https://orcid.org/0000-0001-8075-7895
Abstract
In patients with atrial fibrillation (AF), improved management of modifiable risk factors and concomitant diseases is recommended by guidelines, yet many AF patients have sub-optimal risk factor management. Digital health solutions may offer support in this matter. This study aims to identify how patients with AF perceive they could be supported by a digital tool aimed to optimize management of comorbidities and modifiable risk factors associated with an unhealthy lifestyle.
This was a qualitative, descriptive study based on four semi-structured focus-group interviews analysed by manifest content analysis. Sixteen AF patients with recent in- or outpatient encounters were included [age 68 (52–78) years; 43% female; BMI 29.5 (20.4–35.8) kg/m2; paroxysmal/persistent AF (50%/50%); AF duration 7 (0–22) years]. Relevant comorbidities were hypertension (88%), heart failure (25%), diabetes mellitus type 2 (19%), and ischaemic heart disease (13%). The patients’ suggestions were summarized into three main categories. First, person-centred information is essential, meaning that information should be customized and conveyed in an appropriate manner and include practical tips. Second, patients desire help with managing lifestyle habits in a way that is applicable in everyday life, and patients desire help with creating habits. Third, regular communication is necessary including inspirational reminders and motivational feedback.
Patients with AF request person-centred information, support in managing healthy lifestyle habits, and more regular communication with caregivers. This study provides a first foundation on how to better support AF patients, and using a digital tool in standard care may improve outcomes and reduce cost of care.
Regarding digital risk factor management, patients request person-centred information, help with managing lifestyle habits, and regular communication.
Digital risk factor management should be implemented more in standard care to improve patient outcomes and reduce costs of care.
Background
Atrial fibrillation (AF) is the most frequent cardiac arrhythmia affecting over 3% of the adult population worldwide, and the incidence increases with age.1 In patients with symptomatic AF, restoration of sinus rhythm is recommended, which can be performed temporarily by electrical cardioversion or permanently by catheter ablation using pulmonary vein isolation (PVI).2
Atrial fibrillation is associated with many risk factors. Some of them are non-modifiable such as higher age, male gender, length, and genetic inheritance; others are dependent on unhealthy lifestyle habits, such as overweight, smoking, high alcohol intake, physical inactivity, high intensity training, or unhealthy food habits.2 Several comorbidities are associated with AF, for example, diabetes mellitus, hypertension, heart failure, and obstructive sleep apnoea. In the Atherosclerosis Risk in Communities (ARIC) study, hypertensive disease was the most prevalent comorbidity and carried the highest attributable risk (22%) for AF, followed by elevated body mass index (BMI) (13%), smoking (9.8%), and diabetes (3.1%).3 Over 50% of AF cases in a middle-aged population were accounted for by sub-optimal risk factor control.3
As the most prevalent comorbidity, hypertension is a predictor of recurrent AF in long-term follow-up after PVI4 and a target systolic blood pressure of under 130 mmHg is associated with 40% lower risk of incident AF.5 Elevated BMI is the second most prevalent comorbidity, and a recent metanalysis found a 13% excess risk of recurrent AF after PVI per five units of BMI increase.6 Furthermore, the LEGACY trial showed that 10% weight loss in patients with a BMI over 27 was associated with a six-fold greater chance of arrhythmia-free survival.7 The ARREST-AF cohort study underscored how aggressive risk factor management is essential for the long-term success of AF ablation.8 To improve chances of reducing arrythmia burden, the most recent AF guidelines, published in 2020 by the European Society of Cardiology, state that risk factors and comorbidities should be addressed in AF patients.2 Specifically, guidelines recommend addressing modifiable risk factors, namely, hypertension, hyperlipidaemia, hyperglycaemia, obesity, obstructive sleep apnoea, smoking, alcohol, and physical inactivity.2 Lifestyle interventions are often time-consuming, costly, and demand extensive resources, but there is an unmet need to address this, specifically in patients waiting for AF intervention.
