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All Journal Jurnal Kesehatan Masyarakat Jurnal Kesehatan Masyarakat
Larasati, Victoria
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Education Public Health

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Sleep Quality Affects Humoral Response in Recipients of Two-Dose Sinovac Vaccines Hananta, Linawati; Larasati, Victoria; Surilena, Surilena
Jurnal Kesehatan Masyarakat Vol 18, No 4 (2023)
Publisher : Department of Public Health, Faculty of Sport Science, Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/kemas.v18i4.41950

Abstract

To curb the COVID-19 pandemic, the government distributed Sinovac vaccines. Sleep mediates immune function, including post-vaccination antibody response. This study aimed to analyze whether there was a difference in post-vaccination antibody levels in Sinovac vaccine recipients with poor and good sleep quality. This study used analytical observations of recipients of the two-dose Sinovac vaccine in 2021. Primary data included age, sex, the Pittsburgh Sleep Quality Index (PSQI) questionnaire, and post-vaccination IgG-SARS-CoV-2 antibody levels. The PSQI and IgG SARS-CoV-2 antibody levels were measured a month after the second vaccination. Participants with non-reactive antibody levels before the first vaccination were included, and participants with incomplete data were excluded. The Mann-Whitney test was used to look for associations between sleep quality and post-vaccination IgG SARS-CoV-2 levels. Univariate analysis showed that of 54 participants, 37 (68.5%) were male, and 28 (51.9%) had poor sleep quality. 15 participants (27.78%) were in the 36-45 age group, and median antibody levels in participants who received the second Sinovac Vaccine was 223.5 (199.01) units/mL. Post-vaccination IgG SARS-CoV-2 antibody levels were significantly associated with sleep quality (p=0.036).
Artificial Intelligence in Type II Diabetes Mellitus: Screening, Treatment, and Complication Lians, Airine Stefanie; Tunru, Andi Miyanza Rezkyawan Lakipadada; Chindia, Chindia; Prasetyo, Juan Alexandra; Kie, Justin; Christian, Raffael; Sean, Sherlyn; Larasati, Victoria; Yen, Liauw Djai
Jurnal Kesehatan Masyarakat Vol. 20 No. 4 (2025)
Publisher : Universitas Negeri Semarang in collaboration with Ikatan Ahli Kesehatan Masyarakat Indonesia (IAKMI Tingkat Pusat) and Jejaring Nasional Pendidikan Kesehatan (JNPK)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/kemas.v20i4.1138

Abstract

Type II diabetes mellitus is one of the chronic metabolic diseases that are associated with insulin resistance. Type II diabetes mellitus incidence continues to increase each year and may cause various health complications, even death. Addressing early detection and appropriate treatment is important in decreasing the incidence of type II diabetes mellitus and improving the quality of life in diabetic patients. The potential of artificial intelligence in healthcare is expected to assist in screening, therapy management, and even detection of type II diabetes mellitus complications. Despite limited literature, this study aims to understand the benefit of AI in assisting health workers in screening and managing type II diabetes mellitus. Searches are conducted with search engines, such as PubMed, Science Direct, and Google Scholar, with the keywords “Artificial Intelligence” and “Diabetes Mellitus Type 2”, as well as their synonyms. The search results in twenty English and Indonesian studies were published in the last ten years. These various studies found that many Artificial intelligence models developed to assist in screening, therapy management, and detect complications in patients with type II diabetes mellitus.
Co-Authors Chindia, Chindia Christian, Raffael Kie, Justin Lians, Airine Stefanie Linawati Hananta, Linawati Prasetyo, Juan Alexandra Sean, Sherlyn Surilena Hasan Tunru, Andi Miyanza Rezkyawan Lakipadada Yen, Liauw Djai