Contextual success and pitfalls of mHealth service for maternal and child health in Africa: An Intervention, Context, Actors, Mechanism, and Outcome (ICAMO) framework guided systematic review of qualitative evidence

Abstract

Introduction

Mobile health (mHealth) interventions have shown potential to improve maternal and child health outcomes in Africa, but their effectiveness depends on specific interventions, context, and implementation quality. Challenges such as limited infrastructure, low digital literacy, and sustainability need to be addressed. Further evaluation studies are essential to summarize the impact of mHealth interventions. Thus, this synthesis focuses on qualitative evidence of the impact of mHealth on maternal and child health in Africa to summarize such evidence to help policy decisions.

Methods

A qualitative systematic review guided by the concepts of Intervention, Context, Mechanism, and Outcome (ICAMO) was employed in this study. The GRADE CERQual assessment and methodological constraints tools were utilized in the review to ascertain the level of confidence in the evidence and to examine the methodological limitations. The JBI checklist for qualitative research appraisal was also consulted during the review.

Results

The current review contains 32 eligible studies from databases such as CINAHL, EMBASE, MEDLINE, Scopus, Web of Science, HINARI, and Cochrane Library. The review demonstrated substantial improvements in the HCP-woman relationship, communication system, maternal and child healthcare uptake, health-seeking behavior, and HCP skills. Economic capacities, maternal education, and the low quality of existing services challenged participants.

Conclusion

mHealth significantly improves maternal and child health outcomes in Africa. This review showed it can improve healthcare access, empower women, and contribute to the region's goal of universal health coverage. However, the challenges such as low partner support, high costs for services, and poor quality of current care as narrated by women need commitment from health authorities in the continent. The evidence from this review suggests that mHealth can be implemented to improve maternal and child health in Africa.

Trial registration

PROSPERO: CRD42023461425.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12884-024-06885-2.

Introduction

The World Health Organization (WHO) reports a significant maternal and child health variation between industrialized and low and middle-income countries [1]. Most maternal deaths (99%) take place in less developed nations [2, 3]. Additionally, there is a significant discrepancy in child mortality between developed and low and middle-income countries, with low and middle-income countries accounting for the higher percentage of child deaths [4].

The experimentally founded importance of using mHealth to improve maternal and child health has been reported in low and middle-income countries [5]. Evidence shows that mHealth has been applied directly to mothers and health providers to improve maternal and child health [6]. A study conducted in Bangladesh found that mHealth can help to establish consistent contact with expectant mothers, and also pointed out some requirements, such as outlining the nature of communication with both the woman and her husband [7]. Evidence from clinics that implemented Text4Baby in Atlanta shows mothers were happy to receive messages but also reported the disadvantages of low educational status among mothers [8]. Based on voluntarism and philanthropy, the messaging model is crucial for its sustainability and the potential success of future public–private partnerships in mHealth and public health [9]. A study in China found that promoting EBF, delaying complementary feeding, increasing awareness of WHO breastfeeding guidelines, and improving new mothers' knowledge of child-feeding practices are essential areas assisted by mHealth [10]. A Malaysian study found that exclusive breastfeeding and postpartum care-seeking behavior were enhanced by phone lactation counseling [11]. A study conducted in Ahvaz, Iran, demonstrated that mHealth successfully promotes the health of expectant mothers and newborns [12]. Additionally, in Siriraj Hospital, Thailand, mothers who got SMS messages on their phones during prenatal care reported feeling more satisfied than those who did not receive SMS [13]; and a study conducted in Tamil Nadu, India highlighted the potential of mobile text messages to convey a crucial health message about MCH [14].

The potential of mobile health applications to reduce problems related to mother and child health has been recognized on a global scale as highlighted in the WHO digital roadmap and many studies show mobile health applications can lessen difficulties related to the health of mothers and children, particularly in poor nations [15–17].

Maternal and child health has witnessed a steady increase in efforts to leverage mHealth, or mobile health [18]. Evidence demonstrates that low- and middle-income nations, notably those in Africa, stand to gain the most from the convergence of mHealth [18–20]. The concept of remote maternity and child health services is successful in low and middle-income countries, enabling medical personnel to provide remote essential services efficiently [21–23].

Prior data shows that information sources that save mothers' lives in difficult situations include SMS, video, and audio messages via personal computers, mobile devices, the internet, or web-based systems [24–27]. When access restrictions prevent clients from receiving treatment or appointments, the mHealth service notifies them of the upcoming appointments and provides health education [24, 26–28].

Africa is an ideal continent for this study due to its low and middle-income status, high prevalence of mHealth, and the widespread use of cellular messaging apps [18, 25]. The majority of research across the continent utilizes quantitative evidence, but some studies also employ qualitative methodologies for reality checks [19, 29–32]. Qualitative evidence in Africa is abundant but lacks a clear conclusion and summarization, limiting its influence on policy-making affecting mother and child health [31–34]. This disregards the significance of data from direct respondents. The study aims to synthesize qualitative evidence to support policy and decision-making in Africa to reduce maternal and child health problems, focusing on direct respondents.

Review question

1. What works, for whom, why, in what situation, and how?’ regarding the application of mHealth to improve maternal and child health services in Africa?

2. What is the available evidence on the experience of mHealth service (challenges, and success stories) during pregnancy and postpartum?

