The impact of using a mobile application to improve asthma patients’ adherence to medication in Jordan

Abstract

The main aim of this study is to assess the effectiveness of using a developed asthma mobile application to enhance medication adherence in Jordan. Asthma patients visiting outpatient respiratory clinics and using inhalers were recruited. Patients were assigned into two groups: intervention and control. The intervention group was instructed to download and use the application. Asthma control was assessed using Asthma Control Test (ACT) at baseline and at follow-up of 3 months for both groups. A total of 171 patients (control, n = 83, and intervention, n = 88) participated in the study. After 3 months of usage, patients in the intervention group achieved a significant improvement in ACT score compared to control (p-value <0.05), and reported a significant satisfaction of the application use. Therefore, the asthma mobile application is found as an effective tool to enhance medication adherence in asthma patients.

Keywords

Asthma ACT Medication adherence Mobile application Technology adoption

Introduction

Asthma is a chronic inflammatory disease that affects the airway of the lungs. It is very common and affects people of all ages.^1,2 Globally, asthma has affected >339 million individuals and caused around 417,918 deaths per year.^3,4 In Jordan, a low-resource country, asthma prevalence is high and has been doubled in the last decade.⁵ There is no complete cure for asthma; therefore, the achievable goal of asthma management is to relieve symptoms, decrease the disease progression, and enhance patients’ quality of life.⁶ This can be achieved by avoiding triggers such as dust and pollen and using inhaled medication.⁶ Inhalers are devices that contain drugs which either relax the airway muscles and/or reduce inflammation in the lungs.^2,6 The use of inhaler devices is challenging for most of the patients, in particular, metered-dose inhalers (MDIs) and powder inhalers (DPIs).^7,8 However, incorrect inhalation technique and frequent misuse of inhalers would lead to treatment failure and poor asthma control.^9,10

Mobile health applications (mHealth apps) are innovative digital interventions that have been developed as an easy and viable way to provide patients and health care providers with a wide range of information to manage various conditions, including chronic diseases.^11
–13 Such applications can deliver automated summary reports of patients’ conditions to health care providers and promote adherence to medication regimens.^14
–16 A systematic review analysis investigating the impact of mHealth apps on self-management outcomes in asthmatic patients, showed that mHealth apps improved asthma control and lung function and enhanced patients’ quality of life.¹⁷ In addition, the use and effectiveness of mHealth apps in different age groups of asthmatic patients were investigated and showed promising results, such as enhancing medication adherence and self-management.^18
–21 These findings highlight the importance of this technology in supporting the existing clinical health care in asthma management and medication adherence.

Studies have shown that asthma control is poor among the Jordanian population,^10,22 and this was attributed to multiple factors, including the poor inhalation techniques and the incorrect use of devices.^22,23 Interestingly, no previous studies have investigated the use of mHealth technology to promote adherence to the correct use of inhaler devices and asthma self-management among Jordanians. The current study aimed to explore and assess Jordanian asthmatic patients’ knowledge and attitude and design preferences toward using the mHealth app to enhance adherence to the correct use of inhaler devices and asthma self-management. In addition, the study aimed to design an accessible and culturally appropriate mHealth app and to evaluate its usability and satisfaction.

Methods

Study design, sitting, and patients

This prospective interventional study was conducted over a period of 9 months at the outpatient respiratory clinics of the Jordan University Hospital (JUH), Amman, Jordan. The study was carried out according to the Declaration of Helsinki. The study design and protocol were approved by the Institutional Review Board (IRB) at the Deanship of Scientific Research, The University of Jordan, and JUH, reference number (80/2018/1358). Asthmatic patients using inhalers and who visited the respiratory clinics were recruited. Patients were assigned into two groups: intervention and control. Patients who had a smart mobile phone and were willing to participate and download the mHealth app were included in the intervention group. While those who were willing participate but did not have a smart mobile phone or did not wish to download the app were included in the control group. All patients were asked to sign an informed consent form before filling out a paper-based questionnaire and downloading the app on their smartphones. Patients were informed that data and personal information collected as part of the study were going to be treated as confidential. The inclusion criteria were: patients aged at least 18 years, diagnosed with asthma for at least 6 months, have been using controller inhaler devices for a minimum of 1 month before study recruitment. A follow-up after 3 months was considered.

A total of 190 patients were recruited and agreed to participate in the study. Patients were divided into 102 in the intervention group and 88 in the control group. Of the total, 171 patients (88 in the intervention group and 83 in the control group) completed the study. There was 10% drop-out rate (n = 13 were lost from follow-up, n = 3 died, and n = 3 did not use the app after downloading it). A flow chart of patients’ recruitment is shown in Figure 1.

Figure 1.

Flow chart of patients’ recruitment. A total of 190 asthmatic patients were approached to participate in the study. About 102 patients in the intervention group and 88 in the control group. At the end of the study, 13 patients were lost from follow up, 3 died, 3 did not use the application, and 171 patients successfully completed the study.

