Evidence map›Paper›PMID 42661415›Full record

ArticleInternational journal of methods in psychiatric research2026

Harmonising Depression and Anxiety Measures Across International Cohorts: A Framework Validated Using Measurement Invariance.

James Lian, Pedro F Zuccolo, Omid V Ebrahimi, Daniel Fatori, Abhaya Adlakha, Juan F De La Hoz, Younga H Lee, Adriana Carneiro, Isabela M Benseñor, Paulo A Lotufo and 13 more

Abstract read
In one paragraph

Article in International journal of methods in psychiatric research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

23 authors.

James LianDepartment of Psychiatry, Dementias Platform UK, University of Oxford, Warneford Hospital, Oxford, UK.ORCID https://orcid.org/0000-0002-9758-0472
Pedro F ZuccoloDepartamento de Psiquiatria, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, Brazil.ORCID https://orcid.org/0000-0002-6340-6097
Omid V EbrahimiDepartment of Experimental Psychology, University of Oxford, Oxford, UK.ORCID https://orcid.org/0000-0002-8335-2217
Daniel FatoriDepartamento de Psiquiatria, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, Brazil.ORCID https://orcid.org/0000-0001-7753-894X
Abhaya AdlakhaDepartment of Psychiatry, Dementias Platform UK, University of Oxford, Warneford Hospital, Oxford, UK.ORCID https://orcid.org/0009-0001-9989-4352
Juan F De La HozDepartment of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA.ORCID https://orcid.org/0000-0002-5584-7511
Younga H LeeDepartment of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA.ORCID https://orcid.org/0000-0001-7517-6594
Adriana CarneiroDepartamento de Psiquiatria, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, Brazil.ORCID https://orcid.org/0000-0002-2064-9953
Isabela M BenseñorCentro de Pesquisa Clínica e Epidemiológica, Hospital Universitário, Universidade de São Paulo, Sao Paulo, Brazil.ORCID https://orcid.org/0000-0002-6723-5678
Paulo A LotufoCentro de Pesquisa Clínica e Epidemiológica, Hospital Universitário, Universidade de São Paulo, Sao Paulo, Brazil.ORCID https://orcid.org/0000-0002-4856-8450
Alessandra C GoulartCentro de Pesquisa Clínica e Epidemiológica, Hospital Universitário, Universidade de São Paulo, Sao Paulo, Brazil.
Justin D TubbsDepartment of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA.ORCID https://orcid.org/0000-0002-6671-6816
Devon WattsDepartment of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA.
Yu ZhouDepartment of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA.ORCID https://orcid.org/0009-0001-6547-4413
Lorenza Dall'AglioDepartment of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA.ORCID https://orcid.org/0000-0002-4330-8297
Mihael CudicDepartment of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA.
Morgane KuenziDepartment of Psychiatry, Dementias Platform UK, University of Oxford, Warneford Hospital, Oxford, UK.
CGMHC Consortium
Ronald C KesslerDepartment of Health Care Policy, Harvard Medical School, Boston, Massachusetts, USA.ORCID https://orcid.org/0000-0003-4831-2305
Vikram PatelDepartment of Global Health & Social Medicine, Harvard Medical School, Boston, Massachusetts, USA.
André BrunoniDepartamento de Psiquiatria, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, Brazil.
Jordan W SmollerDepartment of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA.ORCID https://orcid.org/0000-0002-0381-6334
Sarah BauermeisterDepartment of Psychiatry, Dementias Platform UK, University of Oxford, Warneford Hospital, Oxford, UK.ORCID https://orcid.org/0000-0001-9463-6971

Funding

International evaluation of modifiable social determinants of health on COVID-related mental health outcomesRF1MH134638 · NIMH · MASSACHUSETTS GENERAL HOSPITAL · PI BAUERMEISTER, SARAH DIANA, BRUNONI, ANDRÉ RUSSOWSKY · 2023 to 2023
$3.2M
NIMH NIH HHS 1RF1MH134638NIMH NIH HHS RF1 MH134638
6 · The paper itself

Abstract

aimsCross-national research on mental health trajectories requires harmonised measures that are valid and comparable. However, measurement scales often differ between cohorts in item content and cultural context. This study aimed to develop a framework for harmonising mental health measures across international cohorts, focussing on depression and anxiety symptoms.

methodsWe applied a structured, theory-driven approach to align item content across two longitudinal ageing cohorts that used different self-report instruments with heterogeneous item codings: ELSA-UK and ELSA-Brasil. Data were collected before, during, and after the COVID-19 pandemic, providing a natural experiment for examining temporal changes in mental health. The harmonisation process involved: (1) mapping items to DSM-5 symptom domains via expert review; (2) transforming response formats into harmonised ordinal indicators; (3) leveraging the Harmony AI tool to identify semantically equivalent items; and (4) testing measurement invariance across waves and cohorts using multi-group confirmatory factor analysis (MGCFA).

resultsScalar invariance was achieved for depression in both longitudinal and cross-cohort models, enabling meaningful latent mean comparisons between cohorts. For anxiety, scalar invariance was supported within but not across cohorts, likely due to the limited number of conceptually matching items.

conclusionThe proposed harmonisation framework demonstrates the feasibility of robust cross-cultural comparisons of mental health constructs. Its success depends on the conceptual alignment and quality of available items. This approach provides a methodological template for future harmonisation efforts in global health and psychiatric epidemiology.

Indexed as

AnxietyCOVID-19DepressionPsychiatric Status Rating ScalesPsychometricsAgedCohort StudiesFactor Analysis, StatisticalFemaleHumansLongitudinal StudiesMaleMiddle AgedUnited Kingdomartificial intelligenceCOVID‐19data harmonizationlongitudinal cohort studymulti‐group confirmatory factor analysis (MGCFA)

Identifiers

PMID42661415
PMCPMC13522721

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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.