Factors Influencing Telehealth Service Use and Health Outcomes in Patients Undergoing Continuous Ambulatory Peritoneal Dialysis: Cross-Sectional Study.

BACKGROUND: Several studies have demonstrated the efficacy and user acceptance of telehealth in managing patients with chronic conditions, including continuous ambulatory peritoneal dialysis (CAPD). However, the rates of telehealth service use in various patient groups have been low and have declined over time, which may affect important health outcomes. Telehealth service use in patients undergoing CAPD has been recognized as a key challenge that needs to be examined further. OBJECTIVE: This study aimed to explore the rates of telehealth service use over 4 months, identify factors influencing its use, and examine the relationship between telehealth service use and health outcomes in Thai people undergoing CAPD. METHODS: This cross-sectional study, which was a part of a pragmatic randomized controlled trial study, was conducted at a dialysis center in Bangkok, Thailand. The study included patients who were undergoing CAPD. These patients were randomly enrolled in the intervention group to receive telehealth service and additional standard care for 4 months. Data were collected using self-reported questionnaires, including a demographic form, Functional, Communicative, and Critical Health Literacy Scale, Perceived Usefulness Questionnaire, Brief Illness Perception Questionnaire, Patient-Doctor Relationship Questionnaire, and Kidney Disease Quality of Life 36 Questionnaire. Additionally, Google Analytics was used to obtain data on the actual use of the telehealth service. These data were analyzed using descriptive statistics, repeated-measures ANOVA, and regression analyses. RESULTS: A total of 159 patients were included in this study. The mean rate of telehealth service use throughout the period of 4 months was 62.06 (SD 49.71) times. The rate of telehealth service use was the highest in the first month (mean 23.48, SD 16.28 times) and the lowest in the third month (mean 11.09, SD 11.48 times). Independent variables explained 27.6% of the sample variances in telehealth service use. Older age (ß=.221; P=.002), higher perceived usefulness (ß=.414; P<.001), unemployment (ß=-.155; P=.03), and positive illness perception (ß=-.205; P=.004) were associated with a significantly higher rate of telehealth service use. Regarding the relationship between telehealth service use and health outcomes, higher rates of telehealth service use were linked to better quality of life (ß=.241; P=.002) and lower peritonitis (odds ratio 0.980, 95% CI 0.962-0.997; P=.03). CONCLUSIONS: This study provides valuable insights into factors impacting telehealth service use, which in turn affect health outcomes in patients undergoing CAPD.

Exploring health-related quality of life among non-Hodgkin's lymphoma survivors after completion of primary treatment: a cross-sectional study in Thailand.

PURPOSES: To investigate health-related quality of life (HR-QoL) and its influencing factors among non-Hodgkin's lymphoma (NHL) survivors after completion of primary treatment. METHODS: A cross-sectional study with 312 NHL survivors after completing primary treatment using self-reported data collected through face-to-face interviews or postal survey between May 2019 and December 2019. Sociodemographic factors, clinical characteristics, physical symptom distress, anxiety, depression, unmet supportive care needs, and adaptation (post-traumatic growth and post-traumatic stress disorder) were assessed. Data analysis included ANOVA tests to investigate HR-QoL among NHL survivors at different time points and GEE to assess predictors of HR-QoL. RESULTS: The mean score of HR-QoL was 136.05 (SD 19.12). HR-QoL scores reported by NHL survivors in phase I (6 months or less post-treatment) were significantly lower than those in phase II (> 6 months-4 years), phase III (> 4-9 years), and phase IV (over 9 years post-treatment). Regarding HR-QoL domains, NHL survivors in phase I had significantly lower physical well-being and functional well-being scores than those in phases II, III, and IV; and significantly lower lymphoma domain score than those in phase III. GEE analysis showed that physical symptom distress, anxiety, depression, unmet supportive care needs, poor adaptation, and receiving chemotherapy disrupted HR-QoL (all P < .001). CONCLUSIONS: Healthcare providers should re-prioritize intervention guidelines and survivorship care planning to promote HR-QoL among NHL survivors, particularly in phase I, through reducing physical and psychological symptom distress, addressing unmet needs, and enhancing adaptation outcomes.

Factors influencing self-management behaviors in persons with lupus nephritis: A cross-sectional study.

Background: Patients with lupus nephritis experience disease symptoms and side effects from treatment. Although self-management behaviors are important in patients with this disease, there is limited research on the factors influencing these behaviors. Objective: This study aimed to examine the factors influencing self-management behaviors in patients with lupus nephritis. Methods: This cross-sectional study was conducted in 240 patients with lupus nephritis at a university hospital in Thailand between August 2019 and December 2020 using a random sampling method. Data were collected using a demographic and clinical characteristic questionnaire, Self-Management Behavior Questionnaire, Self-efficacy for Managing Chronic Disease: A 6-item Scale, Knowledge about Lupus Nephritis Questionnaire, Family Support Scale, Social Networks in Adult Life Questionnaire, and Memorial Symptom Assessment Scale for Lupus Nephritis. Descriptive statistics and multiple linear regression analyses were employed. Results: The participants reported a moderate level of self-management behaviors. Multiple regression analyses revealed that disease duration, income, symptoms, self-efficacy, knowledge, family support, social networks, and classes of lupus nephritis significantly explained 21% of the variance in self-management behaviors (R2 = 0.21; F(8,231) = 7.73; p <0.001). Family support (ß = 0.32, p <0.001) and symptoms (ß = -0.23, p <0.001) were significant determinants of self-management behaviors in patients with lupus nephritis. Conclusion: The findings provide valuable insight for nurses to better understand the factors influencing self-management behaviors in patients with lupus nephritis. Patients with low family support and high symptom severity may face difficulty in performing self-management behaviors. Nurses should pay more attention to these patients and provide family-based interventions to optimize self-management behaviors in this population.

