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Record W7057740352

“Anti-COVID-19” Medications, Supplements, and Mental Health Status in Indonesian Mothers with School-Age Children

2021· article· en· W7057740352 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsIndonesianMental healthQuarter (Canadian coin)Marital statusPopulationDescriptive researchPandemicMental illness
DOInot available

Abstract

fetched live from OpenAlex

Annette d’Arqom,1,2 Brihastami Sawitri,2,3 Zamal Nasution,4 Riko Lazuardi5 1Division of Pharmacology, Department of Anatomy, Histology, and Pharmacology, Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia; 2Translational Medicine and Therapeutic Research Group, Universitas Airlangga, Surabaya, Indonesia; 3Department of Psychiatry, Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia; 4Institute for Population and Social Research, Mahidol University, Bangkok, Thailand; 5District Level Health Office, Surabaya, IndonesiaCorrespondence: Annette d’ArqomDivision of Pharmacology, Department of Anatomy, Histology, and Pharmacology, Faculty of Medicine, Universitas Airlangga, Jl. Mayjen Prof. Dr. Moestopo 47, Surabaya, 60131, East Java, IndonesiaEmail annette-d-a@fk.unair.ac.idPurpose: The COVID-19 pandemic affects all aspects of life and might cause stress for vulnerable groups such as mothers with school-age children, both housewives and working mothers. With the uncontrolled circulating information about medications, supplements, and herbs that are believed to treat COVID-19, self-medication and misused might escalate. Therefore, this study aims to determine the consumption of “anti-COVID” agents and the mental health of mothers with school-age children in Indonesia.Methods: Online questionnaires regarding medications/supplements for COVID-19 prevention and treatment of “anti-COVID” consumption behavior and mental health using the Depression, Anxiety, and Stress Scales (DASS-21) were distributed among Indonesian mothers with school-age children. Data (n = 610) were analyzed; descriptive and association between sociodemographic factors, “anti-COVID” medications consumption, and mental health were presented.Results: A quarter of the respondents were categorized as having mental disorders, with higher scores of DASS-21 was higher in the housewives’ group. The incidence associated with age, family expenses, and marital status in the working mothers’ group, and only with family expense in the housewives’ group. Moreover, the result showed 80% of the respondents consumed “anti-COVID” medications or supplements to prevent COVID-19, with 75% did self-medication without consulting with a healthcare professional. Friends/family and social media were two primary sources of information regarding the “anti-COVID” products. In the housewives’ group, their consumption behavior was influenced by education. Meanwhile in the working mothers’ group, the consumption behavior was influenced by age, family income, and family expense. In addition, there was no association between the usage of medications/supplements with the respondents’ mental health status.Conclusion: This study showed the importance of controlling information and expanding the mother’s knowledge to find the correct information to minimize the unwanted effect in the post COVID-19 pandemic. Increasing awareness of mental health issues in the community, especially in the vulnerable population such as mother with school-age children, is necessary to avoid detrimental effects that might occur in the future.Keywords: mental health, natural product, self-medication, vitamin

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)0.000
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 score0.014
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.092
GPT teacher head0.517
Teacher spread0.424 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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