Objective

To summarize evidence on mHealth intervention actors, contexts, mechanisms, and outcomes of using mHealth and maternal experience of mHealth during maternal and child health services during pregnancy and postpartum in Africa.

Methods and materials

Study design

Our study utilized a qualitative systematic review informed by the realism evaluation guided by Pawson and Tilley's conceptual model [35] that includes Intervention, Context, Mechanism, and Outcome (ICAMO). The model was modified by Kabongo et al. [15]. The Intervention, Mechanism, Actors, Context, and Outcome (ICAMO) tool was chosen for its comprehensive coverage of all factors influencing the success or failure of mHealth in Africa.

Model description

In today’s increasingly complex world, there is a growing need to understand and make sense of the various factors that influence social phenomena and outcomes [36]. This requires a more sophisticated approach that considers the complexities of organizational factors, rather than relying on traditional analysis methods [37]. The ICAMO framework can be utilized to develop a program theory within the realism synthesis framework, enhancing understanding of complex factors' relationships and their impact on phenomena and outcomes [38]. This approach identifies antecedents, mediators, moderators, and contextual factors influencing outcomes, aiming to identify key mechanisms and processes and explore their interaction to produce specific outcomes. The ICAMO framework aids researchers in creating program theories that go beyond superficial explanations, examining the underlying mechanisms and causal relationships driving a phenomenon and its outcomes [38]. This method emphasizes the significance of considering multiple viewpoints and gathering diverse evidence to gain a comprehensive understanding of the subject matter [38–40]. A comprehensive understanding can guide interventions and policy decisions, enabling more targeted and effective strategies to tackle complex issues. [39]. The analysis presents an integrative framework examining antecedents, mediators, moderators, and contextual factors influencing consumer behavior, identifying research gaps and proposing future research areas [38–41]. This study examines the effectiveness of mHealth in improving maternal and child health in Africa, establishing a foundation for future research on its impact.

Concept definitions in the adopted model

Intervention: refers to the nature of mHealth interventions including various technologies and non-technology interventions, and modalities (text, video, audio, or others) Mechanism: refers to the causal forces that enable people to choose, believe, perceive, reason, act, and make decisions to use or not use the service Actor: refers to the individuals (women or caregivers), groups, and institutions in the interventions Context: refers to the environment in which interaction between actors’ mechanisms occurs. They can be circumstances, facilitators, and constraints that can be pre-existing, organizational, or sociocultural issues that may influence interventions Outcome: refers to the products of interaction between actors and mechanisms in a given context [38, 41]

Program Theories

Initial Program Theory 1. If resources are made accessible for the deployment of mHealth programs, healthcare providers (HCPs) can further acquire knowledge of how to provide maternity and child health services and can be motivated to use mHealth, which enhances both mHealth applications and service delivery. 2. If mHealth education and assisting tools are supplied with material resources and network connections, women can be motivated or encouraged to improve the uptake of maternal and child health services (Fig. 1).

Inclusion criteria

Qualitative studies with the following properties included in the review were.

1. Published scholarly articles and unpublished gray literature involving a qualitative study design works from 2000 to September 2023 in Africa

2. Population: Pregnant, postnatal, and breastfeeding women or women with children aged < 5 years old who have experience with mHealth from African countries.

3. Interventions: Studies are qualitative and not interventional but explore information on mHealth interventions.

4. Primary outcome: Experiences of mothers or caregivers who used mHealth during pregnancy and breastfeeding.

5. Secondary outcome: Barriers and facilitators that influenced women’s use of mHealth during the pregnancy breastfeeding period.

6. Designs: Qualitative studies regarding mHealth conducted in English

Exclusion criteria

Review studies, study protocols, and quantitative studies targeting the measuring of effect sizes.

Study Status

Only qualitative studies were included in this review. For this study, qualitative studies correspond to those that applied qualitative methods for data collection and analysis [42].

Search strategy and information source

Various methods were followed to develop search strategies as per the eligibility criteria. CINAHL, EMBASE, MEDLINE, Scopus, Web of Science, HINARI, and Cochrane Library. Other websites were the WHO website; mHealth Alliance, a SAGE Preprints Community, Research Gate, AMRC Open Research, and International Development Research Centre reports, profit and nonprofit organizational websites, and the WHO International Clinical Trials Registry Portal. The listed databases were searched after preparing strategies for the search. We also tracked references forward and backward to ensure important information was not missed. Snowballing of references from relevant studies was performed. The first author developed the search strategies and shared them with the rest of the team. We designed a search strategy using setting, study design, and analysis (SSA). We used key terms combined with MeSH terms using Boolean (“AND” and “OR”).

Key Search terms: The above databases were searched for articles published between 2000 and September 2023 using the following Boolean combinations: [“mHealth” AND “maternal health”], [“mobile phone” AND “maternal health” AND “child health”], [“mHealth AND “maternal health services”], [mHealth PRE/15 maternal] and [mHealth PRE/15 maternal AND child AND health] (Supporting Information 1).

Study Selection

Articles searched in the databases were imported into Covidence online software for screening and retrieval of full-text articles. We conducted stepwise screening strategies to identify the studies that are eligible for data extraction using Covidence software. We screened the articles for duplicates and subsequently by their titles, abstracts, and full text sequentially. Two members (GG and EAZ) performed these tasks independently. Disagreements between the reviewers were discussed with the research team and resolved through discussion and consensus. However, the use of manual data was crucial in comprehending complex information and producing effective reports. Studies that miss the main eligibility criteria were excluded.