Person-centred care can be described as a partnership where healthcare professionals actively listen to and involve the patient in forming a health plan together.9–11 This type of patient involvement has been shown to have many positive effects on physical and mental health as well as healthcare outcomes.9 Through digital self-management, patients can take on a more active role in the care and treatment of high blood pressure.9 Studies highlight the need for systematic integration of person-centred care into clinical practice10 and an interdisciplinary approach.12
This study aims to identify how patients with AF perceived they could be supported by a digital tool aimed to reduce the impact of comorbidities and manage modifiable risk factors associated with an unhealthy lifestyle.
Methods
Study design
This was a qualitative, descriptive study with an inductive approach, based on semi-structured focus group interviews (FGI) that were analysed by manifest content analysis.13,14
Setting and sample
Participants were eligible for inclusion if they had a diagnosis of AF registered in connection to a recent in- or outpatient visit at the hospital’s department of cardiology. Exclusion criteria were living outside of the city, not being able to attend the interview at the hospital, and not being able to speak and understand the language. The participants were contacted by telephone by a medical doctor (S.K.), received information about the study, and asked if they were interested in participating. By criterion sampling, the first 25 patients with the most recent registered in- or outpatient visit that met the criteria were approached. Out of the approached 25 participants meeting the criteria, 13 were men and 12 were women. Nine declined participation with the main reason stated being lack of time.
Data collection
Baseline data regarding age, sex, weight, BMI, diagnosis, symptomatology, and earlier and current treatment were collected from participants themselves and from the medical records. In February of 2022, a total of 4 semi-structured FGI were conducted with a total of 16 participants. Each of the four FGI took about 2 h and included the moderator, the assistant moderator, and three to five participants. The interviews were carried out in a conference room at the research centre at the hospital. All interviews were moderated by last author M.L. He is a registered nurse and has a PhD and many years of experience both as a researcher and within clinical cardiology. The assistant moderator in all interviews was first author S.K. She is a medical doctor and PhD student. None of the researchers had any prior relationship to any of the study participants. Each interview was based on an interview guide (Supplementary material online, Additional File S1) and began with an introduction of the investigators’ name and occupation, the study, and the participants. Then followed discussions on three central themes. First, the participants were asked about their experience with AF and how they wanted information and support regarding their diagnosis. Second, the participants were asked about their individual comorbidities and risk factors associated with lifestyle and how they desired information and support regarding this. Third, the participants were asked how they perceived eHealth and how digital tools could contribute with information and support in a way that suited them. Each interview concluded with a summary and with asking about interest in testing a digital tool, once developed. According to the methodology of content analysis, we aimed for saturation,15 which was reached at four interviews.
Data analysis
The interviews were recorded (audio and visual) and transcribed verbatim, one by the first author S.K. and three by a contracted transcription service in order to be more time-efficient. A descriptive, qualitative content analysis with an inductive and manifest approach according to Graneheim and Lundman was used.13–15 The transcribed interviews were read several times, first generally and then more in-depth, to identify differences and similarities among the participants’ statements. Then followed identification of initial meaning units, condensation (reduction), labelling with codes, and creation of initial categories and sub-categories. This was done separately by the authors S.K. and M.L. and then compared and discussed until consensus was reached. The process was then further discussed with the author C.N. to strengthen he trustworthiness. C.N. is a registered nurse, has a PhD, and has many years of experience conducting qualitative studies with a focus on patients’ perceptions and person-centred care. Discussions were held throughout the process until consensus was reached. An example of meaning units, codes, and categories for the first category person-centred information is shown in Table 1.