The questionnaires

All patients’ data were collected at baseline using a developed questionnaire consisting of three main domains; the first domain had 12 items regarding patients’ demographics and information about asthma and medication use. The second domain included eight items to assess patients’ knowledge and experience with smartphones and health technology aids. The third domain consisted of six items to explore patients’ attitude toward using mHealth app to enhance medication adherence. Likert scale (strongly agree, agree, neutral, disagree, and strongly disagree) was used to evaluate patients’ attitude toward using the mHealth app. This questionnaire was developed and designed based on an extensive literature review.^{13,18,20,24
–27}

Asthma control for patients from both intervention and control was assessed using Asthma Control Test (ACT). The ACT is a validated patient-based tool that is usually used to evaluate asthma control in clinical practice.^22,28,29 It is recommended by the American Thoracic Society/European Respiratory Society Task Force as an assessment tool of asthma control.³⁰ It is a questionnaire consisting of five questions; four of them are related to symptoms and use of relievers and one question is about patient self-assessed level of control.^28,29,31 ACT reflects asthma patients’ status during the last 4 weeks using a total score ranging from 5 to 25, with higher scores indicating a better asthma control.^22,29 Asthma patients who had scores between 20 and 25 were classified as well controlled; 16–19 as partially controlled; and 5–15 as poorly controlled.³¹ In this study, a validated Arabic version of the ACT test was used.³² ACT was calculated for all recruited patients at baseline and at follow-up after 3 months.

Patients in the intervention group were asked to download the app and notified to use it via a weekly notification. In addition to ACT scores, patients in the intervention group were asked to fill a questionnaire assessing and scoring their satisfaction with the app (i.e. ease of use, information, usefulness for asthma) at follow-up. This custom questionnaire was modified from previously published mHealth App Usability Questionnaire (MAUQ) and satisfaction questionnaires,^19,33,34 which have the reliability and validity required to assess mHealth app usability. In fact, in this study the commonly used questionnaires such as System Usability Scale (SUS) and Post-Study System Usability Questionnaire PSSUQ were not used as these questionnaires were designed to evaluate a software or website, not mHealth app.

The content of all the used questionnaires (at baseline and follow-up) were critically reviewed and validated by distributing initial drafts to several colleagues in the field and then to a sample of 20 patients. The received feedback was considered for reviewing and performing any amendments needed. Full professional demonstration and counseling were provided by the researchers to each patient pertaining to the questionnaire items. A summary of the study design is demonstrated in the flow chart in Figure 2.

Figure 2.

Flow chart of the study design. At recruitment, baseline data was collected from patients in the intervention and control groups. ACT score was calculated for both groups. Intervention group was asked to download the app and was notified weekly to use it. After 3 months, ACT score was re-calculated for both groups. User satisfaction score for the app was assessed in intervention group.

The design mobile health application (asthma mHeath app)

The design science research method³⁵ was used to design and develop the asthma mHealth app. This method is an iterative process that contains six steps; (1) identifying the problem, (2) defining the solution objectives, (3) designing and developing an artifact: mHealth app, (4) demonstrating the designed artifact, (5) evaluating the artifact’s effectiveness, and (6) communicating the outcomes with patients. A software developer designed a platform smartphone app (asthma mHealth app) that runs freely on Android devices (i.e. Samsung and Huawei). The app was designed and prepared in the Arabic language. It contained several items targeting multiple aspects of the patient’s knowledge about asthma, exacerbating triggers, and adherence to the correct use of different inhaler devices. Home page items were “information about asthma” and “medication.” The information about asthma allowed the user to see multiple pages with simply presented information, including asthma definition, symptoms, triggers, severity, and prevention. At the same time, medication menu provides patients with short demonstration videos about the correct use of different inhaler devices, including MDIs, DPIs, and MDIs with spacer. These videos were recorded by a health care provider in the respiratory clinics, where patients used to receive the instructions about their medications. However, the app does not provide reminders or alerts to patients. An outline of the app screens and examples of app screens are shown in Figure 3 (a and b).

Figure 3.

Asthma mHeath app: (a) an outline of app screens and (b) examples of asthma app screens.

Statistical analysis

Statistical analysis was carried out using SPSS version 20.0 (SPSS Inc., Chicago, IL). Descriptive statistics were used to describe demographic and general characteristics of participants. Categorical variables were presented as percentages with frequencies, while continuous variables were presented as mean with standard deviation (SD).

An independent sample t-test was used to test for differences in ACT score between control and intervention groups at recruitment and at follow-up. Paired sample t test was used to test differences in ACT score for the intervention group before and after the use of the mobile application. The same comparison was performed for the control group at recruitment and at follow-up evaluation. Pearson chi-square test and Fisher Exact test were used to find associations between categorical variables. All hypothesis testing were two-sided. A p-value of <0.05 was considered significant.

