Managing With Atrial Fibrillation: An Exploratory Model-Based Cluster Analysis of Clinical and Personal Patient Characteristics

Rush, Kathy L.; Seaton, Cherisse L.; O’Connor, Brian P.; Andrade, Jason G.; Loewen, Peter; Corman, Kendra; Burton, Lindsay; Smith, Mindy A.; Moroz, Lana

doi:10.1016/j.cjco.2023.08.005

Cited by 2 publications

(1 citation statement)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Participants who finished the survey were eligible for a chance to win one of three $150 gift certificates through a random draw. Clinical participant data were obtained via clinician referral letters as part of another project [20]. Clinical patient history data included treatment history, chronic disease history,…”

Section: Data Collectionmentioning

confidence: 99%

Quality of life among patients with atrial fibrillation: A theoretically-guided cross-sectional study

Rush,

Seaton,

Burton

et al. 2023

PLoS ONE

View full text Add to dashboard Cite

Background Patients with atrial fibrillation (AF) have significantly lower health-related quality of life (HRQoL) compared to the general population and patients with other heart diseases. The research emphasis on the influence of AF symptoms on HRQoL overshadows the role of individual characteristics. To address this gap, this study’s purpose was to test an incremental predictive model for AF-related HRQoL following an adapted HRQoL conceptual model that incorporates both symptoms and individual characteristics. Methods Patients attending an AF specialty clinic were invited to complete an online survey. Hierarchical regression analyses were conducted to examine whether individual characteristics (overall mental health, perceived stress, sex, age, AF knowledge, household and recreational physical activity) incremented prediction of HRQoL and AF treatment satisfaction beyond AF symptom recency and overall health. Results Of 196 participants (mean age 65.3 years), 63% were male and 90% were Caucasian. Most reported ‘excellent’ or ‘good’ overall and mental health, had high overall AF knowledge scores, had low perceived stress scores, and had high household and recreation physical activity. The mean overall AF Effect On Quality-Of-Life Questionnaire (AFEQT) and AF treatment satisfaction scores were 70.62 and 73.84, respectively. Recency of AF symptoms and overall health accounted for 29.6% of the variance in overall HRQoL and 20.2% of the variance in AF treatment satisfaction. Individual characteristics explained an additional 13.6% of the variance in overall HRQoL and 7.6% of the variance in AF treatment satisfaction. Perceived stress and household physical activity were the largest contributors to overall HRQoL, whereas age and AF knowledge made significant contributions to AF treatment satisfaction. Conclusions Along with AF symptoms and overall health, individual characteristics are important predictors of HRQoL and AF treatment satisfaction in AF patients. In particular, perceived stress and household physical activity could further be targeted as potential areas to improve HRQoL.

show abstract

Section: Data Collectionmentioning

confidence: 99%