Published on in Vol 11, No 1 (2022): Jan-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/35062, first published .
Ethical, Legal, and Sociocultural Issues in the Use of Mobile Technologies and Call Detail Records Data for Public Health in the East African Region: Scoping Review

Ethical, Legal, and Sociocultural Issues in the Use of Mobile Technologies and Call Detail Records Data for Public Health in the East African Region: Scoping Review

Ethical, Legal, and Sociocultural Issues in the Use of Mobile Technologies and Call Detail Records Data for Public Health in the East African Region: Scoping Review

Review

1Global Health Institute, College of Public Health, University of Georgia, Athens, GA, United States

2Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, GA, United States

3Department of Health Promotion and Behavior, College of Public Health, University of Georgia, Athens, GA, United States

4Department of Epidemiology and Biostatistics, School of Public Health, Makerere University, Kampala, Uganda

5Department of Anatomy, School of Biomedical Sciences, College of Health Sciences, Makerere University, Kampala, Uganda

Corresponding Author:

Juliet Nabbuye Sekandi, MSc, MD, DrPH

Global Health Institute

College of Public Health

University of Georgia

Wright Hall, Room 227B

100 Foster Rd

Athens, GA, 30602

United States

Phone: 1 706 542 5257

Email: jsekandi@uga.edu


Background: The exponential scale and pace of real-time data generated from mobile phones present opportunities for new insights and challenges across multiple sectors, including health care delivery and public health research. However, little attention has been given to the new ethical, social, and legal concerns related to using these mobile technologies and the data they generate in Africa.

Objective: The objective of this scoping review was to explore the ethical and related concerns that arise from the use of data from call detail records and mobile technology interventions for public health in the context of East Africa.

Methods: We searched the PubMed database for published studies describing ethical challenges while using mobile technologies and related data in public health research between 2000 and 2020. A predefined search strategy was used as inclusion criteria with search terms such as “East Africa,” “mHealth,” “mobile phone data,” “public health,” “ethics,” or “privacy.” We screened studies using prespecified eligibility criteria through a two-stage process by two independent reviewers. Studies were included if they were (1) related to mobile technology use and health, (2) published in English from 2000 to 2020, (3) available in full text, and (4) conducted in the East African region. We excluded articles that (1) were conference proceedings, (2) studies presenting an abstract only, (3) systematic and literature reviews, (4) research protocols, and (5) reports of mobile technology in animal subjects. We followed the five stages of a published framework for scoping reviews recommended by Arksey and O’Malley. Data extracted included title, publication year, target population, geographic region, setting, and relevance to mobile health (mHealth) and ethics. Additionally, we used the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) Extension for Scoping Reviews checklist to guide the presentation of this scoping review. The rationale for focusing on the five countries in East Africa was their geographic proximity, which lends itself to similarities in technology infrastructure development.

Results: Of the 94 studies identified from PubMed, 33 met the review inclusion criteria for the final scoping review. The 33 articles retained in the final scoping review represent studies conducted in three out of five East African countries: 14 (42%) from Uganda, 13 (39%) from Kenya, and 5 (16%) from Tanzania. Three main categories of concerns related to the use of mHealth technologies and mobile phone data can be conceptualized as (1) ethical issues (adequate informed consent, privacy and confidentiality, data security and protection), (2) sociocultural issues, and (3) regulatory/legal issues.

Conclusions: This scoping review identified major cross-cutting ethical, regulatory, and sociocultural concerns related to using data from mobile technologies in the East African region. A comprehensive framework that accounts for the critical concerns raised would be valuable for guiding the safe use of mobile technology data for public health research purposes.

Interact J Med Res 2022;11(1):e35062

doi:10.2196/35062

Keywords



The exponential scale and pace of real-time data generated from mobile phones present new opportunities and challenges across multiple sectors, including health care delivery and public health [1]. By 2025, mobile subscribers are projected to grow from 477 million to 617 million [2]. One opportunity arising from the growth trajectory in connected mobile technology devices is the evolving field of mobile health (mHealth). The World Health Organization defines mHealth as medical and public health practice supported by mobile devices such as phones, patient monitors, smartphone apps, and functionalities, including voice or SMS text messages [3]. Globally, mHealth solutions have been deployed to address problems such as a shortage of health care workers [4,5], monitoring medication adherence [6,7], and improving quality of health care [8].

In 2020, the National Institutes of Health (NIH) announced a grand opportunity for health research for new funding, titled “Harnessing Data Science for Health Discovery and Innovation in Africa (DS-I Africa).” The goal is to spur new health discoveries and catalyze innovation in health care, public health, and health research in Africa through data science [9]. Additionally, the DS-I Africa announcement called for research to explore the ethical, legal, and social implications associated with data science [10]. These calls highlight new areas for scientific inquiry and recognize the need to address new ethical challenges when using “big data” streams across Africa.

The use of mobile phone call detail records (CDRs), which are time-stamped activity logs that are also known as billable events, is a relatively new concept in health research [11-14]. Although telecommunication companies have used CDRs for more than three decades for customer billing and targeted marketing purposes, the business sector has only recently innovated more ways to use these data in remote banking and financial service delivery. However, the health sector has sparsely leveraged such enormous amounts of mobile phone data for public health, especially in Africa [3-5]. The Data for Development Challenge, Google Flu Trends, Datathon for Social Good, and the Cairo Transport App Challenge, among others, have used archived CDRs to study human activity [6]. In the field of infectious diseases, innovative use of aggregated anonymized data from CDRs revealed informative patterns of the spatiotemporal transmission of various pathogens in the community, including rubella [15,16], malaria [12,17,18], and Ebola [19,20] in Africa. More recently, the COVID-19 pandemic has accelerated this novel utilization of mobile technologies and CDRs for public health surveillance and research [21-23]. However, a lack of well-established standardized ethical and regulatory frameworks has limited the widespread use of such data in health research, particularly in East Africa [24].

Our ongoing NIH-funded Mapping Tuberculosis Transmission Study (MATTS) in Kampala, Uganda, motivated this scoping review. MATTS takes a unique approach that utilizes individual-level CDRs combined with epidemiologic surveys and molecular data to map potential tuberculosis transmission “hot spots.” During the initiation of the study, members of the research team from the University of Georgia and Makerere University met with key stakeholders representing the public and private sectors in Uganda. The private sector players were telecommunication companies, and the public players were government agencies or regulatory entities. The goal of the meetings was to learn about existing ethical standards and policy guidelines that apply to utilizing CDRs and other data from mobile technologies for health research. The meetings led to several questions about data access, sharing, transfer, storage, security, privacy, confidentiality, legal, regulatory, and social concerns. In the end, our team surmised that the government and telecommunication entities had existing policies and procedures on personal data that did not necessarily accommodate the utilization of mobile data such as CDRs for health research. Therefore, our research serves as a logical step to generate evidence that is critical for informing the development of policy frameworks that will facilitate better access to mobile data for public health research.