Results

The socio-demographic and clinical characteristics of the study population

The socio-demographic and clinical characteristics of the recruited patients were shown in Table 1. Around 34% of the study population aged between 30 and 49 years (n = 22 control, and n = 36 intervention). In addition, there was a statistical difference in age between the study groups (p-value <0.05). Patients in the intervention group were younger than those in the control group. The percentage of males and females was almost equal between the two groups (males were 30% vs 28.4%, and females were 69.9% vs 71.6% in the control and the intervention groups, respectively). Only 4% (n = 7) of the patients were not educated, and were in the control group. Approximately, 32% (n = 57) of the all patients were either a full-time or part-time workers (n = 22 control, and n = 32 intervention). The majority of the patients have been diagnosed with asthma for >6 months (94.7%, n = 162), and there was no statistically significant difference between intervention and control groups with regards to the time of diagnosis (p-value = 0.801). Even though 78.9% (n = 135) of the patients answered that they take their medications regularly on time and 90.1% (n = 154) of them did not have any technical problem when using inhaler devices, the majority of them had either partially controlled (44.4%, n = 76), or uncontrolled asthma (47.4%, n = 81). Interestingly, only 17% (n = 29) of the patients were smokers and comparably distributed between intervention and control groups (p-value = 0.233). Cigarettes smoking was the most common type of smoking (79.4%, n = 23).

Table 1.

Socio-demographic and clinical characteristics of patients at recruitment.

	N (%)			p Value
	Total sample (N = 171)	Control group (N = 83)	Intervention group (N = 88)	p Value
Age (years)				0.002
18–29	34 (19.9)	10 (12.0)	24 (27.3)
30–49	58 (33.9)	22 (26.5)	36 (40.9)
50–59	40 (23.4)	23 (27.7)	17 (19.3)
60–69	26 (15.2)	18 (21.7)	8 (9.1)
70 years and above	13 (7.6)	10 (12.0)	3 (3.4)
Gender				0.806
Male	50 (29.2)	25 (30.1)	25 (28.4)
Female	121 (70.8)	58 (69.9)	63 (71.6)
Marital status				0.025
Single	41 (24.0)	15 (18.1)	26 (29.5)
Married	116 (67.8)	57 (68.7)	59 (67.0)
Divorced	2 (1.2)	1(1.2)	1(1.1)
Widowed	12 (7.0)	10(12)	2(2.3)
Educational level				0.025
Not educated	7 (4.1)	7 (8.4)	0
Primary school	30 (17.5)	13 (15.7)	17 (19.3)
High school	43 (25.1)	25 (30.1)	18 (20.5)
Diploma	25 (14.6)	13 (15.7)	12 (13.6)
Bachler degree	60 (35.1)	22 (26.5)	38 (43.2)
Postgraduate	6 (3.6)	3 (3.6)	3 (3.4)
Employment				0.006
Employed full-time or part-time	57 (31.6)	22 (26.5)	32 (36.3)
Student	20 (11.7)	5 (6.0)	15 (17.0)
Housewife	53 (31.0)	26 (31.3)	27 (30.7)
Unemployed	44 (25.7)	30 (36.1)	14 (15.9)
Months since having asthma				0.801
<6 months	9 (5.3)	4 (4.8)	5 (5.7)
>6 months	162 (94.7)	79 (95.2)	83 (94.3)
Do you take your mediations regularly and on time				0.303
Yes	135 (78.9)	64 (77.1)	71 (80.7)
No	5 (2.9)	1 (1.2)	4 (4.5)
Sometimes	28 (16.4)	17 (20.5)	11 (12.5)
Newly diagnosed	3 (1.8)	1 (1.2)	2 (2.3)
Do you have any technical problem when taking your medication (inhalers)				0.182
Yes	14 (8.2)	10 (12.0)	4 (4.50)
No	154 (90.1)	72 (86.7)	82 (93.2)
Newly diagnosed	3 (1.8)	1 (1.20)	2 (2.3)
Asthma control^#				0.024
Controlled	14 (8.2)	8 (9.6)	6 (6.8)
Partially controlled	76 (44.4)	28 (33.7)	48 (54.5)
Uncontrolled	81 (47.4)	47 (56.6)	34 (38.6)
Smoking				0.233
Yes	29 (17.0)	17 (20.5)	12 (13.6)
No	142 (83.0)	66 (79.5)	76 (86.4)
Type of smoking*				0.289
Nargile	5 (17.2)	4 (23.5)	1 (8.3)
Cigarettes	23 (79.4)	13 (76.5)	10 (83.4)
Others	1 (3.4)	0	1 (8.3)

Asthma Control Test (ACT) scores out of 25; ⩾20, well-controlled asthma; 16–19, moderately controlled asthma; ⩽15, very poorly controlled asthma.

Percentages were calculated out of smokers.

