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Objectives
Mobile health tools have potential to improve the diagnosis and management of acute lower respiratory illnesses (ALRI), a leading cause of paediatric mortality worldwide. The objectives were to evaluate health workers’ perceptions of acceptability, usability and feasibility of Acute Lower Respiratory Illness Treatment and Evaluation (ALR...
Context in source publication
Context 1
... this study, we identified key determinants towards successful implementation of ALRITE, our mHealth decision support tool, from frontline health workers' perspectives ( figure 2). In addition to ALRITE-specific determinants, health workers and administrators identified important individual-level, clinic-level and health systems-level determinants and offered innovative ideas for future app development. ...
Citations
... While e-health had the potential to positively impact health-seeking behaviour, the benefits could be hampered by problems with training. Adequate training for both patients [35,36,43,57,58,64] and HCPs [36,37,48,71] emerged as a key factor to enable technology access and the implementation of e-health interventions [58]. Familiarity with technology, rather than age, was thought to be a key positive determinant of e-health adoption, suggesting that future generations of elderly individuals might be better equipped to utilize e-health solutions [48,53]: ...
... Adequate training for both patients [35,36,43,57,58,64] and HCPs [36,37,48,71] emerged as a key factor to enable technology access and the implementation of e-health interventions [58]. Familiarity with technology, rather than age, was thought to be a key positive determinant of e-health adoption, suggesting that future generations of elderly individuals might be better equipped to utilize e-health solutions [48,53]: ...
... Related to the quality of training at the time of implementation, we noted that pre-existing attitudes towards technology also played a role. Both patients [58,64] and HCPs [48] were more likely to use e-health when they had positive attitudes towards learning new technologies: [48]. ...
Background
Chronic respiratory diseases are important causes of disability and mortality globally. Their incidence may be higher in remote locations where healthcare is limited and risk factors, such as smoking and indoor air pollution, are more prevalent. E-health could overcome some healthcare access obstacles in remote locations, but its utilisation has been limited. An improved understanding of barriers and facilitators to the implementation of e-health in remote locations could aid enhanced application of these approaches.
Methods
We performed a qualitative evidence synthesis to explore factors affecting the successful implementation of e-health interventions in remote locations for patients with chronic respiratory diseases. We searched PubMed, CINAHL, Embase, Web of Science and PsycINFO databases for qualitative and mixed-methods studies. Studies were assessed by two researchers, and 41 studies were included in the synthesis. Quality was assessed via the CASP-tool. Findings were coded with Atlas.ti software and categorised based on an adapted Digital Health Equity Framework.
Results
Nineteen themes were identified across five levels (individual, interpersonal, community, society and technology), with associated facilitators and barriers for implementation. An important facilitator of e-health was its role as a tool to overcome obstacles of distance and to increase access to care and patients’ self-efficacy. Potential barriers included the reduction of in-person interactions and an increased burden of work for healthcare providers. Good quality, usability, adaptability and efficacy of e-health interventions were important for implementation to be successful, as were adaptation to the local setting — including culture and language —and involvement of relevant stakeholders throughout the process.
Conclusions
Several factors affecting the implementation of e-health in remote and rural locations for patients with chronic respiratory disease were identified. Intervention objectives, target population, geographical location, local culture, and available resources should be carefully considered when designing an e-health intervention. These findings can be used to inform the successful design and implementation of future e-health interventions.
... This is achievable through improving patient education, improving disease self-management, decreasing health care costs, and performing remote monitoring of patients, as reported in a recent systematic review of mHealth in LMICs [3]. In addition, mHealth can support preventative measures, facilitate disease management, or support health workers to strengthen the delivery of health care [7][8][9][10]. The WHO has highlighted the need to advance national digital health strategies that can facilitate universal health care [11]. ...
