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Patients with heart failure have low quality of life because of physical impairments and advanced clinical symptoms. One of the main goals of caring for patients with heart failure is to improve their quality of life.
The aim of this study was to investigate the effect of the use of a smartphone-based app on the quality of life of patients with heart failure.
This randomized controlled clinical trial with a control group was conducted from June to October 2018 in an urban hospital. In this study, 120 patients with heart failure hospitalized in cardiac care units were randomly allocated to control and intervention groups. Besides routine care, patients in the intervention group received a smartphone-based app and used it every day for 3 months. Both the groups completed the Minnesota Living with Heart Failure Questionnaire before entering the study and at 3 months after entering the study. Data were analyzed using the SPSS software V.16.
The groups showed statistically significant differences in the mean scores of quality of life and its dimensions after the intervention, thereby indicating a better quality of life in the intervention group (
Use of a smartphone-based app can improve the quality of life in patients with heart failure. The results of our study recommend that digital apps be used for improving the management of patients with heart failure.
Iranian Registry of Clinical Trials IRCT2017061934647N1; https://www.irct.ir/trial/26434
Heart failure (HF) is a complex and progressive clinical syndrome that causes functional or structural impairments in the heart and results in impaired ventricular emptying or filling [
Patients with HF may experience a wide range of symptoms, including shortness of breath, cough, swelling of extremities, and fatigue [
To improve patients’ QoL, lifestyle changes should be made. In patients with HF, self-care and treatment adherence are the important parts of disease management [
Adequate self-care behavior is shown to result in reduced risk of hospitalizations and mortality among patients with HF [
Given the increased prevalence of HF and self-care challenges, the use of simple and accessible technologies to support self-care is important [
Use of apps or software on the smartphone can facilitate monitoring of patients’ health through educational messages, audio files, and video clips. Smartphone-based apps have the potential to collect real-time data and graphically draw data for further interactions [
This study was a randomized clinical trial (pretest and posttest with a control group design,
In this study, patients with HF who were admitted to the cardiac care unit were selected using the following inclusion criteria: age of 18-65 years, being literate, class II or III of HF according to the New York Heart Association classification, patients admitted to the hospital due to exacerbation of HF, having a smartphone or a tablet with the Android operating system, and ability to use a smartphone and the app. Patients who met the following criteria were excluded from analysis: unwillingness to continue participation in the study, no use of the app for 1 week (each patient used a one-time password to enter the software), and death.
The sequential sampling method was used. The randomized block method with the ratio of 1:1 and no permutation was used to assign the patients to the groups. Different modes of assignments to the groups were written on 4 cards and placed in opaque envelopes. Next, the envelopes were placed in a box. A research collaborator who was unaware of the assignment process took the envelopes from the box and determined each patient’s place in the groups. This process was continued until the desired sample size was achieved. It should be noted that due to the nature of the intervention, there was no possibility of blinding the subjects. To estimate the sample size at 95% confidence interval, 80% power, assuming that the effect size of the intervention on the QoL in the intervention group compared to the control group would be at least
The process of this study.
Data were collected from the patients’ medical records and through interviews using the demographic data form, health information form, and Minnesota Living with Heart Failure Questionnaire (MLHFQ).
Demographic data form: A researcher-made demographic form was prepared on the basis of literature review. It was completed before the intervention by examining a patient’s medical file and interviewing him/her. The content validity of this form was assessed and approved by an expert panel.
Health information form: This was a researcher-designed form that was prepared on the basis of literature review. This form was completed before the intervention by examining the patient's medical file and interviewing him/her. The content validity of this form was assessed and approved by an expert panel.
MLHFQ: The MLHFQ is the most common tool for investigating the QoL of patients with HF [
An Android-based smartphone app was developed and evaluated [
Features of the interactive Android-based smartphone app.