Data extraction (selection and coding)

Data were extracted in an Excel spreadsheet prepared by the first author (reviewer) and the extraction sheet was tested on 5% of the included studies that were randomly selected. The study characteristics include the author’s name, year of publication, country of origin, objectives, data collection and analysis methods, sample size, recruitment process, population, and short title consistent with the review questions extracted. Key reflections or quotes from participants in the primary studies and authors’ summaries or themes were also extracted (Supporting information 2). The study findings were extracted from the methods, results, discussions, or elsewhere from the articles included in the review and were imported into NVivo software version 14. However, we extracted information related to configuration using a template developed based on the ICAMO framework (Supporting information 3). From the selected articles, data was extracted by two reviewers (GG and EAZ) independently and verified by the research team.

Quality Appraisal and risk of biases

To assess the quality of all studies included in this review, we applied the JBI checklist for qualitative research appraisal [43]. In JBI, each study is evaluated using the ten criteria checklists with scores extending from 0–10. A study may score 0 or 10. Based on the overall scores we label studies as low quality (0–3), moderate quality (4–7), and high quality (8–10). Two reviewers (GG and EAZ) resolved all disagreements through discussion. Consequently, all studies lie in the 8–10 range indicating high quality [43] (Supporting information 4). Only certain criteria such as "Is the researcher's influence on the research or vice versa addressed" and " ‘Is the researcher's influence on the research or vice-versa addressed’", lack clarity. Recommendations Assessment, Development, and Evaluation (GRADE) and Confidence in the Evidence from Reviews of Qualitative Research Synthesis(CERQual) tool applied to assess risk of biases [44]. Secondly, two authors applied the framework for grading studies (EAZ and GG) to evaluate the methodological limitations, relevance, coherence, and adequacy of qualitative research findings.

Strategy for data synthesis

We included and extracted studies as per the eligibility criteria of the review. After generating the data, we refined iteratively to form main themes and subthemes in NVivo. The preliminary and final synthesis get refined through repeated revisions. The final output of the review was presented by consulting enhancing transparency in reporting the synthesis of qualitative research (ENTREQ) reporting guidelines [43, 45].

Results

The review analyzed 32 articles published in Africa from 2015 to 2023, focusing on the impact of mHealth on maternal and child health. Eighty hundred thirty-two articles were identified through database searches, with 283 excluded due to duplication, 493 by title and abstract mismatch, and 14 excluded by other criteria as depicted on the PRISMA diagram (Fig. 2).

Fig. 2.

PRISMA flow diagram showing screening stages of the review

Characteristics of the included studies

The current review contains 32 eligible studies that gathered data through interviews [29, 32, 46–60], in-depth interviews [5, 29, 51, 57, 59, 61–65], key informant interviews (KI) [65–67], observation and document review [52, 59, 64], and FGDs [29, 33, 50, 51, 53, 58, 59, 62, 64, 66, 68–70]. Most studies followed purposive sampling and analyzed data using thematic, framework, and theory-based approaches (Fig. 1). The studies primarily examined the feasibility and acceptability [46, 51, 53, 62, 66, 69], experiences [5, 32, 50, 57, 59, 60, 64, 70, 71], barriers and challenges [47, 54–58, 65], reflections [48], engaging men [68], perspective [48, 52, 62], and perceptions [5, 31] of mHealth adoption in improving maternal and child health in Africa. Most studies used purposive sampling methods, despite some using simple random, convivence, and stratified methods (Supplementary 5).

Fig. 1.

The schematic representation outlines the steps involved in the ICAMO application

Methodological limitations of the studies

Four studies [58, 64, 66, 72] had minor methodological limitations. None of the studies had researcher reflexivity. Overall, the included studies exhibited high methodological quality as per the criteria presented in Table 1.

Table 1.

