Evaluation of Hausa mobile health apps quality

Muhammad DG1, Ahmad HY2*, Umar R3

1Department of Physiotherapy, General Hospital Dutse, Jigawa State, Nigeria.
2Department of Physiotherapy, Murtala Muhammad Specialist Hospital, Kano, Nigeria.
3Department of Physiotherapy, General Hospital Birnin Kudu, Jigawa State, Nigeria.

*Correspondence: Hassan Yusuf Ahmad; +234 706 604 6456; Hassan04@gmail.com

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Abstract

Background: Mobile Health (mHealth) involves the utilization of mobile communication to promote health by supporting healthcare practices. To the best of our knowledge, the quality of mobile health apps available to the 65 million Hausa speakers globally is yet to be evaluated in a study.
Objective: To evaluate the quality of Hausa mobile health apps available on Google play store.
Materials and Methods: This is a cross-sectional descriptive study of the quality of Hausa mobile health apps available on Google play store. A search of the Google play store for Hausa mobile health apps was conducted on 19th September, 2021. Hausa words “KiwonLafiya”, “CutadaMagani” and “RashinLafiya” were utilized in the search for relevant apps. The Mobile App Rating Scale (MARS) was used to evaluate the quality of the Hausa mobile health apps found. Two of the authors separately applied the MARS which was validated by the third author. Four MARS domains (Engagement, Functionality, Aesthetics, Information) were assessed to evaluate app quality, the mean score in each domain and the overall mean were determined from the two separate quality ratings conducted.
Result: Eight Hausa mobile apps were found. Majority of the apps were on women health; n = 3 (37.5%) and health education; n = 3 (37.5%). Three of the apps (37.5%) had > 10,000 downloads. Seven out of the eight apps (87.5%) were developed by an individual developer. The functionality domain had the highest mean score, followed by aesthetics and engagement domains, while the least mean score was in the information domain. The overall mean from rater one’s rating was 3.18 ± 0.31 and 2.84 ± 0.60 from rater two’s rating, which showed an acceptable quality.
Conclusion: The reviewed apps were of an acceptable quality, however, health education features within mobile health apps needs more improvement.

Keywords: Mobile Health, Hausa, Mobile apps, Telemedicine.

Cite this article: Muhammad DG, Ahmad HY, Umar R. Evaluation of Hausa mobile health apps quality. Yen Med J. 2022;4(1):11–15.

INTRODUCTION

Technological innovations have become central to our daily activities in various dimensions. Particularly, computers and mobile phones have greatly improved individual access to information, dissemination and exchange of information with others and how we learn, exchange knowledge and render services.1,2 Mobile Health (mHealth) is a component of electronic health (eHealth).3,4 Simply put, mHealth involves the utilization of mobile communication to aid healthcare delivery processes like health data collection, patient examination, treatment and delivery of health care information,.4,5 At the beginning of its development in 2003, Mobile Health (mHealth) was defined as wireless telemedicine involving the use of mobile telecommunication and multimedia technologies and their integrations with mobile health care delivery system.6  Also, mHealth was defined as “medical and public health practice supported by mobile devices, such as mobile phones, patient monitoring devices, personal digital assistants (PDAs), and other wireless devices” by World Health Organization.4

According to the International Telecommunication Union (ITU) mobile phone subscription reached almost 6 billion worldwide in 2011, caused in most part by a rise in users from developing countries.7 Developing countries accounted for more than 80% of the 660 million new subscriptions during that year.7 By estimation, over 95% of the population worldwide would have been using mobile phones by 2013,8 meaning that mobile phone services would have reached more people than water and sanitation services.9 It was a clear indication of large and rapid penetration of mobile phone access in the developing world. The utilization of information technology in health care delivery is in many ways modifying how health care is traditionally perceived, with significant influence on how health care services are accessed and rendered. The change resulting from this new culture is what was defined as a move from “industrial age medicine’’ to “information age health care”, where health care providers and health care services consumers are exposed to, and increasingly use or deploy information tools in dispensing and receiving services.2 Africa has been documented to have witnessed the fastest growth in mobile phone subscribers in the world, estimated at 955 million in 2015.10