... Among the 20 included studies, 9 were apps and 11 were SMS interventions. Based on the World Bank 2022 Country Group by Income LMIC status [28], 8 were low income [8,9,[29][30][31][32][33][34], 6 were lower middle income [10,[35][36][37][38][39], and 6 were upper middle income [7,21,[40][41][42][43]. Of the 20 studies, 7 focused on people living with or at risk of acquiring HIV [7,21,31,33,34,39,41]; the remaining studies targeted malaria [8,30,35,36], tuberculosis [31,38,42,43], pneumonia [10,30], dengue [37], a grouping of "respiratory illnesses" [9] or "childhood chronic infectious diseases" [29], HPV [40], or COVID-19 [32]. ...
... Based on the World Bank 2022 Country Group by Income LMIC status [28], 8 were low income [8,9,[29][30][31][32][33][34], 6 were lower middle income [10,[35][36][37][38][39], and 6 were upper middle income [7,21,[40][41][42][43]. Of the 20 studies, 7 focused on people living with or at risk of acquiring HIV [7,21,31,33,34,39,41]; the remaining studies targeted malaria [8,30,35,36], tuberculosis [31,38,42,43], pneumonia [10,30], dengue [37], a grouping of "respiratory illnesses" [9] or "childhood chronic infectious diseases" [29], HPV [40], or COVID-19 [32]. There were 2 studies that addressed multiple diseases [30,31]. ...
Background
Mobile health (mHealth) interventions have the potential to improve health outcomes in low- and middle-income countries (LMICs) by aiding health workers to strengthen service delivery, as well as by helping patients and communities manage and prevent diseases. It is crucial to understand how best to implement mHealth within already burdened health services to maximally improve health outcomes and sustain the intervention in LMICs.
Objective
We aimed to identify key barriers to and facilitators of the implementation of mHealth interventions for infectious diseases in LMICs, drawing on a health systems analysis framework.
Methods
We followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist to select qualitative or mixed methods studies reporting on determinants of already implemented infectious disease mHealth interventions in LMICs. We searched MEDLINE, Embase, PubMed, CINAHL, the Social Sciences Citation Index, and Global Health. We extracted characteristics of the mHealth interventions and implementation experiences, then conducted an analysis of determinants using the Tailored Implementation for Chronic Diseases framework.
Results
We identified 10,494 titles for screening, among which 20 studies met our eligibility criteria. Of these, 9 studies examined mHealth smartphone apps and 11 examined SMS text messaging interventions. The interventions addressed HIV (n=7), malaria (n=4), tuberculosis (n=4), pneumonia (n=2), dengue (n=1), human papillomavirus (n=1), COVID-19 (n=1), and respiratory illnesses or childhood infectious diseases (n=2), with 2 studies addressing multiple diseases. Within these studies, 10 interventions were intended for use by health workers and the remainder targeted patients, at-risk individuals, or community members. Access to reliable technological resources, familiarity with technology, and training and support were key determinants of implementation. Additional themes included users forgetting to use the mHealth interventions and mHealth intervention designs affecting ease of use.
Conclusions
Acceptance of the intervention and the capacity of existing health care system infrastructure and resources are 2 key factors affecting the implementation of mHealth interventions. Understanding the interaction between mHealth interventions, their implementation, and health systems will improve their uptake in LMICs.
... O enfermeiro deve classificar corretamente as doenças respiratórias, diferenciando entre pneumonia e condições com sibilos, para um manejo adequado. A interpretação precisa dos dados é essencial para decisões clínicas informadas (Ellington et al., 2021). ...
... A carga de trabalho elevada com poucos profissionais de saúde treinados para avaliar os pacientes, além da falta de oportunidades para educação continuada ou treinamentos, dificultam as práticas realizadas pelos enfermeiros (Ellington et al., 2021). ...
... No estudo desenvolvido por Ellington e colaboradores, foi demonstrado que os enfermeiros encontraram dificuldades em seguir as diretrizes da OMS para o manejo de doenças da infância, especialmente na contagem da frequência respiratória e na avaliação de sibilos, devido à falta de recursos como estetoscópios e oxímetros de pulso (Ellington et al., 2021). ...
