A Pre–Post,Mixed-Methods Study to Pilot Test a Gamified Heart Failure Self-Care Education Intervention

Abstract

Objective:

Self-care is essential to improving heart failure patient outcomes. However, the knowledge and behaviours necessary for self-care decision making, such as symptom perception and management, are complex and require patient education. The objective of this study was to test the feasibility, acceptability, and potential effectiveness of a web-based, gamified heart failure patient education solution, Heart Self-Care Patient Education (HeartSCaPE), that used narrative and virtual reward gamification techniques.

Materials and Methods:

This mixed-methods study used a pre-post-test design with an embedded explanatory qualitative phase. Patients completed the Self-Care of Heart Failure Index, that measured self-care behaviour change and the Dutch Heart Failure Knowledge Scale, used to measure heart failure knowledge. Usability measures of HeartSCaPE were tracked using Google Analytics and the System Usability Scale.

Results:

Nineteen patients completed the study, with a subset of six participating in semi-structured interviews. We found increases in HF knowledge despite high baseline knowledge scores. Post-intervention self-reported HF self-care behaviours (maintenance, management and confidence), as measured by the Self-Care of Heart Failure Index, were also improved. Knowledge and self-care scores were not correlated. Participants also scored HeartSCaPE as highly usable. In interviews, participants described valuing the opportunity to practice self-care decision-making. There were mixed opinions regarding the use of virtual rewards.

Conclusion:

We found that a gamified web-based solution that uses narrative and reward-based gamification techniques has the potential to improve HF patient knowledge and self-care. Further research is needed to confirm the study's clinical benefits and address technology literacy inequities.

Introduction

Heart failure (HF) is a complex, life-limiting disease that for most patients, has a severe impact on quality of life.¹ Globally, HF prevalence is rising, with an estimated 64.3 million people living with the disease worldwide.² HF has the highest 30-day hospital readmission rate of any chronic disease, which drives up health care expenditures.³ Previous research estimates that up to 50% of HF hospital admissions are due to preventable causes.⁴

Many of these preventable causes may be traced to HF self-care, which refers to the process of patients' naturalistic decision making in a real-world setting to maintain physiologic stability through symptom management.^5,6 However, HF self-care is complex, and patients face many barriers to develop adequate self-care.⁷ The Situation-Specific Theory of Heart Failure differentiates HF knowledge and HF self-care skills as distinct but linked through experience with self-care decision making.⁵ Evidence also shows substantial gaps in most patients' HF self-care knowledge demonstrating the need for patient education interventions that allow patients to practice self-care decision making, removed from the stress of a health crisis.^8,9

An emerging trend in education and health-behavior change literature, aimed at increasing patient engagement in education, is the concept of gamification, or adding game design elements to nongame contexts.^10,11 However, rigorous evidence about gamification is limited and little is known about the best gamification techniques since game design elements are highly variable, especially in specific populations, such as people living with HF.^10,12

Of the interventions published in peer-reviewed journals, one platform used a casino slot game and knowledge-testing questions and found improvements in HF knowledge but not self-care behavior.¹³ Other gamified interventions aimed at HF patients have primarily been focused on exercise and behavior tracking, with only some incorporating education elements.^14–17

It is recommended that, when designing a gamified intervention aimed at behavior change, the gamification techniques chosen should be linked to a validated psychological behavior change element.¹² Therefore, we chose to include narrative and rewards gamification techniques, which are linked to action planning and psychological reinforcement.¹⁸ We applied rewards using virtual points linked to time spent on the website and created a narrative using “choose your own adventure” storylines. The first author, (A.L.), carried out the development of the website in collaboration with (K.L.R.) and (M.M.), who are content experts and (K.H.), who is a computer scientist and has expertise in user interface design. The website went through several rounds of iterations among the team to improve its features and usability. We then move to the first phase of website testing by participants where we received feedback from a focus group of experienced HF clinicians.¹⁹

With the increasing need to support patients with HF in their self-care,²⁰ the objective of this study was to test the feasibility, acceptability, and potential effectiveness of a web-based theory-informed, gamified heart Self-Care Patient Education (HeartSCaPE) solution, with the potential to inform a larger trial.

