Boredom in inpatient mental healthcare settings: a scoping review
Bibliographic record
Abstract
Introduction To identify the scope of existing literature exploring boredom experienced by those using inpatient mental health services, we conducted a scoping review. Method We performed a comprehensive literature search of four databases: Medline, EMBASE, CINAHL and PsycINFO. This search resulted in 978 titles and abstracts, which were reviewed by two independent raters. Results A total of 19 studies met the criteria for inclusion. Inter-rater reliability was assessed (k = 0.719 (95% confidence interval 0.500 to 0.938), P < 0.05 (full-text)), resulting in a ‘good’ strength of agreement according to the Practical Statistics for Medical Research. A content analysis resulted in the identification of four primary themes: (a) boredom as an acknowledged problem in inpatient mental health settings; (b) consequences of boredom; (c) models for addressing boredom through meaningful activity; and (d) the occupational therapy role in addressing state and trait boredom. Conclusion Occupational therapists play an important role in addressing the boredom experienced by those receiving treatment for mental illness in hospital settings. Further empirical evidence is needed to develop a better understanding of the influence of boredom on inpatient service users’ mental health, and additional models need to be developed to address this persistent problem.
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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 | 0.009 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.019 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".