Examples of meaning units, codes, and categories related to the category person-centred information
| Meaning units | Codes | Categories |
|---|---|---|
| ‘…there is research saying that …’ | Information | Person-centred information |
| ‘…one can do as much as one wants to…’ | Customized | |
| …so that one can choose…’ | Options |
| Meaning units | Codes | Categories |
|---|---|---|
| ‘…there is research saying that …’ | Information | Person-centred information |
| ‘…one can do as much as one wants to…’ | Customized | |
| …so that one can choose…’ | Options |
Examples of meaning units, codes, and categories related to the category person-centred information
| Meaning units | Codes | Categories |
|---|---|---|
| ‘…there is research saying that …’ | Information | Person-centred information |
| ‘…one can do as much as one wants to…’ | Customized | |
| …so that one can choose…’ | Options |
| Meaning units | Codes | Categories |
|---|---|---|
| ‘…there is research saying that …’ | Information | Person-centred information |
| ‘…one can do as much as one wants to…’ | Customized | |
| …so that one can choose…’ | Options |
Ethical considerations
The study protocol adhered to the Declaration of Helsinki and was approved by the regional ethical review board. Patients provided written informed consent. Signed forms were collected before the interviews. All participants were informed of the premises of the study beforehand, participation was voluntary, and they could at any time choose to discontinue their involvement in the study without having to state a reason for it. A detailed consolidated criteria for reporting qualitative research (COREQ) checklist is provided as a supplement (see Supplementary material online, Additional File S2).
Results
The patients’ characteristics are shown in Table 2. Each participant had a unique background and story of how they had been diagnosed with AF. Individual symptoms varied from light fatigue or dyspnoea during physical activity to completely disabling symptoms hindering almost all daily activities. Many participants mentioned stress as a triggering factor, whilst some had experienced other triggers such as alcohol, lack of sleep, physical activity, and resting after recent physical activity. However, a recurring reflection from the participants was how their AF had a very large impact and caused a great deal of discomfort in their daily lives. Interestingly, we found that only 19% of participants in the study were satisfied with their current level of physical activity and 19% stated that they were satisfied with their current eating habits.
Patient characteristics
| Characteristics | n = 16 |
|---|---|
| Age in years, mean ± standard deviation | 68 ± 8 |
| Male, n (%) | 9 (56) |
| Female, n (%) | 7 (44) |
| Duration of atrial fibrillation in years, mean ± standard deviation | 7.5 ± 7.5 |
| Paroxysmal atrial fibrillation, n (%) | 8 (50) |
| Persistent atrial fibrillation, n (%) | 8 (50) |
| Comorbidities and risk factors | |
| Body mass index in kg/m², mean ± standard deviation | 29.5 ± 4.1 |
| CHADSVASC score, mean ± standard deviation | 3 ± 1.3 |
| Hypertension, n (%) | 14 (88) |
| Diabetes mellitus type 2, n (%) | 3 (19) |
| Heart failure, n (%) | 4 (25) |
| Ischaemic heart disease, n (%) | 2 (13) |
| Current smoker, n (%) | 0 (0) |
| Former smoker, n (%) | 10 (63) |
| Never smoked, n (%) | 6 (38) |
| Alcohol consumption (≥1 unit/week), n (%) | 13 (82) |
| Treatment | |
| Beta-blockers, n (%) | 12 (75) |
| Antihypertensive, n (%) | 12 (75) |
| Statins, n (%) | 10 (63) |
| Digoxin, n (%) | 1 (6) |
| Antiarrythmics, n (%) | 2 (13) |
| Non–vitamin K antagonist oral anticoagulants, n (%) | 14 (88) |
| Warfarin | 1 (6) |
| Undergone ≥ 1 electrical cardioversion, n (%) | 10 (63) |
| Undergone ≥ 1 pulmonary vein isolation, n (%) | 12 (75) |
| Characteristics | n = 16 |