Methods

Study design

We used a mixed-methods, pre–post intervention design with an embedded qualitative element²¹ to assess the impact of HeartSCaPE on participants' HF self-care behaviors and knowledge. Consistent with Creswell & Creswell's explanatory sequential design, we used the qualitative element after the quantitative data collection to understand and explain the quantitative findings. For the qualitative phase, we chose qualitative description for its high applicability to developing clinical interventions.^22,23 Throughout the study phases, we also assessed the usability of HeartSCaPE with a standardized usability scale²⁴ and participants' qualitative feedback.

HeartSCaPE was designed as a web-based solution to offer easy access from both desktop and mobile devices and included seven scenarios that were “choose your own adventure” style. The scenarios covered the basics of HF self-care and asked participants to make decisions as they navigated through the scenario, with different decisions producing different outcomes and feedback given based on decisions (Table 1). There was no minimum time requirement for participants to spend on scenarios or requirement that they complete all seven scenarios, and participants had access to HeartSCaPE for 14 days. We chose 14 days because of the relatively short nature of the intervention, and to avoid study attrition for this pilot study.

Table 1.

Scenario Descriptions

Scenario	Description	Key takeaways (Presented at the end of each scenario and summarized the learning objectives of the scenario. Many learning objectives are repeated for repetition)
Heart Racing	In this scenario, the participant has family visiting for a vacation. As they move through the scenario, they have an episode of atrial fibrillation (heart racing) and have to make decisions about whether to call an ambulance.	• Swelling in the legs is a sign of worsening HF. • Swelling legs is caused by the extra fluid that stays in the body. • Try and break up the activities of the day with regular rest breaks to manage fatigue. • A racing heart could be a sign of a heart problem called an arrhythmia. If your heart is racing, you should seek medical attention. • HF patients should restrict fluids as directed by their health care provider—You should be tracking how much you are drinking on a daily basis.
Heart Racing Example screenshot

What is HF?	In this scenario, there is an upcoming appointment with a HF specialist nurse. During this scenario, the participant has to decide what questions they want to ask the nurse. They also learn about the causes of HF.	• HF is a complex disease and there's a lot to learn. • Two common causes of HF are high blood pressure (hypertension) and heart attack (myocardial infarction) • The heart's main function is to pump blood around the body • HF means that the heart is weakened in some way and is having trouble pumping blood out to the body • It is important for patients to regularly check if their body is retaining extra fluid
What is HF? Example screenshot

Out to Dinner	The participant has been invited to a friend's birthday dinner. They recently had an appointment with a dietician and are adjusting to making dietary changes for their HF. In this scenario, they also have to manage a HF exacerbation after noticing a sharp increase in their weight.	• HF patients should follow a low-salt diet. Extra salt can make your body retain fluid. • Water pills (diuretics) are commonly prescribed medications for HF patients to reduce extra fluid in the body. • Leg swelling in HF is caused by fluid building up in the leg. • Patients with HF should weigh themselves each day.
Out to Dinner Example screenshot

Going Home	After a recent hospitalization for HF, the participant is discharged home with a new list of medications. The participant must make decisions about some confusion related to new medications. They also have to manage a HF exacerbation after having a new onset of shortness of breath.	• Ask for clarification if you're not sure why you are taking a medication. • Take medications as prescribed. • Shortness of breath is a sign of worsening HF. • Avoid taking diuretics (water pill) in the evening to avoid having to get up during the night to go to the bathroom. Try taking the evening dose in the mid-afternoon. • Attending follow-up appointments is important even if you are feeling well.
Going Home Example screenshot