Patients in the intervention group received the smartphone-based app besides routine care. It was installed on their Android phones, and the patients were taught how to use the program via a 30-minute face-to-face session. The app brochure was also provided to the patients. The method of measuring vital signs, monitoring symptoms, and recording them in the app were taught to patients via the educational content of the app. Every week for 6 consecutive weeks and then every month for about 2 months, notifications were sent to the patients to remind them to use the app. Patients were asked to enter their daily vital signs, symptoms, and weight in the app, which provided the opportunity for health care providers to telemonitor the changes in the data in the text and graph format. In addition, patients could evaluate their daily conditions and its changes by visualizing the recorded data in the shape of a graph. Further, the daily use of the app by the patients was evaluated by the management panel on the internet and encouragements for the use of the app were provided, as needed. Patients and researchers could interact with each other depending on the patients’ needs. During the app usage period (3 months), the patients were supported in terms of how to use the program. To provide support, the researcher’s telephone number was provided to the patients for contact purposes, if needed. The patients in the control group received routine care, which included the provision of a brochure and the method of taking medicines and referral to the doctor at a clinic 2 weeks later. Moreover, the patients in the control group were provided with the smartphone-based app after data collection.
Descriptive statistics (frequency, mean, and SD) were used to analyze the qualitative and quantitative data. The Kolmogorov-Smirnov test was used to assess the normal distribution of the quantitative variables. The two-sided
In this study, data collected from 111 patients were used for the analysis. The groups showed no statistically significant differences before the study regarding demographic characteristics (
Demographic and health information of the patients with heart failure before the intervention.
Variables, subgroups | Intervention group, n=55 | Control group, n=56 | |||
|
.38 | ||||
|
Male | 34 (62) | 30 (54) |
|
|
|
Female | 21 (38) | 26 (46) |
|
|
|
.24 | ||||
|
<40, n (%) | 10 (18) | 7 (13 |
|
|
|
40-49, n (%) | 14 (25) | 12 (22) |
|
|
|
50-59, n (%) | 15 (27) | 12 (21) |
|
|
|
>60, n (%) | 16 (29) | 25 (45) |
|
|
|
Mean (SD) | 50.07 (11.77) | 52.78 (12.2) |
|
|
|
.18 | ||||
|
Elementary to high school | 25 (46) | 35 (63) |
|
|
|
After high school and before entering university | 19 (35) | 15 (27) |
|
|
|
University degree | 11 (20) | 6 (10) |
|
|
|
.18 | ||||
|
Married | 51 (93) | 46 (82) |
|
|
|
Single | 4 (7) | 10 (18) |
|
|
|
.69 | ||||
|
Unemployed | 4 (7) | 7 (13) |
|
|
|
Housewife | 20 (36) | 24 (43) |
|
|
|
Employed | 15 (27) | 13 (23) |
|
|
|
Retired | 4 (7) | 7 (13) |
|
|
|
.31 | ||||
|
Adequate | 19 (35) | 13 (23) |
|
|
|
Somewhat adequate | 20 (36) | 20 (36) |
|
|
|
Not adequate | 16 (29) | 23 (41) |
|
|
Time since diagnosis (years), mean (SD) | 4.52 (4.41) | 4.57 (5.01) | .96 | ||
Body mass index, mean (SD) | 25.96 (3.83) | 25.42 (4.59) | .50 | ||
|
.97 | ||||
|
Yes | 8 (15) | 8 (14) |
|
|
|
No | 47 (85) | 48 (86) |
|
|
|
.36 | ||||
|
No | 17 (31) | 13 (23) |
|
|
|
Yes | 38 (69) | 43 (77) |
|
|
|
|
||||
|
Diabetes | 19 (50) | 26 (61) | .34 | |
|
Hypertension | 28 (74) | 33 (77) | .75 | |
|
Pulmonary disease | 5 (13) | 5 (13) | .71 | |
|
|
||||
|
Yes | 31 (56) | 33 (59) | .12 | |
|
No | 24 (44) | 23 (41) | .11 | |
|
.08 | ||||
|
1 time | 18 (55) | 10 (42) |
|
|
|
2 times | 11 (33) | 5 (21) |
|
|
|
3 times or more | 4 (12) | 9 (38) |
|
|
Ejection fraction, mean (SD) | 29.41 (9) | 29.19 (9) | .90 |
Comparison of the mean scores of the quality of life before and after the intervention between and within the groups.