|---|---|
| Age in years, mean ± standard deviation | 68 ± 8 |
| Male, n (%) | 9 (56) |
| Female, n (%) | 7 (44) |
| Duration of atrial fibrillation in years, mean ± standard deviation | 7.5 ± 7.5 |
| Paroxysmal atrial fibrillation, n (%) | 8 (50) |
| Persistent atrial fibrillation, n (%) | 8 (50) |
| Comorbidities and risk factors | |
| Body mass index in kg/m², mean ± standard deviation | 29.5 ± 4.1 |
| CHADSVASC score, mean ± standard deviation | 3 ± 1.3 |
| Hypertension, n (%) | 14 (88) |
| Diabetes mellitus type 2, n (%) | 3 (19) |
| Heart failure, n (%) | 4 (25) |
| Ischaemic heart disease, n (%) | 2 (13) |
| Current smoker, n (%) | 0 (0) |
| Former smoker, n (%) | 10 (63) |
| Never smoked, n (%) | 6 (38) |
| Alcohol consumption (≥1 unit/week), n (%) | 13 (82) |
| Treatment | |
| Beta-blockers, n (%) | 12 (75) |
| Antihypertensive, n (%) | 12 (75) |
| Statins, n (%) | 10 (63) |
| Digoxin, n (%) | 1 (6) |
| Antiarrythmics, n (%) | 2 (13) |
| Non–vitamin K antagonist oral anticoagulants, n (%) | 14 (88) |
| Warfarin | 1 (6) |
| Undergone ≥ 1 electrical cardioversion, n (%) | 10 (63) |
| Undergone ≥ 1 pulmonary vein isolation, n (%) | 12 (75) |
Patient characteristics
| Characteristics | n = 16 |
|---|---|
| Age in years, mean ± standard deviation | 68 ± 8 |
| Male, n (%) | 9 (56) |
| Female, n (%) | 7 (44) |
| Duration of atrial fibrillation in years, mean ± standard deviation | 7.5 ± 7.5 |
| Paroxysmal atrial fibrillation, n (%) | 8 (50) |
| Persistent atrial fibrillation, n (%) | 8 (50) |
| Comorbidities and risk factors | |
| Body mass index in kg/m², mean ± standard deviation | 29.5 ± 4.1 |
| CHADSVASC score, mean ± standard deviation | 3 ± 1.3 |
| Hypertension, n (%) | 14 (88) |
| Diabetes mellitus type 2, n (%) | 3 (19) |
| Heart failure, n (%) | 4 (25) |
| Ischaemic heart disease, n (%) | 2 (13) |
| Current smoker, n (%) | 0 (0) |
| Former smoker, n (%) | 10 (63) |
| Never smoked, n (%) | 6 (38) |
| Alcohol consumption (≥1 unit/week), n (%) | 13 (82) |
| Treatment | |
| Beta-blockers, n (%) | 12 (75) |
| Antihypertensive, n (%) | 12 (75) |
| Statins, n (%) | 10 (63) |
| Digoxin, n (%) | 1 (6) |
| Antiarrythmics, n (%) | 2 (13) |
| Non–vitamin K antagonist oral anticoagulants, n (%) | 14 (88) |
| Warfarin | 1 (6) |
| Undergone ≥ 1 electrical cardioversion, n (%) | 10 (63) |
| Undergone ≥ 1 pulmonary vein isolation, n (%) | 12 (75) |
| Characteristics | n = 16 |
|---|---|
| Age in years, mean ± standard deviation | 68 ± 8 |
| Male, n (%) | 9 (56) |
| Female, n (%) | 7 (44) |
| Duration of atrial fibrillation in years, mean ± standard deviation | 7.5 ± 7.5 |
| Paroxysmal atrial fibrillation, n (%) | 8 (50) |
| Persistent atrial fibrillation, n (%) | 8 (50) |
| Comorbidities and risk factors | |
| Body mass index in kg/m², mean ± standard deviation | 29.5 ± 4.1 |
| CHADSVASC score, mean ± standard deviation | 3 ± 1.3 |
| Hypertension, n (%) | 14 (88) |
| Diabetes mellitus type 2, n (%) | 3 (19) |
| Heart failure, n (%) | 4 (25) |
| Ischaemic heart disease, n (%) | 2 (13) |
| Current smoker, n (%) | 0 (0) |
| Former smoker, n (%) | 10 (63) |
| Never smoked, n (%) | 6 (38) |
| Alcohol consumption (≥1 unit/week), n (%) | 13 (82) |
| Treatment | |
| Beta-blockers, n (%) | 12 (75) |
| Antihypertensive, n (%) | 12 (75) |
| Statins, n (%) | 10 (63) |
| Digoxin, n (%) | 1 (6) |
| Antiarrythmics, n (%) | 2 (13) |
| Non–vitamin K antagonist oral anticoagulants, n (%) | 14 (88) |
| Warfarin | 1 (6) |
| Undergone ≥ 1 electrical cardioversion, n (%) | 10 (63) |
| Undergone ≥ 1 pulmonary vein isolation, n (%) | 12 (75) |
Categories
Seven sub-categories and three categories emerged (Table 3) that described what patients with AF found important in a digital tool aimed to reduce the impact of comorbidities and manage modifiable risk factors associated with an unhealthy lifestyle.