Get Moving!	The participant is starting a new exercise program after a recent diagnosis of HF. In this scenario, they learn about the benefits and safety of exercising with HF. During the scenario, they have to manage an episode of dizziness during an exercise session.	• The heart's main function is to pump blood around the body. • The heart is a muscle that can be strengthened through exercise. • It is important to exercise regularly. It is also important to take regular breaks. • Start slowly with exercise programs and increase the length of time and intensity of exercise gradually. • Ask a friend or family member to join you if you're worried about feeling dizzy or chest pain.
Get Moving! Example screenshot

Achoo!	During this scenario, the participant is asked to babysit for a neighbor. Unfortunately, one of the children gets sick, and the participant has to decide if they will still babysit. In this scenario, participants also learn about the importance of vaccinations and how to manage HF when sick.	• You should avoid people who are sick. • It is important to keep your vaccinations up to date. • Do not stop taking medication if you are sick. • Check-in with your family doctor if you're sick. • HF patients should restrict their fluids as directed by their health care provider. • A cold or flu can cause a rapid worsening of HF symptoms.
Achoo! Example Screenshot

The Camping Trip	On a camping trip, the participant forgets some of their HF medications at home and must decide what to do. They also learn about managing their fluids and diet throughout the scenario.	• People with HF should weigh themselves each day. • It is important for patients to regularly check if their body is retaining fluid by checking for marks from socks or shoes or visible swelling of the feet and ankles. • HF patients should keep track of the fluid they drink as directed by their health care provider. • If you have increased shortness of breath or swelling in your legs, you should contact your health care provider. • If you gain 4 pounds (2 kg) in 2–3 days or 5 pounds (2.5 kg) in a week you need to contact your doctor or nurse.
The Camping Trip Example screenshot

HF, heart failure.

Sample and setting

We used Qualtrics software²⁵ to collect patient consents and quantitative data. (A.L.) collected consent from participants. We included English-speaking adults who were diagnosed with HF and had basic computer skills. We excluded participants who had an acute mental illness, substance use disorder, palliative care goals, lacked consistent access to a computer or mobile device, or lacked the cognitive ability, dexterity, or vision necessary to navigate a computer independently. We recruited participants through both an urban, hospital-based HF clinic in BC, Canada, and through social media channels. Clinic nurses screened patients attending the clinic for exclusion criteria before referring them to the study team. Participants recruited online were screened by a study team member (A.L.). While there is no consensus on recommended pilot study size, a range of 10 per group to 60 per group has been suggested, and we aimed for 20 participants.²⁶ We obtained ethics approval for this study through harmonized review by a western Canadian University and regional health authority (Certificate No.: H20-02390).

Quantitative phase

Measures

Participants completed all questionnaires online from their personal computers. Participants completed baseline quantitative measures at the time of study consent before using HeartSCaPE. We assessed change in knowledge using the Dutch Heart Failure Knowledge Scale, which is valid and reliable in measuring improvements in HF self-care knowledge.^27,28 The scale includes 15, self-administered multiple choice questions, for a total score out of 15, with higher scores representing better knowledge.²⁷ The construct validity of the Dutch knowledge scale has been tested by comparing newly diagnosed HF patients without education to those who had received HF education, which the scale consistently differentiates.²⁷

Behavior change was measured using the Self-Care of Heart Failure Index (SCHFI). The SCHFI is a 22-item scale that measures HF self-care maintenance and management behaviors and self-care confidence with higher scores indicating better self-care. Its authors recommend reporting changes in individual SCHFI variables rather than a total score, to facilitate more meaningful interpretation.²⁹ Each of the three scores is standardized to a score of 100, with a possible range of 0–100. Scores ≥70 are associated with adequate self-care.²⁹ The SCHFI has been used widely with HF patients at all stages of the disease and in multiple contexts and has been shown to be valid and reliable.^29–32

