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Record W3004085634 · doi:10.3399/bjgp20x707753

Predicting and preventing relapse of depression in primary care

2020· letter· en· W3004085634 on OpenAlexaff
Andrew S. Moriarty, Joanne Castleton, Simon Gilbody, Dean McMillan, Shehzad Ali, Richard D Riley, Carolyn Chew‐Graham

Bibliographic record

VenueBritish Journal of General Practice · 2020
Typeletter
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsWestern University
FundersDepartment of Health and Social CareNational Institute for Health and Care Research
KeywordsDepression (economics)MedicinePsychosocialPsychiatryPrimary careCohortMajor depressive episodePediatricsInternal medicineFamily medicineMood

Abstract

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Background Postnatal depression necessitates timely and effective interventions to mitigate adverse maternal and child outcomes in the short term and over the life course. British south Asian women with depression are often underserved and undertreated due to stigma, language barriers, and cultural barriers. This trial aimed to test the clinical efficacy of a culturally adapted, group cognitive behavioural therapy (CBT)-based intervention, the Positive Health Programme (PHP), delivered by non-specialist health workers for postnatal depression in British south Asian women. Methods This study was a randomised controlled trial, with culturally adapted recruitment and an internal pilot, comparing the PHP (intervention group) with treatment as usual (control group) in British south Asian women with postnatal depression. The study was conducted at five centres across the UK. Participants were aged 16 years or older, met the DSM-5 criteria for depression, and had infants aged 0–12 months. Randomisation (1:1) was stratified by centre, with a block size of 18, and was done through an independent remote telephone service. The PHP was delivered over 12 group sessions in 4 months. The primary outcome was recovery from depression (defined as a Hamilton Depression Rating Scale [HDRS] score ≤7) at 4 months after randomisation, and an assessment was also done at 12 months. Analysis was on an intention-to-treat basis including only participants with non-missing outcome data; we used a random-effects logistic regression model including fixed covariates for study site, baseline depression severity (HDRS score), parity, and years in education and a random coefficient for therapy group. This trial is registered with the ISRCTN (ISRCTN10697380). Findings Of the 9136 individuals approached for recruitment between Feb 8, 2017, and March 29, 2020, 4296 women were eligible for and consented to screening, among whom 732 screened positive and were randomly allocated: 368 (50%) to the PHP group and 364 (50%) to the control group. Participants were mostly of Pakistani (397 [55%] of 719 with available data), Indian (176 [24%]), or Bangladeshi ethnicity (127 [18%]), with an overall mean age of 31·4 years (SD 5·2), with their youngest infants having a mean age of 23·6 weeks (14·2). At 4 months from randomisation, the proportion of participants who showed recovery from depression on the HDRS was significantly higher in the PHP group (138 [49%] of 281) than in the control group (105 [37%] of 281; adjusted odds ratio 1·97 [95% CI 1·26–3·10]). At the 12-month follow-up, this difference was no longer significant (1·02 [95% CI 0·62–1·66]). Interpretation In British south Asian women with postnatal depression, a culturally adapted group CBT-based intervention could aid in quicker recovery from depression compared with treatment as usual. Further research is needed to identify how to sustain the treatment effect and establish strategies for scale-up.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.025
GPT teacher head0.338
Teacher spread0.314 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations24
Published2020
Admission routes1
Has abstractyes

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