Results: sub-categories and categories
| Sub-categories | Categories |
|---|---|
| Importance of customized information | Person-centred information |
| Information conveyed in an appropriate manner | |
| Provision of practical tips | |
| Support applicable in everyday life | Managing healthy lifestyle habits |
| Support in creating healthy habits | |
| Inspirational reminders | Regular communication |
| Motivational feedback |
| Sub-categories | Categories |
|---|---|
| Importance of customized information | Person-centred information |
| Information conveyed in an appropriate manner | |
| Provision of practical tips | |
| Support applicable in everyday life | Managing healthy lifestyle habits |
| Support in creating healthy habits | |
| Inspirational reminders | Regular communication |
| Motivational feedback |
Results: sub-categories and categories
| Sub-categories | Categories |
|---|---|
| Importance of customized information | Person-centred information |
| Information conveyed in an appropriate manner | |
| Provision of practical tips | |
| Support applicable in everyday life | Managing healthy lifestyle habits |
| Support in creating healthy habits | |
| Inspirational reminders | Regular communication |
| Motivational feedback |
| Sub-categories | Categories |
|---|---|
| Importance of customized information | Person-centred information |
| Information conveyed in an appropriate manner | |
| Provision of practical tips | |
| Support applicable in everyday life | Managing healthy lifestyle habits |
| Support in creating healthy habits | |
| Inspirational reminders | Regular communication |
| Motivational feedback |
Person-centred information
The first category person-centred information recurred throughout the interviews and included the sub-categories customized information, conveyed in an appropriate manner, and practical tips.
The participants agreed on that there is a need for customized information, and they perceived that this is especially important when using a digital medium. Participants wanted information from experts, and it was also brought up that participants would value information from other patients to find out how their experience has been. The participants meant that there is a need for customizing the information to the participants’ different backgrounds, prior knowledge, and predisposition. When discussing providing either very detailed or more general information, there were suggestions that different options should be provided for different patients. There was an agreement on options that would enable those with a greater interest to actively choose to obtain details, for example, about risks and interventions, that others may decline to read if they were more anxious. As one participant suggested regarding adapting the information to the patient:
One could have both options, maybe one could have a link, for those who want more details, click here.
Specifically, there were requests of options to obtain more information about AF, risk factors, triggers, and interventions. Furthermore, participants wanted recommendations on healthy lifestyle, eating habits, physical activity, alcohol, stress, and medication. For example, stress may be a trigger and they described difficulties dealing with stressful work, being in a stressed mode, and difficulties in relaxing. Regarding eating habits and physical activity, they wanted support that would fit their lifestyle and daily routine whilst helping them to stay healthy and be in a good mood. Concerning alcohol, informing about what happens when one drinks to much was desired as well as information about administration of medication for those who wish about the indications, possible interactions, and proper administration of medications.