We also assessed HeartSCaPE's usability with the System Usability Scale (SUS), the most widely used usability scale. The SUS is a list of 10 items that participants rate on a Likert scale from strongly agree to strongly disagree designed to test perceived usability of websites. Possible scores range from 0 to 100, then the score is converted to a percentile or letter grade. The SUS has excellent reliability and concurrent validity with other measures of perceived and objective usability such as the Metric for User Experience and successful task completion.^24,33

After baseline surveys were completed, we emailed participants deidentified login information to access HeartSCaPE. We used these deidentified participant IDs and Google Analytics data to track the time spent on HeartSCaPE and the scenarios that were completed. We used a “how-to” video on the homepage that included a screen share of a study team member using the website to familiarize participants with the website.¹⁹ Participants were otherwise required to be independent in navigating the website. At the end of the 14 days, we asked participants to repeat the SCHFI and Dutch knowledge scale and to complete the usability scale.

Data analysis

Data analysis was completed using SAS version 9.4.³⁴ Demographic data and website usage were summarized using descriptive statistics. We also assessed for differences in website use and usability between demographic groups of sex, age, and education level. We calculated the mean change and 95% confidence intervals (CIs) for total HF knowledge and HF self-care behavior scores following the intervention. We used Cohen's d_av, a variation of Cohen's d used for within-subject designs, to estimate the effect size of the intervention on behavior and knowledge scores.³⁵ Finally, we performed Pearson's correlation to explore associations between knowledge and self-care behavior scores.³⁶

Qualitative phase

Data collection

We sought qualitative feedback by inviting a subset of participants who completed the quantitative phase of the research to participate in semistructured interviews (interview guide in Supplementary Data). We selected participants for variability in age, sex, and amount of HeartSCaPE use. Interviews were conducted over the telephone by (A.L.) and were subsequently transcribed verbatim. Interview questions focused on participants' overall experience, HeartSCaPE usability, elements of gamification, motivation to use HeartSCaPE, and behavior change.

Data analysis

We used semantic and inductive thematic analysis to analyze the qualitative data.³⁷ Data analysis involved a theory-naive perspective because we were interested in the overall experiences of participants and the insights they offered to help explain the quantitative results. Using a semantic approach, we identified themes from the explicit language used in the data and aimed to keep themes close to the participants' original language.^23,37 Two team members (A.L. & K.L.R.) initially coded the transcripts using NVivo,³⁸ then common themes were clustered. Final theme names were created through consensus.

Results

Sample characteristics

We recruited 23 participants, 4 of whom were lost to follow-up, leaving 19 participants who completed the study. Seven of the 19 participants were recruited from the clinic. Of the four who were lost to follow-up, two completed consent only and two completed only baseline measures but never logged into the website. Baseline participant demographics are listed in Table 2. Participants were an average of 63.3 (standard deviation [SD] = 14.5) years old and predominantly female (57.8% vs. 42.1%), with a mean time since HF diagnosis of 9 months (range 2–156). The highest number of reported comorbidities was seven, with all except three participants reporting at least one comorbidity in addition to HF.

Table 2.

