scholarly journals Patient perspectives on factors associated with enrollment and retention in chronic disease self-management programs: a systematic review

2016 ◽  
pp. 21 ◽  
Author(s):  
Samantha Paige ◽  
Michael Stellefson ◽  
Briana Singh
Keyword(s):  
Systematic Review ◽  
Chronic Disease ◽  
Patient Perspectives ◽  
Self Management ◽  
Factors Associated

scholarly journals Web 2.0 Chronic Disease Self-Management for Older Adults: A Systematic Review

2013 ◽  
Vol 15 (2) ◽  
pp. e35 ◽  
Author(s):  
Michael Stellefson ◽  
Beth Chaney ◽  
Adam E Barry ◽  
Enmanuel Chavarria ◽  
Bethany Tennant ◽  
...  
Keyword(s):  
Systematic Review ◽  
Older Adults ◽  
Chronic Disease ◽  
Web 2.0 ◽  
Self Management

scholarly journals Psychological factors associated with diabetes self-management among adolescents with Type 1 diabetes: A systematic review

2016 ◽  
Vol 23 (13) ◽  
pp. 1749-1765 ◽  
Author(s):  
Kelly Martinez ◽  
Sharon F Frazer ◽  
Martin Dempster ◽  
Andrea Hamill ◽  
Hanora Fleming ◽  
...  
Keyword(s):  
Systematic Review ◽  
Type 1 Diabetes ◽  
Psychological Factors ◽  
Data Extraction ◽  
Dietary Behaviour ◽  
Self Management ◽  
Eligibility Criteria ◽  
Factors Associated ◽  
Exercise Behaviour

This review aims to synthesise the literature examining the psychosocial variables related to self-management (insulin adherence, non-adherence and administration, blood sugar monitoring, dietary behaviour, exercise behaviour) in adolescents with type 1 diabetes. A systematic search of three electronic databases was carried out and, after the application of eligibility criteria, 21 articles were assessed for quality prior to data extraction. Numerous psychological factors were found to be associated with self-management; however, correlations were typically small to moderate. The strongest associations were found between social anxiety and diet (among males); greater intrinsic motivation, conscientiousness and diet; and extraversion and exercise.

scholarly journals The Effects of Self-Management Interventions on Depressive Symptoms In Adults With Chronic Physical Disease(S) Experiencing Depressive Symptomatology: A Systematic Review And Meta-Analysis

2021 ◽  
Author(s):  
Lydia Ould Brahim ◽  
Sylvie Lambert ◽  
Nancy Feeley ◽  
Chelsea Coumoundouros ◽  
Jamie Schaffler ◽  
...  
Keyword(s):  
Systematic Review ◽  
Depressive Symptoms ◽  
Chronic Disease ◽  
Glycemic Control ◽  
Depressive Symptomatology ◽  
Meta Analysis ◽  
Self Management ◽  
Control Group ◽  
Physical Disease ◽  
Management Interventions

Abstract Background: Chronic diseases are the leading cause of death worldwide. It is estimated that 20% of adults with chronic physical diseases experience concomitant depression, increasing their risk of morbidity and mortality. Low intensity psychosocial interventions, such as self-management (SM), are part of recommended treatment; however, no systematic review has evaluated the effects of depression SM interventions for this population. Objectives: The primary objective was to examine the effect of SM interventions on reducing depressive symptomatology in adults with chronic disease(s) and co-occurring depressive symptoms. Secondary objectives were to evaluate the effect of these interventions on improving other psychosocial and physiological outcomes (e.g., anxiety, glycemic control) and to assess potential differential effect based on key participant and intervention characteristics (e.g., chronic disease, provider). Methods: Studies comparing depression SM interventions to a control group were identified through a) systematic searches of databases to June 2018 [MEDLINE (1946 -), EMBASE (1996 -), PsycINFO (1967 -), CINAHL (1984 -)] and b) secondary ‘snowball’ search strategies. The methodological quality of included studies was critically reviewed. Screening of all titles, abstracts, and full texts for eligibility was assessed independently by two authors. Data were extracted by one author and verified by a second. Results: Fifteen studies were retained: 12 for meta-analysis and three for descriptive review. In total, these trials included 2064 participants and most commonly evaluated interventions for people with cancer (n = 7) or diabetes (n = 4). From baseline to < 6 months (T1), the pooled mean effect size was -0.47 [95% CI -0.73, -0.21] as compared to control groups for the primary outcome of depression and -0.53 [95% CI -0.91, -0.15] at ≥ 6-months (T2). Results were also significant for anxiety (T1 and T2) and glycemic control (T2). SM skills of decision-making and taking action were significant moderators of depression at T1. Conclusion: SM interventions show promise in improving depression and anxiety in those with concomitant chronic physical disease. The findings may contribute to the development of future SM interventions and delivering evidence-based care to this population. Further high-quality RCTs are needed to identify sources of heterogeneity and investigate key intervention components. Prospero registration: CRD42019132215