Parameters, Domain/times | Intervention group, n=55 | Control group, n=56 | Independent |
||||||
|
|||||||||
|
Before, mean (SD) | 18.87 (6.73) | 21.75 (8.76) | 1.937 (109) | .055 | ||||
|
After, mean (SD) | 11.96 (5.44) | 22.71 (8.05) | 8.226 (109) | <.001 | ||||
|
Paired |
7.23 (54) | 2.274 (55) | N/Aa | N/A | ||||
|
<.001 | .03 | N/A | N/A | |||||
|
Changes, mean (SD) | –6.90 (7.08) | 0.96 (3.17) | 7.53 (74.52) | <.001 | ||||
|
|||||||||
|
Before, mean (SD) | 9.26 (5.41) | 10.96 (5.10) | 1.703 (109) | .09 | ||||
|
After, mean (SD) | 4.14 (2.77) | 11.71 (4.80) | 10.149 (109) | <.001 | ||||
|
Paired |
7.26 (54) | 2.803 (55) | N/A | N/A | ||||
|
<.001 | .007 | N/A | N/A | |||||
|
Changes, mean (SD) | –5.11 (5.22) | 0.75 (2.00) | 7.836 (69.27) | <.001 | ||||
|
|||||||||
|
Before, mean (SD) | 14.76 (5.77) | 14.68 (6.29) | 0.072 (109) | .94 | ||||
|
After, mean (SD) | 9.92 (4.21) | 15.7 (5.60) | 6.127 (109) | <.001 | ||||
|
Paired |
5.59 (54) | 2.667 (55) | N/A | N/A | ||||
|
<.001 | .01 | N/A | N/A | |||||
|
Changes, mean (SD) | –4.83 (6.41) | 1.02 (2.86) | 6.228 (74.41) | <.001 | ||||
|
|||||||||
|
Before, mean (SD) | 42.91 (15.62) | 47.42 (16.38) | 1.483 (109) | .14 | ||||
|
After, mean (SD) | 26.03 (9.67) | 50.13 (15.54) | 9.787 (109) | <.001 | ||||
|
Paired |
7.82 (54) | 3.55 (55) | N/A | N/A | ||||
|
<.001 | .001 | N/A | N/A | |||||
|
Changes, mean (SD) | –16.88 (16.00) | 2.71 (5.71) | 8.617 (67.34) | <.001 |
aN/A: not applicable.
Correlation of the mean scores of the quality of life with the demographic and health information of patients with heart failure.
Variables, groups | Quality of life | |||
Mean (SD) | ||||
|
.51a | |||
|
Male | 46.06 (17.56) |
|
|
|
Female | 44.00 (13.95) |
|
|
Age (years) | N/Ab | .74c | ||
|
.76d | |||
|
Elementary to high school | 46.20 (15.69) |
|
|
|
After high school and before entering university | 43.64 (16.06) |
|
|
|
University degree | 44.7 (18.23) |
|
|
|
.08a | |||
|
Married | 52.35 (12.7) |
|
|
|
Single | 44.15 (16.32) |
|
|
|
.48d | |||
|
Unemployed | 50.81 (16.29) |
|
|
|
Housewife | 42.75 (12.9) |
|
|
|
Employed | 45.71 (19.09) |
|
|
|
Retired | 46.29 (17.42) |
|
|
|
.02d | |||
|
Adequate | 40.29 (14.92) |
|
|
|
Somewhat adequate | 43.57 (14.72) |
|
|
|
Not adequate | 50.86 (17.02) |
|
|
Time since the diagnosis (years) |
N/A | .08c | ||
Body mass index |
N/A | .64c | ||
|
.20a | |||
|
Yes | 44.38 (15.83) |
|
|
|
No | 49.98 (17.32) |
|
|
|
.89a | |||
|
No | 45.53 (17.23) |
|
|
|
Yes | 45.06 (15.77) |
|
|
|
<.001a | |||
|
Yes | 38.26 (10.45) |
|
|
|
No | 52.50 (17.78) |
|
|
Ejection fraction |
N/A | .07c |
aIndependent
bN/A: not applicable.
cPearson correlation test.
dAnalysis of variance test.
