Workplace and non-workplace loneliness: a comparative study on risk factors and impacts on absenteeism and mental health among employees in Spain
Bibliographic record
Abstract
Introduction Loneliness can manifest in various aspects of life, including personal and professional contexts. Although most of studies on loneliness are focused on general loneliness without the specification on any context, the study of workplace loneliness has garnered increased attention in recent years and researchers explore how loneliness in professional settings affects labor satisfaction, productivity and mental health of workers. However, few studies have directly compared workplace and non-workplace loneliness, particularly in terms of their prevalence, agreement with each other, risk factors, and consequences Objectives The aim of this study is to (1) evaluate prevalences and concordance between workplace and non-workplace loneliness, (2) compare sociodemographic risk factors between workplace and non-workplace loneliness, (3) compare working conditions-related risk factors between the two contexts of loneliness, and (4) compare their impact on absenteeism, depression, anxiety and substance use disorder.er. Methods A representative sample of the employee residing in Spain (n=5400) was surveyed using computer-assisted web interviews (CAWI). Logistic regression models were constructed to compare the effects of risk factors for workplace and non-workplace loneliness (including sociodemographic factors, and factors related to working conditions), as well as the impact of workplace and non-workplace loneliness on absenteeism, and symptoms of depression, anxiety, and substance use disorder. Results 40,7% of active workers report experiencing workplace loneliness, while 42.0% report non-workplace loneliness. The level of concordance between both types of loneliness is low (k=0.36). Both types are more prevalent among younger workers and migrated people. Other sociodemographic risk factors (being female, non-married, and non-heterosexual) were significantly associated with non-workplace loneliness. Meanwhile, risk factors related to working conditions -particularly working under stress and labor precariousness- were associated with both types of loneliness, which showed an independent impact on absenteeism, depression, anxiety, and substance use disorder. Conclusions Most of social determinants of workplace loneliness are rooted in the work environment, indicating that effective interventions should focus on addressing labor conditions and precariousness to improve both workplace and non-workplace loneliness and their impacts on absenteeism and mental health. Disclosure of Interest None Declared
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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 | 0.001 | 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 | 0.001 |
| 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".