Patients’ knowledge and experience with smart mobile phones and health technology aids

The majority of the patients in this study (96% of the total sample) had a mobile phone, 94.5% of them had a smartphone (Table 2). All patients in the intervention group had smart mobile phones with android platform. In addition, almost >90% of the patients believed that the smart mobile phone is useful in their life (74.2%, n = 115 agree, and 17.4%, n = 27 strongly agree). Furthermore, 95.5% (n = 148) of the patients who had smartphones, usually use their mobiles without any assistant (n = 64 control, and n = 84 intervention). Nevertheless, only 26.5% (n = 41) of the patients who had smart mobile phone, have ever heard about mHealth apps (n = 13 control, and n = 28 intervention). Among these, only 4.5% (n = 4 intervention) had used mHealth apps to manage any chronic conditions before participating in this study. Table 2 presents as assessment of patients’ knowledge and experience with smart mobile phone and health technology aids.

Table 2.

Assessment of patients’ knowledge and experience with smart mobile phones and health technology aids.

	N (%)
	Total sample (N = 171)	Control group (N = 83)	Intervention group (N = 88)
Do you have a mobile phone
Yes	164 (95.9)	76 (91.6)	88 (100)
No	7 (4.1)	7 (8.4)	0
Is your mobile phone smart*
Yes	155 (94.5)	67 (88.2)	88 (100)
No	9 (5.5)	10 (11.8)	0
For how long do you have your smart mobile phone?**
<1 year	3 (1.9)	1 (1.5)	2 (2.3)
Between 1 and 2 years	9 (5.8)	4 (6.0)	5 (5.7)
>2 year	143 (92.3)	62 (92.5)	81 (92.0)
What is the brand/type of your smart mobile phone?**
iPhone/Apple	13 (8.4)	13 (19.4)	0
Samsung/Android	45 (29.0)	18 (26.9)	27 (30.7)
Huawei/Android	88 (56.8)	31 (46.3)	57 (64.8)
Others/Android	9 (5.8)	5 (7.4)	4 (4.5)
Do you find your smart mobile phone useful?**
Strongly agree	27 (17.4)	8 (11.9)	19 (21.6)
Agree	115 (74.2)	53 (79.1)	62 (70.5)
Neutral	13 (8.4)	6 (9.0)	7 (8.0)
Disagree or strongly disagree	0	0	0
Do you use your mobile by yourself or there is someone who can assist you using mobile if needed?**
Use by myself all the time	148 (95.5)	64 (95.5)	84 (95.5)
Need assistance some time	7 (5.5)	3 (5.5)	4 (4.5)
Have you ever heard about mHealth app?**
Yes	41 (26.5)	13 (19.4)	28 (31.8)
No	114 (73.5)	54 (80.6)	60 (68.2)
Have you used mHealth apps to manage any chronic conditioned do you have?^&
Yes	4 (9.8)	0	4 (4.5)

Percentage was calculated based on the total number of patients who have ever heard about mobile applications.

Percentages were calculated out of patients having a mobile.

Percentages were calculated out of patients having a smart mobile.

Patients’ attitude toward using mHealth app to enhance medication adherence

Patients’ attitude toward using the mHealth app to enhance medication adherence was investigated at recruitment, according to the patients’ responses to six items using the Likert scale as demonstrated in Table 3. Before using our designed asthma mobile app, none of the patients believed that the use of the mHealth app would be a useful tool to enhance medication adherence. Similarly, 96.5% of the total sample thought that the use of the mHealth app would not be an effective tool to provide patients with information regarding the correct use of inhaler devices. On the other hand, only one patient from the overall patients indicated that the use of the mHealth app would help to remind patients to take their medications on time. Approximately 96% of the total sample did not agree that the mHealth apps’ use could help patients follow doctor’s instructions regarding treatment plan and medication use. Furthermore, 73.1% of all patients indicated that the use of the mHealth app would not affect the number of times that patients would have to visit the clinic. In addition, there was a statistically significant difference between control and intervention groups’ responses with regards to the effect of the use of the mHealth app on the number of clinic visits, p-value <0.05. Finally, most of the patients at recruitment (97.7%) considered that the mHealth app would provide inaccurate and untrusted health-related information. It is clear from these findings that most of the patients (control and intervention groups) had a negative attitude toward the use of the mHealth app at the recruitment stage and prior to the application use.

Table 3.

Patients’ attitude toward using the mHealth app to enhance medication adherence.

