Evidence map›Paper›PMID 38078193›Full record

ArticleEClinicalMedicine2023

Differential impact of preventive cognitive therapy while tapering antidepressants versus maintenance antidepressant treatment on affect fluctuations and individual affect networks and impact on relapse: a secondary analysis of a randomised controlled trial.

Junus M van der Wal, Claudia D van Borkulo, Jonas M B Haslbeck, Christien Slofstra, Nicola S Klein, Tessa F Blanken, Marie K Deserno, Anja Lok, Maaike H Nauta, Claudi L Bockting

Open access · goldAbstract read
In one paragraph

Article in EClinicalMedicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.0field-weighted citation impact, top 22% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
  3. Network analysis: An overview for mental health research.International journal of methods in psychiatric research · 2024
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 6 institutions in 1 country.

Junus M van der WalDepartment of Psychiatry, Amsterdam UMC, location AMC, Meibergdreef 5, 1105 AZ, Amsterdam, the Netherlands.
Claudia D van BorkuloCentre for Urban Mental Health, University of Amsterdam, Amsterdam, the Netherlands.
Jonas M B HaslbeckDepartment of Psychological Methods, University of Amsterdam, Nieuwe Achtergracht 129-B, 1018 WS, Amsterdam, the Netherlands.
Christien SlofstraLentis Psychiatric Institute, Centre for Integrative Psychiatry Research, Hereweg 80, 9725 AG, Groningen, the Netherlands.
Nicola S KleinDepartment Trauma Centre, GGZ Drenthe Mental Health Institute, Altingerweg 1, 9411 PA, Beilen, the Netherlands.
Tessa F BlankenDepartment of Psychological Methods, University of Amsterdam, Nieuwe Achtergracht 129-B, 1018 WS, Amsterdam, the Netherlands.
Marie K DesernoDepartment of Psychological Methods, University of Amsterdam, Nieuwe Achtergracht 129-B, 1018 WS, Amsterdam, the Netherlands.
Anja LokDepartment of Psychiatry, Amsterdam UMC, location AMC, Meibergdreef 5, 1105 AZ, Amsterdam, the Netherlands.
Maaike H NautaDepartment of Clinical Psychology and Experimental Psychopathology, University of Groningen, Bloemstraat 36, 9712 LE, Groningen, the Netherlands.
Claudi L BocktingDepartment of Psychiatry, Amsterdam UMC, location AMC, Meibergdreef 5, 1105 AZ, Amsterdam, the Netherlands.
Amsterdam University Medical Centers · NLUniversity of Amsterdam · NLGGZ Drenthe · NLLentis · NLMaastricht University · NLUniversity of Groningen · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: There is an urgent need to better understand and prevent relapse in major depressive disorder (MDD). We explored the differential impact of various MDD relapse prevention strategies (pharmacological and/or psychological) on affect fluctuations and individual affect networks in a randomised setting, and their predictive value for relapse. Methods: We did a secondary analysis using experience sampling methodology (ESM) data from individuals with remitted recurrent depression that was collected alongside a randomised controlled trial that ran in the Netherlands, comparing: (I) tapering antidepressants while receiving preventive cognitive therapy (PCT), (II) combining antidepressants with PCT, or (III) continuing antidepressants without PCT, for the prevention of depressive relapse, as well as ESM data from 11 healthy controls. Participants had multiple past depressive episodes, but were remitted for at least 8 weeks and on antidepressants for at least six months. Exclusion criteria were: current (hypo)mania, current alcohol or drug abuse, anxiety disorder that required treatment, psychological treatment more than twice per month, a diagnosis of organic brain damage, or a history of bipolar disorder or psychosis. Fluctuations (within-person variance, root mean square of successive differences, autocorrelation) in negative and positive affect were calculated. Changes in individual affect networks during treatment were modelled using time-varying vector autoregression, both with and without applying regularisation. We explored whether affect fluctuations or changes in affect networks over time differed between treatment conditions or relapse outcomes, and predicted relapse during 2-year follow-up. This ESM study was registered at ISRCTN registry, ISRCTN15472145. Findings: Between Jan 1, 2014, and Jan 31, 2015, 72 study participants were recruited, 42 of whom were included in the analyses. We found no indication that affect fluctuations differed between treatment groups, nor that they predicted relapse. We observed large individual differences in affect network structure across participants (irrespective of treatment or relapse status) and in healthy controls. We found no indication of group-level differences in how much networks changed over time, nor that changes in networks over time predicted time to relapse (regularised models: hazard ratios [HR] 1063, 95% CI <0.0001->10 000, p = 0.65; non-regularised models: HR 2.54, 95% CI 0.23-28.7, p = 0.45) or occurrence of relapse (regularised models: odds ratios [OR] 22.84, 95% CI <0.0001->10 000, p = 0.90; non-regularised models: OR 7.57, 95% CI 0.07-3709.54, p = 0.44) during complete follow-up. Interpretation: Our findings should be interpreted with caution, given the exploratory nature of this study and wide confidence intervals. While group-level differences in affect dynamics cannot be ruled out due to low statistical power, visual inspection of individual affect networks also revealed no meaningful patterns in relation to MDD relapse. More studies are needed to assess whether affect dynamics as informed by ESM may predict relapse or guide personalisation of MDD relapse prevention in daily practice. Funding: The Netherlands Organisation for Health Research and Development, Dutch Research Council, University of Amsterdam.

Indexed as

Affect fluctuationsEcological momentary assessmentNetwork theoryPersonalisationRecurrent depressionRelapse prevention

Identifiers

PMID38078193
PMCPMC10700372
OpenAlexW4388883857

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.