Browsing by Subject "eHealth"

Background: The prevalence of smoking among Chinese men has been one of the highest globally despite decades of smoking cessation efforts. Previous studies suggest that smoking cessation interventions could be more effective in achieving abstinence when they are culturally adapted. Based on the “smoking rationalization belief” framework and recent development on electronic health (eHealth) technology, we developed the Community Centered eHealth Smoking Cessation Intervention (CCeSCI).Research question: What are the common beliefs of East and Southeast Asian male smokers that make quitting so difficult, and how can we inform and refine the CCeSCI trial design and implementation in order to address those cognitive misconceptions and to achieve a better quitting outcome? Method: We conducted a comprehensive literature review on the common beliefs of East and Southeast Asian smokers and a qualitative study on beliefs and attitudes of Chinese smokers and community workers to inform the CCeSCI study design and implementation. A total of eighteen in-depth interviews were conducted, including five with community workers and thirteen with adult male smokers. The smoking rationalization belief framework (including six domains) was used to guide the thematic analyses of the qualitative data. Findings: Both the literature review and the qualitative study revealed that the six domains in the rationalization beliefs framework -- smoking functional beliefs, risk generalization beliefs, social acceptability beliefs, safe smoking beliefs, self-exempting beliefs, and "quitting is harmful" beliefs -- were the major themes of male smokers. In addition, fatalism, family matters, no need for help, indifference and pessimism, and "I can quit when I decide to" were the most popular attitudes among smokers. For community workers, the major themes were "environmental factors are the most important," "leadership support is crucial," "mixed attitudes regarding cessation clinics," and "individual willingness matters." We also identified some common barriers to smoking cessation efforts. We found high heterogeneity among smokers in their beliefs and attitudes, but less so for community workers. Conclusions: Current smoking cessation efforts have largely neglected the rich diversity of rationalization beliefs among smokers and the misalignment of perceptions between community workers and smokers. Future interventions should focus more on addressing the specific psychological dependence of smokers and their rationalization beliefs by placing them at the center of their decision-making. Integrated with supply-side intervention in the communities and eHealth technologies, CCeSCI has a promising future in improving smoking abstinence with better acceptability, feasibility, and generalizability among adult male smokers in East and Southeast Asian countries.

Background: According to the WHO 2020 NCD report, the COVID-19 pandemic disrupted diabetes care in 49% of countries. eHealth emerged as a solution to disease management challenges during the unprecedented outbreak. Due to the rapidly expanding nature of eHealth use during the pandemic, this study aimed to determine 1) the sociodemographic factors associated with eHealth during COVID-19 and 2) whether eHealth was associated with diabetes management and clinical outcomes. Methods: Using quantitative data from cross-sectional surveys from Kunshan and Taicang, China (n=309) and Manila, Philippines (n=150) (data sets uncombined), we performed Chi-squared and Fisher’s exact tests and univariate logistic regressions to determine the relationship of eHealth use and sociodemographic characteristics. We then performed logistic and linear regression to determine the association of eHealth use with diabetes disease outcomes. Results: In China, younger age (p=0.02), higher education level (p=0.001), married marital status (p=0.03), suburban residence type (p=0.001), and higher household monthly income during COVID-19 (p=0.004) were associated with using eHealth. In the Philippines, younger age (p= 0.009) and higher education level (p=0.01) were associated with eHealth use. eHealth use was associated with undergoing FBS testing in the last three months (OR = 2.19, 95%CI = 1.00, 4.78), undergoing HbA1c testing in the last three months (OR = 3.64, 95%CI = 1.01, 13.15), and reporting disease control per their last HbA1c test (OR = 9.98, 95%CI = 3.41, 29.18) in the Philippines, adjusting for various demographic characteristics. Conclusions: Our data indicated eHealth use could positively affect diabetes clinical and management outcomes for people with diabetes in China and the Philippines. We posit more research is needed for the impacts of eHealth on clinical outcomes as well as the methods for eHealth implementation and integration in LMIC.

Background: Primary healthcare is an important facet of non-communicable disease treatment and eHealth is a viable strategy to strengthen PHC in urban low-middle income settings such as in Lima, Peru. This study aimed to describe the current use of eHealth technologies in primary healthcare settings in urban Peru, assess the perceived effectiveness of eHealth technologies in NCD service delivery at the PHC level, and identify barriers and facilitators to the utilization of eHealth technologies at the PHC level.

Methods: In-depth interviews using a semi-structured interview guide were conducted among identified and invited policy makers, researchers and experts, and healthcare workers in Lima, Peru. Three districts in Lima were selected and interviews with healthcare workers were conducted at facilities from those districts. Interviews were transcribed and thematic analysis was utilized to identify themes in the data.

Results: A total of 14 participants were interviewed, including 2 policymakers, 5 experts, and 7 healthcare workers. Current use of eHealth were electronic medical records and telehealth applications. Participants were in favor of eHealth use and perceived eHealth as being effective. Human resources and digital literacy were factors cited as facilitators while data security, political climate, and compatibility were seen as barriers to implementation and utilization of eHealth.

Conclusions: The use of eHealth in Peru is still in its early stages, particularly in PHC settings and for service delivery of NCDs. At the intersection of these three topics there has been little progression of integration and utilization. Sentiment towards eHealth among researchers, policymakers, and healthcare workers is high and a number of barriers must be addressed to implement and utilize eHealth and reap its benefits.