In utilizing CDRs, there are potential points of ethical breaches as personal information flows from a user’s mobile phone to a database for health research purposes. For example, when a user activates a connection to mobile phone networks by calling or texting, “event-driven” personal data are generated in real time and stored as CDRs, whereas “network-driven” data are generated when the cell phone is not in active use (see Multimedia Appendix 1). The event-driven metadata in the records contain the caller and recipient phone numbers, date and time of the call, call duration, and the coordinates of the geographical location of the cell tower that serviced the billable event [25]. Each of the data points generated can potentially result in privacy breaches if the data are accessed without ethical safeguards [26]. The Belmont Report provides standard bioethics guidance for researchers based on the core ethical principles (ie, respect for persons, beneficence, and justice) [27]. Even so, we expect that there are new ethical challenges related to the use of the data generated from mobile phones or other technology/devices that warrant further evaluation.

We situated this scoping review in the East African region because of the cross-cutting similarities in sociocultural context, the landscape and stage of mobile technology infrastructure development, and the likelihood of future unified regulatory policies given shared economic interests. Scoping reviews are useful for examining emerging evidence when it is still unclear what other, more specific, questions can be addressed by a more precise systematic review [28]. The objective of the scoping review was to explore the ethical and related concerns that arise from the use of data from CDRs and mobile technology interventions for public health in the context of East Africa.

Our review findings are used to inform an ongoing primary study to explore ethical, legal, sociocultural, and regulatory concerns from the perspective of key stakeholders in the public and private sectors in Uganda. We expect that this work will further inform the development of comprehensive guidelines relevant to mHealth and public health research in the East African region.


Design

We followed five of the six stages of the framework for scoping reviews proposed by Arksey and O’Malley [29]: (1) identifying the research question; (2) identifying relevant studies; (3) study selection; (4) charting the data; and (5) collating, summarizing, and reporting the results. The sixth stage of the framework is optional, which was not included in this scoping review. It involves a consultation exercise with stakeholders to gain a more holistic view of the issues under evaluations. Additionally, we used the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) Extension for Scoping Reviews checklist to guide the presentation of this scoping review [30]. We applied existing definitions to identify common ethical concerns related to informed consent, privacy and confidentiality, and data security and protection. We also used team consensus to classify concerns that fit within legal, regulatory, and sociocultural categories.

Operational Definitions

Privacy of health information refers to an individual’s right to control the acquisition, uses, or disclosures of his or her identifiable health data for others [31,32]. Confidentiality refers to the obligations of those who receive information to respect the privacy interests of those to whom the data relate [31,32]. Data security refers to the physical, technological, or administrative safeguards or tools used to protect identifiable health data from unwarranted access or disclosure [32]. Data protection is closely related to data security, which refers to adopting appropriate, reasonable, technical, and organizational measures to prevent loss, damage, or unauthorized destruction or processing of personal data [33]. General ethical concerns refer to research processes that fail to uphold or violate the principles of respect for persons, balance of potential benefits and harms, and equitable sharing of benefits and burdens across research groups [27].

Identification of the Research Question

The primary research question was: what are the ethical, privacy, and data security concerns pertaining to the use of mHealth technologies and mobile phone data for public health research in the East African region? The rationale for focusing on the five countries in East Africa was that the ethics and mHealth technology landscapes are likely to be similar in several ways within the same region. Therefore, the findings could inform regional guidelines and policies.

Identification of Relevant Studies

A systematic search of the literature was performed on November 18, 2020, in the PubMed database using the search terms “mobile,” “ethics,” and “East Africa.” The detailed search strategy and terms used are provided in Textbox 1. The search was limited to English and included only studies focused on the East Africa region. We considered only articles published from 2000 to 2020 due to the widespread use of mobile technology during this period in the region of interest.

Full search strategy of the scoping review in the PubMed database.

(“Digital Health” [Title/Abstract] OR “Telemedicine” [MeSH (Medical Subject Heading)] OR “Cell Phone” [MeSH] OR “Smartphone” [MeSH] OR “mHealth” [Title/Abstract] OR “telemedicine” [Title/Abstract] OR “remote monitoring” [Title/Abstract] OR “mobile technology” [Title/Abstract] OR “mobile health” [Title/Abstract] OR “video observed therapy” [Title/Abstract] OR “video observed treatment” [Title/Abstract] OR “video directly observed treatment” [Title/Abstract] OR “video directly observed therapy” [Title/Abstract] OR “Call Detail Records” [Title/Abstract] OR “cell phone” [Title/Abstract] OR “cell phone” [Title/Abstract] OR “mobile phones” [Title/Abstract] OR “smartphone” [Title/Abstract] OR “cellphone data” [Title/Abstract] OR “cell phone data” [Title/Abstract] OR “data privacy” [Title/Abstract] OR “cell phone/ethics” [MeSH] OR “Cell Phone/legislation and jurisprudence” [MeSH] OR “Cell Phone Use/legislation and jurisprudence”[Mesh] OR “Cell Phone Use/therapeutic use”[Mesh]) AND (“bioethics” [MeSH] OR “ethics” [Mesh] OR “bioethics” [Title/Abstract] OR “public health ethics” [Title/Abstract] OR “ethics” [Title/Abstract] OR “research ethics” [Title/Abstract] OR “autonomy” [Title/Abstract] OR “personal autonomy” [MeSH] OR “principle-based ethics” [MeSH] OR “personal autonomy” [Title/Abstract] OR “principle-based ethics” [Title/Abstract] OR “privacy” [MeSH] OR “confidentiality” [MeSH] OR “computer security” [MeSH] OR “privacy” [Title/Abstract] OR “confidentiality” [Title/Abstract] OR “computer security” [Title/Abstract] OR “data anonymization” [Title/Abstract] OR “data compromising” [Title/Abstract] OR “compromising of data” [Title/Abstract] OR “data security” [Title/Abstract] OR “information protection” [Title/Abstract] OR “Data Protection” [Title/Abstract] OR “Data Security” [Title/Abstract] OR “information protection” [Title/Abstract] OR “Data encryption” [Title/Abstract] OR “Data encryptions” [Title/Abstract] OR “social justice” [Title/Abstract]) AND (“Africa” [MeSH] OR “Africa, South of the Sahara” [MeSH] OR “Africa, Eastern” [MeSH] OR “Tanzania” [MeSH] OR “Rwanda” [MeSH] OR “Burundi” [MeSH] OR “Kenya” [MeSH] OR “Uganda” [MeSH] OR “Tanzania” [ALL] OR “Rwanda” [ALL] OR “Burundi” [ALL] OR “Kenya” [ALL] OR “Uganda” [ALL])

Textbox 1. Full search strategy of the scoping review in the PubMed database.

Study Selection

Retrieved studies reporting on mobile technology and health in the East African region were included for further review. Two independent reviewers for each article applied the inclusion and exclusion criteria, with an additional author serving as the tiebreaker in the event of uncertainty regarding whether an article met the inclusion or exclusion criteria. Studies were included if they were (1) related to mobile technology and health, (2) published in English from 2000 to 2020, (3) available in full text, and (4) conducted in the East African region. We excluded articles that (1) were conference proceedings, (2) without full text or presenting an abstract only, (3) systematic and literature reviews, (4) research protocols, and (5) reports of mobile technology in animal subjects.

