A mixed analysis approach to elucidate the multiple chronic condition experience of English- and Spanish-speaking older adults

• Main Authors: Thomas-Purcell KB, Jacobs RJ, Seidman TL, Acevedo A, Waldrop-Valverde D, Ownby RL
• Format: Article
• Language: English
• Published: Dove Medical Press 2019-02-01
• Series: Clinical Interventions in Aging
• Subjects: multimorbidity; mHealth; self-management; qualitative; cluster analysis; treatment adherence
• Online Access: https://www.dovepress.com/a-mixed-analysis-approach-to-elucidate-the-multiple-chronic-condition--peer-reviewed-article-CIA

Kamilah B Thomas-Purcell,1,2 Robin J Jacobs,3 Tyler L Seidman,2 Amarilis Acevedo,2 Drenna Waldrop-Valverde,4 Raymond L Ownby2 1Department of Health Science, College of Health Care Sciences, Nova Southeastern University, Fort Lauderdale, FL, USA; 2Department of Psychiatry and Behavioral Medicine, Dr. Kiran C. Patel College of Osteopathic Medicine, Nova Southeastern University, Fort Lauderdale, FL, USA; 3Department of Medical Education, Dr. Kiran C. Patel College of Osteopathic Medicine, Nova Southeastern University, Fort Lauderdale, FL, USA; 4Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, GA, USA Background: Having multiple chronic conditions (MCCs) is the most common health condition in older adults. The management of each condition presents many challenges. A key factor in patients’ ability to manage their own health care is their level of health literacy. Purpose: The purpose of this mixed analysis study was to elucidate the experience of older adults living with MCCs and identify associations among the experiences to determine targets for future mobile health (mHealth) interventions focused on MCCs and health literacy. Participants and methods: Using the Abilities, Skills, and Knowledge Model as a framework, semi-structured interviews were completed with 25 older adults in English and Spanish. Interviews were analyzed using inductive thematic analysis and hierarchical cluster analysis. Results: The main themes from these results included 1) Reflections of chronic disease; 2) Emotional aspects of chronic disease; 3) Physical barriers to well-being; 4) Quality-of-care factors; and 5) Cognitive strategies for self-management. Qualitative results highlighted the importance of a multi-targeted approach to chronic disease self-management (CDSM). Cluster analysis identified associations within the qualitative data, revealing the importance of the subthemes related to coping with pain and the impact of the patient–provider relationship on treatment adherence. Conclusion: Results support the utility of mHealth interventions to improve health literacy and promote CDSM. Keywords: multimorbidity, mHealth, self-management, qualitative, cluster analysis, treatment adherence