Statement			N (%)			p Value*
Statement		Agree	Neutral	Disagree	Strongly disagree	p Value*
1. Do you think that the use of mHealth app will be a useful tool to enhance patient adherence to medication	Total sample (N = 171)	0	5 (2.9)	136 (79.5)	30 (17.5)	–
	Control (N = 83)	0	4 (4.8)	69 (83.1)	10 (12.0)	0.081
	Intervention (N = 88)	0	1 (1.1)	67 (76.1)	20 (22.7)	0.081
2. Do you think that the use of mHealth app will be an effective tool to provide patient with information regarding the correct use of inhaler devices	Total sample	0	6 (3.5)	125 (73.1)	40 (23.4)	–
	Control	0	4 (4.8)	56 (67.5)	23 (27.7)	0.250
	Intervention	0	2 (2.3)	69 (78.4)	17 (19.3)	0.250
3. Do you think that the use of mHealth app will help in reminding patient to take their medication on time	Total sample	1 (0.6)	24 (14.0)	122 (71.3)	24 (14.0)	–
	Control	0	9 (10.8)	63 (75.9)	11 (13.3)	0.448
	Intervention	1 (1.1)	15 (17.0)	59 (67.0)	13 (14.8)	0.448
4. Do you think that the use of mHealth app will allow patient to follow doctor instructions regarding treatment plan and medication use	Total sample	0	7 (4.1)	130 (76.0)	34 (19.9)	–
	Control	0	3 (3.6)	64 (77.1)	16 (19.3)	0.930
	Intervention	0	4 (4.5)	66 (75.0)	18 (20.5)	0.930
5. Do you think that the use of mHealth app will reduce the number of times that patients would have to visit the clinic	Total sample	2 (1.2)	44 (25.7)	101 (59.1)	24 (14.0)	–
	Control	1 (1.2)	13 (15.7)	55 (66.3)	14 (16.9)	0.034
	Intervention	1 (1.1)	31 (35.2)	46 (52.3)	14 (16.9)	0.034
6. In general, do you think that mHealth app will provide accurate and trusted health-related information	Total sample	1 (0.6)	3 (1.8)	143 (84.2)	23 (13.5)	–
	Control	0	1 (1.2)	72 (87.8)	9 (11.0)	0.511
	Intervention	1 (1.1)	2 (2.3)	71 (80.7)	14 (15.9)	0.511

p-Value was calculated using Pearson chi square test.

The effect of designed asthma mobile app use on asthma control

The ACT score was calculated for each patient at recruitment and after a follow-up of 3 months, as an objective measure for asthma control. As shown in Table 4, during recruitment (baseline), there was no statistically significant difference in ACT scores between intervention and control groups (19.4 ± 4.4 versus 18.3 ± 4.6, respectively, p-value = 0.134). For 3 months, the intervention group used the designed asthma mobile app as an educational tool on how to use their inhaler devices and as an additional source of information about asthma. On the contrary, the control group did not use the app and only received traditional patient education from the health care providers. Interestingly, the intervention group had significantly higher ACT scores than control at follow-up (21.1 ± 3.7 versus 19.7 ± 4.0, respectively, p-value = 0.016) (Table 4), indicating that their asthma symptoms were enhanced after using the app and following the instructions on how to use the inhaler devices properly. In addition, the ACT scores of both control and intervention groups were increased (enhanced asthma symptoms) significantly at follow up, p-value <0.001 (Table 4). However, the extent of the increase was higher among the intervention group, from 19.4 ± 4.4 to 21.1 ± 3.7 (Table 4). Differences in ACT among control and intervention groups before and after app use were 1.4 versus 1.7, respectively (Table 4).

Table 4.

Comparison of ACT score (out of 25) between control and intervention groups.

	Control (N = 83) (mean ± SD)	Intervention (N = 88) (mean ± SD)	p-Value
At recruitment (baseline)	18.3 ± 4.6	19.4 ± 4.4	0.134*
At 3 months of follow up	19.7 ± 4.0	21.1 ± 3.7	0.016*
p-Value^#	<0.001	<0.001

p Values were calculated using paired sample t test.

p Values were calculated using independent sample t test.

Furthermore, the asthma control of the study population was investigated as numbers and percentages of patients in each category according to the patients’ ACT scores (Table 5). Consistent with data in Table 4, asthma symptoms were improved among study groups at follow up. The number of patients with either controlled or partially controlled asthma had increased among both control and intervention groups at follow-up. However, the percentage of increase in controlled asthma category among intervention group was significantly higher than control (difference in increase was; 8% versus 2.4%, respectively, Table 5).

Table 5.

Asthma control before and after the use of asthma mobile app.

Overall asthma control	Before use at recruitment (baseline)			After use at 3 months of follow up
	N (%)			N (%)
	Control (N = 83)	Intervention (N = 88)	p-Value	Control (N = 83)	Intervention (N = 88)	p-Value
Controlled (ACT ⩾ 20)	8 (9.6)	6 (6.8)	0.024	10 (12.0)	13 (14.8)	0.037
Partially controlled (ACT = 16–19)	28 (33.7)	48 (54.5)		39 (47.0)	55 (62.5)
Poorly controlled (ACT ⩽ 15)	47 (56.6)	34 (38.6)		34 (41.0)	20 (22.7)

Users’ satisfaction with asthma mobile app

The satisfaction with the designed asthma mobile app use was investigated among patients who used it (intervention group, n = 88). As shown in Table 6, results revealed mostly high satisfaction with app’s ease of use, content, and usefulness for asthma. Even though 8% (n = 8) of the users indicated that using the app requires time, the majority of the users indicated that they were satisfied with the app and they would like to use it again.