Charting of the Data

Two authors (CH and CB) performed abstract screening. Three authors (KM, CH, and CB) subsequently reviewed full-text articles, and extracted and stored the data in a Microsoft Excel database developed for this review. From the eligible studies, we extracted the title, publication year, journal name, impact factor, target population, geographic region, setting, and relevance to mHealth and ethics. For each stage of the review, two reviewers (KM and CB) independently reviewed each full-text article. Discrepancies were discussed collectively until consensus was reached.

Collating, Summarizing, and Reporting Results

Given the diversity of articles included in the final scoping review, we employed an iterative team discussion approach to the analysis in order to establish the main themes related to ethical and related concerns. We use descriptive statistics to summarize the characteristics of the studies, including country of publication, year of publication, area of focus, study design, and mHealth intervention employed.


Articles Selected

The search identified 94 articles eligible for further review (Figure 1). Of these, 59 did not meet the inclusion criteria and 5 additional studies were excluded based on a review of titles and abstracts. We included 33 studies published in 22 journals in the final scoping review.

Figure 1. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagram showing article search and screening.
View this figure

Study Characteristics

The 33 articles retained in the final scoping review represent studies conducted in three out of five East African countries, including 14 (42%) from Uganda and 13 (39%) from Kenya (Table 1). The number of studies published on ethical concerns of mHealth technology use and mobile phone data increased over time, beginning with one in 2009 and climbing to six in 2018. The articles were mostly published in the journal AIDS and Behavior, followed by Journal of Medical Internet Research and BMC Public Health. The majority of mHealth interventions were SMS-based, followed by mobile phone app–based, whereas CDR aggregate data analysis was seldom used among the studies we reviewed. More than half of the studies included were observational in study design, followed by a mixed methods design. Two of the 33 studies included met the eligibility criteria but did not mention ethical concerns beyond compliance with human research and approval from respective institutional review boards.

Three main categories of concerns related to the use of mHealth technologies and mobile phone data can be conceptualized as (1) ethical issues (adequate informed consent, privacy and confidentiality, data security and protection), (2) sociocultural issues, and (3) regulatory/legal issues. These themes are not necessarily mutually exclusive. A detailed summary of each study by theme is provided in Table 2. Ethical concerns were predominantly identified in the included studies, which are discussed in detail below.

Table 1. Summary of articles included in the scoping review for final analysis (N=33).
CharacteristicsStudies, n (%)
Country

Uganda14 (42)

Kenya13 (39)

Tanzania5 (15)

Uganda and Tanzania1 (3)
Publication year

20091 (3)

20101 (3)

20111 (3)

20122 (6)

20134 (12)

20141 (3)

20153 (9)

20164 (12)

20175 (15)

20186 (18)

20195 (15)
mHealtha intervention

SMS messaging14 (42)

Mobile phone app5 (15)

Mobile phone4 (12)

CDRb aggregate analysis2 (6)

Voice and SMS messaging2 (6)

Mobile phone survey2 (6)

Tablet2 (6)

Computer-assisted personal interviewing1 (3)

Telemedicine1 (3)
Study design

Observational23 (70)

Mixed methods4 (12)

Descriptive report2 (6)

Modelling2 (6)

Quasiexperimental1 (3)

Randomized controlled trial1 (3)
Area of focus

HIV/AIDS15 (45)

Reproductive health4 (12)

Infectious disease3 (9)

Noncommunicable disease3 (9)

Eye and vision health2 (6)

Maternal and child health2 (6)

Data management1 (3)

Image-based health1 (3)

Telemedicine2 (3)

amHealth: mobile health.

bCDR: call detail record.

Table 2. Descriptive themes identified regarding ethical, legal, regulatory, and sociocultural concerns of mobile health (mHealth) interventions and mobile phone data use.
Studies and countriesDomain of concernmHealth interventionKey recommendation
Adequate informed consent

Uganda [34,35], Kenya [36]Cannot consent due to failed understanding of technologyComputer-assisted personal interviewing, mobile phone surveys, telemedicineParticipants’ inadequate understanding of the capabilities of mHealth interventions; thus, the question of whether they understood sufficiently to properly consent was raised

Tanzania and Uganda [37]Consent must be a prerequisite to mHealth interventionsImage-based mHealth appNot provided

Kenya [38]Consent needed for different types of prevention of mother-to-child transmission informationSMS text messagingNot provided
Privacy and confidentiality

Uganda [39-48]Password/PINa protectionSMS text messaging, mobile job aid, mobile phone toolUse of PIN and passwords offers protection of confidentiality. However, the mere presence of passwords may arouse suspicion by intimate partners and others

Kenya [38,49-53]Phone theft, data breachesSmartphone appNot provided

Tanzania [16,18,54,55]Phone sharingSmartphone appNot provided
Data security and protection

Tanzania [56-58]Data breaches, phone theft, access rights to protect client dataSmartphone app, mobile job aid, mobile appmHealth interventions should have an eye toward maternal perception of data security, and with prior and ongoing consultation with community members. Locking phones with a password improves the ability of CHWsb to maintain confidentiality of their clients’ information, particularly for women who did not want to disclose their use of family planning to their husband or other family members

Kenya [50,59]Phone theftSMS text messaging, smartphone ophthalmic examNot provided

Uganda [34,35]Mobile phone numbers linked to national ID cardsComputer-assisted personal interviewing, interactive voice surveyNot provided
Sociocultural

Tanzania [56,60]Breach of pregnancy-related informationMobile phone appSupport from male heads of household may be important in implementing successful mHealth interventions

Uganda [43]Gender dynamics, delivery of interactive voice survey in voice of opposite sexInteractive voice survey, SMS messagingPreference of male or female voices for phone call interventions may vary based on the patient’s gender
Regulatory/legal

Tanzania [56]Data protection legislationMobile phone appData protection legislation is needed in regions where local dynamics are important when protecting individuals’ health data

Uganda [35]National ethics guidelinesInteractive voice surveyNot provided

aPIN: personal identification number.

bCHW: community health worker.

Ethical Concerns

Adequate Informed Consent

Five studies (15%) described adequate consent concerns pertaining to mHealth technology use. In Uganda, participants feared that computer-assisted personal interviews to collect maternal health data also involved audio recording of their responses. To address this concern, the researchers reiterated the need to ensure that participants clearly understand how the technology works and answer any questions during the consent process [34]. In addition, Mwaka and colleagues [35] echoed the importance of understanding consent requirements and how local cultural norms impact participation in mobile phone–based surveys.

In Kenya, researchers questioned the validity of informed consent when there are English words that have no direct equivalent translation in a native local dialect such as Kiswahili. For example, one study [36] found that more than half of the participants did not understand several translated words such as “videoconference,” “store and forward,” “digital photograph,” “wireless,” or “email” in either language. Thus, a combination of words was needed to explain telemedicine terms; nevertheless, the participants seemed to have a poor understanding, thereby threatening the validity of the consent process [36]. Jennings and colleagues [38] further pointed out the need to include a standardized technology orientation for prevention of mother-to-child transmission (PMTCT) to ensure adequate informed consent. The technology orientation should be applicable to all users regardless of their specific health condition.

