Exploring spillover, turnover intention, burnout and family configuration dynamics among experienced audiologists.
Bibliographic record
Abstract
Objective: This study addresses the research gap in work-family dynamics among audiologists by examining family structures' influence. It explores the intersection of spillover, burnout, turnover intentions and family structure, an underexplored area in audiology. The study also focuses on four spillover components (negative work-to-family, negative family-to-work, positive work-to-family, and positive family-to-work), to identify key work and family domain predictors and their professional implications. Design: An online questionnaire was administered, comprising self-made questions for the demographics, work and family domain sections. The MIDUS 2 questionnaire was used to examine all four domains of spillover, Maslach's Burnout Inventory was used to assess burnout and the 5-item Turnover Intention Scale from Rahman (2020), an adaptation of Roodt’s (2004) scale, was also utilized to assess turnover intention. Study Sample: 98 clinicians completed the survey, which included 49 parents and 49 non-parents. These clinicians practiced in Australia, Canada, Denmark, Germany, Ireland, Israel, Japan, New Zealand, Portugal, the U.K., and the U.S.A. Results: The results indicate significant differences in all four forms of spillover between parents and non-parents, with NWFS being the only form of spillover showing significant differences between partnered and single parents. Work predictors (work hours, work flexibility, work support, job position, and parental status) revealed that work flexibility had a significant negative association with NWFS and job position showed a significant positive association with NWFS. Parental status also showed a significant negative association with NWFS, with parents experiencing less NWFS than non-parents. When exploring the same work predictors on PWFS, work flexibility showed a significant positive association, while parental status had a significant negative association, showing parents experiencing less PWFS than non-parents. All other predictors were not significant for NWFS or PWFS. Additionally, relationship status, rather than parental status, was used with the same work predictors. Only work flexibility showed a significant negative association with NWFS, while other predictors were not significant. Family predictors (number of children, age of the youngest/only child, family support, and relationship status) indicated that the number of children had a significant negative association with NFWS, while the other predictors were not significant. Additionally, the overall model examining family predictors for PFWS was not significant. When exploring burnout, NWFS was significantly positively associated with emotional exhaustion, whereas PFWS and parental status were significantly negatively associated with emotional exhaustion, with parents experiencing less emotional exhaustion than non-parents. The model examining NWFS and parental status for depersonalization was not significant. Lastly, emotional exhaustion and parental status were significantly positively associated with higher turnover intentions. Similarly, depersonalization and parental status also showed a significant positive relationship with turnover intentions. Both analyses indicate that parents experience greater turnover intentions than non-parents. Conclusion: This study examined spillover, burnout, turnover intentions, and family structure among audiologists. Parental status significantly predicted spillover, while relationship status affected only NWFS. Workplace flexibility and support were also found to be key in reducing negative spillover and enabling positive spillover, whereas family predictors had less impact, which is possibly unique to audiology. Additionally, negative spillover was strongly correlated with emotional exhaustion, while positive spillover mitigated its effects. Parent audiologists also reported lower emotional exhaustion but higher turnover intentions, highlighting work-family balance challenges. Hence, these findings highlight the need for organizational strategies to improve clinician well-being and retention.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".