The participants also brought up how the information needs to be conveyed in an appropriate manner since this determines how it is received. The manner in which information is conveyed encompasses the level and tone as well as characteristics of the medium or person conveying the information. These are all factors that need to be appropriate and adapted to the receiver for it to be taken well. Many participants agreed that there should be no pointing fingers and that information should be put nicely and without being too moralizing. As one patient described regarding the importance of the tone:
It easily becomes somewhat moralizing, and it doesn’t appeal to me.
Some participants described how information in a condescending tone in the past had had a negative effect and how much they would value a sense of care and love in information also from caregivers.
There was also a desire for practical tips that would fit the participants. Although many participants felt that they had heard many recommendations and tips before, they were missing tips on how to implement them. It is important to have tips and recommendations that are practical and realistic and can be implemented in each individual’s daily life. The importance of a range of different practical tips was emphasized, so that each patient could choose what fit them and their lifestyle best. For example, regarding stress, some suggested practical tips on relaxation and breathing. Other major areas where participants wished for practical information were regarding food and eating habits as well as regarding physical activity. There was an example of a well-known celebrity in Sweden doing televised physical activity exercises, whom they considered trustworthy and normal, showing how everyone can do something.
Managing healthy lifestyle habits
The second category managing lifestyle habits was also central and included the sub-categories suggestions being applicable everyday life and help in creating healthy habits.
Central in all interviews was the need for customized information that was not too complicated or time-consuming to be applicable in everyday life. They agreed on that it is very difficult to make major lifestyle changes alone. There is not a lack of knowledge about what should be done, as the participants felt that they had heard the same recommendations from caregivers many times and tried their best to implement them. As one participant described, when previously trying to implement too much too fast, ‘one lasts a week’. Many described having done everything to change their habits but failed after a while. Recommendations are often complicated, expensive, and time-consuming to uphold in the long run in their everyday lives, as one participant summarized:
It is often way too complicated with these apps, the menus are too difficult, it is too expensive, and if I should alone start and buy all the food they recommend, which is often different for each day on these menus, then it becomes too complicated.
As suggested by the participants themselves, it is important for healthcare professionals to be human and realistic.
It was agreed on that behavioural change is extremely difficult and that help in creating healthy habits is something that many wish that caregivers would help with. As participants suggested, it may be good to limit recommendations and focus on a manageable goal, for example, ‘10 good tips’. For example, when being limited by symptoms but being recommended physical activity, there is a need for help and support in how they individually could implement habits adapted to their diagnosis and lifestyle. Many participants also came back to food habits and agreed on that creating habits could be facilitated by, for example, introducing menus and recipes that were reasonable concerning both time and price.
Regular communication
The third category regular communication was another theme throughout the interviews and included the sub-categories inspirational reminders and motivating feedback.
Many participants though that inspirational reminders may be received well and be especially important in a digital tool to improve the user experience. It could be a form of regular interaction which creates a connection with the caregiver. As discussed, they were more likely to exercise or eat well if they received a reminder from their phones. As one participant illustratively described how reminders would aid his eating habits:
If my phone reminded me […] ‘do not open the pantry today’, then of course I would not open it as much, most certainly.
It was also suggested that some need to be reminded about the importance of medications and the positive impact on outcomes to be motivated to continue taking them. It was agreed on that the reminders should not be demanding but rather inspirational and motivating to create positive communication and a sense of teamwork and to have the desired effect.
The importance of motivating feedback was another need that came up consistently in all the interviews, and this is also essential to include in digital communication for user engagement. Many lacked regular communication with caregivers, and only instructions at one time may not help. Instead, support and feedback, either personally or digitally, may create a sense of teamwork and enable participants to implement change. Motivating feedback may, as one participant described, create a motivated sense of empowerment and inspire a sense of:
I think I want to decide this, it is my life, and I have to do it.
It was agreed that feedback should be not judgmental, but motivating, in order to have a positive impact. Regularity was also described as essential to maintain an initial level of motivation.