Methodological limitations in original articles

	Was the context described?	Was the sampling strategy appropriate and described?	Was the data collection strategy appropriate and described?	Was the data analysis appropriate and described?	Were the findings supported by evidence?	Is there evidence of researcher reflexivity?	Have ethical issues have been taken into consideration?	Overall assessment of methodological limitations
Mwase I, 2020 [19, 70]	Yes	Yes	Yes	Yes	Yes	No	Yes	None
Musiimenta A,2021 [46]	Yes	Yes	Yes	Yes	Yes	No	Yes	None
Namatovu HK, 2021 [47]	Yes	Yes	Yes	Yes	Yes	No	Yes	None
Muthelo, L, 2023 [48]	Yes	Yes	Yes	Yes	Yes	No	Yes	None
Itanyi IU, 2023 [71]	Yes	Yes	Yes	Yes	Yes	No	Yes	None
Ayiasi RM, 2015 [61]	Yes	Yes	Yes	Yes	Yes	No	Yes	None
Duclos V, 2017 [49]	Yes	Yes	Yes	Yes	Yes	No	Yes	None
Harrington EK, 2019 [68]	Yes	Yes	Yes	Yes	Yes	No	Yes	None
Thomsen CF, 2019 [50]	Yes	Yes	Yes	Yes	Yes	No	Yes	None
Dev R, 2019 [51]	Yes	Yes	Yes	Yes	Yes	No	Yes	None
Mutanda JN, 2016 [66]	Yes	Yes	Yes	Yes	Yes	No	Yes	Minor
Hackett K, 2019 [62]	Yes	Yes	Yes	Yes	Yes	No	Yes	None
Ebenso B, 2021 [52]	Yes	Yes	Yes	Yes	Yes	No	Yes	None
Atukunda EC, 2021 [63]	Yes	Yes	Yes	Yes	Yes	No	Yes	None
Gebremariam KT, 2020 [30, 69]	Yes	Yes	Yes	Yes	Yes	No	Yes	None
Rothstein JD, 2016 [53]	Yes	Yes	Yes	Yes	Yes	No	Yes	None
Isler J, 2019 [64]	Yes	Yes	Yes	Yes	Yes	No	Yes	Minor
Tumuhimbise W, 2020 [54]	Yes	Yes	Yes	Yes	Yes	No	Yes	None
Mekonnen ZA, 2021 [65]	Yes	Yes	Yes	Yes	Yes	No	Yes	None
Bekyieriya E, 2023 [67]	Yes	Yes	Yes	Yes	Yes	No	Yes	None
Ilozumba O, 2018 [55]	Yes	Yes	Yes	Yes	Yes	No	Yes	None
Klingberg S, 2022 [56]	Yes	Yes	Yes	Yes	Yes	No	Yes	None
Muller N, 2020 [57]	Yes	Yes	Yes	Yes	Yes	No	Yes	None
Olajubu AO, 2022 [32]	Yes	Yes	Yes	Yes	Yes	No	Yes	None
Trafford Z, 2020 [29]	Yes	Yes	Yes	Yes	Yes	No	Yes	None
Coleman J, 2020 [33]	Yes	Yes	Yes	Yes	Yes	No	Yes	None
Fischer AE, 2018 [31]	Yes	Yes	Yes	Yes	Yes	No	Yes	None
Brinkel J, 2017 [58]	Yes	Yes	Yes	Yes	Yes	No	Yes	Minor
Pelt SV, 2023 [5]	Yes	Yes	Yes	Yes	Yes	No	Yes	None
Abejirinde IOO, 2018 [59]	Yes	Yes	Yes	Yes	Yes	No	Yes	None
Musabyimana A, 2018 [72]	Yes	Yes	Yes	Yes	Yes	No	Yes	Minor
Arnaert A, 2019 [60]	Yes	Yes	Yes	Yes	Yes	No	Yes	Minor

Confidence in the review findings

We graded seven findings, using the GRADE CERQual assessment approach in Table 2. Except for two that are moderate, all are of high confidence evidence (Table 2).

Table 2.

Confidence in the Evidence from Reviews of Qualitative Research

Summary of review finding	Studies contributing to the review finding	Methodological limitations	Coherence	Relevance	Adequacy	CERQual assessment of confidence in the evidence	Explanation of CERQual assessment
Women accepted mobile apps as supportive	[46, 51, 64, 67, 71]	No or very minor	Very minor concerns	No or very minor concerns	very Minor concerns	moderate Confidence	Minor concerns regarding coherence and relevance No or very minor methodological limitations, and minor concerns regarding the adequacy
Improved and increased utilization of health care service among women exposed to mobile phones compared to those unexposed	[5, 29, 31, 32, 46, 48–52, 54, 55, 58, 61, 63, 65, 66, 68–71]	No or very minor	No or very Minor concerns	No or very Minor concerns	No or very Minor concerns	High Confidence	Minor concerns regarding coherence and relevance No or very minor methodological limitations, and minor concerns regarding the adequacy
Reduce inequalities in access to skilled maternal care	[56, 57, 67, 68, 72]	No or very minor	No or very Minor concerns	No or very Minor concerns	No or very Minor concerns	High Confidence	Minor concerns regarding coherence and relevance No or very minor methodological limitations, and minor concerns regarding the adequacy
improved knowledge, attitudes, and practices of using services	[51, 60, 66, 68]	No or very minor	No or very Minor concerns	No or very Minor concerns	No or very Minor concerns	High Confidence	Minor concerns regarding coherence and relevance No or very minor methodological limitations, and minor concerns regarding the adequacy
Closeness between pregnant women and HCPs	[48–53, 70]	No or very minor	very Minor concerns	very Minor concerns	very Minor concerns	moderate Confidence	The text expresses minor concerns about coherence and relevance, with no or very minor methodological limitations, and minor concerns about adequacy
Respondents believed that mHealth contributed to reducing maternal and child mortality rates	[50, 57, 72]	No or very minor	very Minor concerns	No or very Minor concerns	No or very Minor concerns	High Confidence	The text expresses minor concerns about coherence and relevance, with no or very minor methodological limitations, and minor concerns about adequacy
improved communication (connection between HCPs and mothers)	[47, 52, 54, 61–63, 68, 70, 72]	very minor	No or very Minor concerns	No or very Minor concerns	very Minor concerns	High Confidence	The text expresses minor concerns about coherence and relevance, with no or very minor methodological limitations, and minor concerns about adequacy