Table 6.

Users’ satisfaction for asthma application (N = 88).

Satisfaction statements	Strongly agree	Agree	Neutral	Disagree*
Satisfaction statements	N (%)
1. It was easy to use this app	23 (26.1)	62 (70.5)	3 (3.4)	0
2. It was easy for me to learn to use the app	27 (30.7)	58 (65.9)	3 (3.4)	0
3. The navigation was consistent when moving between screens	27 (30.7)	56 (63.6)	5 (5.7)	0
4. It was easy to use the interface	21 (23.9)	65 (73.9)	2 (2.3)
5. Whenever I made a mistake using the app, I could recover easily and quickly	31 (35.2)	53 (60.2)	4 (4.5)
6. The information in the app (e.g. about asthma) was well organized and easy to understand	23 (26.1)	61 (69.3)	3 (3.4)	1 (1.1)
7. The information in the app could help me to use the inhaler correctly	18 (20.5)	62 (70.5)	8 (9.1)
8. I feel comfortable using this app in social settings	15 (17.0)	67 (76.1)	6 (6.8)
9. The amount of time involved in using this app has been fitting for me	14 (15.9)	53 (60.2)	14 (15.9)	7 (8.0)
10. I would use this app again	11 (12.5)	67 (76.1)	8 (9.1)	2 (2.3)
11. The language used in the app is engaging (interests me)	13 (14.8)	41 (46.6)	30 (34.1)	4 (4.5)
12. This app has all the functions and capabilities I expected it to have	12 (13.6)	58 (65.9)	16 (18.2)	2 (2.3)
13. This app provides an acceptable way to receive health care service, such as accessing educational material	16 (18.2)	58 (65.9)	12 (13.6)	2 (2.3)
14. Overall, I am satisfied with the app	21 (23.9)	62 (70.5)	4 (4.5)	1 (1.1)

None of the patients had chosen strongly disagree to answer any of the 14 questions

Discussion

This prospective interventional study presents and evaluates a new platform in the management of asthma. It introduces the use of mHealth technology to enhance asthma management and medication adherence. An important aspect of medication adherence in asthma is the correct use of inhaler devices, as poor technique might directly affect asthma control. To the best of our knowledge, this study is the first to investigate the use and effectiveness of a designed mHealth app that delivers evidence-based informed asthma content and demonstrates the correct use of different inhaler devices through videos recorded by a health care provider.

Prior to implementing the mHealth app, patients’ knowledge and experience with smart mobile phones and health technology aids were assessed. Results indicated that the majority of the study population had a smart mobile phone available for at least 2 years. In addition, <90% of them used their smart mobile phones without any assistant. Clinically, most patients had either partially controlled asthma or poorly controlled asthma. These findings were in accordance with several previous studies that have shown poor asthma control among the Jordanian population,^10,22 and the incorrect use of different inhaler devices was one of the associated factors.^22,23

Only 26.5% of the patients had heard about mHealth apps before conducting this study. Therefore, implementing the mHealth app to enhance medication adherence and asthma self-management is necessary and would be a new platform for managing asthma among the Jordanian population. Initially, the patients (n = 171) were assigned into intervention and control groups. Elderly, not educated patients, and those who have mobile platforms other than Android, were included in the control group and received the traditional patient education from the health care providers as they could not use the designed asthma app. As a result, patients in the intervention group were younger, more educated, and employed. More than half of the intervention group had partially controlled asthma. However, at baseline, there was no statistically significant difference in ACT scores between control and intervention groups (p-value = 0.134), indicating that both groups had a similar level of asthma control at the beginning of the study.

Indeed, all the patients (control and intervention groups) had a negative attitude toward using mHealth apps at the recruitment stage and before the use of the designed asthma mobile app. This was expected as only 4.5% of them were familiar with mHealth apps. Additionally, the idea of using the mHealth app for asthma management has not been previously investigated among the Jordanian population. Most previous studies focused on pharmacists’ role in enhancing patients’ use of inhaler devices.^22,23 Moreover, studies evaluated the attitude of the general population on mHealth apps’ use indicated that older individuals had a negative attitude and were less receptive to using these apps.²⁴ Consistently, in our study, <45% of the patients aged 50 years and above; they were to have concerns about using a new non-traditional way to deliver medical advice.

Interestingly, at the follow-up of 3 use of the designed asthma mobile app asthma mobile app, a significant change in users’ attitude was noticed, particularly in the aspect of users’ satisfaction. The majority of the users reported high satisfaction with the ease of use, content, and usefulness of the app. Moreover, most of the users showed an interest in using the app and reported their satisfaction with it. This satisfaction with our designed asthma mobile app was translated clinically as a significant improvement in the ACT score among the intervention group.