Privacy and Confidentiality

Among the 33 included studies, 22 (67%) described privacy and confidentiality concerns regarding utilizing mHealth technology and mobile phone data. Specifically, two studies were not focused directly on end-user experiences regarding privacy and confidentiality, but highlighted the need for additional research on how mHealth technologies could improve patient privacy [61,62].

Four studies conducted in Uganda explored an SMS-based intervention to support care among people living with HIV/AIDS (PLWHA) and revealed mixed results. Some participants had no privacy concerns related to disclosure of their personal health–related information, including their HIV status [39-42]. For example, participants believed that using personal identification numbers or passwords increased protection of their individual data. End users completing health surveys using interactive voice response (IVR) technology in Uganda also indicated that their confidentiality was increased by using mobile phone–based surveys [43].

Moreover, there were increased privacy concerns in situations where the participants had not disclosed their HIV status to family members or friends, especially when a phone was shared. Three studies in Uganda described privacy and confidentiality concerns pertaining to the use of SMS-based reminders for medication adherence, fearing that they could result in unintended HIV status disclosure when messages are seen by others [44,45,54]. Similar privacy and confidentiality concerns were expressed among pregnant HIV-infected women in Kenya indicating opposition to receiving messages with HIV-related terms such as “infection” or “medication,” in fear that it would disclose their HIV status [49]. Additionally, perceptions of data privacy may differ between health care workers and patients. Two studies in Uganda focused on the impact of using mHealth interventions to improve care among PLWHA. The community health workers (CHWs) expressed concerns of threat to data confidentiality if the phone is stolen or multimedia capabilities are misused, while the participants perceived the smartphone to protect their confidentiality [46,47].

In Kenya, end users of mHealth technologies supporting PMTCT, antiretroviral therapy (ART) adherence, and family planning indicated that their personal privacy was protected while discussing sensitive health matters via call or text compared to face-to-face encounters [38,50-52]. Similarly, two other studies in Kenya [55] and Tanzania [53], respectively, found minimal confidentiality concerns among participants using a smartphone to support family planning services and HIV testing. Moreover, participants indicated that they were more likely to answer questions honestly using the mHealth intervention compared to speaking in person with a provider or attending a clinic [53,55].

Aggregated and anonymized CDR data may present minimal ethical and privacy concerns when compared to individual-level or other mobile phone data. Tatem and colleagues [18] analyzed aggregate-level CDRs in Tanzania to inform malaria elimination. The researchers did not explicitly explore privacy and confidentiality concerns, but they noted that aggregated and anonymized CDRs could support analysis without compromising the privacy of the mobile phone users. Wesolowski and colleagues [16] also used aggregated and anonymized mobile phone data in the form of CDRs combined with community health surveys in Kenya to study the impact of travel on the transmission dynamics of malaria. Again, the researchers did not examine privacy concerns directly, but pointed out privacy concerns as a potential barrier to the availability of CDR data for health research.

Data Security and Protection

Seven of the 33 studies (21%) described data security and protection concern among users. Two studies in Tanzania described mixed levels of data security and protection concerns between CHWs and their female clients during the use of mHealth interventions to improve the quality of maternal and family planning services [56,57]. CHWs had positive views when using smartphones to collect reproductive health data from their clients. They noted that using mobile technology improved data security and protection of clients’ privacy. However, some of the female clients expressed concerns about potential data breaches if personal information related to their pregnancy is stored on the smartphone and accidentally shared. In Kenya, a few data security and protection concerns were reported when researchers analyzed the perceptions of HIV-infected patients toward a mobile phone messaging intervention to support ART adherence [50]. In rural Uganda, Mercader and colleagues [34] assessed the acceptability of computer-assisted personal interviewing for maternal, newborn, and child health surveys, and concluded that respondents perceived personal health data recorded on tablets as more secure than paper surveys.

In Uganda, the new requirement to link the National Identification Number (NIN) with one’s personal phone number is perceived as a threat to data privacy and security. Mwaka and colleagues [35] explored the views of 14 key stakeholders regarding the potential challenges for obtaining consent during implementation of mobile phone surveys for IVR-based noncommunicable disease research. Some key informants highlighted overlapping concerns regarding data security and privacy where the identity of the respondent can be traced through the linkage between the NIN and phone number. In Kenya, health care providers and stakeholders expressed data security and protection concerns in using a smartphone-based ophthalmic exam, recommending a secure data encryption system to protect personal data [59].

In Tanzania, Steiner and colleagues [58] reviewed four field applications of a mobile device deployed to support low-resourced countries with data entry and project monitoring. The researchers created a data collection platform with user-defined access rights to ensure the data security and protection of clients [58]. During a 3-day workshop focused on addressing ethical issues of safety and privacy among mHealth developers and users in low-resource settings, the authors gathered solutions from 27 mHealth stakeholders from various geographical regions, including Uganda and Tanzania [37]. The stakeholders concluded that patient authorization and informed consent must remain prerequisites to mHealth interventions, specifically during the implementation and scale-up stages.

Sociocultural Issues

Three mHealth studies (9%) described concerns related to complex gender dynamics and sociocultural beliefs. In Tanzania, two studies revealed gender-based power imbalances among women and men. Female participants reported low mobile phone ownership and expressed concerns about spouses being suspicious that if a wife owned a phone, it may facilitate infidelity in the relationship [56,60]. In Uganda, female participants expressed sociocultural concerns pertaining to using mHealth interventions to support health. For example, some participants were reluctant to use IVR for health purposes because of community beliefs that there are “evil spirits” that could claim the life of the recipient if one received unknown calls. In addition, women participants were particularly apprehensive about IVR surveys being sent to their cell phones if they were being administered in a male voice; they feared that this would raise suspicion of cheating by their spouses and could spark domestic violence [43]. Phone sharing is particularly common in countries within Africa, thus creating another potential source of privacy breaches and sociocultural concerns.

Regulatory and Legal Issues

Two studies raised regulatory and legal concerns regarding using mHealth technology. These studies reflect the perspectives of the researchers governing the studies and the key stakeholders surveyed. In Tanzania, researchers concluded that the findings of their study on reproductive health provided impetus for stronger data protection legislation in regions such as rural Tanzania [56]. Protecting individuals’ health data is particularly important given the inherent sociocultural beliefs surrounding the secrecy of health information [56]. In Uganda, researchers indicated that the processes for mobile phone surveys should follow standard international regulatory guidelines for sharing personal information while also ensuring alignment with existing local laws and policies [35].


Principal Findings

The aim of this scoping review was to synthesize the current state of evidence on the ethical, sociocultural, legal, and regulatory concerns related to the use of mHealth technologies and mobile phone data for public health research in the East Africa region. Our review builds on a growing body of work examining concerns with mHealth data security, privacy, and confidentiality [24]. To our knowledge, this is the first study to synthesize end-user and public health research concerns pertaining to mobile phone data use in the East Africa region. Five interrelated themes emerged as key concerns with the use of mobile phone data and mHealth interventions: adequate informed consent, privacy and confidentiality, data security and protection, sociocultural issues, and regulatory/legal issues. Of equal concern is the collection, use, and sharing of personal information such as CDRs to third parties without the notice or consent of consumers. Countries need to put in place legislation to protect the privacy and secure these personal data while facilitating their use for the good of the populations. In the future, these themes and others could inform the formulation of a framework for ethical regulatory policies using mHealth in the East African Community (EAC) region.