The results are summarized in Figure 1.
What patients with AF request in a digital tool aimed at optimizations of comorbidities and modifiable risk factors associated with an unhealthy lifestyle.
Discussion
Atrial fibrillation is highly prevalent and causes a substantial utilization of healthcare resources.16 Obviously, despite frequent healthcare encounters, patients in our study perceived the education and advice given in relation to AF as non-sufficient. Surprisingly, only 19% of participants were satisfied with their current level of physical activity and their eating habits. This leaves much to be desired regarding aiding patients with education and support to enable healthy lifestyle habits. The quest for more frequent and individualized information, as expressed by our patients, seems to further increase the demand on healthcare. However, a more person-centred approach, on the other hand, may decrease healthcare utilization by enabling patient empowerment and improving the outcomes of AF treatment. This can be done, for example, as desired by patients and by better management of lifestyle factors and comorbidities. To lower the clinician burden in a more person-centred AF management strategy, digital solutions may play an important role.
Similarly to what we found concerning the need for customized information, one important component of person-centred care is the importance of tailored information with shared decision-making ‘respecting the patient’s information needs and preferences’.17 The participants in our study emphasized how the manner in with information is conveyed can determine how well it is received. Likewise, other studies have described important characteristics of the clinician–patient relationship such as mutual trust, caring, and guidance.17 According to our participants. the mutual trust and care must be conveyed by the wording, tone, and person giving the information and advice, and this can be regarded as an essential part of building a mutual partnership. In addition to this, our participants requested individualized practical tips. This has previously been concluded in a review of digital weight management interventions, namely, that personalization is central to the success of the intervention.18 The review found that patients became frustrated with impersonal and generic recommendations and found that ‘nontailored digital interventions were difficult […] to integrate into their daily routine’.18 All these factors highlight how any information or recommendation needs to be customized and implementation of person-centred care is central to this.
Regarding the management of healthy lifestyle habits and behavioural change, our participants emphasized that recommendations need to be adapted to them and easily applicable in their everyday lives. This relates to understanding the patients’ narrative, as described by Ekman et al., and the impact of the diagnosis on patients’ everyday life.10 Suggested behavioural changes thus need to be agreed on by shared decision-making and be ‘suited to the patient’s lifestyle, preferences, beliefs, values, and health issues’.10 Participants in our study pointed out the need for support from caregivers with behavioural change and creating new habits. For example, behavioural change techniques designed to increase physical activity often include information about health consequences, goal setting, as well as monitoring and support.19 However, the importance of consistent and appropriate measurements is essential to evaluate the effect for individual patients as well as general outcomes.19 A digital tool can be helpful in all these steps, if it is well defined how behaviours such as physical activity are measured. Furthermore, intervention towards desired behavioural change relates to the concept of nudging which incorporates choice architecture interventions to promote behaviour change. A recent meta-analysis only found a small to medium effect size (Cohen’s d = 0.43) of nudging.20 However, they did find that interventions targeting decision structure were more effective than those only targeting decision information or decision assistance.20 Thus, when designing interventions for behavioural change, it may be wise to focus on intervening by minimizing the patients’ effort in choice (such as by suggested or default options), by intervening in the structure of options (range and organization to promote automatic choice), or by focusing on the consequences of a certain choice and thus motivating it.20 These findings are consistent with what the participants of our study themselves suggested in terms of options to choose from and motivating change in behaviour through information and informing of consequences.
