How do Informal Caregivers of Seniors’ Tasks Lead to Presenteeism and Absenteeism Behaviors? A Canadian Quantitative Study
Bibliographic record
Abstract
This study extends our knowledge on the role of informal caregivers of seniors and the impact of this role on presenteeism and absenteeism at work. Based on the conservation of resources theory, this article seeks to gain insights into the mechanisms and antecedents of presenteeism and absenteeism among employees who are also informal caregivers of seniors. Specifically, this article argues that family-work conflict and emotional exhaustion mediate the relationship between the informal caregiver's role, presenteeism, and absenteeism. Quantitative data (questionnaire) from this cross-sectional study were collected from 915 informal caregivers of seniors from 8 Canadian organizations. Structural equation modelling (SEM) was undertaken using IBM SPSS AMOS 28.0 to test all hypotheses. Informal caregivers of seniors who need to coordinate and organize healthcare are at a higher risk of experiencing family-work conflict. Family-work conflict experienced by informal caregivers subsequently leads to emotional exhaustion, presenteeism, and absenteeism. Because informal caregiving of seniors is likely to increase in coming years for many workers, organizations must be aware of the possible consequences of this role on work productivity. This study shows that not all tasks of informal caregivers of older adults lead to presenteeism and absenteeism through family-work conflict and emotional exhaustion. This study is innovative because, to our knowledge, no study of informal caregivers of older adults has examined the effect of different tasks in this role on presenteeism and absenteeism.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".