Sample Characteristics

	All (n = 19)	Female (n = 11) (57.8)	Male (n = 8) (42.1)
Age, years, mean (SD)	63.3 (14.5)	66.4 (8.7)	59 (19.8)
Marital status (%)
Widowed	3 (15)	3 (27.3)	0 (0)
Single	3 (15.8)	2 (18.2)	1 (12.5)
Separated	1 (5.3)	0 (0)	1 (12.5)
Married or remarried	10 (52.6)	5 (45.5)	5 (62.5)
Divorced	2 (10.53)	1 (9.1)	1 (12.5)
Race/ethnicity (%)
Asian	2 (11.1)	0 (0)	2 (25)
Caucasian	16 (84.2)	11 (100)	5 (62.5)
Not answered	1 (5.30	0 (0)	1 (12.5)
Level of education (%)
More than high school	14 (73.7)	7 (63.6)	7 (87.5)
High school or less	5 (26.3)	4 (36.4)	1 (12.5)
Living arrangements (%)
Lives alone	6 (31.7)	4 (36.4)	2 (2)
Lives with children	1 (5.3)	1 (9.1)	0 (0)
Lives with other family	3 (15.8)	2 (18.2)	1 (12.5)
Lives with partner	9 (57.4)	4 (36.4)	5 (62.5)
Country of residence (%)
Canada	11 (57.9)	5 (45.5)	6 (75)
New Zealand	2 (10.5)	1 (9.1)	1 (12.5)
United Kingdom	2 (10.5)	1 (9.1)	1 (12.5)
United States	4 (21.1)	4 (36.4)	0 (0)
Self-reported number of comorbidities, mean (SD)	2.6 (1.9)	2.5 (1.6)	2.6 (1.9)
Self-reported chronic health problems (%)
Hypertension	9 (40.9)	7 (63.6)	2 (25)
Coronary heart disease	9 (40.9)	6 (0.24)	2 (25)
Arthritis	6 (27.3)	4 (36.4)	2 (25)
Diabetes	5 (22.7)	3 (27.3)	2 (25)
Atrial fibrillation	4 (18.2)	4 (36.4)	0 (0)
Valvular heart disease	3 (13.6)	2 (18.2)	1 (12.5)
Stroke	3 (13.6)	3 (27.3)	0 (0)
Sleep apnea	2 (9.1)	1 (9.1)	1 (12.5)
Thyroid disease	2 (9.1)	2 (18.2)	0 (0)
COPD	1 (4.5)	0 (0)	0 (0)
Cancer	1 (4.5)	0 (0)	1 (12.5)
Other	9 (40.9)	4 (36.4)	5 (62.5)
Self-reported time since HF diagnosis, months, median (IQR)	24 (5.5, 72)	9.5 (3.3, 60)	36 (6.3, 66)
Medications per participant, mean (SD)	5 (1.5)	4.5 (1.5)	5.5 (1.5)
Medication (%)
Anticoagulants/antiplatelets	11 (57.9)	8 (72.7)	3 (37.5)
Antihypertensives	14 (73.7)	9 (81.8)	5 (62.5)
Diuretics	9 (47.4)	6 (54.5)	3 (37.5)
Beta blockers	12 (63.2)	9 (81.8)	3 (37.5)
Antiarrhythmics	7 (36.8)	4 (36.4)	3 (37.5)
Statins	10 (52.6)	7 (63.6)	3 (37.5)
Other	5 (26.3)	3 (27.3)	2 (25)
Self-reported hospital admission in the last year (%)
None	10 (52.6)	5 (45.5)	5 (62.5)
One	7 (36.8)	5 (45.5)	2 (25)
Two	1 (5.3)	1 (9.1)	0 (0)
Three	1 (5.3)	0 (0)	1 (12.5)
Self-reported average length of hospital admission %
<5 Days	3 (15.8)	1 (9.1)	2 (25)
>5 Days	8 (42.1)	5 (45.5)	3 (37.5)
Not applicable	8 (42.1)	5 (45.5)	3 (37.5)
Self-reported overall health (%)
Poor	2 (10.5)	0 (0)	2 (25)
Fair	10 (52.6)	7 (63.6)	3 (37.5)
Good	7 (36.8)	4 (36.4)	3 (37.5)
Self-reported mental health (%)
Fair	8 (42.1)	5 (45.5)	3 (37.5)
Good	9 (47.4)	5 (45.5)	4 (50)
Excellent	2 (10.5)	1 (9.1)	1 (12.5)

COPD, chronic obstructive pulmonary disease; IQR, interquartile range; SD, standard deviation.

HeartSCaPE use and usability

The number of sessions per user ranged from one to seven throughout the 2-week intervention period, with an average session duration of 13:57 minutes and 11 page views. Thirteen (68.4%) participants visited four or more scenarios. Participants scored HeartSCaPE usability at 79.36/100. Male participants, participants with high school or less education and participants older than 70, on average had longer total website use time. Participants older than 70, participants with more than a high school education and participants who were male, on average scored the website higher on the usability scale (Table 3).