Introdução: As medidas preventivas, o diagnóstico precoce e o tratamento adequado podem evitar as principais causas associadas ao óbito infantil: infecções respiratórias agudas, doenças diarreicas e desnutrição. Nesse sentido, o enfermeiro pode atuar de forma sistematizada a fim de promover a saúde infantil no âmbito da Atenção Primária em Saúde. Objetivo: Investigar, na literatura, evidências científicas sobre as condutas dos enfermeiros nas doenças prevalentes na infância na Atenção Primária à Saúde. Método: Revisão integrativa nas bases de dados PubMed, CINAHL, Web of Science, SCOPUS e Biblioteca Virtual em Saúde, em português, inglês e espanhol, sem data definida. Resultado: Foram analisados oito estudos, sendo a maioria realizada (37,5%) e publicada (62,5%) no Brasil. Cinco (62,5%) foram estudos de Intervenção/Tratamento ou Diagnóstico/Teste Diagnóstico nível VI. As categorias identificadas sobre as condutas dos enfermeiros foram: A) Atuação nas doenças frequentes: imunização, avaliação do crescimento/desenvolvimento, amamentação, introdução alimentar, infecções respiratórias e diarreia. B) Passos e procedimentos: avaliação e classificação adequadas das doenças, identificação de tratamentos apropriados, e aconselhamento claro às mães sobre tratamento e retorno. C) Lacunas na assistência dos enfermeiros. Conclusão: Apesar de atuar nas condições que mais influenciam na saúde infantil e realizar passos e procedimentos recomendados da Atenção Integral, os enfermeiros não realizam uma prática sistematizada, além de apresentarem lacunas em sua assistência. Recomenda-se outros estudos com outras abordagens metodológicas a fim de compreender as condutas dos enfermeiros nas doenças prevalentes na infância na Atenção Primária à Saúde.
... While the use of artificial intelligence (AI) in the healthcare field is increasing in recent years, especially in HICs, previous studies have evoked various barriers to the uptake of clinical decision support tools on smartphones by patients and healthcare providers (HCPs). Concerns such as theft of devices, fear of a data breach and perceptions of reduced patient trust were highlighted, though more research is needed to better understand the acceptability of AI as a clinical decision support tool in patients in the Global South [9][10][11]. ...
... With respect to HCP competence concerns encountered in our study, similar perspectives were reported by other studies exploring the acceptability of similar CAD tools in various healthcare domains. A study in Uganda regarding HCPs' perspectives on the acceptability of a mobile health tool revealed a concern that using a mobile application in front of patients and their families would undermine their trust in the HCP's ability to diagnose and treat [9]. This perception was echoed in another study in the UK where HCPs were worried that using mobile tools during patient interactions would be perceived as unprofessional [11]. ...
Background
Cervical cancer is the fourth most frequent cancer among women, with 90% of cervical cancer-related deaths occurring in low- and middle-income countries like Cameroon. Visual inspection with acetic acid is often used in low-resource settings to screen for cervical cancer; however, its accuracy can be limited. To address this issue, the Swiss Federal Institute of Technology Lausanne and the University Hospitals of Geneva are collaborating to develop an automated smartphone-based image classifier that serves as a computer aided diagnosis tool for cancerous lesions. The primary objective of this study is to explore the acceptability and perspectives of women in Dschang regarding the usage of a screening tool for cervical cancer relying on artificial intelligence. A secondary objective is to understand the preferred form and type of information women would like to receive regarding this artificial intelligence-based screening tool.
Methods
A qualitative methodology was employed to gain better insight into the women’s perspectives. Participants, aged between 30 and 49 were invited from both rural and urban regions and semi-structured interviews using a pre-tested interview guide were conducted. The focus groups were divided on the basis of level of education, as well as HPV status. The interviews were audio-recorded, transcribed, and coded using the ATLAS.ti software.