African countries have rapidly adopted the use of mobile technologies to support their daily needs such as social, economic, education, and travel needs, among many others. Specifically, the East African region shows a dominance in the adoption of mHealth programs to overcome some structural barriers in the health system [63]. Studies in high-income countries deploying mHealth interventions have revealed concerns mostly related to data privacy, security, storage, and transmission [64-66]. In contrast, most studies in the East African region highlight concerns about the potential disclosure of personal health information at the user interface, such as reading text messages. The pace of development and access to mobile technology could partly explain these differences in concerns between high- and low-income settings.

Sociocultural issues seem to influence the differential levels of positive and negative perceptions around data privacy and confidentiality concerns by gender and user group across the East African region (see Multimedia Appendix 2). For example, privacy and confidentiality concerns in Uganda and Tanzania highlighted gender norms and cultural beliefs that exist around secrecy about pregnancy and childbirth due to a fear of supernatural powers that could cause harm to the mother and unborn child. These beliefs could inhibit the willingness to share pregnancy-related personal information via the phone [67,68]. In addition, the issues of phone sharing due to limited mobile phone ownership among women could precipitate sociocultural tensions. For example, spousal conflicts and violence, especially directed toward female mHealth users, have been reported when women receive various forms of health support from male health care workers. Although mHealth interventions are beneficial, implementers must be mindful to anticipate the issues that may result from phone sharing in the cultural context of Africa [69].

mHealth data have the potential to enhance or jeopardize privacy. For example, the HIV-related stigma and discrimination among PLWHA in Africa could be attenuated if disclosure of HIV status is kept confidential. The findings of this scoping review suggest that among PLWHA mHealth interventions, supporting patient care should be accompanied by unique personal identification numbers or passwords to facilitate protection of privacy and confidentiality of HIV-related information. Several studies from Kenya and Uganda revealed that populations experienced difficulty in understanding the capability of mHealth interventions, which in turn raises questions about the informed consent process [34-36].

The lack of comprehensive ethical frameworks to guide the use of mHealth in public health research and practice remains a challenge across countries in the EAC region [70]. Very few studies included in this review explored the legal concerns of data use beyond pointing to the need for legal and regulatory policies for data protection and privacy of personal data. In 2018, MEASURE Evaluations published a report of guidelines developed for Kenya and Tanzania to help mHealth program managers and Ministry of Health officials systematically address mHealth data privacy and security issues [24]. The authors acknowledged that the guidelines were limited in scope, only serving as a building block that would allow stakeholders to be informed, and guide the teams responsible for developing and implementing responsible data practices, especially data security and privacy.

Legal regulation of personal health information within the EAC is not uniformly developed. The Republic of Uganda [33] and the Republic of Kenya [71] passed their data protection laws in 2019, whereas Rwanda passed a similar law in 2021 [72]. Tanzania currently has a draft data protection bill that has not yet passed into law, whereas Burundi does not have a law that specifically regulates personal data protection. Based on the experience of our health research team in Uganda, the new law is not yet operationalized into clear policy guidance, particularly in the context of public health research and practice. As such, we have encountered barriers to access CDR data from telecommunication companies even when we present written and signed consent from the cell phone owners. To the greatest extent possible, each nation needs to cooperate to set up regional mobile technology standards reflecting its local situations and government policy regulations [65]. The results of our scoping review serve to highlight concerns and gaps that must be addressed to create an enabling policy and regulatory environment for public health researchers. Additionally, public views on the use of CDRs in health research must also be explored.

Future Implications for Public-Private Partnerships

Our work has implications for public-private partnerships, given the potential mutual benefits from CDRs, a largely untapped emerging data type that is collected by telecommunication companies in the EAC region. First, the public and private sectors could share expert human capital financial and infrastructural resources to catalyze the growth of these entities within the region. For example, the public health research enterprise could quickly access a large quantity of rich data on spatial and temporal mobility patterns of the population, which are routinely collected but underutilized by telecommunication companies. This approach to collecting specific data would likely be far more efficient and cost-effective than traditional methods. Second, the private sector could gain new business insights about the populations they serve based on a range of geospatial or data-mining analyses and interpretations generated by public researchers and data scientists. In Africa, many lessons can be learned from major innovations in banking and agriculture that have already spawned from the extensive digital infrastructure. Lastly, we envision a unique opportunity for the public health and private sectors to engage jointly with regulatory policymakers to advance data governance policies for mutual benefit. It is important to note that this process will likely be dynamic given the rapidly evolving mobile technology landscape.

Limitations

This scoping review has some limitations. First, we acknowledge that we might have missed studies relevant to mHealth and ethical, legal, or privacy concerns in the East Africa region if they were published in electronic databases other than PubMed, in a language other than English, or outside of the period of our study. Second, studies published from Rwanda and Burundi may have been excluded from this review specifically because English was specified as the only language for articles that met other inclusion criteria. In this case, any published articles written in French could have been excluded; however, during our search, we did not identify any such articles in the initial screening. Overall, we believe that the majority of the public health research articles are accessible through PubMed. Therefore, we do not expect that our findings and conclusions were significantly influenced by any papers we might have missed.

Conclusions

This scoping review identified major cross-cutting ethical, regulatory, and sociocultural concerns related to use of data from mobile technologies in the East African region. A comprehensive framework that accounts for ethical, sociocultural, legal, and regulatory concerns in the cultural context of the EAC region is needed to guide the safe use of mobile technology data for public health research purposes.

Acknowledgments

We acknowledge the contributions of Abirami Balajee in coordination of the initial PubMed search, literature review, and assistance in the initial data abstraction process. This study was funded through the National Institutes of Health/National Institute of Allergy and Infectious Diseases administrative supplement (2R01AI093856-06AI).

Authors' Contributions

Conceptualization: JNS, CCW, RK, ESM, NK; Data Review and Abstraction: CB, CH, KM; Methodology and Formal Analysis: KM, CB, CH, JNS, PDO; Supervision: JNS, PD-O; Writing original draft: KM, JNS; Writing reviewing editing to final manuscript: JNS, KM, CB, PD-O, CH, RK, NK, CCW, ESM. All authors approved the final version of the manuscript for submission.

Conflicts of Interest

None declared.

Multimedia Appendix 1

Data sharing pathways for mobile phone records in mHealth and public health research.

DOCX File , 157 KB

Multimedia Appendix 2

Positive and negative perceptions about privacy, confidentiality, and safety of data collected with mobile phones.