Major Themes

The relevant themes used to develop the ICAMO model are presented in Table 3 below. The intervention (I) theme contains communication between HCPs and clients, communication among HCPs, reminders, health education, and data management. Mothers and health care professionals (HCPs) all reported the effect of mHealth in the form of a communication supporting system between clients and caregivers and among health care providers, reminders, and health education [5, 33, 49, 52, 59, 61–63, 69, 72]. Participants reported that the mHealth platform is immensely useful in providing health information that enables them to know why it is important to take the service. It highly improved communication between providers and mothers. It helped mothers to maintain their appointments as reminders to facilitate the process [5, 29, 31–33, 46, 48–52, 55, 59, 62, 65, 66, 68, 69]. mHealth applied as a decision support system and data management [53, 59, 62]. It improved knowledge and awareness of steps in big procedures and enabled caregivers to provide quality services. The ability of mothers to use mobile phones [65], read and understand messages [32, 51, 67], type messages (text, video, and voice) [51, 55, 64, 66], and the level of socioeconomic status [31, 32, 46–49, 55–57, 64, 65, 67] to buy mobiles and data were the context (C-) factors that influenced this intervention. Receiving health information, connecting with caregivers, and obtaining service at low cost motivated (M +) [32, 52, 56, 58, 63, 67, 70] mothers to use maternal and child health services.

Table 3.

Identified subthemes guided by the ICAMO major themes

Major themes	Subthemes
Intervention	Using mHealth for • Communication between HCPs and clients [5, 33, 49, 52, 59–63, 69, 72] • Communication among HCPs [59] • Reminders and health education [5, 29, 31–33, 46, 48–52, 55, 59, 62, 65, 66, 68, 69] • Data management [53, 62]
Context	• Intersectoral collaborations [58, 65] • workload for health care professionals (-) [29, 33, 49, 53, 72] • Socioeconomic challenges [31, 32, 46–49, 55–57, 64, 65, 67] • Traditional healers [29, 48] • Reading ability and illiteracy [32, 49, 51, 65, 67] • Message limit [31, 59] • Social integration [5, 58] • Communication language challenges [31, 48, 56, 64, 65] • Security challenges [49, 65, 68] • Continuity challenge [49, 56, 58, 65, 72] • Time challenges [49, 51, 57, 69, 72] • Network connectivity [48, 53, 56, 67] • Health facility-related challenges [47, 49]
Actors	• Mothers … husband and family • HCPs
Mechanisms	• Dis-satisfaction with existing service (-) [5, 47, 65, 72] • Motivation due to access of health information [52, 53, 60, 72] • Change in attitude toward use of services [55, 68] • Perceived importance of using mHealth [5, 31, 49, 56, 57, 62, 69] • Satisfaction mHealth assisted services [5, 51, 52, 59, 61, 68, 69] • Feel as if someone out there cared for me [5, 32, 47, 68, 69]
Outcomes	• Mobile apps accepted [5, 29, 31–33, 46, 48–52, 55, 59–63, 65, 66, 68, 69, 72] as supportive and motivators to maternal and child health by o Women o HCPs • Respondents believed that mHealth contributed to reducing maternal and child mortality rates [72] • Improved knowledge, attitudes, and practices of using services [32, 33, 55, 59, 60, 64, 66, 67] • Reduce inequalities in access to skilled maternal care [48, 57] • Improved communication [54, 70] • Improved utilization of health care service among women [33, 48, 49] • Improved maternal & child health [51, 54, 66] • The improved skill of labor-management [50] • Improved the seeking of health care services in good time [53, 63, 69] • Reduced maternal & newborn complications and life losses [50]

The potential success of mHealth intervention (I) has been affected by the vast number of other contexts (C) such as intersectoral collaborations (C +) [58, 65], the workload for health care professionals (C-) [29, 33, 49, 53, 72], traditional healers [29, 48] (C-), reading ability and illiteracy(C-) [32, 49, 51, 65, 67], message limit (C-) [31, 59], social integration [5, 58], communication language challenges(C-) [31, 48, 56, 64, 65], security challenges(C-) [31, 49, 65, 68], continuity challenge(C-) [49, 56, 58, 65, 72], time challenges(C-) [49, 51, 57, 69, 72], network connectivity(C-) [48, 53, 56, 67], and health facility-related challenges (C-) [47, 49].

Mechanisms (M) are the hidden forces that drive achieving a given objective or outcome. Most driving forces (M) as mentioned by participants are satisfaction (M-) with existing service [5, 47, 65, 72], motivation [32, 52, 56, 58, 63, 67, 70] due to access to health information, change in attitude toward the use of services (M +) [32, 33, 55, 59, 64, 67], perceived importance of using mHealth (M +) [5, 31, 49, 56, 57, 62, 69], satisfaction with mHealth assisted services(M +) [5, 51, 52, 59, 61, 68, 69] and feeling as if someone out there cared for me (M +) [5, 32, 47, 68, 69].

The successful positive mechanism (M +) encourages clients to take or use the intended service which is the direct objective of the intervention. Participants were influenced by the mechanisms to portray the outcomes (O) such as mobile apps accepted by women and HCPs as supportive and motivators to maternal and child health [5, 29, 31–33, 48–52, 55, 59, 61–63, 65, 66, 68, 69, 72], respondents believing mHealth contributed to reducing maternal and child mortality rates [72], improved knowledge, attitudes, and practices of using services [32, 33, 55, 59, 64, 67], reduce access inequalities to skilled maternal care [48, 57], improvement in communication [70], utilization of health care service among women [48, 49], maternal & child health [51, 54, 66], skill of labor-management [50], and seeking of health care services in good time [53, 63, 69]. Poor personal communication which reduced visits was also noticed in the review [72] (Table 3). The details of each subthemes are provided in additional supporting files (Supporting information 1 & 2).

