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Challenges facing mental health systems arising from the COVID-19 pandemic: Evidence from 14 European and North American countries

2023· review· en· W4383896884 on OpenAlexaff
Janet R. Cummings, Xinyue Zhang, Coralie Gandré, Alisha Morsella, Laura Shields‐Zeeman, Juliane Winkelmann, Sara Allin, Gonçalo Figueiredo Augusto, Fidelia Cascini, Zoltán Cserháti, Antonio Giulio de Belvis, Astrid Eriksen, Inês Fronteira, Margaret Jamieson, Liubovė Murauskienė, William Palmer, Walter Ricciardi, Hadar Samuel, Silvia Gabriela Scîntee, Māris Taube, Karsten Vrangbæk, Ewout van Ginneken

Bibliographic record

VenueHealth Policy · 2023
Typereview
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPandemicCoronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Mental healthCoronavirus InfectionsPolitical scienceGeographyMedicineVirologyPsychiatryOutbreak

Abstract

fetched live from OpenAlex

We assessed challenges that the COVID-19 pandemic presented for mental health systems and the responses to these challenges in 14 countries in Europe and North America. Experts from each country filled out a structured questionnaire with closed- and open-ended questions between January and June 2021. We conducted thematic analysis to investigate the qualitative responses to open-ended questions, and we summarized the responses to closed-ended survey items on changes in telemental health policies and regulations. Findings revealed that many countries grappled with the rising demand for mental health services against a backdrop of mental health provider shortages and challenges responding to workforce stress and burnout. All countries in our sample implemented new policies or initiatives to strengthen mental health service delivery - with more than two-thirds investing to bolster their specialized mental health care sector. There was a universal shift to telehealth to deliver a larger portion of mental health services in all 14 countries, which was facilitated by changes in national regulations and policies; 11 of the 14 participating countries relaxed regulations and 10 of 14 countries made changes to reimbursement policies to facilitate telemental health care. These findings provide a first step to assess the long-term challenges and re-organizational effect of the COVID-19 pandemic on mental health systems in Europe and North America.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.964
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.498
GPT teacher head0.555
Teacher spread0.057 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

Citations29
Published2023
Admission routes1
Has abstractyes

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