DOI: 10.5061/dryad.gtht76hsf
title: Quality of life among patients with atrial fibrillation

description: 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.
description: # Quality of life among patients with atrial fibrillation
 [https://doi.org/10.5061/dryad.gtht76hsf](https://doi.org/10.5061/dryad.gtht76hsf) | Element | Notes | | ------- | ----- | | Title \* | Quality of life among patients with atrial fibrillation:  A theoretically-guided cross-sectional study | | Creator \* | Dr. Kathy L Rush | | Description \* | The primary motivation behind the creation of this dataset is to bring attention to the notably reduced health-related quality of life (HRQoL) individuals suffering with atrial fibrillation (AF) experience when compared to both the general population and individuals with other heart-related conditions. Current research tends to concentrate on understanding how AF symptoms impact HRQoL, often overlooking the significance of individual characteristics determining HRQoL. To bridge this research gap, this study aims to establish an enhanced predictive model for HRQoL in individuals with AF. This model is based on an adapted HRQoL conceptual framework that takes into account both the influence of symptoms and the unique characteristics of each individual. | | Alternate Title | Quality of life among patients with atrial fibrillation | | Contact Name | Dr. Kathy L Rush | | Contact Email | [kathy.rush@ubc.ca](mailto:kathy.rush@ubc.ca) | | Contact Other | | | Update Frequency \* | One time upload September 2023 | | Date Issued | September 2023 | | Date Created \* | Data collection began November 2020 | | Start Date | 11/1/2020 | | End Date | 10/31/2021 | | Spatial Coverage | British Columbia | | Usage Considerations | This dataset is used to answer the associated research questions and fulfill the purpose of the study. We examined 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 | ## Methodology ***Sample and Recruitment*** All patients of the clinic with an AF diagnosis who were over 18 years and could complete an online survey or had a family member who could assist, were eligible to participate. The clinic’s booking clerk sent a letter detailing the research study (by mail or email) to all patients with upcoming appointments during the recruitment period. The letter informed patients of the ongoing study and to expect a telephone initiation from a research team member regarding their eligibility and interest in the study. Patient contact information was then shared with the research team using secure file transfer. Subsequently a research assistant (a physician or a licensed practical nurse) who had no prior relationship with participants contacted patients by telephone. Recruitment began in November 2020 and continued for one year until a sample size of approximately 200 was achieved. A post hoc power analysis assuming a medium effect size estimated required sample size for modelling to be 114, indicating appropriate sample size had been achieved for analyses (Faul et al., 2007). ***Data Collection*** Study data were collected using an online survey hosted on Qualtrics (Qualtrics, Provo, UT). Prior to taking the survey, all participants gave electronic consent. Participants who finished the survey were eligible for a chance to win one of three $150 gift certificates through a random draw. ***Measures*** Overall Health: Participants were asked to rate their overall health on a scale ranging from 1 (poor) to 4 (excellent) (Ware et al., 1996). Overall mental health: Participants were asked to rate their overall mental health on a scale ranging from 1 (poor) to 4 (excellent) (Ahmad et al., 2014). Perceived stress (S. Cohen et al., 1983): The Perceived Stress Scale (PSS-10), a 10-item, 5-point scale, measures the degree to which situations in one's life are appraised as stressful, ability to control aspects of life, confidence in handling problems, or being unable to cope with demands. The PSS-10 previously had a reliability alpha of .78 and correlated in a predictable way with other measures of stress (S. Cohen et al., 1983) Socio-demographic characteristics: These included sex, age, marital status, race/ethnicity, education, and income. AF Knowledge (McCabe et al., 2020). The Knowledge about AF tool is a 28-item multiple choice-style questionnaire including questions about AF symptoms, treatment, medications, risk factors, and lifestyle. Participants are asked to choose one of 3 options for each question, only one of which is the correct response. The tool was developed using research on gaps in patient knowledge and patient values and management preferences. Knowledge scores are calculated as a percentage of correct answers, with higher numbers indicating higher knowledge. Four items were removed from the overall knowledge percent scores, as per McCabe et al. (McCabe et al., 2020) finding that these items had factor loadings below .45 and were not reliable predictors of overall test performance and knowledge. Household and recreational physical activity (Gill et al., 2008). Physical activity scores are calculated based on the Phone-FITT questionnaire. The questionnaire was originally designed to be administered via telephone, so it was adapted for the use in an online survey by displaying the questions as checkboxes. First, participants were asked to indicate their participation in various household and recreational activities in a typical week within the past month, or specific months for season dependent activities. If they participated in an activity, participants were also asked to provide a frequency (times per week, and months per year for seasonal activities only), as well as choose a duration from 1 (1-15 minutes) to 4 (1 hour or more) and an intensity from 1 (breathing normally and able to carry on a conversation) to 3 (too out of breath to carry on a conversation). Scores are calculated as the sum of the frequency, duration, and intensity for all household and all recreational activities, with higher scores indicating higher physical activity. The Phone-FITT has previously demonstrated test-retest reliability as well as convergent validity (i.e., positive correlations with accelerometer counts) (Gill et al., 2008) Atrial Fibrillation Effect on QualiTy-of-Life Questionnaire (AFEQT) (Spertus et al., 2011). The AFEQT is a 20-item, 7-point scale comprising overall HRQoL and three sub-domains: symptoms, daily activities, treatment concerns, along with AF treatment satisfaction. The AFEQT was developed for use as an outcome measure in trials and interventions and for disease management. Overall HRQoL scores are calculated as the sum of items 1-18, accounting for unanswered items, and normed on a scale from 0-100, with higher numbers indicating higher HRQoL. Treatment satisfaction scores follows the same calculation for items 19-20, with higher scores indicating higher treatment satisfaction; while it is included in the AFEQT, AF treatment satisfaction is not calculated in the overall HRQoL with the other subscales. A difference of + or minus 5 points on the AFEQT are clinically meaningful (Holmes et al., 2019) ***Data cleaning*** Two-hundred and three participants responded to the survey. Seven participants were missing one third or more of the scale scores and were removed. Of the remaining 196 participants, less than 1% of data were missing for variables included in the primary analyses. Missing data were replaced using multiple imputation (Austin et al., 2021). ## Description of the data and file structure Details of data structure and contents can be found in the supplemental file AF\_QoL\_Codebook. | Variable | Description | | -------- | ----------- | | Sex | participant sex | | Age | participant age | | AFQoL\_Overall\_Score\_Norm | AFQET Overall quality of life score | | AFQoL\_SymptomScore | AFQET symptom score (symptom impact on quality of life) | | AFQoL\_ActivScore | AFQET activity score (AF impact on activity) | | AFQoL\_TreatConcernScore | AFQET treatment concern | | Imput\_AFeQoL\_Treat\_Satisfaction | AFQET treatment satisfaction with imputation | | Windsor\_Imput\_Knowledge | Knowledge score with Windsor imputation | | Imput\_PSS10 | Perceived stress with imputation | | LastAF | Last time in AF | | MH\_rating | Mental health rating | | Imput\_Overall\_Health | overall health rating with imputation | | Windsor\_Household\_Activ\_Score | Phone-FITT Household activity score with Windsor imputation | | Rec\_Activ\_Score | Phone-FITT recreation activity score  |