The participants of our study agreed on the need for regular communication consisting of both inspirational reminders and motivational feedback. This is in line with a previous review of digital weight management interventions, regular and encouraging feedback was found to be highly valued, and furthermore coaching was found to enhance user engagement.18 An example was given of how text messages were appreciated for ‘clear, practical tips and reminders’ as long as they were not perceived as generic or impersonal.18 Another review on digital interventions on healthy lifestyle management also brought up customized and personalized feedback and coaching as a central feature.21 They identified feedback generation as one of the features responsible for successful implementation of digital interventions.21
Trustworthiness of a qualitative study can be assessed by considering credibility, dependability, confirmability, transferability, and authenticity.13,14 Credibility in this study can be considered high since all included participants have experience related to AF, comorbidities, and risk factors associated with an unhealthy lifestyle. To maintain dependability, and trustworthiness, ongoing discussions were held throughout the analysis process until consensus was reached. The choice of FGI allowed for open discussions considering different perspectives and enabled the exploration of themes, perceptions, and meaning. Thus, this study is person-centred and investigates patients’ own perceptions. Saturation was reached at 4 interviews with a total of 16 individuals, with each interview 90–120 min long, which produced a large amount of material for analysis. As described in the baseline data (Table 2), participants were representative of patients with AF which increases the generalizability of the results.
However, there are also limitations to this study. Although the baseline characteristics may be considered transferable to patients in a Swedish context, it may be lower when considering other countries. Also, although several participants had previously smoked and successfully quit, current smokers were not represented, which may affect the transferability to smokers. Also, a larger sample size may have given more reliable data. Furthermore, only a manifest content analysis was conducted, since the subject matter was not deemed to be very sensitive, and it was considered unlikely that participants had any latent desires or perceptions that they could not express in the setting of FGI. However, there may be latent content and implied meanings that were not identified in the analysis, which would constitute a weakness to the study.
Hopefully, our results can lay the foundation in the development of a digital tool helping patients with AF to optimize treatment of comorbidities and risk factors associated with lifestyle. Future studies should explore what specific features are desirable in a digital tool, test if a developed prototype fits patients’ requirements, and finally investigate if a final product can aid patients with AF in optimizing treatment of comorbidities and risk factors associated with healthy lifestyle habits.
Conclusions
To summarize, there is an unmet need to support patients with AF in optimizing modifiable risk factors. Patients with AF request person-centred information, support in managing healthy lifestyle habits, and more regular communication with caregivers. This study provides a first foundation on how to support AF patients to reduce the impact of comorbidities and manage modifiable risk factors associated with an unhealthy lifestyle. Using a digital tool in standard care for patients with AF may improve outcomes and reduce cost of care.
Author contributions
Sofia Klavebäck: Conceptualization, methodology, validation, formal analysis, investigation, data curation, writing—original draft, writing—review & editing, visualization, and project administration. Emma Svennberg: Conceptualization, methodology, writing—review & editing, visualization, project administration, supervision, and funding acquisition. Carolin Nymark: Validation, formal analysis, writing—review & editing, and supervision. Frieder Braunschweig: Conceptualization, methodology, writing—review & editing, visualization, project administration, supervision, and funding acquisition. Matthias Lidin: Conceptualization, methodology, validation, formal analysis, investigation, data curation, writing—original draft, writing—review & editing, visualization, project administration, and supervision.
Ethics
Approved by the Swedish Ethical Review Authority (Dnr. 2021-05361-01).
Supplementary material
Supplementary material is available at European Journal of Cardiovascular Nursing online.
Funding
This work was partly funded by Innovationsfonden Region Stockholm and research grant from the Swedish Research Council Vetenskaps Rådet (DNR 2022-01466). E.S. is funded by a grant from Region Stockholm (clinical researcher).
Data availability
Not available due to ethical regulations.
References
Author notes
Conflict of interest: E.S. has received speaker/consultancy fees from Bayer, Bristol–Myers Squibb–Pfizer, Boehringer Ingelheim, Johnson & Johnson, and Merck Sharp & Dohme. F.B. has received speaker/consultancy fees from Biotronik, Medtronic, Abbott, Boston Scientific, Boehringer, Novartis, Pfizer, and Orion. M.L. has received speaker/consultancy fees from Pfizer, Eli Lilly, Novo Nordisk, AbbVie, Sanofi, Bayer MSD, and UCB Pharma. For the remaining authors, none was declared.
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