Quality of life in bipolar disorder: towards a dynamic understanding
Bibliographic record
Abstract
BACKGROUND: Although quality of life (QoL) is receiving increasing attention in bipolar disorder (BD) research and practice, little is known about its naturalistic trajectory. The dual aims of this study were to prospectively investigate: (a) the trajectory of QoL under guideline-driven treatment and (b) the dynamic relationship between mood symptoms and QoL. METHODS: In total, 362 patients with BD receiving guideline-driven treatment were prospectively followed at 3-month intervals for up to 5 years. Mental (Mental Component Score - MCS) and physical (Physical Component Score - PCS) QoL were measured using the self-report SF-36. Clinician-rated symptom data were recorded for mania and depression. Multilevel modelling was used to analyse MCS and PCS over time, QoL trajectories predicted by time-lagged symptoms, and symptom trajectories predicted by time-lagged QoL. RESULTS: MCS exhibited a positive trajectory, while PCS worsened over time. Investigation of temporal relationships between QoL and symptoms suggested bidirectional effects: earlier depressive symptoms were negatively associated with mental QoL, and earlier manic symptoms were negatively associated with physical QoL. Importantly, earlier MCS and PCS were both negatively associated with downstream symptoms of mania and depression. CONCLUSIONS: The present investigation illustrates real-world outcomes for QoL under guideline-driven BD treatment: improvements in mental QoL and decrements in physical QoL were observed. The data permitted investigation of dynamic interactions between QoL and symptoms, generating novel evidence for bidirectional effects and encouraging further research into this important interplay. Investigation of relevant time-varying covariates (e.g. medications) was beyond scope. Future research should investigate possible determinants of QoL and the interplay between symptoms and wellbeing/satisfaction-centric measures of QoL.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".