The use of the designed asthma mobile app enhanced patients’ adherence to the proper use of inhaler devices and thus improved their symptoms and overall asthma control. Although there was an improvement in symptoms in the control group who did not use the app, this was due to the traditional patient education provided by the physician and the clinical pharmacist to all of the study groups. The results showed that patients who had used the designed asthma mobile app for 3 months had better asthma control as the number of patients with poor asthma control decreased. This is in line with previous studies that have shown that adherence and correct medication use were related to better asthma control.^36,37

Strength and limitation

A strength of our study was the relatively high number of patients with a low drop-out rate. The low drop out in this study might be attributed to the socio-demographic and behavioral characteristics of the participants. First, most of the patients who used the app were young, and this group of population has been shown to have less drop-out rate.³⁸ Second, using a mHealth app to support asthma patients to adhere to their medication was new in Jordan as no previous studies have investigated this before. Therefore, patients lack such a needed functionality, and thus they enthusiastically adopt it. Third, asthma is a chronic disease, so patients used to visit the clinic regularly where they were notified to use the app by the physician, which might potentially maintain patients’ interests to use the app. Moreover, the designed asthma mobile app was aligned with patients’ requirements, as it presents different demonstration videos in the Arabic language on how to correctly use several types of inhaler devices and preventers. In addition to its ease of use, the app could be used by the patient in the mode of no internet availability. On the other hand, the app lacks interactive approaches between patients and healthcare providers, including asthma action plans and monitoring of asthma control with feedback. A modification on the used app utilizing interactive approaches between patients and health care providers is under investigation by our research group and would be focusing on the engagement of pharmacists in supporting asthma patients, especially those who were non-adherent to their medications. Among the limitations of this study was a response bias. At the recruitment, motivated, young patients and those having an android platform were probably more interested in participating in the intervention group and more willing to use the app. Therefore, age was not matched between intervention and control groups, which is a limitation in this study. In addition, notifying patients in the intervention group to use the app could be a limitation in this study. However, these patients were supposed to get the instructions on how to use the inhalers by using the app, not by the traditional way by health care providers.

Conclusion

In this study, a smart mobile phone mHealth app for asthma patients was developed. This app incorporated several features that have significantly improved patients’ adherence to medication use and overall asthma control. Therefore, healthcare providers may consider the implementation of mHealth approaches in the treatment of patients with asthma and enhancing medication adherence, especially in the current corona virus disease (COVID-19) pandemic that has affected the proper interaction between patient and healthcare providers.

Footnotes

Acknowledgements

We would like to thank Sujood Nawash, Marwa abdeen, and Batool Alkhawldeh for their help in data collection.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This project was funded by the Deanship of Scientific Research at the University of Jordan.

ORCID iDs

Rima Hijazeen

Shereen M Aleidi

References

Bousquet

Khaltaev

Cruz

, et al. International European Respiratory Society/American Thoracic Society guidelines on severe asthma. Eur Respir J 2014; 44(5): 1377–1378.

Chung

Wenzel

Brozek

, et al. International ERS/ATS guidelines on definition, evaluation and treatment of severe asthma. Eur Respir J 2014; 43(2): 343–373.

Vos

Abajobir

Abate

, et al. Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990–2016: a systematic analysis for the Global burden of Disease study 2016. Lancet 2017; 390(10100): 1211–1259.

World Health Organisation. Asthma fact sheet 2020 [cited 2020 14.9.2020].

Almomani

Al-Eitan

Al-Sawalha

, et al. Association of genetic variants with level of asthma control in the Arab population. J Asthma Allergy 2019; 12: 35–42.

(Gina) GIfA. Global strategy for asthma management and prevention 2020 [cited 2020 14.9.2020]. www.ginasthma.org.

Giraud

Allaert

Roche

Inhaler technique and asthma: feasability and acceptability of training by pharmacists. Respir Med 2011; 105(12): 1815–1822.

Price

Bosnic-Anticevich

Briggs

, et al. Inhaler competence in asthma: common errors, barriers to use and recommended solutions. Respir Med 2013; 107(1): 37–46.

Janežič

Locatelli

Kos

Inhalation technique and asthma outcomes with different corticosteroid-containing inhaler devices. J Asthma 2020; 57(6): 654–662.

10.

Basheti

Obeidat

Ammari

, et al. Associations between inhaler technique and asthma control among asthma patients using pressurised MDIs and DPIs. Int J Tuberculosis Lung Dis 2016; 20(5): 689–695.

11.

Ventola

CL.

Mobile devices and apps for health care professionals: uses and benefits. Pharm Therap 2014; 39(5): 356–364.

12.

Mosa

Yoo

Sheets

A systematic review of healthcare applications for smartphones. BMC Med Inform Decis Mak 2012; 12(1): 67.

13.

Piette

List

Rana

, et al. Mobile health devices as tools for worldwide cardiovascular risk reduction and disease management. Circulation 2015; 132(21): 2012–2027.

14.

Price

Williamson

McCandless

, et al. Hispanic migrant Farm workers’ attitudes toward mobile phone-based telehealth for management of chronic health conditions. J Med Internet Res 2013; 15(4): e76.