Results of the two-factor analysis of variance.
Variables, Domain/times | Intervention group, n=55, mean (SD) | Control group, n=56, mean (SD) | Partial eta squared | |||
Group variable | Income | Hospitalization | ||||
|
||||||
|
Before | 18.87 (6.73) | 21.75 (8.76) | 0.066 (0.034) | 0.185 (0.034) | 0.169 (0.025) |
|
After | 11.96 (5.44) | 22.71 (8.05) | 0.000 (0.357) | 0.343 (0.021) | 0.396 (0.007) |
|
||||||
|
Before | 9.26 (5.41) | 10.96 (5.10) | 0.098 (0.027) | 0.213 (0.031) | 0.105 (0.026) |
|
After | 4.14 (2.77) | 11.71 (4.80) | 0.000 (0.473) | 0.088 (0.048) | 0.399 (0.007) |
|
||||||
|
Before | 14.76 (5.77) | 14.68 (6.29) | 0.999 (0.000) | 0.112 (0.043) | 0.315 (0.010) |
|
After | 9.92 (4.21) | 15.7 (5.60) | 0.000 (0.235) | 0.134 (0.040) | 0.614 (0.003) |
|
||||||
|
Before | 42.91 (15.62) | 47.42 (16.38) | 0.146 (0.021) | 0.087 (0.048) | 0.111 (0.025) |
|
After | 26.03 (9.67) | 50.13 (15.54) | 0.000 (0.449) | 0.107 (0.044) | 0.366 (0.008) |
In this study, according to the findings, changes in the QoL score and its dimensions in the intervention group were more than those of the control group, and the effect size of the intervention was high. Therefore, use of a smartphone-based app increased the QoL and its dimensions in patients with HF. It is believed that new technologies such as apps can increase patients’ satisfaction with medical care and improve their relationships with health care staff and subsequently improve their QoL [
Interventions that improve QoL are integral parts of the management of HF [
The smartphone-based app used in our study provides a novel telemonitoring and education method for patients with HF. This study was conducted on those patients who were able to communicate and were literate, with an ejection fraction of less than 45%. For generalizability, similar studies should be conducted in illiterate patients. In this study, the effect of the intervention was studied after 3 months, but the long-term effects of the intervention need to be further researched. In this study, the mediator effects of knowledge and self-care improvement were not evaluated, and therefore, these should be investigated in future studies. Within 3 months of the study process, some medication errors were identified. Therefore, studies should be performed to demonstrate the efficacy of software in improving patient safety and reducing medication errors.
Our study showed that the use of a smartphone-based app increased the QoL of patients with HF. Interventions that improve QoL constitute an integral part of the management of HF, which can be carried out by the health care provider through continuous follow-up of patients using such apps. Nurses as well as patients and their families can use smartphone-based interactive software. Provision of facilities such as counselling centers can provide patients and their families with information about how to use this software to improve their QoL. The results of this research can be considered by nursing managers for patient education. However, it is necessary to study the cost-effectiveness of such interactive software. This method can be used by nurses and other health care providers in HF clinics and heart transplantation centers to improve patients’ and families’ satisfaction with health care, which needs to be further studied in the future.
CONSORT-eHEALTH checklist (V1.6.1).
heart failure
Minnesota Living with Heart Failure Questionnaire
quality of life
The Iran University of Medical Sciences supported this study. All authors of this paper declare their consent to publish this study in this journal. The Iran University of Medical Sciences financially supported this study.
The data, materials, app, and its codes are available. The datasets generated or analyzed during this study are available from the corresponding author on reasonable request.
Study design: MD, TNG
Data collection: MD, TNG, FVA
Data analysis: MD, TNG, FVA
Manuscript writing: MD, TNG, FVA
None declared.