What mechanisms do not work for which outcome why?

Some mothers report low satisfaction with eHealth which is linked to reducing its utilization due to contexts such as involvement in design, illiteracy, lack of training, and high internet/data service costs [47]. Participants felt that the national organizational/technical infrastructure is lacking, for example, irregular/unpredictable power outages and mobile network restrictions [58]. This reduced the acceptance of mHealth among some participants. Insufficient infrastructure and lack of motivated healthcare workers decrease maternal satisfaction in existing healthcare [5] and decrease attendance in the healthcare system. The number of messages sent to client may reduce their interest in checking messages over time. This can lead to missing crucial information and visits [69]. The lack of motivation among Community Health Workers (CHWs) in using RapidSMS over time increases their turnover rate” [72]. The reason is that the CHW argued for more financial compensation as RapidSMS increased workloads [72]. The CHWs also reported the lack of a place to recharge batteries to access messages during a stay in the field for work as a demotivating factor. This makes them miss the visits or timely information which is discouraging [49]. When transport is not available, they regret why they got this pregnancy. Even when they went to the hospital they were required to do a scan which they couldn’t do because of no money and they regretted it [64]. Mothers think entering health centers always means ‘money out’. [57]. The presence of traditional healers lowers visits to health institutions [29, 31]. It is not because mothers do not want to go to health facilities, but their illiteracy requires them to remember appointments rather than having a written reminder [49]. Healthcare providers also admitted similar issues. They believe they will have problems increasing service uptaking with clients' education level is negligent [51]. Pregnant women in some areas prefer to deliver at home to prove their faithfulness to their husbands [67]. Even among those who follow antenatal care, some give birth at home because the matrone is less expensive compared to the hospital. Some participants believe message overload may decrease interest and reduce the effect of information [31]. When the community is unaware of mHealth, they may become suspicious and pressurize women to stop taking messages [5, 58]. Thus, training for the community and making mothers aware that they will be taking messages are important. Even some women do not have experience receiving messages from strangers and are also not adaptive to some language wording which can affect their interest in information and attending health services [31, 48, 56, 64]. Some healthcare providers believe, that if most mothers do not have smartphones, it is difficult to promote maternal and child health through mHealth [65]. Some also think that taking the tablets to workplaces in the community exposes them to robbery which discourages them from taking tablets with them [55]. We shoot the picture of the X-ray and send it to doctors/specialists using WhatsApp, but you need more data, it is costly and not encouraging [31].

What mechanism works for which outcome why?

The participants' support for mHealth is far greater than the limitations experienced. Mothers believe that their Antenatal Care (ANC) attendance has improved from the previous pregnancy and are inspired by mHealth [46, 48]. Because the app and phones remind people to keep their clinic appointments, they view them as helpful supports to increase taking service [46]. Additionally, moms think that mHealth help ready for childbirth [48]. Time was saved, transportation expenses were decreased, and clients felt more supported during phone consultations [61]. Mothers are influenced to use cell phones for information, as it allows them to stay home, shorten commutes, and prevent bicycle breakdowns [49]. That phone consultation creates a deep impression and lingering memory [48] and mothers receive notes of encouragement about service [63]. Some say they hear encouraging messages and go for service [63]. These communications gave mothers hope that there was someone out there who was concerned about children and moms. They report that they enjoy making many calls because they can hear a real person clearly and it feels genuine. These messages keep us informed and alert and are helpful in our care [63]. Mothers are happy since they [text messages] remind them of their children’s vaccination date and are fine with the text messages sent a day before their vaccination date [65]. The voice messages are appreciated for covering more people except the deaf and have directly affected our follow-up [55]. Some mothers think that even if they knew the information provided with the phone previously, it motivated them about the service they take [32]. They think getting information through mHealth increases their confidence about the pregnancy so that they feel supported and change place of birth, and child feeding compared to previous pregnancies [29, 32]. Mother thinks phones become part of their lives with SMS health education information, emergency calls, and no queue for the information [33, 59, 69]. Some report that mHealth helped them to know what to eat, how to manage stress, and motivated them to take self-care and follow mHealth instructions [32]. Some mothers even believe they will pay if they have to because they know its importance for themselves and their baby's care [33]. Mothers think HCPs who utilize technology are believed to possess superior knowledge of their patient's conditions, leading to better care and follow-up [59].

Healthcare providers are also happy that more pregnant women are coming for ANC because of new devices involved in their care [59]. Some reported that they weren't following procedure before they received the helping software and despite being competent to know the dosage of their prescription, they could forget, thus, having apps saves time, increases motivation, and increases client satisfaction [50, 66]. They believe they are doing what they are doing because smartphone applications positively influence community perceptions of health services and client expectations of health workers; policymakers and implementers must ensure these expectations are met [62]. People in the communities are getting to know about the existence of mHealth and are motivated to use services since they think they are getting good attention [67]. Video training is considered more beneficial by healthcare providers than face-to-face training due to its collaborative nature with all staff members [52].