Table 3.

Website Use and Usability by Demographics

	Total website use, minutes, mean (SD)	Total website use, minutes, Mdiff	SUS score, mean (SD)	SUS score, Mdiff
Total sample	31.33 (28.53)		79.36 (18.63)
Age
≤70	27.22 (19.97)	8.8	72.83 (17.22)	12.42
>70	36.02 (37.50)		85.25 (18.69)
Education
≤High school	42.28 (40.41)	14.59	73.13 (24.54)	7.90
>High school	27.68 (24.11)		81.03 (17.41)
Sex
Female	24.12 (21.49)	18.02	77.50 (21.82)	4.44
Male	42.15 (35.52)		81.94 (14.11)

≤High school = education of high school or less.

>High school = more than high school education.

Mdiff = mean difference; SUS, System Usability Scale.

Knowledge and self-care behavior change

Table 4 shows the mean change and 95% CIs for change in knowledge and self-care behavior scores from baseline to follow-up. The average baseline knowledge score was 12.79, SD (1.18). The total knowledge scores increased, mean difference = 0.77, [95% CI 0.02–1.35], and d_av = 0.57. However, all of the individual HF knowledge variables had CIs that crossed zero, except for the knowledge variable of HF symptoms/symptom recognition (Table 4). There were increases in mean scores for all three self-care variables, with no CI crossing zero. Self-care score effect sizes ranged from d_av = 0.46 (maintenance) to d_av = 0.74 (management) (Table 4). Furthermore, there was an increase in the proportion of participants with an average SCHFI score above the adequate self-care cut point. At baseline (6/19 = 31.58%), participants had an average SCHFI of ≥70, and at follow-up (13/19 = 68.42%), participants had an average SCHFI of ≥70. There was no significant correlation between change in knowledge score and change in behavior score (r = 0.07, P = 0.61).

Table 4.

Knowledge and Self-Care Behavior Change

Variable	Time		Change (mean)	95% CI	d_av
Variable	Baseline, mean (SD)	Post, mean (SD)	Change (mean)	95% CI	d_av
Dutch Heart Failure Knowledge Scale
Total score	12.79 (1.18)	13.47 (1.22)	0.77	0.02 to 1.35	0.57
HF symptoms/symptom recognition	4.58 (0.61)	4.95 (0.23)	0.37	0.04 to 0.70	0.88
HF in general	3 (0.75)	3.11 (0.88)	0.11	−0.28 to 0.5	0.13
HF treatment	5.21 (0.85)	5.53 (0.7)	0.32	−0.11 to 0.74	0.41
Self-Care of Heart Failure Index
Maintenance	75.03 (18.27)	83.14 (17.31)	8.01	2.13 to 14.09	0.46
Management	46 (26.01)	63.5 (20.96)	17.5	6.31 to 25.51	0.74
Confidence	55.01 (17.77)	65.68 (18.69)	10.67	4.21 to 17.12	0.59

CI, confidence interval; d_av, Cohen's d_av.

Qualitative results

Six participants agreed to interviews, and most were female (n = 4), with ages ranging from 40 to 79 years. The median length of time since HF diagnosis for those participating in interviews was 66 months, with an interquartile range of 26–120 months.

HeartSCaPE usability and content

Participants generally found HeartSCaPE easy to use, except for one participant who expressed more difficulty. Participant 15 said, “If you've ever touched a computer before, the website was very easy to navigate.” Participants also talked about the basic nature of the content. Participant 16, who was diagnosed with HF 11 months prior, elaborated: “It wasn't too much. It was just challenging enough. You know how do you say it? TMI? Sometimes with that, you just zone out. And I didn't feel that tendency to zone out.” Even those participants who found some of the content a review described it as valuable, as Participant 19 highlighted. “For people that are brand new, this might be wonderful for them. If they're open to it. You know so many people are shell-shocked by the whole process.”