Hausa is the most commonly spoken language in West Africa, with over 50 million native speakers and 15 million non-native speakers in Northern Nigeria, the republic of Niger, Northern Cameroon and Ghana.11 Hausa is a major world language, spoken as a mother tongue by more than 30 million people in Northern Nigeria and Southern part of Niger Republic. It is also widely used as a second language (by millions of people) and has expanded rapidly as a lingua franca.12

Health telematics can play an important role in promoting the lives of patients, especially in the weaker sections of the community including the disabled, elderly and chronically ill patients.13 Moreover, mobile health-monitoring appliances contribute great potential aid for such patients who may be able to receive good health services without having to frequently visit their doctor. These technologies bring potential advantages to both patient and doctor; doctors can focus more on superior task by saving time normally spent with consulting chronically ill patients,13 and patients can move about in their environment without having to make extensive trips to the doctor, especially if they reside in a remote location. Mobile health or mHealth using wireless communication devices to support public health and clinical practice has great potential to enhance this virtuous cycle. More than any other modern technology, mobile phones are used throughout the developing world,14 and innovative application of mobile technology to existing health care delivery and monitoring systems offers great promise for improving the quality of life.

The Mobile App Rating Scale (MARS) is a tool created to provide researchers, professionals, and clinicians with a concise means to categorize and rate the quality of mHealth apps.15 MARS consists of 23 items and 4 objective quality subscales; engagement, functionality, aesthetics, and information quality. The MARS has demonstrated high levels of interrater reliability for evaluating the quality of mHealth apps, effect on well-being,15 and mindfulness.16 However, training and expertise in mHealth and the relevant health field is required to administer it.

In Nigeria, healthcare service delivery is plagued by many problems including inadequate number of health facilities, inadequately equipped health institutions, lack of professionals and poverty which limits individuals from accessing available services.17 As at this day, many mobile health applications are locally available in Nigeria.18 This means several people would benefit from mobile health applications for easy access to health personnels. Therefore, we aimed to evaluate the quality of Hausa mobile health apps as Hausa language is a widely spoken language among those underserved by the healthcare systems in West Africa.11

METHODOLOGY

This is a cross-sectional descriptive study of the quality of Hausa mobile health apps available on Google play store. A search of the Google play store for Hausa mobile health apps was conducted on 19th September, 2021. Hausa words “Kiwon Lafiya”, “Cuta da Magani” and “Rashin Lafiya” were utilized in the search for relevant apps. Excluding non-relevant apps; apps in English and other languages other than Hausa, herbal or any non-orthodox based apps, only eight apps met the inclusion criteria. The MARS was used to evaluate the quality of the Hausa mobile health apps found. Two of the authors separately applied the MARS (rater 1 and rater 2) which was validated by the third author. Four MARS domains (Engagement, Functionality, Aesthetics, Information) were assessed to evaluate app quality, the mean score in each domain and the overall mean were determined from the two separate quality ratings conducted.

RESULT

Eight Hausa mobile apps were found. Majority of the apps were on women health; n = 3 (37.5%) and health education; n = 3 (37.5%). Three of the apps (37.5%) had > 10,000 downloads. Seven out of the eight apps (87.5%) were developed by an individual developer (see Table 1). As shown in Table 2, the functionality domain had the highest mean score; rater 1 = 3.75 ± 0.21 and rater 2 = 3.00 ± 0.68 followed by aesthetics; rater 1 = 3.38 ± 0.28 and rater 2 = 3.29 ± 0.28 and engagement; rater 1 = 3.35 ± 0.38 and rater 2 = 2.77 ± 0.98, while the least mean score was in the information domain; rater 1 = 2.23 ± 0.36 and rater 2 = 2.31 ± 0.45. The overall mean from rater one’s rating was 3.18 ± 0.31 and 2.84 ± 0.60 from rater two’s rating, which showed an acceptable quality.

