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Record W3023052555 · doi:10.1177/0706743720926676

Mental Health of Communities during the COVID-19 Pandemic

2020· editorial· en· W3023052555 on OpenAlexaffvenue
Daniel Vigo, Scott B. Patten, Kathleen Pajer, Michael Krausz, Steven Taylor, Brian Rush, Giuseppe Raviola, Shekhar Saxena, Graham Thornicroft, Lakshmi N. Yatham

Bibliographic record

VenueThe Canadian Journal of Psychiatry · 2020
Typeeditorial
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsPublic Health OntarioUniversity of TorontoUniversity of OttawaUniversity of CalgaryUniversity of British Columbia
FundersNational Institute of Mental HealthMedical Research Council
KeywordsCoronavirus disease 2019 (COVID-19)Pandemic2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Mental healthGeographyVirologyPsychologyMedicinePsychiatryOutbreakInfectious disease (medical specialty)Disease

Abstract

fetched live from OpenAlex

Introducción: El estudio surge a partir del reconocimiento de las necesidades en torno a la Salud Mental en el TrabajoSMT de un grupo de administrativos adscritos a una universidad pública de Colombia y desde la implementación de la modalidad de trabajo en casa derivada de la situación epidemiológica COVID-19. El objetivo es contribuir a fortalecer la salud mental en el trabajo a través de un programa fundamentado en el Modelo de Creencias en Salud-MCS. Metodología: Dicho programa se desarrolló mediante plataformas digitales, en el que se abordaron temáticas relacionadas con el manejo del estrés y la gestión del tiempo, siguiendo una metodología cualitativa, con enfoque de Investigación Acción-IA. Resultados y Discusión: Se obtiene la identificación de situaciones y/o estímulos percibidos como barreras para la realización de conductas salutogénicas y desde un enfoque preventivo, la estrategia centrada en educación para la salud aportó de forma significativa sobre el autocuidado en el desarrollo del trabajo en casa. Conclusiones: La implementación de este tipo de programas, que involucran a la comunidad durante el proceso, contribuyen sustancialmente al fortalecimiento de la salud mental en el trabajo desde necesidades contextualizadas, especialmente durante la contingencia sanitaria por COVID-19

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.421
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.003
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 head0.063
GPT teacher head0.391
Teacher spread0.328 · 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
GenreEditorial

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

Citations242
Published2020
Admission routes2
Has abstractyes

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