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Record W3096947756 · doi:10.2196/24298

Mental Health and Burnout Syndrome Among Postgraduate Students in Medical and Multidisciplinary Residencies During the COVID-19 Pandemic in Brazil: Protocol for a Prospective Cohort Study

2020· article· en· W3096947756 on OpenAlexvenueno aff
Rebeca da Nóbrega Lucena Pinho, Thaís Ferreira Costa, Nayane Miranda Silva, Adriana Ferreira Barros Areal, André De Mattos Salles, Andréa Pedrosa Ribeiro Alves Oliveira, Carlos Henrique Reis Esselin Rassi, Caroline Elizabeth Brero Valero, Ciro Martins Gomes, Dayde Lane Mendonça da Silva, Fernando Araújo Rodrigues de Oliveira, Isadora Jochims, Ivan Ranulfo, Juliana De Brito Seixas Neves, Lucas Alves de Brito Oliveira, Maria Nogueira Dantas, Marta Alves Rosal, Mayra Veloso Ayrimoraes Soares, Patrícia Shu Kurizky, Viviane Uliane Peterle, Yasmin Furtado Faro, Ana Paula Monteiro Gomides, Licia da Mota, Cleandro Pires de Albuquerque, Cézar Kozak Simaan, Verônica Moreira Amado

Bibliographic record

VenueJMIR Research Protocols · 2020
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare professionals’ stress and burnout
Canadian institutionsnot available
Fundersnot available
KeywordsBurnoutMental healthPsychosocialMedicineAnxietyCoping (psychology)CohortFamily medicineMultidisciplinary approachPsychiatryPsychologyClinical psychology

Abstract

fetched live from OpenAlex

BACKGROUND: The COVID-19 pandemic has led to high levels of physical, psychological, and social stress among health care professionals, including postgraduate students in medical and multidisciplinary residencies. This stress is associated with the intense fear of occupational exposure to SARS-CoV-2, the virus known to cause COVID-19. These professionals are at risk of developing physical and mental illnesses not only due to the infection but also due to prolonged exposure to multidimensional stress and continued work overload. OBJECTIVE: This study aims to evaluate the prevalence of symptoms suggestive of mental disorders and burnout syndrome and determine the risk factors for burnout among postgraduate students in medical and multidisciplinary residencies in Brazil during the COVID-19 pandemic. METHODS: For this prospective cohort study with parallel groups, participants were recruited between July and September 2020 to achieve a sample size of at least 1144 participants. Research instruments such as Depression, Anxiety, and Stress Scale; Patient Health Questionnaire; Brief Resilient Coping Scale; and Oldenburg Burnout Inventory will be used to collect data. Data will be collected in 2 waves: the first wave will include data related to sample characterization and psychosocial evaluation, and the second wave will be launched 12 weeks later and will include an evaluation of the incidence of burnout as well as correlations with the potential predictive factors collected in the first wave. Additionally, we will collect data regarding participants' withdrawal from work. RESULTS: The recruitment took place from July 29 to September 5, 2020. Data analyses for this phase is already in progress. The second phase of the study is also in progress. The final data collection began on December 1, 2020, and it will be completed by December 31, 2020. CONCLUSIONS: We believe the findings of this study will help evaluate the impact of the COVID-19 pandemic on the mental health conditions of health professionals in Brazil as well as contribute to the planning and implementation of appropriate measures that can alleviate these mental health challenges. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/24298.

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)0.013
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.225
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0000.000

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 head0.301
GPT teacher head0.648
Teacher spread0.347 · 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 designObservational
Domainnot available
GenreProtocol

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

Citations22
Published2020
Admission routes1
Has abstractyes

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