MétaCan
Menu
Back to cohort
Record W4361225361 · doi:10.1016/j.lanepe.2023.100621

Epidemiological overview of major depressive disorder in Scandinavia using nationwide registers

2023· article· en· W4361225361 on OpenAlexaff
Joëlle A. Pasman, Joeri Meijsen, Marit Haram, Kaarina Kowalec, Arvid Harder, Ying Xiong, Thuy-Dung Nguyen, Andreas Jangmo, John Shorter, Jacob Bergstedt, Urmi Das, Richard Zetterberg, Ashley Tate, Paul Lichtenstein, Henrik Larsson, Ingvild Odsbu, Thomas Werge, Ted Reichborn‐Kjennerud, Ole A. Andreassen, Patrick F. Sullivan, Alfonso Buil, Martin Tesli, Yi Lu

Bibliographic record

VenueThe Lancet Regional Health - Europe · 2023
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsUniversity of Manitoba
FundersNational Institute of Mental HealthHorizon 2020Horizon 2020 Framework ProgrammeEuropean Research CouncilNational Institutes of HealthVetenskapsrådetH2020 European Research CouncilNorges ForskningsrådEuropean Commission
KeywordsEpidemiologyMedicinePsychiatryPsychologyPathology

Abstract

fetched live from OpenAlex

Background: Major depressive disorder (MDD) is a common psychiatric disorder associated with a high disease burden. This study gives a comprehensive overview of the prevalence, outcomes, treatment, and genetic epidemiology of MDD within and across the Scandinavian countries. Methods: This study has aimed to assess and compare across Norway, Denmark, and Sweden 1) the prevalence and trajectories of MDD and comorbidity, 2) outcomes and treatment, and 3) heritability (Denmark and Sweden only). The analyses leveraged data on 272,944 MDD cases (and 6.2 million non-cases) from Norway, Sweden, and Denmark in specialist care in national longitudinal health registers covering 1975-2013. Relying on harmonized public data global comparisons of socioeconomic and health metrics were performed to assess to what extent findings are generalizable. Findings: MDD ranked among the most prevalent psychiatric disorders. For many cases, the disorder trajectory was severe, with varying proportions experiencing recurrence, developing comorbid disorders, requiring inpatient treatment, or dying of suicide. Important country differences in specialist care prevalence and treatment were observed. Heritability estimates were moderate (35-48%). In terms of socioeconomic and health indices, the Scandinavian nations were comparable to one another and grouped with other Western nations. Interpretation: The Scandinavian countries were similar with regards to MDD epidemiological measures, but we show that differences in health care organization need to be taken into consideration when comparing countries. This study demonstrates the utility of using comprehensive population-wide registry data, outlining possibilities for other applications. The findings will be of use to policy makers for developing better prevention and intervention strategies. Funding: Swedish Research Council (Vetenskapsrådet, award D0886501 to PFS), US National Institutes of Mental HealthR01 MH123724 (to PFS), European Union's Horizon 2020 Research and Innovation Program (847776 and 964874, to OA) and European Research Council grant (grant agreement ID 101042183, to YL).

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score0.152

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.007
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.336
GPT teacher head0.490
Teacher spread0.154 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations31
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueThe Lancet Regional Health - EuropeSame topicMental Health Treatment and AccessFrench-language works237,207