Fear of depression recurrence among individuals with remitted depression: a qualitative interview study
Bibliographic record
Abstract
BACKGROUND: Major Depressive Disorder (MDD) is a prevalent psychiatric condition and the largest contributor to disability worldwide. MDD is highly recurrent, yet little is known about the mechanisms that occur following a Major Depressive Episode (MDE) and underlie recurrence. We explored the concept of fear of depression recurrence (FoDR) and its impact on daily functioning among individuals in remission from MDD. METHODS: = 27.7, SD = 8.96) underwent semi-structured qualitative interviews. The interviews explored participants' experiences of FoDR including the frequency, severity, content, triggers, and impact of fears and associated coping strategies. We used content analysis to analyze the transcriptions. RESULTS: Most participants (73%) reported having FoDR, with varying frequency, severity, and duration of fears. The triggers and content of participants' fears often mirrored the symptoms (e.g., low mood, anhedonia) and consequences (e.g., job loss, social withdrawal) endured during past MDEs. Some participants reported a minimal impact of FoDR on daily functioning, whereas others reported a positive (e.g., personal growth) or negative (e.g., increased anxiety) influence. LIMITATIONS: Our sample size did not allow for explorations of differences in FoDR across unique MDD subtypes or sociocultural factors. CONCLUSIONS: The concept of FoDR may present a window into understanding the unique cognitive and behavioural changes that occur following MDD remission and underlie depression recurrence. Future research should aim to identify underlying individual differences and characteristics of the disorder that may influence the presence and impact of FoDR. Finally, a FoDR measure should be developed so that associations between FoDR and recurrence risk, depressive symptoms, and other indices of functioning can be determined.
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 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 | 0.016 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| 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".