DOCX File , 137 KB

  1. Schuttner L, Sindano N, Theis M, Zue C, Joseph J, Chilengi R, et al. A mobile phone-based, community health worker program for referral, follow-up, and service outreach in rural Zambia: outcomes and overview. Telemed J E Health 2014 Aug;20(8):721-728 [FREE Full text] [CrossRef] [Medline]
  2. Parasuraman S, Sam A, Yee SK, Chuon BC, Ren L. Smartphone usage and increased risk of mobile phone addiction: a concurrent study. Int J Pharma Investig 2017;7(3):125. [CrossRef]
  3. The Mobile Economy sub-Saharan Africa. GSMA. 2020.   URL: https://www.gsma.com/mobileeconomy/sub-saharan-africa/ [accessed 2021-05-11]
  4. WHO Global Observatory for eHealth. mHealth: new horizons for health through mobile technologies: second global survey on eHealth. Geneva: World Health Organization; 2011.
  5. Källander K, Tibenderana JK, Akpogheneta OJ, Strachan DL, Hill Z, ten Asbroek AHA, et al. Mobile health (mHealth) approaches and lessons for increased performance and retention of community health workers in low- and middle-income countries: a review. J Med Internet Res 2013 Jan 25;15(1):e17 [FREE Full text] [CrossRef] [Medline]
  6. Dawood N, Mahomed Asmail F, Louw C, Swanepoel DW. Mhealth hearing screening for children by non-specialist health workers in communities. Int J Audiol 2021 Apr 12;60(sup1):S23-S29. [CrossRef] [Medline]
  7. Sekandi JN, Buregyeya E, Zalwango S, Dobbin KK, Atuyambe L, Nakkonde D, et al. Video directly observed therapy for supporting and monitoring adherence to tuberculosis treatment in Uganda: a pilot cohort study. ERJ Open Res 2020 Jan 06;6(1):00175-2019 [FREE Full text] [CrossRef] [Medline]
  8. Labrique AB, Vasudevan L, Kochi E, Fabricant R, Mehl G. mHealth innovations as health system strengthening tools: 12 common applications and a visual framework. Glob Health Sci Pract 2013 Aug 06;1(2):160-171. [CrossRef]
  9. The NIOH. Harnessing Data Science for Health Discovery and Innovation in Africa (DS-I Africa) Research Hubs (U54–Clinical Trial Optional). National Institutes of Health Department of Health and Human Services.   URL: https://grants.nih.gov/grants/guide/rfa-files/RFA-RM-20-015.html [accessed 2021-05-11]
  10. Harnessing Data Science for Health Discovery and Innovation in Africa (DS-I Africa): Ethical, Legal, and Social Implications Research (U01 – Clinical Trial Not Allowed). National Institutes of Health Department of Health and Human Services.   URL: https://grants.nih.gov/grants/guide/rfa-files/RFA-RM-20-017.html [accessed 2021-05-11]
  11. Milusheva S. Managing the spread of disease with mobile phone data. J Dev Econ 2020 Nov;147:102559 [FREE Full text] [CrossRef] [Medline]
  12. Pindolia DK, Garcia AJ, Wesolowski A, Smith DL, Buckee CO, Noor AM, et al. Human movement data for malaria control and elimination strategic planning. Malar J 2012 Jun 18;11(1):205 [FREE Full text] [CrossRef] [Medline]
  13. Wesolowski A, Eagle N, Tatem AJ, Smith DL, Noor AM, Snow RW, et al. Quantifying the impact of human mobility on malaria. Science 2012 Oct 12;338(6104):267-270 [FREE Full text] [CrossRef] [Medline]
  14. Jones KH, Daniels H, Heys S, Ford DV. Challenges and potential opportunities of mobile phone call detail records in health research: review. JMIR Mhealth Uhealth 2018 Jul 19;6(7):e161 [FREE Full text] [CrossRef] [Medline]
  15. The Mobile Economy West Africa. GMSA. 2018.   URL: https://tinyurl.com/2nzc3c69 [accessed 2021-05-11]
  16. Wesolowski A, Metcalf CJE, Eagle N, Kombich J, Grenfell BT, Bjørnstad ON, et al. Quantifying seasonal population fluxes driving rubella transmission dynamics using mobile phone data. Proc Natl Acad Sci U S A 2015 Sep 01;112(35):11114-11119 [FREE Full text] [CrossRef] [Medline]
  17. Buckee CO, Wesolowski A, Eagle NN, Hansen E, Snow RW. Mobile phones and malaria: modeling human and parasite travel. Travel Med Infect Dis 2013 Jan;11(1):15-22 [FREE Full text] [CrossRef] [Medline]
  18. Tatem AJ, Qiu Y, Smith DL, Sabot O, Ali AS, Moonen B. The use of mobile phone data for the estimation of the travel patterns and imported Plasmodium falciparum rates among Zanzibar residents. Malar J 2009 Dec 10;8(1):287 [FREE Full text] [CrossRef] [Medline]
  19. Leidig JT, Thelsen C, Vogel N, Scripps J, Wolffe G. Modeling Ebola virus diffusion in Senegal using mobile phone datasets and agent-based simulation. 2015 Presented at: NetMob 2015; April 8-10, 2015; Boston, MA.
  20. Kramer AM, Pulliam JT, Alexander LW, Park AW, Rohani P, Drake JM. Spatial spread of the West Africa Ebola epidemic. R Soc Open Sci 2016 Aug;3(8):160294 [FREE Full text] [CrossRef] [Medline]
  21. Attipoe-Dorcoo S, Delgado R, Gupta A, Bennet J, Oriol NE, Jain SH. Mobile health clinic model in the COVID-19 pandemic: lessons learned and opportunities for policy changes and innovation. Int J Equity Health 2020 May 19;19(1):73 [FREE Full text] [CrossRef] [Medline]
  22. Ming LC, Untong N, Aliudin NA, Osili N, Kifli N, Tan CS, et al. Mobile health apps on COVID-19 launched in the early days of the pandemic: content analysis and review. JMIR Mhealth Uhealth 2020 Sep 16;8(9):e19796 [FREE Full text] [CrossRef] [Medline]
  23. Oliver N, Lepri B, Sterly H, Lambiotte R, Deletaille S, De Nadai M, et al. Mobile phone data for informing public health actions across the COVID-19 pandemic life cycle. Sci Adv 2020 Jun 05;6(23):eabc0764 [FREE Full text] [CrossRef] [Medline]
  24. Spigel L, Wambugu S, Villella C. mHealth Data Security, Privacy, and Confidentiality: Guidelines for Program Implementers and Policymakers. Measure Evaluation. 2018.   URL: https://www.measureevaluation.org/resources/publications/ms-17-125a.html [accessed 2021-05-11]
  25. Oliver N, Matic A, Frias-Martinez E. Mobile network data for public health: opportunities and challenges. Front Public Health 2015 Aug 07;3:189. [CrossRef] [Medline]
  26. Letouzé E, Vinck P, World Bank Group, D4D team. The law, politics and ethics of cell phone data analytics. White Paper series: Data-Pop Alliance. 2015.   URL: https://tinyurl.com/4rn2eav3 [accessed 2011-05-11]
  27. The Belmont report: ethical principles and guidelines for the protection of human subjects of research. US Department of Health & Human Services. 1978.   URL: https://www.hhs.gov/ohrp/regulations-and-policy/belmont-report/index.html [accessed 2021-05-11]
