiatric diseases among a large population of customer service employees (n=1238, 640 females and 598 males). The study's goals were document presence of sleep disorders, anxiety and depression among customer service advisors and determine the influence of the socioeconomic status (pSES), duration in position and full-time or part-time shift on the diseases above. METHODS: Linear regressions and ANOVA with a Tukey multiple comparisons of means was performed to analyze correlation and differences between citizens, international students and immigrants in their pSES and neuropsychiatric diseases. RESULTS: =89,77% for depression). DISCUSSION: Insomnia, sleepiness and anxiety are more prevalent for full-time employees (higher for immigrants and international students compared to Canadians) compared with part-time employees, while depression was similarly higher for Canadian and immigrants compared to international students. Regarding full-time employees, symptoms of insomnia, anxiety and depression were higher for men compared to women. Regarding part-time employees, symptoms of insomnia and sleepiness were higher for women compared to men. Employees working full-time with rotating shifts are more exposed to insomnia, sleepiness and anxiety than employees working part-time. More research is needed to understand mental health of customer service employees regardless of their area and it is worthy of interest to study the link between sleep disorders and mood disorders with work conditions. Here some practical suggestions are made to reduce neuropsychiatric disorders for customer service employees or to at least mitigate the work burden on their brains.
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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".