Summary of Final Program Theories 1. Including mHealth interventions in routine service delivery can inspire healthcare providers to provide better care to mothers and children, offering a new perspective and enabling continued utilization. 2. If mHealth intervention is not backed by incentives, CHW motivation gradually declines, which damages maintaining mHealth interventions and enhancing mother and child health. 3. Women’s awareness of the benefits of mHealth for their own and their children's health leads to improved health-seeking behavior and increased motivation to improve maternity and child healthcare. 4. If women who cannot afford the service receive support from mHealth interventions, their motivation will not alter and the number of women using maternity and child health services will remain the same. 5. If women receive organized reminders and health education messages from the mHealth intervention team, they become more motivated to pursue maternity and child healthcare. 6. If women receive more mHealth messages than they can handle, they get bored and stop reading or checking them, which reduces the impact of the messages and the use of maternal and child health.

They believe they do not need to be experts and express how mHealth videos affected the level of their knowledge and confidence to give care [31, 52]. They are confident that clients believe and trust that if they tell them something, it is true because we use the technology [59]. CHWs are very pleased to use the system! They are happy to see how they are assisting women and women are asking them to send both common and alert messages for their emergency cases. [72]. The system also helped HCPs to know the client's health rights and that bridged the gap with the community and encouraged their task [55]. Some think, they can see dropped maternal and neonatal mortality, and reached MDG because of mobile technology [72]. Using mHealth brought substantial difference because those who are registered [on the SMS platform] are no longer afraid to come to the hospitals but some of the people who are not registered have a negative attitude towards hospitals [55]. The CHWs using phones have improved their reporting more than CHWs who don’t have Phones [62] because of motivation and support from mobile-based technologies.

The final program theory shows that mHealth is a complex intervention that needs multidimensional support. The intervention may not work in a completely poverty (women cannot afford service) area when a lot of information is provided to women, and without additional support such as incentives for HCPs, and sensitization for women regarding mHealth.

Discussion

For this review, we reviewed 32 qualitative articles published in English across Africa, examining the use of the ICAMO realism model to determine what works, for whom, why, under what circumstances, and how mHealth applications are effective. Most studies focused on women and HCPs in the last two decades. We affirmed, modified, and added some parts of the initial program theories. Despite all the challenges, the findings demonstrated improvements in the HCP-woman relationship, the communication system, the uptake of maternal and child health care, health-seeking behavior, HCP skills, life losses, and knowledge and attitude as well as the services uptaking practice [32, 33, 48–51, 53–55, 57, 59, 63, 64, 66, 67, 69, 70, 72]. Despite its promising effects, mHealth's effectiveness in Africa's mother and child health services is influenced by various criteria. The success of mHealth depends on the contexts such as socioeconomic, geographical locations, and infrastructural factors. Healthcare facilities are sparse and difficult to access due to long distances and poor road infrastructure. Our review showed that mHealth can bridge these difficulties by providing information to the mothers. This enables mothers with limited or non-existent service areas to receive essential health services without traveling long distances [48, 52, 53, 57, 60, 72]. In most situations, SMS text, voice, video messages, mobile apps (communication tool), and telemedicine (remote consultation) were used to deliver essential information to mothers [5, 29, 31–33, 46, 48–53, 55, 59–63, 65, 66, 68, 69, 72]. Pregnant women, health care providers and community health workers were all beneficiaries of mHealth. Access, convenience, cost-effectiveness, and timeliness motivated actors to use the service [5, 31, 49, 52, 53, 56, 57, 60, 62, 69, 72]. Overall, mHealth tends to be more effective in low- and middle-income countries with limited access to essential care, where health crises occur, and in vulnerable remote areas. mHealth solved most of the service uptaking challenges, however, service costs hinder the utilization of the care. Considering difficulties and opportunities, prior reviews revealed how mHealth enhanced service uptake and mother and child health [38, 73–75]. The consistent findings suggest that mHealth services may share similar opportunities and constraints across different regions of the African continent.

Successful implementation of mHealth in Africa faces challenges such as digital literacy, language barriers, infrastructure limitations, privacy, data security, sustainability, cultural relevance, and community engagement [5, 29, 31, 32, 48, 49, 51, 56, 58, 64, 65, 67]. mHealth enhances self-care and reduces transportation costs, but participants face challenges such as traditional healers, service fees, limited funds, low education, and network connectivity [47–49, 51, 53, 56–58, 65, 67, 69, 72]. mHealth implementation in low and middle-income countries is often challenged by the identified issues [75, 76]. Mothers may be aware of health services but struggle financially due to poor economic conditions, highlighting the need for economic empowerment and health information provision [71]. Some mothers choose to give birth at home, despite their knowledge, to demonstrate their loyalty to their husbands [67]. Improving maternal and child health goes beyond providing health information; poor care quality hinders mothers from following mHealth-based information to health institutions [5, 67, 71]. This shows that the current study aligns with previous findings in a similar category. Most mothers believe healthcare providers support them, mHealth is important and they are satisfied with services. [5, 31, 49, 51–53, 56, 57, 59, 61, 62, 68, 69, 72]. Many participants valued the benefits of adopting mHealth, with consistent mothers' reports indicating its effectiveness in improving maternal and child health [5, 38, 67, 71, 73–75]. Healthcare professionals appreciate mHealth for its support in adhering to protocols, boosting self-esteem, bridging community gaps, encouraging work, and helping them achieve their objectives [55, 59, 62, 72]. Similar studies have highlighted the importance of mHealth in enhancing maternal and child health for healthcare providers [38, 74]. Some HCPs find using tablets to assess mothers problematic due to the lack of cell phones, community robberies, and significant data costs [31, 55, 65]. This information is also consistent with other studies in low and middle-income countries [38, 74]. The mHealth application in Africa has numerous benefits, but significant obstacles must be addressed to improve mother and child health.

