Evidence map›Paper›PMID 35055408›Full record

ReviewJournal of personalized medicine2022

The Contribution of "Individual Participant Data" Meta-Analyses of Psychotherapies for Depression to the Development of Personalized Treatments: A Systematic Review.

Pim Cuijpers, Marketa Ciharova, Soledad Quero, Clara Miguel, Ellen Driessen, Mathias Harrer, Marianna Purgato, David Ebert, Eirini Karyotaki

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Journal of personalized medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 9 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 9 pooled it
–field-weighted citation impact
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

31 citing papers in PubMed, 9 syntheses or guidelines pooled it.

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  13. Review
  14. Big data and psychiatry: advances, constraints and future directions.World psychiatry : official journal of the World Psychiatric Association (WPA) · 2026
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  17. Innovations to improve outcomes and uptake of psychotherapies for mental disorders: a state-of-the-art review.World psychiatry : official journal of the World Psychiatric Association (WPA) · 2026
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  20. Frontiers in psychology · 2025
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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

9 authors.

Pim CuijpersDepartment of Clinical, Neuro- and Developmental Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands.ORCID 0000-0001-5497-2743
Marketa CiharovaDepartment of Clinical, Neuro- and Developmental Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands.ORCID 0000-0002-7131-1549
Soledad QueroDepartment of Basic, Clinical Psychology and Psychobiology, Universitat Jaume I, 12006 Castellón, Spain.ORCID 0000-0002-8973-1250
Clara MiguelDepartment of Clinical, Neuro- and Developmental Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands.
Ellen DriessenDepartment of Clinical Psychology, Behavioural Science Institute, Radboud University and Depression Expertise Center, Pro Persona Mental Health Care, 6500 HB Nijmegen, The Netherlands.ORCID 0000-0002-9602-1548
Mathias HarrerClinical Psychology and Psychotherapy, Friedrich-Alexander-University Erlangen-Nuremberg, 91054 Erlangen, Germany.
Marianna PurgatoWHO Collaborating Centre for Research and Training in Mental Health and Service Evaluation, Department of Neurosciences, Biomedicine and Movement Sciences, Section of Psychiatry, University of Verona, 37129 Verona, Italy.
David EbertPsychology and Digital Mental Health Care, Technical University Munich, 80333 Munich, Germany.
Eirini KaryotakiDepartment of Clinical, Neuro- and Developmental Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While randomized trials typically lack sufficient statistical power to identify predictors and moderators of outcome, "individual participant data" (IPD) meta-analyses, which combine primary data of multiple randomized trials, can increase the statistical power to identify predictors and moderators of outcome. We conducted a systematic review of IPD meta-analyses on psychological treatments of depression to provide an overview of predictors and moderators identified. We included 10 (eight pairwise and two network) IPD meta-analyses. Six meta-analyses showed that higher baseline depression severity was associated with better outcomes, and two found that older age was associated with better outcomes. Because power was high in most IPD meta-analyses, non-significant findings are also of interest because they indicate that these variables are probably not relevant as predictors and moderators. We did not find in any IPD meta-analysis that gender, education level, or relationship status were significant predictors or moderators. This review shows that IPD meta-analyses on psychological treatments can identify predictors and moderators of treatment effects and thereby contribute considerably to the development of personalized treatments of depression.

Indexed as

depressionindividual participant data meta-analysismoderatorspredictorspsychotherapy

Identifiers

PMID35055408
PMCPMC8781368

What OpenQuestion holds

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Registered trials

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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.