  28. Munn Z, Peters MDJ, Stern C, Tufanaru C, McArthur A, Aromataris E. Systematic review or scoping review? Guidance for authors when choosing between a systematic or scoping review approach. BMC Med Res Methodol 2018 Nov 19;18(1):143 [FREE Full text] [CrossRef] [Medline]
  29. Arksey H, O'Malley L. Scoping studies: towards a methodological framework. Int J Soc Res Method 2005 Feb;8(1):19-32. [CrossRef]
  30. Tricco AC, Lillie E, Zarin W, O'Brien KK, Colquhoun H, Levac D, Tunçalp, et al. PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation. Ann Intern Med 2018 Oct 02;169(7):467-473. [CrossRef]
  31. Arora S, Yttri J, Nilse W. Privacy and security in mobile health (mHealth) research. Alcohol Res 2014;36(1):143-151 [FREE Full text] [Medline]
  32. Cohn SP, National Committee on Vital and Health Statistics. Privacy and confidentiality in the Nationwide Health Information Network. American Health Information Management Association. 2006 Jun 22.   URL: https://library.ahima.org/doc?oid=75960#.YoJAPJPMKi5 [accessed 2021-05-11]
  33. The Data Protection and Privacy Act 2019. Uganda Ministry of Information and Communications Technology. 2019.   URL: https://ict.go.ug/wp-content/uploads/2019/03/Data-Protection-and-Privacy-Act-2019.pdf [accessed 2021-05-11]
  34. Mercader HFG, Kabakyenga J, Katuruba DT, Hobbs AJ, Brenner JL. Female respondent acceptance of computer-assisted personal interviewing (CAPI) for maternal, newborn and child health coverage surveys in rural Uganda. Int J Med Inform 2017 Feb;98:41-46. [CrossRef] [Medline]
  35. Mwaka E, Nakigudde J, Ali J, Ochieng J, Hallez K, Tweheyo R, et al. Consent for mobile phone surveys of non-communicable disease risk factors in low-resource settings: an exploratory qualitative study in Uganda. Mhealth 2019 Aug;5:26. [CrossRef] [Medline]
  36. Odhiambo R, Mars M. Patients' understanding of telemedicine terms required for informed consent when translated into Kiswahili. BMC Public Health 2018 May 03;18(1):588 [FREE Full text] [CrossRef] [Medline]
  37. Laflamme L, Chipps J, Fangerau H, Juth N, Légaré F, Sawe HR, et al. Targeting ethical considerations tied to image-based mobile health diagnostic support specific to clinicians in low-resource settings: the Brocher proposition. Glob Health Action 2019 Sep 18;12(1):1666695 [FREE Full text] [CrossRef] [Medline]
  38. Jennings L, Ong'ech J, Simiyu R, Sirengo M, Kassaye S. Exploring the use of mobile phone technology for the enhancement of the prevention of mother-to-child transmission of HIV program in Nyanza, Kenya: a qualitative study. BMC Public Health 2013 Dec 05;13(1):1131 [FREE Full text] [CrossRef] [Medline]
  39. Campbell JI, Aturinda I, Mwesigwa E, Burns B, Santorino D, Haberer JE, et al. The Technology Acceptance Model for Resource-Limited Settings (TAM-RLS): a novel framework for mobile health interventions targeted to low-literacy end-users in resource-limited settings. AIDS Behav 2017 Nov 18;21(11):3129-3140 [FREE Full text] [CrossRef] [Medline]
  40. Siedner MJ, Haberer JE, Bwana MB, Ware NC, Bangsberg DR. High acceptability for cell phone text messages to improve communication of laboratory results with HIV-infected patients in rural Uganda: a cross-sectional survey study. BMC Med Inform Decis Mak 2012 Jun 21;12(1):56 [FREE Full text] [CrossRef] [Medline]
  41. Siedner MJ, Santorino D, Haberer JE, Bangsberg DR. Know your audience: predictors of success for a patient-centered texting app to augment linkage to HIV care in rural Uganda. J Med Internet Res 2015 Mar 24;17(3):e78 [FREE Full text] [CrossRef] [Medline]
  42. Kunutsor S, Walley J, Katabira E, Muchuro S, Balidawa H, Namagala E, et al. Using mobile phones to improve clinic attendance amongst an antiretroviral treatment cohort in rural Uganda: a cross-sectional and prospective study. AIDS Behav 2010 Dec 11;14(6):1347-1352. [CrossRef] [Medline]
  43. Ssemugabo C, Rutebemberwa E, Kajungu D, Pariyo GW, Hyder AA, Gibson DG. Acceptability and use of interactive voice response mobile phone surveys for noncommunicable disease behavioral risk factor surveillance in rural Uganda: qualitative study. JMIR Form Res 2019 Dec 03;3(4):e15000 [FREE Full text] [CrossRef] [Medline]
  44. Musiimenta A, Atukunda EC, Tumuhimbise W, Pisarski EE, Tam M, Wyatt MA, et al. Acceptability and feasibility of real-time antiretroviral therapy adherence interventions in rural Uganda: mixed-method pilot randomized controlled trial. JMIR Mhealth Uhealth 2018 May 17;6(5):e122. [CrossRef] [Medline]
  45. Rana Y, Haberer J, Huang H, Kambugu A, Mukasa B, Thirumurthy H, et al. Short message service (SMS)-based intervention to improve treatment adherence among HIV-positive youth in Uganda: focus group findings. PLoS One 2015 Apr 16;10(4):e0125187 [FREE Full text] [CrossRef] [Medline]
  46. Chang LW, Kagaayi J, Arem H, Nakigozi G, Ssempijja V, Serwadda D, et al. Impact of a mHealth intervention for peer health workers on AIDS care in rural Uganda: a mixed methods evaluation of a cluster-randomized trial. AIDS Behav 2011 Nov 8;15(8):1776-1784 [FREE Full text] [CrossRef] [Medline]
  47. Chang LW, Njie-Carr V, Kalenge S, Kelly JF, Bollinger RC, Alamo-Talisuna S. Perceptions and acceptability of mHealth interventions for improving patient care at a community-based HIV/AIDS clinic in Uganda: a mixed methods study. AIDS Care 2013 May 08;25(7):874-880 [FREE Full text] [CrossRef] [Medline]
  48. Hermans S, Elbireer S, Tibakabikoba H, Hoefman B, Manabe Y. Text messaging to decrease tuberculosis treatment attrition in TB-HIV coinfection in Uganda. Patient Prefer Adherence 2017;11:1479-1487. [CrossRef] [Medline]
  49. Ronen K, Unger JA, Drake AL, Perrier T, Akinyi P, Osborn L, et al. SMS messaging to improve ART adherence: perspectives of pregnant HIV-infected women in Kenya on HIV-related message content. AIDS Care 2018 Apr 18;30(4):500-505 [FREE Full text] [CrossRef] [Medline]
  50. Kinyua F, Kiptoo M, Kikuvi G, Mutai J, Meyers AF, Muiruri P, et al. Perceptions of HIV infected patients on the use of cell phone as a tool to support their antiretroviral adherence; a cross-sectional study in a large referral hospital in Kenya. BMC Public Health 2013 Oct 21;13(1):987 [FREE Full text] [CrossRef] [Medline]
  51. Vahdat HL, L'Engle KL, Plourde KF, Magaria L, Olawo A. There are some questions you may not ask in a clinic: providing contraception information to young people in Kenya using SMS. Int J Gynaecol Obstet 2013 Nov 02;123(Suppl 1):e2-e6 [FREE Full text] [CrossRef] [Medline]