Behavior change

The challenge of adopting behavior changes and engaging in self-care was a prominent theme in the interviews. Participants described multiple barriers to self-care, such as caretaking for a partner with dementia, work obligations, and feeling dismissed by health care providers. As described by Participant 16: “Everybody wants to prevent further complications, but the work of doing it is hard.”

Participants also described experiencing uncertainty in their decisions, particularly regarding acute events. Participant 6 described an event of new-onset chest pain. “We're trying to figure out how bad it is. My wife said, ‘Do you want me to call?’ And I was like, ‘No. I'm all right for the moment. I think?’ (laughs).” The wife and caregiver of participant 5 discussed her husband's recent hospital admission: “Maybe that step could have been averted somewhere in between there? If he had, you know, knew enough to say, ‘Should I call right now?’ ”

Despite their high baseline knowledge, some participants described the opportunity to practice decision making as valuable and talked about knowledge and behavior as two distinct concepts. For example, Participant 6 described how completing a scenario caused her to reevaluate her self-care behavior.

It would certainly make me think about it when I might not have otherwise… You know, I tend to have a bit of chest pain, but it's usually gone pretty quick. So, I thought about it, and I did reach out to my doctor.

Gamification

Participants identified that narrative gamification was a strength of HeartSCaPE. Participant 6 said, “I liked the choices, [it] was probably the thing that I liked the most about it.” Participant 5 described how scenarios allowed for decision-making practice: “You know, you can kind of put yourself in those shoes… like this could be a real-life situation.”

Participants also appreciated the nonconfrontational nature of the scenarios. Participant 16 said, “I thought that the format was good because it eased my need to be defensive or already make excuses for myself.” This participant elaborated: “People get weary. Weary of listening to education, but to be able to make it palatable. It's so important.”

The participants identified some risks of gamification, such as pressure to pick the “right” answers: “A lot of people might know what answer they should pick. It might not necessarily be what [they] would do” (Participant 5). Furthermore, there was mixed support for using virtual rewards as a technique of gamification. Some participants were strongly in favor: “You know, we don't always pat ourselves on the back. So, when there's a virtual patting on the back, it feels good” (Participant 16). On the other hand, some thought the rewards did not add any value: “I didn't really care. I'm not a stick and the carrot kind of person. Yeah. I mean, some people find that useful, not me” (Participant 19).

Discussion

In testing HeartSCaPE, we found improvements in both knowledge and behavior change after 2 weeks of HeartSCaPE use. As recommended for pilot studies, we did not perform formal hypothesis testing for intervention effectiveness, but instead examined the magnitude of effect.³⁹ We found a moderate effect on knowledge of HF (Cohen's d_av = 0.57) and self-care behavior (Cohen's d_avs ranging from 0.46 to 0.74). There was no significant correlation between knowledge increase and behavior change in the sample. However, since this was a pilot study, these results are preliminary, and a more extensive study is needed to confirm these results. Explanatory qualitative interviews supported the quantitative results, with participants describing the value of practicing self-care decision making, as offered through the scenarios.

Participants varied in degree of intervention completion. We did not use reminders to participants to finish scenarios, since a key reason for using gamification was to increase participant motivation to engage in education materials.¹⁰ Overall, participants scored the website in the 85–89th percentile of the SUS, assigning it a usability score of an A-.²⁴ Therefore we do not believe usability was a significant barrier to results.