 

 

Table 1: characteristics of the apps

Variables                               

N

%

App topic

 

 

Women health                         

3

37.5

Health education                     

3

37.5

Dental care                              

1

12.5

Children health                        

1

12.5

 

 

 

Downloads

 

 

101-999                                  

3

37.5

1000-10000                             

2

25.0

>10000                                   

3

37.5

 

 

 

Developer

 

 

Individual                                

7

87.5

Company                    

1

12.5

 

 

Table 2: Mean scores of MARS domain

MARS domain           

rater 1 (X ± SD)                      

rater 2 (X ± SD)

Engagement                            

3.35 ± 0.38

2.77 ± 0.98

Functionality               

3.75 ± 0.21      

3.00 ± 0.68

Aesthetics                    

3.38 ± 0.28

3.29 ± 0.28

Information                             

2.23 ± 0.36

2.31 ± 0.45

App quality                            

3.18 ± 0.31

2.84 ± 0.60

 

 

DISCUSSION

To the best of our knowledge, this is the first study that evaluated the quality of mobile apps available to the 65 million Hausa speakers globally. The apps evaluated are of an acceptable quality, showing that the users of the apps are consuming good information. A possible reason for attaining such quality is that the apps may have been translated from an originally English language-designed app or developed by or in collaboration with health personnels or a health-related company. Majority of the apps excluded during the search were unorthodox based apps. This indicates that there are more unorthodox mobile health apps available on Google play store. There is therefore a need for more apps that are orthodox based as such information is considered more reliable.

 

The high mean score obtained in the functionality and aesthetics domain indicates that the apps were functioning well, easy to use with visual aids. This is consistent with a study19 on Chinese apps. Engagement of a mobile app defined as the friendliness of an app, is one of the determining factors of app uptake by consumers and the ability of an app to influence the health outcome of the users.20 In this study, the scores from the engagement aspects of the apps were not as high compared to functionality and aesthetics. This too is in tandem with the findings of Gong et al19 and Schoeppe et al.21

 

Similar to findings from other studies,19,21 the scores from the information domain of the apps were the least, implying that the apps were likely disseminating information that is not evidence based to the users. This could do more harm than good19 and may hinder achievement of one of the aims of mHealth tools, that is, disseminating an evidenced based patient guided information.22 In agreement with Gong et al,19 improving on the health education features within mobile health apps will in turn improve the quality of the apps.

 

CONCLUSION

The reviewed apps were of an acceptable quality, however, health education features within mobile health apps needs more improvement.  

Conflict of Interest

The authors declared that there are no conflicts of interest

Author Contributions

Quality ratings were conducted by UR and AHY and validated by MDG. All authors made substantial contribution to the study and the manuscript.

