Publication: Factors Predicting Fatigue in Pulmonary Tuberculosis Patients Receiving Anti-Tuberculosis Drugs
Issued Date
2021-01-01
Resource Type
ISSN
22288082
Other identifier(s)
2-s2.0-85102827987
Rights
Mahidol University
Rights Holder(s)
SCOPUS
Bibliographic Citation
Siriraj Medical Journal. Vol.73, No.3 (2021), 167-173
Suggested Citation
Wipratchaya Thedthong, Wimolrat Puwarawuttipanit, Chongjit Saneha, Yong Rongrungruang Factors Predicting Fatigue in Pulmonary Tuberculosis Patients Receiving Anti-Tuberculosis Drugs. Siriraj Medical Journal. Vol.73, No.3 (2021), 167-173. doi:10.33192/Smj.2021.22 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/78791
Research Projects
Organizational Units
Authors
Journal Issue
Thesis
Title
Factors Predicting Fatigue in Pulmonary Tuberculosis Patients Receiving Anti-Tuberculosis Drugs
Other Contributor(s)
Abstract
Objective: To explore the predictive factors on fatigue among pulmonary tuberculosis patients receiving antituberculosis drugs. Methods: This study is a predictive correlational research designed. The sample was comprised of 125 patients at the out-patient department, a tertiary hospital in Bangkok setting. The data were collected between January to February 2020. The questionnaires included mini-cognitive assessment instrument (Mini-Cog); the demographic characteristics questionnaire; Piper fatigue scale-12 (PFS-12); Nutrition alert form (NAF); the Pittsburgh sleep quality index (PSQI); and the Center for epidemiologic studies depression scale (CES-D). All data were analyzed by using descriptive statistics and multiple regression analysis. Results: The sample had a mean age of 58.45 years (SD = 15.374) of which 60.8% were males. Overall, the mean score of fatigue was a moderate level (Mean = 4.90, SD = 2.455). From the multiple regression analysis, age, nutritional status, sleep quality, and depression could explain the variances on fatigue in the sample group as 52.5% (R2 =.525, F = 33.119, p <.001). Nutritional status, sleep quality, and depression are the variables found to be capable in predicting fatigue of pulmonary tuberculosis patients with statistical significance (β =.316, p <.001, β =.226, p <.05 and β =.340, p <.001). Conclusion: Nutritional status, sleep quality, and depression could affect fatigue. Healthcare teams should assess patients to prevent and manage the aforementioned symptoms to reduce suffering from fatigue and a better quality of life.