Motivating and inhibiting factors influencing the application of mhealth technology in post-abortion care: a review study

Articles related to the factors influencing the use of mhealth technology in post-abortion care were searched in PubMed, Scopus, Web of Science, ProQuest, Embase databases and Google Scholar. The search strategy used in PubMed was as follows:

This study included English-language articles on mHealth in post-abortion care published from 2010 to 1st November 2023. Exclusions comprised of book chapters, letters, and commentaries, non-English articles, those lacking full texts, and those diverging from the study aim which was identifying factors influencing the use of mhealth technology in post-abortion care. In fact, articles not primarily emphasizing mHealth services for post-abortion care, and those focusing on unrelated issues such as using telemedicine for medical abortion were excluded.

Adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) flow diagram [36], our screening process was systematically implemented. Upon obtaining relevant articles, EndNote software (X20, Clarivate) was employed for meticulous reference management, ensuring the elimination of duplicates. After removing duplicates, the title and abstract of the remaining articles were reviewed.

A data extraction form was used to determine factors influencing the use of mhealth technology in post-abortion care. This form included the name of the authors, year of the study, name of the country, research objective, type of study, and factors influencing the use of mhealth technology in post-abortion care. To report the findings, factors influencing the use of mhealth technology in post-abortion care were initially divided into two categories, motivating and inhibiting factors. Then, using the method of content analysis, the results were extracted, tabulated, summarized, and finally synthesized narratively.

The factors shaping the acceptance and adoption of mhealth technology in post-abortion care were thoughtfully organized into key domains, showcasing a nuanced understanding. The factors influencing the acceptance and utilization of mhealth technology for post-abortion care were broadly categorized into individual, technical, economic, and ethico-legal domains. Individual factors included several items such as willingness to receive counseling, and educational level. Technical factors were related to the technological aspects of mhealth technology implementation, including multilingual support, readability of messages, customization options, accessibility challenges, and usability issues. Economic factors delve into the financial aspects, addressing cost reduction, affordability for patients, and the ability to compare costs for different services. Lastly, ethico-legal factors considered the ethical and legal implications, such as data security, concerns about privacy, and the availability of websites or apps to the general public. This comprehensive framework provided a structured understanding of diverse factors influencing the integration of mhealth technology in post-abortion care.

Motivating factors influencing the use of mhealth technology in post-abortion care were mentioned in all selected studies. The objectives of these studies were mainly related to the use of mhealth in preventing pregnancy after an abortion [17, 19, 39‐45], the feasibility of using mhealth technology for post-abortion care [30, 40, 47, 48], the cost-effectiveness of mhealth interventions after an abortion [46] and the use of mhealth in post-abortion family planning [20]. The analysis of the motivating and inhibiting factors across the diverse mHealth intervention studies reveals key insights into the adoption and success of these interventions.

Motivating factors included individual, ethico-legal, economic, and technical factors, which are described in the following sections.

Inhibiting factors affecting the use of mhealth technology in post-abortion care were stated in 13 studies (81.2%). These studies were conducted in Canada [19, 35], Kenya [38], Venezuela [39], Vietnam [40], Pakistan[41], Myanmar [42], Cambodia [20, 43, 45], Australia [47], Bangladesh [17], and South Africa [48] between 2014 and 2023. The inhibiting factors included individual, ethico-legal, economic, and technical factors which are described in the following section.

In general, despite numerous successful instances of implementing telemedicine and mHealth in post abortion care, the adoption of technology can still be influenced by various factors. These factors are nuanced and depend on the patient's specific condition, priorities, perceptions, and the intended purposes of utilizing the technology. Within the scope of this study, a range of motivating and inhibiting factors were identified, shedding light on the complexities of mHealth implementation in post-abortion care. Recognizing and understanding these factors is pivotal, as leveraging motivating elements enhances the likelihood of successful technology implementation, while overlooking them may result in implementation failure. Therefore, a thorough identification and detailed consideration of these factors are essential to effectively meet the diverse requirements of users in the context of post-abortion care.

The purpose of this study was to identify factors influencing the use of mhealth technology in post-abortion care. The review of selected articles indicated that these factors can be divided into two categories, namely, motivating factors and inhibiting factors. These factors included some individual, technical, economic, and ethico-legal factors, too.