Results
A total of 32 participants took part in the six focus groups, and 38% of participants had a primary level of education. The perspectives identified were classified using an adapted version of the Technology Acceptance Model. Key factors influencing the acceptability of artificial intelligence include privacy concerns, perceived usefulness, and trust in the competence of providers, accuracy of the tool as well as the potential negative impact of smartphones.
Conclusion
The results suggest that an artificial intelligence-based screening tool for cervical cancer is mostly acceptable to the women in Dschang. By ensuring patient confidentiality and by providing clear explanations, acceptance can be fostered in the community and uptake of cervical cancer screening can be improved.
Trial registration
Ethical Cantonal Board of Geneva, Switzerland (CCER, N°2017–0110 and CER-amendment n°4) and Cameroonian National Ethics Committee for Human Health Research (N°2022/12/1518/CE/CNERSH/SP). NCT: 03757299.
... Picterus JP was perceived by all participants as a device that is easy to use, useful and compatible with work routines. Several authors have considered such positive perceptions and attitudes among stakeholders as determining factors for the acceptance and adoption of mHealth innovations by HCWs [45][46][47][48][49]. Contrarily, researchers have found that HCWs feel frustrated and unwilling to use mobile devices when the apps delay the workflow or are not easy to use [46]. ...
Background
Neonatal jaundice is a common condition that can lead to brain damage and disabilities when severe cases go undetected. Low- and middle-income countries often lack accurate methods for detecting neonatal jaundice and rely on visual assessment, resulting in a higher incidence of adverse consequences. Picterus Jaundice Pro (Picterus JP), an easy-to-use and affordable smartphone-based screening device for the condition, has demonstrated higher accuracy than visual assessment in Norwegian, Philippine and Mexican newborns. This study aimed to identify the barriers and facilitators to implementing Picterus JP in public health services in low-income settings in Mexico by exploring the current process of neonatal jaundice detection and stakeholders’ perspectives in that context.
Methods
Qualitative data collection techniques, including one focus group, 15 semi-structured interviews and four observations, were employed in urban and rural health facilities in Oaxaca, Mexico. The participants included medical doctors, nurses and health administrators. The data were analysed by thematic analysis guided by the Consolidated Framework for Implementation Research.
Results
The analysis yielded four main themes: (I) the current state of neonatal care and NNJ detection, (II) the needs and desires for enhancing NNJ detection, (III) the barriers and facilitators to implementing Picterus JP in the health system and (IV) HCWs’ expectations of Picterus JP. The findings identify deficiencies in the current neonatal jaundice detection process and the participants’ desire for a more accurate method. Picterus JP was perceived as easy to use, useful and compatible with the work routine, but barriers to adoption were identified, including internet deficiencies and costs.
Conclusions
The introduction of Picterus JP as a supporting tool to screen for neonatal jaundice is promising but contextual barriers in the setting must be addressed for successful implementation. There is also an opportunity to optimise visual assessment to improve detection of neonatal jaundice.
... There have been a small number of observational and participatory design studies that aim to inform the design of systems and datasets in this area (e.g. [21,38,55,71,100]). A rare example of a study of the real-world deployment of an AI system is Beede et al. 's ethnographic study of a deep learning system for diabetic retinopathy in hospital settings [8]. ...
Artificial Intelligence (AI) based technologies are increasingly being integrated into public sector programs to help with decision-support and effective distribution of constrained resources. The field of Computer Supported Cooperative Work (CSCW) has begun to examine how the resultant sociotechnical systems may be designed appropriately when targeting underserved populations. We present an ethnographic study of a large-scale real-world integration of an AI system for resource allocation in a call-based maternal and child health program in India. Our findings uncover complexities around determining who benefits from the intervention, how the human-AI collaboration is managed, when intervention must take place in alignment with various priorities, and why the AI is sought, for what purpose. Our paper offers takeaways for human-centered AI integration in public health, drawing attention to the work done by the AI as actor, the work of configuring the human-AI partnership with multiple diverse stakeholders, and the work of aligning program goals for design and implementation through continual dialogue across stakeholders.