Social determinants of health and glycemic control in persons with type 2 diabetes mellitus attending a tertiary hospital in Nepal: A cross-sectional study.

Background: Diabetes mellitus (DM) is an emerging global public health challenge worldwide, including Nepal. Social determinants of health (SDOH) play a major role in glycemic control among persons with type 2 DM (T2DM). However, little is known about the association between SDOH and glycemic control among individuals with T2DM in Nepal. Objective: This study aimed to identify the level of glycemic control and SDOH associated with glycemic control among Nepalese with T2DM. Methods: This cross-sectional study was conducted at a tertiary hospital in Kathmandu, Nepal, among 135 Nepalese diagnosed with T2DM who attended follow-up appointments. Convenience sampling and inclusion criteria were utilized for participant selection. Data were collected from April to June 2021 using validated scales. Descriptive statistics, Chi-square test, and binary logistic regression were employed to analyze the data. Results: The mean age of the participants in this study was 53.84 (SD = 11.78) years, and the average monthly household income was 567.64 (SD = 362.30) USD. The majority of the participants (77.8%) were literate and had no health insurance coverage (73.3%). Approximately 64.4% of the participants showed suboptimal glycemic control indicated by glycated hemoglobin (HbA1c) ≥7%. The significant determinants of good glycemic control included monthly household income of >850 USD (odds ratio [OR] = 12.20, 95% confident interval [CI] = 1.76-84.61, p = 0.011) and 341-600 USD (OR = 7.64, 95% CI 1.35-42.98, p = 0.021), being literate (OR = 6.37, 95% CI = 1.65-24.49, p = 0.007), having health insurance (OR = 5.82, 95% CI = 1.49-22.65, p = 0.011), sufficient health literacy (OR = 3.46, 95% CI = 1.10-10.83, p = 0.03), and high (OR = 16.17, 95% CI = 2.36-110.67, p = 0.005) and moderate (OR = 7.02, 95% CI = 1.26-39.07, p = 0.026) food availability, respectively. Conclusion: The study revealed suboptimal glycemic control in Nepalese with T2DM. This study presents essential social determinants of glycemic control in this population. Therefore, healthcare providers, particularly nurses, should pay more attention to assessing social determinants and provide targeted interventions to patients with T2DM who have low income, are illiterate, have no health insurance coverage, have insufficient health literacy, and have low resources for food availability.

Risk factors associated with uncontrolled blood pressure among patients with non-dialysis chronic kidney disease in Vietnam.

Background: Uncontrolled blood pressure rates are high in patients with non-dialysis chronic kidney disease, worsening the disease progression and leading to end-stage renal disease. However, studies on uncontrolled blood pressure in patients with non-dialysis chronic kidney disease and its associated factors in Vietnam are scarce.Objectives: This study aimed at identifying uncontrolled blood pressure rates and risk factors associated with uncontrolled blood pressure among Vietnamese patients with non-dialysis chronic kidney disease. Methods: A cross-sectional, correlational study design was employed among 182 participants coming to follow up at two tertiary hospitals in Vietnam. The participants were selected by a convenience sampling technique. Data were collected using Participant Demographic Information Form, Clinical Characteristics Form, Alcohol Use Disorders Identification Test, Pittsburgh Sleep Quality Index, Charlson Comorbidity Index, and an automated office oscillometric upper arm device. Descriptive statistics, Chi-square, Fisher's Exact Test, and binary logistic regression were used to analyze the data. Results: 63.2% of the participants could not control their BP less than 130/80 mmHg. Poor sleep quality (OR 2.076, 95%CI 1.059-4.073, p=.034) and severe comorbidities (OR 2.926, 95%CI 1.248-6.858, p=.013) were risk factors associated with uncontrolled blood pressure among Vietnamese patients with non-dialysis chronic kidney disease. Interestingly, the study found a high rate of awareness toward the importance of blood pressure control but a low rate of known blood pressure targets. Conclusion: Uncontrolled blood pressure rates among Vietnamese patients with non-dialysis chronic kidney disease were high. Sleep quality and comorbidity severity were significantly associated with uncontrolled blood pressure in this population. To achieve blood pressure targets, nurses and other healthcare providers should pay more attention to the patients with poor sleep quality and severe comorbidities.

Treatment-Related Quality of Life in Nepalese Women with Breast Cancer

Objective: To identify the level of quality of life and its predictors in Nepalese women with breast cancer while receiving chemotherapy. Methods: This cross-sectional study with a predictive design was conducted for a conveniently selected sample of 85 Nepalese women with primary breast cancer receiving chemotherapy at outpatient clinics of three cancer hospitals of Kathmandu, Nepal. Data were collected during December 2016 and February 2017 using demographic sheets, the European Organization for Research and Treatment of Cancer Quality of Life Core Questionnaire and the modified Medical Outcomes Study Social Support Survey. Descriptive and inferential statistics were employed for data analysis. Results: The mean age of the sample was 50.2 years (SD = 11.50). Study participants reported moderate to poor quality of life (M = 33.5, SD = 23.5). Multiple regression analysis showed that age, years of education, stage, past breast surgery, overall symptom severity, and social support significantly explained 56.8% of the variance in quality of life (R2 = .568, F (8,76) = 12.469, p = .000). However, overall symptom severity (ß = -.477, p= .000) and social support (ß = .183, p = .050) were the most important predictors. Conclusions: As Nepalese women reported decreased quality of life, nurses should provide preventive and supportive services to improve the quality of life of their patients during chemotherapy.