  52. Velloza J, Ngure K, Kiptinness C, Quame-Amaglo J, Thuo N, Dew K, et al. A clinic-based tablet application to support safer conception among HIV serodiscordant couples in Kenya: feasibility and acceptability study. Mhealth 2019 Feb;5:4. [CrossRef] [Medline]
  53. Dev R, Woods NF, Unger JA, Kinuthia J, Matemo D, Farid S, et al. Acceptability, feasibility and utility of a Mobile health family planning decision aid for postpartum women in Kenya. Reprod Health 2019 Jul 08;16(1):97 [FREE Full text] [CrossRef] [Medline]
  54. Atukunda EC, Musiimenta A, Musinguzi N, Wyatt MA, Ashaba J, Ware NC, et al. Understanding patterns of social support and their relationship to an ART adherence intervention among adults in rural southwestern Uganda. AIDS Behav 2017 Feb 26;21(2):428-440 [FREE Full text] [CrossRef] [Medline]
  55. Conserve DF, Muessig KE, Maboko LL, Shirima S, Kilonzo MN, Maman S, et al. Mate Yako Afya Yako: Formative research to develop the Tanzania HIV self-testing education and promotion (Tanzania STEP) project for men. PLoS One 2018 Aug 27;13(8):e0202521 [FREE Full text] [CrossRef] [Medline]
  56. Hackett KM, Kazemi M, Sellen DW. Keeping secrets in the cloud: mobile phones, data security and privacy within the context of pregnancy and childbirth in Tanzania. Soc Sci Med 2018 Aug;211:190-197. [CrossRef] [Medline]
  57. Braun R, Lasway C, Agarwal S, L'Engle K, Layer E, Silas L, et al. An evaluation of a family planning mobile job aid for community health workers in Tanzania. Contraception 2016 Jul;94(1):27-33. [CrossRef] [Medline]
  58. Steiner A, Hella J, Grüninger S, Mhalu G, Mhimbira F, Cercamondi CI, et al. Managing research and surveillance projects in real-time with a novel open-source eManagement tool designed for under-resourced countries. J Am Med Inform Assoc 2016 Sep;23(5):916-923. [CrossRef] [Medline]
  59. Lodhia V, Karanja S, Lees S, Bastawrous A. Acceptability, usability, and views on deployment of Peek, a mobile phone mHealth intervention for eye care in Kenya: qualitative study. JMIR Mhealth Uhealth 2016 May 09;4(2):e30 [FREE Full text] [CrossRef] [Medline]
  60. Thobias J, Kiwanuka A. Design and implementation of an m-health data model for improving health information access for reproductive and child health services in low resource settings using a participatory action research approach. BMC Med Inform Decis Mak 2018 Jun 25;18(1):45 [FREE Full text] [CrossRef] [Medline]
  61. Kivuti-Bitok LW, McDonnell G, Pokhariyal GP, Roudsari AV. Self-reported use of internet by cervical cancer clients in two National Referral Hospitals in Kenya. BMC Res Notes 2012 Oct 09;5(1):559 [FREE Full text] [CrossRef] [Medline]
  62. Henry JV, Winters N, Lakati A, Oliver M, Geniets A, Mbae SM, et al. Enhancing the supervision of community health workers with WhatsApp mobile messaging: qualitative findings from 2 low-resource settings in Kenya. Glob Health Sci Pract 2016 May 26;4(2):311-325. [CrossRef]
  63. Lee S, Cho Y, Kim S. Mapping mHealth (mobile health) and mobile penetrations in sub-Saharan Africa for strategic regional collaboration in mHealth scale-up: an application of exploratory spatial data analysis. Global Health 2017 Aug 22;13(1):63 [FREE Full text] [CrossRef] [Medline]
  64. Altmann S, Milsom L, Zillessen H, Blasone R, Gerdon F, Bach R, et al. Acceptability of app-based contact tracing for COVID-19: cross-country survey study. JMIR Mhealth Uhealth 2020 Aug 28;8(8):e19857 [FREE Full text] [CrossRef] [Medline]
  65. Whittaker R. Issues in mHealth: findings from key informant interviews. J Med Internet Res 2012 Oct 02;14(5):e129 [FREE Full text] [CrossRef] [Medline]
  66. Schnall R, Higgins T, Brown W, Carballo-Dieguez A, Bakken S. Trust, perceived risk, perceived ease of use and perceived usefulness as factors related to mHealth technology use. Stud Health Technol Inform 2015;216:467-471 [FREE Full text] [Medline]
  67. Spangler SA, Bloom SS. Use of biomedical obstetric care in rural Tanzania: the role of social and material inequalities. Soc Sci Med 2010 Aug;71(4):760-768. [CrossRef] [Medline]
  68. Mgata S, Maluka SO. Factors for late initiation of antenatal care in Dar es Salaam, Tanzania: a qualitative study. BMC Pregnancy Childbirth 2019 Nov 12;19(1):415 [FREE Full text] [CrossRef] [Medline]
  69. Jones KH, Daniels H, Heys S, Ford DV. Toward an ethically founded framework for the use of mobile phone call detail records in health research. JMIR Mhealth Uhealth 2019 Mar 22;7(3):e11969 [FREE Full text] [CrossRef] [Medline]
  70. mHealth Regulation Impact Assessment: Africa. Mobile for Development mHealth. GSMA. 2015.   URL: https://tinyurl.com/yz5nmn3f [accessed 2021-05-11]
  71. The Data Protection Act, 2019. Office of the Data Protection Commissioner Kenya. 2019.   URL: https://www.odpc.go.ke/dpa-act/ [accessed 2021-05-11]
  72. Rwanda: Data protection law published in the Official Gazette. DataGuidance. 2021 Oct 18.   URL: https://www.dataguidance.com/news/rwanda-data-protection-law-published-official-gazette [accessed 2022-05-16]


ART: antiretroviral therapy
CDR: call detail record
CHW: community health worker
DS-I Africa: Harnessing Data Science for Health Discovery and Innovation in Africa
EAC: East African Community
IVR: interactive voice response
MATTS: Mapping Tuberculosis Transmission Study
mHealth: mobile health
NIH: National Institutes of Health
NIN: National Identification Number
PLWHA: people living with HIV/AIDS
PMTCT: prevention of mother-to-child transmission
PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-analyses


Edited by T Leung; submitted 19.11.21; peer-reviewed by D Lizotte, U Bork; comments to author 09.12.21; revised version received 17.02.22; accepted 14.04.22; published 02.06.22

Copyright

©Juliet Nabbuye Sekandi, Kenya Murray, Corinne Berryman, Paula Davis-Olwell, Caroline Hurst, Robert Kakaire, Noah Kiwanuka, Christopher C Whalen, Erisa Sabakaki Mwaka. Originally published in the Interactive Journal of Medical Research (https://www.i-jmr.org/), 02.06.2022.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Interactive Journal of Medical Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.i-jmr.org/, as well as this copyright and license information must be included.