... Picterus JP was perceived by all participants as a device that is easy to use, useful and compatible with work routines. Several authors have considered such positive perceptions and attitudes among stakeholders as determining factors for the acceptance and adoption of mHealth innovations by HCWs (45)(46)(47)(48)(49). Contrarily, researchers have found that HCWs feel frustrated and unwilling to use mobile devices when the apps delay the work ow or are not easy to use (46). ...
Background: Neonatal jaundice is a common condition that can lead to brain damage and disabilities when severe cases go undetected. Low- and middle-income countries often lack accurate methods for detecting neonatal jaundice and rely on visual assessment, resulting in a higher incidence of adverse consequences. Picterus Jaundice Pro (Picterus JP), an easy-to-use and affordable smartphone-based screening device for the condition, has demonstrated higher accuracy than visual assessment in Norwegian, Philippine and Mexican newborns. This study aimed to identify the barriers and facilitators to implementing Picterus JP in public health services in low-income settings in Mexico by exploring the current process of neonatal jaundice detection and stakeholders’ perspectives in that context. Methods: Qualitative data collection techniques, including one focus group, 15 semi-structured interviews and four observations, were employed in urban and rural health facilities in Oaxaca, Mexico. The participants included medical doctors, nurses and health administrators. The data were analysed by thematic analysis guided by the Consolidated Framework for Implementation Research. Results: The analysis yielded four main themes: (I) the current state of neonatal care and NNJ detection, (II) the needs and desires for enhancing NNJ detection, (III) the barriers and facilitators to implementing Picterus JP in the health system and (IV) HCWs’ expectations of Picterus JP. The findings identify deficiencies in the current neonatal jaundice detection process and the participants’ desire for a more accurate method. Picterus JP was perceived as easy to use, useful and compatible with the work routine, but barriers to adoption were identified, including internet deficiencies and costs. Conclusions: The introduction of Picterus JP as a supporting tool to screen for neonatal jaundice is promising but contextual barriers in the setting must be addressed for successful implementation. There is also an opportunity to optimise visual assessment to improve detection of neonatal jaundice.
... Several qualitative studies exploring HCPs' perceptions about factors and barriers related to digital health acceptance in endocrinology and other therapy areas have been published in the scientific literature [29,[31][32][33][34]. Some have explored HCPs' perceptions about mHealth tools used in children's health care [29,[31][32][33][34][35][36][37], concluding that early engagement of end users is critical to the development and effective implementation of such tools to enhance patient-centric care. Notably, a mixed methods formative research study has explored technology acceptance and the use of digital health tools for the emotional support of parents of children undergoing GH treatment, using educational content to help parents and caregivers understand their children's treatment journey [38]. ...
Background:
Digital solutions targeting children's health have become an increasingly important element in the provision of integrated health care. For the treatment of growth hormone deficiency (GHD), a unique connected device is available to facilitate the delivery of recombinant human growth hormone (r-hGH) by automating the daily injection process and collecting injection data such that accurate adherence information is available to health care professionals (HCPs), caregivers, and patients. The adoption of such digital solutions requires a good understanding of the perspectives of HCPs as key stakeholders because they leverage data collection and prescribe these solutions to their patients.
Objective:
This study aimed to evaluate the third generation of the easypod device (EP3) for the delivery of r-hGH treatment from the HCP perspective, with a focus on perceived usefulness and ease of use.
Methods:
A qualitative study was conducted, based on a participatory workshop conducted in Zaragoza, Spain, with 10 HCPs experienced in the management of pediatric GHD from 7 reference hospitals in Spain. Several activities were designed to promote discussion among participants about predefined topics based on the Technology Acceptance Model and the Unified Theory of Acceptance and Use of Technology to provide their perceptions about the new device.
