Participants' Views on Lifestyle Intervention Program Enhancing Long-Term Health-Related Behaviors Improvement among Prehypertension and/or Prediabetes Mellitus Older Adults: A Qualitative Study Examined in Thailand at Health Promoting Hospitals

Applying the PDSA cycle to a group activity promoting lifestyle change for the active ageing of older Thai adults - a focused ethnography

Background

The proportion of the older Thai population is increasing rapidly. Lifestyle may impact active ageing in later life. Interventions that empower older Thai adults to initiate and carry out lifestyle changes are needed. This study applied the Plan-Do-Study-Act (PDSA) cycle, a tool for improving lifestyle changes, with the aim of exploring interactions among older Thai adults when participating in group activities.

Method

Focused ethnography was used based on participant observations, field notes and video recordings of 15 older Thai adults aged 62–78 years.

Results

Older Thai adults faced difficulties at the beginning since they were unfamiliar with initiating and carrying out lifestyle changes according to the PDSA concept. This provided a learning opportunity enabling older Thai adults to reach their individual goals of lifestyle change.

Conclusions

The PDSA cycle has the potential to empower older adults in group contexts to promote lifestyle changes related to active ageing.

Facilitators and Barriers to Uptake of Community-Based Diabetes Prevention Program Among Multi-Ethnic Asian Patients With Prediabetes

OBJECTIVE

This study aimed to identify facilitators and barriers to the uptake of a community-based diabetes prevention program (DPP) from the perspectives of decliners with prediabetes in a multi-ethnic Asian community.

METHODS

Semi-structured interviews were conducted with 29 individuals with prediabetes who declined participation in a large community-based diabetes prevention program in Singapore. Thematic analysis was undertaken to identify themes, which were subsequently mapped onto the Capacity-Opportunity-Motivation and Behavior model (COM-B).

RESULTS

We identified 16 key themes under three COM-B domains. Health status at the time of invitation, perceived ability of self-management, understanding of prediabetes condition and/or the program intention (Capability) were important determinants. Family commitment had the strong potential to enable or hinder physical and social Opportunity related to participation. Many participants desired involvement of physician as part of program invitation and component. Fear of exacerbation coupled with an automatic aversion for suffering influenced Motivation for participation.

CONCLUSION

Identifying facilitators and barriers embedded in the COM-B will assist systematic program modifications to increase participation of individuals with prediabetes. How information about modifiable risk factors is communicated by physicians at the point of diagnosis and program introduction is key to participation. Co-locating programs with family activity, development of mHealth, readiness assessment, and tailored explanation of program purpose may increase participation. These findings will be used to guide future national interventions in the community to ensure successful implementation.

Analysis of Factors Affecting Depression in Older Adults in South Korea

Objective: This study aimed to analyze the factors affecting depression among South Korean middle-aged and older adults using data from the Korean Longitudinal Study of Aging. Methods: We analyzed data regarding demographic characteristics, lifestyle, quality of life, cognitive level, and depression. Cognitive level and depression were evaluated using the Korean-Mini-Mental Status Examination and Center for Epidemiological Studies Depression Scale, respectively. Results: Depression was correlated with age, gender, residential area, level of education, alcohol intake, regular exercise, life satisfaction, and cognitive level, but not smoking. Furthermore, depression was highly affected by age, residential area, regular exercise, life satisfaction, and cognitive level, with a prediction accuracy of 80.26% achieved through machine learning analysis. Conclusions: Various factors are associated with depression in middle-aged and older adults. Therefore, multifaceted interventions for preventing depression in these age groups are required.