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Record W4382793505 · doi:10.32831/jik.v11i2.455

[no title]

2023· article· W4382793505 on OpenAlexaff
Akbar Azi Hendro Kartiko, Avicena Sakufa Marsanti, Zaenal Abidin

Bibliographic record

VenueJurnal Ilmu Kesehatan · 2023
Typearticle
Language
FieldMedicine
TopicPublic Health and Nutrition
Canadian institutionsSNC-Lavalin (Canada)
Fundersnot available
KeywordsMedicineGynecology

Abstract

fetched live from OpenAlex

Pandemi covid-19 menciptakan kekhawatiran terhadap beragam kondisi. Berbagai masalah psikis muncul terutama terjadi pada lansia yaitu kecemasan yang berdampak pada penurunan kesehatan, aktivitas fisik, status fungsional, sampai beresiko pada kematian. Tujuan penelitian ini adalah untuk menganalisis kecemasan lansia selama pandemi covid-19 di wilayah Puskesmas Demangan Kota Madiun.
 Penelitian ini merupakan penelitian kualitatif dengan informan penelitian lansia usia 45-59 tahun yang mengalami kecemasan di wilayah kerja Puskesmas Demangan Kota Madiun. Pengumpulan data menggunakan teknik triangulasi sumber yaitu wawancara, observasi, dan dokumen pada sumber yang sama.
 Hasil penelitian dilakukan pada 18 lansia diperoleh pernyataan yang menunjukkan lansia mengalami kecemasan selama pandemi covid-19 berjumlah 6 lansia, 12 lansia menganggap covid-19 adalah virus atau penyakit biasa. Lansia yang mengalami kecemasan selama covid-19 dikarenakan memiliki riwayat penyakit degeneratif, sehingga memiliki resiko tinggi terpapar covid-19.
 Simpulannya adalah kecemasan lansia selama pandemi covid-19 adalah lansia yang memiliki riwayat penyakit degeneratif. Saran yang diberikan adalah lansia tetap mematuhi protokol kesehatan dimanapun berada dan segera melakukan vaksinasi lengkap.

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)0.008
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.174
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.011
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.002

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 head0.054
GPT teacher head0.367
Teacher spread0.313 · 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; both teacher heads agree on what is shown here.

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
Published2023
Admission routes1
Has abstractyes

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