Results:
Participants reported 2 key advantages of EP3 over previous easypod generations: the touch screen interface and the real-time data transmission functionality. All participants (10/10, 100%) agreed that the new device should be part of a digital health ecosystem that provides complementary functionalities including data analysis.
Conclusions:
This study explored the perceived value of the EP3 autoinjector device for the treatment of GHD by HCPs. HCPs rated the new capabilities of the device as having substantial improvements and concluded that it was highly recommendable for clinical practice. EP3 will enhance decision-making and allow for more personalized care of patients receiving r-hGH.
... 51,52,57 Two (20%) defined usability as "the design factors that affect the user experience of operating the application's device and navigating the application for its intended purpose". 46,50 Other definitions of usability included: ...
Objective
The aim of this study was to determine the methods and metrics used to evaluate the usability of mobile application Clinical Decision Support Systems (CDSSs) used in healthcare emergencies. Secondary aims were to describe the characteristics and usability of evaluated CDSSs.
Materials and Methods
A systematic literature review was conducted using Pubmed/Medline, Embase, Scopus, and IEEE Xplore databases. Quantitative data were descriptively analyzed, and qualitative data were described and synthesized using inductive thematic analysis.
Results
Twenty-three studies were included in the analysis. The usability metrics most frequently evaluated were efficiency and usefulness, followed by user errors, satisfaction, learnability, effectiveness, and memorability. Methods used to assess usability included questionnaires in 20 (87%) studies, user trials in 17 (74%), interviews in 6 (26%), and heuristic evaluations in 3 (13%). Most CDSS inputs consisted of manual input (18, 78%) rather than automatic input (2, 9%). Most CDSS outputs comprised a recommendation (18, 78%), with a minority advising a specific treatment (6, 26%), or a score, risk level or likelihood of diagnosis (6, 26%). Interviews and heuristic evaluations identified more usability-related barriers and facilitators to adoption than did questionnaires and user testing studies.
Discussion
A wide range of metrics and methods are used to evaluate the usability of mobile CDSS in medical emergencies. Input of information into CDSS was predominantly manual, impeding usability. Studies employing both qualitative and quantitative methods to evaluate usability yielded more thorough results.
Conclusion
When planning CDSS projects, developers should consider multiple methods to comprehensively evaluate usability.
... Detailed background research provided first-hand information about the problem-such as an illness-to be tackled in the community as well as how best to handle it (47). Furthermore, the implementers of these user-centered digital initiatives ensured to acquire as much information about the community health workers, location, need, opportunities, and other information relevant to the implementation and acceptability of the solution (46,48,49). These included pre and post evaluation of the knowledge of health care workers and feedback from test users (50,51). ...
... These included pre and post evaluation of the knowledge of health care workers and feedback from test users (50,51). The questions addressed topics about the design and usability of the application as well as pertinent issues concerning potential blockades to its mass adoption (48,52,53). They sought to gain knowledge from the successes and failures of past implementers. ...
The agenda for Universal Health Coverage has driven the exploration of various innovative approaches to expanding health services to the general population. As more African countries have adopted digital health tools as part of the strategic approach to expanding health services, there is a need for defining a standard framework for implementation across board. Therefore, there is a need to review and employ an evidence-based approach to inform managing challenges, adopting best approaches, and implement informed recommendations. We reviewed a variety of digital health tools applied to different health conditions in primary care settings and highlighted the challenges faced, approaches that worked and relevant recommendations. These include limited coverage and network connectivity, lack of technological competence, lack of power supply, limited mobile phone usage and application design challenges. Despite these challenges, this review suggests that mHealth solutions could attain effective usage when healthcare workers receive adequate onsite training, deploying applications designed in an intuitive and easy to understand approach in a manner that fits into the users existing workflows, and involvement of the stakeholders at all levels in the design, planning, and implementation stages of the interventions.