REFERENCES

  1. Ozdalga E, Ozdalga A, Ahuja N. The smartphone in medicine: A review of current and potential use among physicians and students. JMedInternet Res. 2004;14(5):128 – 138. 
  2. Salami OO. Privacy protection for mobile health (mHealth) in Nigeria: A consideration of the EU regime for data protection as a conceptual model for reforming Nigeria’s privacy legislation (Master’sthesis). Published April, 2015. Available from: https://dalspace.library.dal.ca/bitstream/handle/10222/56333/Salami-Olufunke-LLM-Law-April2015.pdf?sequence. Accessed November 27, 2021. 
  3. Melia R, Francis K, Duggan J, et al. Mobile Health Technology Interventions for Suicide Prevention: Protocol for a Systematic Review and MetaAnalysis. JMIR Res Protoc. 2018;7(1):e28. 
  4. World Health Organization (WHO). mHealth: New horizons for health through mobile technologies: second global survey on eHealth. Available from: http://www.who.int/goe/publications/goe_mhealth_web.pdf. Accessed November 27, 2021. 
  5. World Health Organization (WHO). Global Observatory for eHealth-survey 2009 figures. Available from: http://www.Who.int/goe/survey/2009/figures/en/index2/htm. Accessed November 27, 2021. 
  6. Istepanian SH, Lacal J. Emerging Mobile Communication Technologies for Health: Some Imperative Notes on MHealth. Proceedings of: 25th Institute of Electrical and Electronics Engineers (IEEE) Engineering in Medicine and Biology Society Annual International Conference; 2003; Cancun, Mexico. 
  7. Key statistical highlight: ITU data release June 2012. Geneva: International Telecommunication Union; 2012. 
  8. The world in 2013: ICT Fact and Figure. Geneva: International Telecommunication Union; 2013. 
  9. Amplifying the Impact: Examining the Intersection of mobile Health and mobile Finance: A discussion guide for collaborative insight presented by World Economic Forum, partnership with the mHealth Alliance. Geneva: World Economic Forum; 2011. 
  10. Ericsson Mobility Report 2015. Stockholm: Ericsson; 2015. Available from: http://www.ericsson.com/res/docs/2015/mobilityreport/emr-nov-2015-regional-report-Africanafrica.pdf. Accessed November 27, 2021. 
  11. National African Language Resources Center. Hausa language and culture, 2010. Madison, US: National African Language Resources Center (NALC), University of Wisconsin-Madison; 2010. 
  12. Jaggar PJ. Hausa. Amsterdam, Netherlands: John Benjamins Publishing Company; 2001. 
  13. Schwaibold M, Gmelin M, Von WG et al. Key factors for personal health monitoring and diagnosis devices. Paper presented at: 2nd Conference on
    Mobile Computing; 2002; Heidelberg, DE. 
  14. Sutherland E. Counting mobile phones, SIM cards, and customers. Park town, South Africa: Learning Information Networking and Knowledge Centre, University of the Witwatersrand; 2006. Available from: http://link.wits.ac.za/papers/link-Mobile_numbers.pdf. 
  15. Okaro AO, Ohagwu CC, Njoku J. Awareness and perception of national health insurance scheme (NHIS) among radiographers in South-east Nigeria. Am J Sci Res. 2010;8:18–25. 
  16. Okoruwa S. Top 5 apps for health care; 2018. Available from: https://connectnigeria.com/articles/2018/07/top-5-apps-for-health-care. Accessed November 27, 2021. 
  17. Stoyanov SR, Hides L, Kavanagh DJ, Zelenko O, Tjondronegoro D, Mani M. Mobile app rating scale: a new tool for assessing the quality of health mobile apps. JMIR Mhealth Uhealth. 2015;3(1):e27. 
  18. Mani M, Kavanagh DJ, Hides L, Stoyanov SR. Review and Evaluation of Mindfulness-Based iPhone Apps. JMIR Mhealth Uhealth. 2015;3(3):e82. 
  19. Gong E, Zhang Z, Jin X, Liu Y, Zhong L, Wu Y etal. Quality, Functionality, and Features of Chinese Mobile Apps for Diabetes Self-Management:
    Systematic Search and Evaluation of Mobile Apps. JMIR Mhealth Uhealth. 2020;8(4):e14836. 
  20. Tomlinson M, Rotheram-Borus MJ, Swartz L, Tsai AC. Scaling up mHealth: where is the evidence. PLoS Med. 2013;10(2):e1001382. doi:10.1371/journal.pmed.1001382. 
  21. Schoeppe S, Alley S, Rebar AL, Hayman M, Bray NA, Van-Lippevelde W et al. Apps to improve diet, physical activity and sedentary behaviour in children and adolescents: a review of quality, features and behaviour change techniques. Int J Behav Nutr Phys Act. 2017;14(1):83. doi:10.1186/s12966-017-0538-3. 
  22. Oldenburg B, Taylor C, O’Neil A, Cocker F, Cameron L. Using new technologies to improve the prevention and management of chronic conditions in populations. Annu Rev Public Health. 2015;36:483-505. doi: 10.1146/annurev-publhealth-031914-122848.
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