According to the literature, the use of mhealth technology can help improve quality of care and service delivery, as well as reducing human errors and the cost of care [49]. Despite the potentials of this technology to provide services at any time and place, the acceptance and continuous use of it by the end-users are among the most important concerns of the system developers, as the use of mhealth technology does not necessarily mean its acceptance [50]. Gill et al. suggested that patient-centered design is a suitable and useful method for planning and carrying out interventions for patients, especially in post-abortion care [30].

In the study conducted by Mutua et al., motivating and inhibiting factors influencing the implementation of telemedicine included the legal factors (e.g., liability and jurisdiction, clinical governance, informed consent, data confidentiality, and security), cultural factors (e.g., language, trust, and resistance to change), contextual factors (e.g., resources and infrastructure), and sustainability factors (e.g., cost, integration into the national health systems, and financing) [4]. Regarding the use of mhealth in post-abortion care, Aung et al. indicated that individual motivating factors include patient's need to receive information about the abortion complications and methods of preventing pregnancy after abortion, communicate with the clinical staff to receive appropriate emotional and informational support, access to get care at any time and place at a low cost [42]. In other studies, providing unique clinical and emotional support for each patient and addressing her problems were among the individual motivating factors [46, 51]. While in the current study, motivating and inhibiting factors were identified in detail, some researchers used other approaches to categorize influencing factors. For example, Zhang et al. used the technology acceptance model (TAM) and reported that perceived ease of use and perceived usefulness are significant reasons for the acceptance and use of mhealth technologies [52]. Similarly, Mohamed et al. found that in some cases, perceived usefulness is more important than perceived ease of use for users [29]. Grossman et al. mentioned that ease of access to health care services at any time and place is one of the factors influencing the use of mhealth technology, and the effectiveness of these services are comparable with face-to-face clinical visits [53]. Zahedul-Alam et al. showed that performance expectancy, effort expectancy, social influence, facilitating conditions, and perceived reliability have a significant impact on the willingness to use mhealth technology [54]. It should be noted that in the present study, although the technology acceptance models and their variables were not examined, the research findings are generally consistent with the findings of other similar studies.

In terms of inhibiting factors, our study resonates with the findings of several studies in which network connection problems, lack of internet access in deprived areas, and inappropriate system design were commonly reported as technical inhibiting factors [19, 20, 35, 39, 41, 43, 45, 48]. Ngo et al., reported insufficient facilities, equipment, budget constraints, and clinicians' knowledge gaps as inhibiting factors [40].

Some studies investigated users’ experiences of using telemedicine technology. In this study, insufficient facilities, equipment, budget, and knowledge of clinicians about using the technology were reported as other factors inhibiting the use of telemedicine [55]. In addition, one of the main concerns of the users in using mhealth technology is the privacy issues [48]. Therefore, data protection and privacy have been recognized as the most essential features required for developing mhealth systems [56].

Another factor that can negatively influence the acceptance and use of mhealth technology is resistance to change, which can be caused by the lack of awareness of the usefulness of the technology [25]. In some cases, the resistance might be due to some cultural beliefs ​​and traditions, which can be resolved through education [57]. It seems that improving financial, organizational, and technical support along with creating changes in the thoughts, feelings, and attitudes of users would help increase the acceptance of new technologies [28]. Given the sensitivity of healthcare, especially in terms of patient health conditions, technology acceptance issues must be meticulously considered in the early stages of system design and implementation, as emphasized in a study by Luigi-Bravo et al. [19, 39, 52].

It is notable that the exploration of motivating and inhibiting factors in diverse mHealth interventions provides crucial insights for developing patient-centered systems. Prioritizing patient needs is essential for fostering engagement, trust, and positive health outcomes. Designing patient-centered mHealth systems requires a multifaceted approach, understanding individual preferences and many other factors for personalized support.

The current study has certain limitations. Firstly, despite conducting a thorough search across selected databases, it is possible that some relevant studies were inadvertently omitted from the review. The vast and dynamic nature of research literature makes it challenging to ensure absolute inclusivity. Secondly, the inclusion criterion for articles written exclusively in English might introduce a language bias, potentially overlooking pertinent studies in other languages. The exclusion of studies in languages other than English may have limited the scope of our review, and there could be valuable insights from non-English literature that were not incorporated. Future research endeavors should aim for broader language inclusivity to enhance the comprehensiveness and representativeness of the findings.