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Record W4409788212 · doi:10.5539/gjhs.v14n7p69

Social Functioning and Mental Health Status during COVID-19 Pandemic

2022· article· en· W4409788212 on OpenAlexvenueno aff
Mst. Nargish Akhtar Banu, Tanjina Atique, Mst. Nadira Parvin, Sharker Md. Numan, Mohammad Habibur Rahman, Md. Muarraf Hossain, Md. Kariul Islam

Bibliographic record

VenueGlobal Journal of Health Science · 2022
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsnot available
FundersMississippi Department of Marine Resources
KeywordsPandemicCoronavirus disease 2019 (COVID-19)Mental health2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)BetacoronavirusMEDLINEMedicineEnvironmental healthPsychologyPsychiatryVirologyPolitical scienceOutbreakDiseaseInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: A descriptive type of cross-sectional study was carried out to assess the social functioning and mental health status of the COVID-19 pandemic with 117 samples. The aim of the study was to determine the social functioning and mental health status of the Bangladesh University of Health Sciences (BUHS) faculties and officers during the COVID-19 pandemic. METHODOLOGY: A descriptive type of cross-sectional study was carried out with 117 University teachers and other officers who took part in the study over three months from June-2020 to August-2020. All participants who was fulfilled the inclusion criteria were invited in this study. Convenience sampling technique was used to recruit the study participants. AOQ form (Borderline Personality Disorder Mental Health assessment form) is used to measure the mental health outcomes of the respondents. The Social Functioning Questionnaire (SFQ), an eight-item self-report scale (score range 0-24), was developed from the Social Functioning Schedule (SFS). RESULTS: The socio-demographic characteristics of the respondents were considered as sex, occupation, type of family, history of chronic diseases, living area, and work from home. The study revealed that more than half 53.8% (n = 63) of the respondents were male. It was found that 69.2 % (n = 81) of them belonged to nuclear families; among them, 84.6% (n = 99) were living in urban areas and 54.7% (n = 64) worked from home. It shows a statistically significant (p = 0.001) association between sex and money problem. Male has more significant money problems than females. There was a significant association between social functioning and mental health scores (r = .391, p = .001). The results showed a partial correlation between social functioning score and mental health score after adjusting for age and sex. Here, r = .276 and p = .003. This means that social functioning and mental health scores are significantly correlated even after controlling for age and sex. There was a significant association between mental health and social function status (p = 0.01). CONCLUSION: This study found a significant association between mental health and social function status. This would be helpful for future mental health support for those individuals with prior vulnerable mental health status.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
models agreeAgreement compares identical category sets and study designs across arms.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.011
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.093
GPT teacher head0.478
Teacher spread0.385 · 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

Labeled directly by 2 models reading the full record.

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

Citations0
Published2022
Admission routes1
Has abstractyes

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