Factors influencing delays in the diagnosis and treatment of bipolar disorder in adolescents and young adults: A systematic scoping review.
Bibliographic record
Abstract
Background Care for bipolar spectrum disorders is often delayed, and these delays are associated with a poorer prognosis. However, little is known about the specific factors that contribute to these delays. Bipolar disorder onset peaks in adolescents and young adults, where barriers to care may be distinct from younger or older populations. Aims To identify the available evidence on factors contributing to delays in care for adolescents and young adults with bipolar disorder. Method We performed a pre-registered systematic search of the literature on delays in the care of 13- to 24-year olds diagnosed with bipolar disorder. Our search yielded n = 5991 unique articles published between 2000 and 2025. Two independent reviewers screened abstracts and full texts for eligibility according to a priori inclusion criteria. Findings from included studies ( n = 27) were summarised in a narrative synthesis, organised according to patient, disease and systemic factors within the Model of Pathways to Treatment. Results Findings were limited to observational levels of evidence. There was a relative paucity of research in the appraisal and help-seeking intervals. Some factors in delays to care were consistently identified across multiple studies. However, there were also contradictions or a lack of replication around identified factors. Conclusions Research in this area has been declining in the past decade despite contradictory findings and ongoing significant delays in bipolar disorder care. Factors contributing to delays in bipolar disorder care can be effectively organised according to appraisal, help-seeking, diagnostic and pre-treatment intervals. This enables a systematic approach to identifying areas in need of quality improvement and further research.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".