15.

Jenkins

Burkett

N-S

Ovbiagele

, et al. Stroke patients and their attitudes toward mHealth monitoring to support blood pressure control and medication adherence. mHealth 2016; 2: 24.

16.

Whitehead

Seaton

The effectiveness of self-management mobile phone and tablet apps in long-term condition management: a systematic review. J Med Internet Res 2016; 18(5): e97.

17.

Farzandipour

Nabovati

Sharif

, et al. Patient self-management of asthma using mobile health applications: a systematic review of the functionalities and effects. Appl Clin Inform 2017; 8(4): 1068–1081.

18.

Kosse

Bouvy

de Vries

, et al. Effect of a mHealth intervention on adherence in adolescents with asthma: a randomized controlled trial. Respir Med 2019; 149: 45–51.

19.

Davis

Peters

Calvo

, et al. “Kiss myAsthma”: using a participatory design approach to develop a self-management app with young people with asthma. J Asthma 2018; 55(9): 1018–1027.

20.

Kosse

Bouvy

Belitser

, et al. Effective engagement of adolescent asthma patients with mobile health-supporting medication adherence. JMIR Mhealth Uhealth 2019; 7(3): e12411.

21.

Farzandipour

Nabovati

Heidarzadeh Arani

, et al. Enhancing asthma patients’ self-management through smartphone-based application: design, usability evaluation, and educational intervention. Appl Clin Inform 2019; 10(5): 870–878.

22.

Basheti

Salhi

Basheti

, et al. Role of the pharmacist in improving inhaler technique and asthma management in rural areas in Jordan. Clin Pharmacol 2019; 11: 103–116.

23.

Basheti

Obeidat

Reddel

HK.

Inhaler technique education and asthma control among patients hospitalized for asthma in Jordan. Saudi Pharm J 2018; 26(8): 1127–1136.

24.

Davies

Kotadia

Mughal

, et al. The attitudes of pharmacists, students and the general public on mHealth applications for medication adherence. Pharm Pract 2015; 13(4): 644.

25.

McGillicuddy

Weiland

Frenzel

, et al. Patient attitudes toward mobile phone-based health monitoring: questionnaire study among kidney transplant recipients. J Med Internet Res 2013; 15(1): e6.

26.

Proudfoot

Parker

Hadzi Pavlovic

, et al. Community attitudes to the appropriation of mobile phones for monitoring and managing depression, anxiety, and stress. J Med Internet Res 2010; 12(5): e64.

27.

Kouris

Mougiakakou

Scarnato

, et al. Mobile phone technologies and advanced data analysis towards the enhancement of diabetes self-management. J Med Internet Res 2010; 5(4): 386–402.

28.

Korn

Both

Jung

, et al. Prospective evaluation of current asthma control using ACQ and ACT compared with GINA criteria. Ann Allergy Asthma Immunol 2011; 107(6): 474–479.

29.

Nathan

Sorkness

Kosinski

, et al. Development of the asthma control test: a survey for assessing asthma control. J Allergy Clin Immunol 2004; 113(1): 59–65.

30.

Reddel

Taylor

Bateman

, et al. An official American Thoracic Society/European Respiratory Society statement: asthma control and exacerbations: standardizing endpoints for clinical asthma trials and clinical practice. Am J Respir Crit Care Med 2009; 180(1): 59–99.

31.

Schatz

Sorkness

, et al. Asthma control test: reliability, validity, and responsiveness in patients not previously followed by asthma specialists. J Allergy Clin Immunol 2006; 117: 549–556.

32.

Lababidi

Hijaoui

Zarzour

Validation of the Arabic version of the asthma control test. Ann Thorac Med 2008; 3(2): 44–47.

33.

Lewis

JR.

IBM computer usability satisfaction questionnaires: psychometric evaluation and instructions for use. Int J Hum Comput Interact 1995; 7(1): 57–78.

34.

Zhou

Bao

Setiawan

IMA

, et al. The mHealth app usability questionnaire (MAUQ): development and validation study. JMIR Mhealth Uhealth 2019; 7(4): e11500.

35.

Hevner

Chatterjee

. Design science research in information systems. Design research in information systems. Springer, 2010. pp. 9–22. DOI: 10.1007/978-1-4419-5653-8.

36.

Jentzsch

Silva

GCG

Mendes

GMS

, et al. Treatment adherence and level of control in moderate persistent asthma in children and adolescents treated with fluticasone and salmeterol. J Pediatr 2019; 95: 69–75.

37.

Haughney

Price

Kaplan

, et al. Achieving asthma control in practice: understanding the reasons for poor control. Respir Med 2008; 102(12): 1681–1693.

38.

Meyerowitz-Katz

Ravi

Arnolda

, et al. Rates of attrition and dropout in app-based interventions for chronic disease: systematic review and meta-analysis. J Med Internet Res 2020; 22(9): e20283.