Baseline knowledge scores were high compared with other studies reporting preeducation knowledge scores, not unexpected since those who had received previous HF self-care education were included.^40,41 Despite the high baseline knowledge scores, the increased knowledge scores postintervention reflect that the gamified approach contributed to knowledge gains. Additionally, self-care behavior improved after just 2 weeks, perhaps related to the psychological behavior change elements of the chosen gamification techniques.¹⁸ Moreover, the SCHFI score increases (Table 4) for all three self-care variables were above the 8-point increase the authors of the scale consider clinically relevant. Although the authors did not expand on what clinical outcomes they would expect to change with this self-care improvement, recent work has shown a link between improved self-care and reduced overall mortality.^29,42

We found no significant correlation between knowledge and behavior scores. Rather than suggesting that knowledge is unrelated to self-care, we propose that the high baseline knowledge indicates that participants already possessed most of the knowledge necessary to perform adequate self-care. Jaarsma and Strömberg⁴³ made a similar argument that knowledge alone is not enough to improve HF self-care behavior, based on the “Middle Range Theory of Self-care in Chronic Illness.”^6,44

The Situation-Specific Theory of Heart Failure Self-Care discusses how processes (experience, skills, knowledge, or values) impact the three HF self-care variables of maintenance, symptom recognition, and management.⁵ Self-care self-efficacy mediates the relationship between predictors of self-care and self-care behavior or outcomes and is influenced by experiential learning.⁵ Therefore, simulating decision making through scenario-based education may increase self-efficacy, which could explain the improved self-care scores in our sample.

Our results align with previous studies that have examined digital HF interventions. A recent meta-analysis examined mobile digital health interventions to manage cardiovascular diseases, including HF. Indraratna et al. found that mobile interventions were associated with significantly lower rates of hospitalization (n = 1595; odds ratio 0.77, 95% CI: 0.62–0.97). Similar to Radhakrishnan et al.,¹³ we found that participants were accepting gamified HF education, and many reported that they enjoyed learning through games. Radhakrishnan et al's game prototype was based on a casino slot game that used knowledge-testing questions,¹³ rather than storylines to deliver education.

While some of our scenarios repeated learning outcomes, scenario storylines were varied to maintain participant attention. Our results show that participants were engaged by the website. The average session duration of 14 minutes was further corroborated with participant support in our qualitative data. Other gamified interventions have used multimodal gamification techniques such as linking activity trackers and weight tracking to the intervention.^16,17 While feasibility and acceptability studies have shown initial support of these interventions,¹⁶ in this study we show that additional technology and monitoring may not be necessary to create behavior change.

Limitations and recommendations for future work

This study has some limitations. Participants self-selected and were required to have basic skills to navigate a computer independently and therefore may have been more motivated to partake in self-care. Since some computer literacy is needed to use this intervention, there is also the risk that the intervention may increase the health equity gap. The lack of a control group that received nongamified education and our reliance on self-reported behavior limit the strength of conclusions that we may draw. Finally, the small sample size, which aligns with our pilot study objective of assessing feasibility, limits the generalizability of our findings. Future research in a larger trial might also include testing against a nongamified intervention as an active control group. Finally, increasing the follow-up period and measuring clinical outcomes such as hospital admissions would increase evidence of the long-term impact of using HeartSCaPE.

Conclusion

This embedded mixed-methods study found that a web-based, gamified HF education solution that uses narrative and reward-based gamification techniques has the potential to improve HF knowledge and self-care. This study extends previous evidence that patient education should be theory based, engaging, and patient centered. However, further research is needed to address the accessibility inequities, such as those faced by patients with limited computer literacy or vision impairments. More evidence is also needed on the long-term impacts of gamified patient education and how to sustain behavior change.

Footnotes

Acknowledgment

The authors would like to thank all of the participants who took part in this study. This research would not have been possible without their generosity with their time.

Authors' Contributions

A.L.: conceptualization (lead); writing—original draft (lead); formal analysis (lead); and writing—review and editing (equal). M.M.: Supervision (equal); and review and editing (equal). K.H.: Supervision (equal); and review and editing (supporting). K.R.: Supervision (lead); and review and editing (equal).

Author Disclosure Statement

No competing financial interests exist.

Funding Information

The first author received the CIHR Canada Graduate Scholarships—Master's program scholarship #24894 in support of this project.

Supplementary Material

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