As shown in the key findings of this study, mHealth aims to directly affect mothers and health providers to enhance maternal and child health [6]. mHealth facilitates seamless communication among healthcare providers, women, and their husbands [7]. Despite having low socioeconomic backgrounds, low sociodemographic mothers are content with receiving messages [8]. The program has significantly enhanced the awareness of WHO child-feeding guidelines among mothers [10]. Similar to our findings, audio messages, brief video services, and SMS are sent through web-based systems, mobile devices, PCs, and the internet improved maternal and child health status [24–27]. The mHealth service notifies clients of treatment or appointment delays due to access restrictions, reminds them of upcoming appointments, and provides health education on transportation [24, 26–28]. Our study suggests that mHealth can improve maternal and child health by facilitating communication between care providers and mothers through low-cost, easy-to-implement methods like text voice, and videos. Other studies indicate that mHealth programs can alter healthcare utilization patterns, utilized for policymakers, and guide the implementation of mHealth programs in low- and middle-income countries. [15, 77, 78]. It is essential to achieve the Sustainable Development Goals (SDG-3).

Strengths and limitations

The ICAMO model was utilized to evaluate the intervention, context, actors, effective mechanisms, and outcomes, providing a comprehensive view of the mHealth application. We also used standard qualitative review tools like CERQual, methodological limitations evaluation tool, and JBI checklist to assess the reliability and realism of mHealth's studies as strengths.

This review is part of a doctoral project and its scope is limited to the African context.

The diverse cultures and linguistics of Africa might impacted the findings of mHealth. Furthermore, mHealth might be affected by fragmented health systems, inoperability, and economic and infrastructure barriers. We searched many databases and could not locate many unpublished sources that could contribute to bias. Thus, we recommend the application of findings in context.

Recommendations

Mobile health (mHealth) has significant potential to enhance healthcare delivery in Africa, where access to healthcare services may be limited. Based on our findings, we recommend the following points.

Recommendation for practice

• ✓ The tailored implementation of mHealth in a specific local context requires thorough assessments to address specific health challenges and cultural contexts.

• ✓ To apply mHealth in a wider catchment may require network access and adequate existing infrastructure.

• ✓ The implementers need to design user-friendly interfaces and prepare adequate capacity-building training. They should be able to track performance and use a feedback system.

Recommendations for research

• ✓ The feasibility of implementing successful mHealth interventions in other regions or countries with comparable conditions should be established.

• ✓ Evaluating the economic impact of mHealth interventions compared to traditional methods through cost–benefit analyses.

• ✓ The research should investigate the factors that influence the adoption and continuous use of mHealth tools across various populations.

• ✓ Promote collaboration among technologists, healthcare professionals, policymakers, and researchers to create comprehensive mHealth solutions.

• ✓ Explore the potential of emerging technologies such as AI and blockchain in improving mHealth solutions and addressing existing challenges.

Conclusion

mHealth has the potential to improve maternal and child health outcomes in Africa by removing healthcare access barriers, providing women with tools to take charge of their health, and achieving universal health coverage and Sustainable Development Goals. The integration of mobile technology into health systems has the potential to significantly enhance accessibility, efficiency, and quality of care. To fully realize the potential of mHealth in the continent, several key factors including poor quality of the existing care, poor socioeconomic status, and poor sociodemographic factors. Increasing partner support, access to mobile devices, access to internet connectivity, and financial empowerment of women are other additional homework.

Abbreviations

mHealth

Mobile Health

ICAMO

Intervention Context Mechanism & Outcome

WHO

World Health Organization

ENTREQ

Enhancing transparency in reporting the synthesis of qualitative research

HCPs

Health Care Providers

CHWs

Community Health Workers

VHT

Village Health Team

ANC

Antenatal Care

PNC

Postnatal Care

SMS

Sort Message Service

FP

Family Planning

CERQual

Confidence in the Evidence from Reviews of Qualitative research

Authors’ contributions

GG developed the initial drafts of the protocol, results, discussion, and manuscript, EAZ is involved in method writing, validation, and initial and final draft writing whereas AD and RF are both equally involved in refining the protocol, results, discussion, and producing the edited final manuscript.

Funding

The authors do not receive funding for this specific work.

Data availability

No datasets were generated or analysed during the current study.

Declarations

Ethical approval and consent to participate

This review was conducted based on the protocol registered in POSPERO. The registration number is PROSPERO: CRD42023461425. The review recognition was based on the registration and protocol was not prepared. The authors also declare that all steps and activities are performed according to the available international guidelines.

Consent of publication

Not applicable.

Competing interests

The authors declare no competing interests.