The impact of bipolar disorder upon work functioning: a qualitative analysis
Bibliographic record
Abstract
OBJECTIVES: One important but sometimes poorly-captured area of functioning concerns an individual's ability to work. Several quantitative studies have now indicated that bipolar disorder (BD) can have a severe, and often enduring, negative impact upon occupational functioning. While this data indicates that employment rates are relatively low in this patient population, it throws little light on the specific ways in which this complex psychiatric condition can affect work, or upon how these effects are subjectively interpreted by individuals with BD. In order to further elucidate the relationship between BD and work, we report here on a series of exploratory qualitative interviews undertaken to develop a disease-specific measure of quality of life in BD. METHODS: We conducted 52 interviews with people with BD (n = 35), their caregivers (n = 5) and healthcare professionals (n = 12) identified by both convenience and purposive sampling. The affected sample came from a variety of employment situations, ranging between people with no employment history through to those in highly skilled, stable professional positions. Interviews were tape recorded, transcribed verbatim and analysed thematically. RESULTS: Respondents described the different ways in which the symptoms of depression and hypo/mania presented in the workplace. Five main themes emerged from the data: lack of continuity in work history, loss, illness management strategies in the workplace, stigma and disclosure in the workplace, and interpersonal problems at work. CONCLUSIONS: Patient outcome in BD has traditionally been determined by the assessment of clinical characteristics such as rates of relapse, hospitalization, or degree of symptom reduction. More recently, however, there has been increasing interest in expanding the assessment of outcome to include the measurement of indices such as functioning, a key facet of which relates to an individual's ability to work. The qualitative data obtained here highlights the often complex, varied and intermittent effects of an episodic condition such as BD upon work functioning, and points to the importance of developing more sophisticated and precise measures of occupational functioning for this population.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".