Gambaran kualitas hidup peserta Pos Binaan Terpadu Penyakit Tidak Menular (POSBINDU PTM) dengan kejadian hipertensi di wilayah kerja Unit Pelaksana Teknis (UPT) Puskesmas Abang I, Karangasem, Bali, Indonesia
Bibliographic record
Abstract
Background: Hypertension is a disease that is a significant problem in the world. The prevalence of hypertension worldwide based on JNC-7 covers more than two-thirds of individuals after the age of 65 years. Hypertension can have an impact on the quality of life of patients which is influenced by various complications. PTB with the occurrence of hypertension in UPT Puskesmas Abang I, Karangasem, Bali, Indonesia.Methods: A cross-sectional study with a total sampling technique was conducted to the 5 villages in the Abang I Public Health Services during September-October 2018. A total of 48 respondents who meet the inclusion and exclusion criteria were included in this study. The variables assessed included gender, age group, level of education, occupational status, degree of hypertension, and overall quality of life among respondents based on the SF-36 questionnaire. Data were analyzed using SPSS software version 17 for Windows. Results: The gender proportion of females and males did not differ (50.00%). Most respondents were ≥ 65 years-old (54.17%), followed by low education level (85.42%), jobless (52.08%), hypertension (HT) grade II (56.25%), Rerata systolic blood pressure 159.5±18 mmHg, and diastolic blood pressure of 93±8 mmHg. Most respondents have a good quality of life in the domain of physical roles (100.00%), health (58.33%), vitality (60.41%), emotions (64.58%), and mental health (58.33%).Conclusion: The quality of life among respondents with hypertension at UPT Abang I Public Health Services, Karangasem, Bali, Indonesia showed good results in the domains of a physical role, health, vitality, emotions, and mental health. Latar Belakang: Hipertensi adalah salah satu penyakit yang menjadi masalah utama di dunia. Prevalensi hipertensi di seluruh dunia berdasarkan JNC-7 mencakup lebih dari dua pertiga individu setelah usia 65 tahun. Hipertensi dapat berdampak pada kualitas hidup pasien dimana dipengaruhi oleh berbagai komplikasi penyertanya. Penelitian ini bertujuan untuk mengetahui gambaran kualitas hidup peserta POSBINDU PTM dengan kejadian hipertensi di UPT Puskesmas Abang I, Karangasem, Bali, Indonesia.Metode: Penelitian ini menggunakan desain potong lintang dengan teknik Total Sampling pada 5 Desa di Kawasan UPT Kesmas Abang I selama September-Oktober 2018. Sebanyak 48 orang yang telah memasuki kriteria inklusi dan eksklusi dimasukkan dalam penelitian ini. Variabel yang dinilai meliputi jenis kelamin, kelompok usia, tingkat pendidikan, status pekerjaan, derajat hipertensi, dan kualitas hidup responden secara keseluruhan berdasarkan kuisioner SF-36. Data dianalisis menggunakan piranti lunak SPSS versi 17 untuk Windows.Hasil: Proporsi jenis kelamin perempuan dan laki-laki tidak berbeda (50%). Sebagian besar pasien berusia ≥ 65 tahun (54,17%), diikuti dengan pendidikan rendah (85,42%,), tidak bekerja (52,08%,), hipertensi (HT) derajat II (56,25%), rata-rata tekanan darah sistolik 159.5±18 mmHg, dan tekanan darah diastolik 93±8 mmHg. Sebagian besar responden memiliki kualitas hidup yang baik pada domain peran fisik (100,00%), kesehatan (58,33%), vitalitas (60,41%), emosi (64,58%), dan kesehatan mental (58,33%).Kesimpulan: Kualitas hidup responden dengan hipertensi di UPT Puskesmas Abang I, Karangasem, Bali, Indonesia menunjukkan hasil yang baik pada domain peran fisik, kesehatan, vitalitas, emosi, dan kesehatan mental.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".