scholarly journals Factors Associated With Intention to Adopt mHealth Apps Among Dementia Caregivers With a Chronic Condition: Cross-sectional, Correlational Study (Preprint)

2021 ◽  
Author(s):  
Kyra Jennifer Waligora Mendez ◽  
Chakra Budhathoki ◽  
Alain Bernard Labrique ◽  
Tatiana Sadak ◽  
Elizabeth K Tanner ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Chronic Disease ◽  
Chronic Condition ◽  
Self Management ◽  
Dementia Caregivers ◽  
Cross Sectional ◽  
Web Based ◽  
Factors Associated ◽  
Intention To Adopt ◽  
Mhealth Apps

BACKGROUND In the United States, nearly 80% of family caregivers of people with dementia have at least one chronic condition. Dementia caregivers experience high stress and burden that adversely affect their health and self-management. mHealth apps can improve health and self-management among dementia caregivers with a chronic condition. However, mHealth app adoption by dementia caregivers is low, and reasons for this are not well understood. OBJECTIVE The purpose of this study is to explore factors associated with dementia caregivers’ intention to adopt mHealth apps for chronic disease self-management. METHODS We conducted a cross-sectional, correlational study and recruited a convenience sample of dementia caregivers. We created a survey using validated instruments and collected data through computer-assisted telephone interviews and web-based surveys. Before the COVID-19 pandemic, we recruited dementia caregivers through community-based strategies, such as attending community events. After nationwide closures due to the pandemic, the team focused on web-based recruitment. Multiple logistic regression analyses were used to test the relationships between the independent and dependent variables. RESULTS Our sample of 117 caregivers had an average age of 53 (SD 17.4) years, 16 (SD 3.3) years of education, and 4 (SD 2.5) chronic conditions. The caregivers were predominantly women (92/117, 78.6%) and minorities (63/117, 53.8%), experienced some to extreme income difficulties (64/117, 54.7%), and were the child or child-in-law (53/117, 45.3%) of the person with dementia. In logistic regression models adjusting for the control variables, caregiver burden (odds ratio [OR] 1.3, 95% CI 0.57-2.8; <i>P</i>=.57), time spent caregiving per week (OR 1.7, 95% CI 0.77-3.9; <i>P</i>=.18), and burden of chronic disease and treatment (OR 2.3, 95% CI 0.91-5.7; <i>P</i>=.08) were not significantly associated with the intention to adopt mHealth apps. In the final multiple logistic regression model, only perceived usefulness (OR 23, 95% CI 5.6-97; <i>P</i>&lt;.001) and the interaction term for caregivers’ education and burden of chronic disease and treatment (OR 31, 95% CI 2.2-430; <i>P</i>=.01) were significantly associated with their intention to adopt mHealth apps. Perceived ease of use (OR 2.4, 95% CI 0.67-8.7; <i>P</i>=.18) and social influence (OR 1.8, 95% CI 0.58-5.7; <i>P</i>=.31) were not significantly associated with the intention to adopt mHealth apps. CONCLUSIONS When designing mHealth app interventions for dementia caregivers with a chronic condition, it is important to consider caregivers’ perceptions about how well mHealth apps can help their self-management and which app features would be most useful for self-management. Caregiving factors may not be relevant to caregivers’ intention to adopt mHealth apps. This is promising because mHealth strategies may overcome barriers to caregivers’ self-management. Future research should investigate reasons why caregivers with a low education level and low burden of chronic disease and treatment have significantly lower intention to adopt mHealth apps for self-management. CLINICALTRIAL

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