Sage Journals: Discover world-class research

Abstract

Introduction/Objectives

Digital health literacy (DHL) is increasingly recognised as a core competency for frontline health workers in digitalising health systems, particularly in resource-constrained settings. This study examined how Tanzanian primary care workers understand and apply DHL, as well as the contextual factors that influence its development and use.

Methods

A qualitative descriptive design was used. In-depth interviews were conducted with 30 health workers, including nurses, clinical officers, and community health workers, from urban and rural public primary healthcare facilities in the Dodoma region. Data were analysed thematically using Braun and Clarke's framework, supported by NVivo 15.

Results

Three main themes emerged: (a) varied conceptualisations of DHL, ranging from basic operational use to applied understanding for clinical decision-making and patient education; (b) DHL's influence on data quality, care continuity, and patient communication; and (c) disparities shaped by infrastructure, cadre, training access, and organisational culture. Rural staff and community health workers reported lower DHL and less access to support.

Conclusions

Improving DHL requires not only technical training but also ongoing mentorship, supportive organisational cultures, and equity-focused strategies. Tailored interventions are needed to build DHL capacity across all cadres and facility levels.

Keywords

Digital health literacy primary healthcare health workers Tanzania qualitative research health information systems

Introduction

Health literacy is a critical determinant of health outcomes and an essential component of equitable, patient-centred care.^1,2 Defined broadly as the ability to obtain, understand, evaluate, and use health information to make informed decisions, health literacy is strongly linked to improved self-care, treatment adherence, and service utilisation.^3,4 In recent years, as digital technologies have become embedded in healthcare delivery, the concept of health literacy has evolved to include digital health literacy (DHL). DHL refers to the ability of individuals, including healthcare workers, to search, understand, evaluate, and apply digital health information and tools to support informed health decisions and enhance care delivery. DHL is conceptualised as a composite of technical, cognitive, and communicative competencies essential for engaging effectively with digital health technologies.^5–9 This shift is particularly significant in primary care settings, where technology is increasingly used to support patient engagement, disease monitoring, and service efficiency.^10,11

Globally, digital health literacy (DHL) has gained recognition as a key enabler of health system performance and population-level well-being, particularly in the context of universal health coverage and the Sustainable Development Goals.^12,13 However, disparities in digital access and literacy risk deepening existing health inequalities, especially in developing countries, where infrastructural, linguistic, and educational challenges persist.^14–16 For frontline health workers in these settings, limited digital skills may not only undermine their ability to use health technologies but also their capacity to guide patients in navigating digital health tools.^17,18 This has implications for informed decision-making, continuity of care, and the realisation of digital health's potential in improving outcomes. In Sub-Saharan Africa, digital health interventions, including mobile health (mHealth), electronic health records (EHRs), and decision-support tools, have been introduced to strengthen healthcare delivery in under-resourced settings.^19–25

In Tanzania, the government has implemented a series of national initiatives aimed at digitalising the health sector, most notably the Tanzania Digital Health Strategy 2019–2024. This strategy prioritises the integration of digital infrastructure and the use of interoperable electronic systems to support routine health service delivery across all levels of care.²⁶ One of the key components of this digital transformation is the Government of Tanzania Health Operations Management Information System (GOTHOMIS), which is currently the main EHR system used in the country. As of June 1, 2025, a total of 6066 health facilities representing 82.02% of all public facilities were using GOTHOMIS in various versions. Adoption rates vary by facility type, with coverage reaching 99.47% among district hospitals, 98.09% among health centres, and 79.14% among dispensaries.²⁷ However, despite this significant uptake, the effective and consistent use of these systems remains uneven, particularly in lower-level primary care facilities where the majority of Tanzanians first access the health system.²⁸

Several studies have identified persistent barriers that hinder the effective use of digital health tools, including limited initial and ongoing training, low digital health literacy among frontline healthcare workers, inadequate technical support, and usability challenges often associated with language and interface design.^29,30 These challenges are especially pronounced in rural and under-resourced settings, where infrastructure limitations compound the difficulties of system adoption and usage.^31,32 As a result, while the infrastructural reach of digital systems, such as GOTHOMIS, has expanded considerably, questions remain about the capacity of health workers to effectively engage with these tools to support data quality, clinical decision-making, and patient education.

Health workers play a central role in the successful implementation of digital health tools.^33–35 They input data, interpret clinical guidelines embedded in software, communicate digital information to patients, and often troubleshoot problems with limited support.^36,37 Their understanding and confidence in using digital health systems directly influence the quality of data, continuity of care, and the effectiveness of patient education and referral systems.³³

This study seeks to fill this gap by exploring DHL among Tanzanian primary care workers, with three specific objectives: (i) to examine how health workers understand DHL; (ii) to explore how DHL affects their ability to deliver informed, effective, and person-centred care; and (iii) to identify contextual disparities that influence DHL. Drawing on qualitative interviews with nurses, clinical officers, and community health workers in both urban and rural settings, the study aims to generate evidence that can inform context-sensitive strategies to build capacity, reduce inequities, and strengthen the integration of digital tools into primary care practice.

Literature review

Theoretical review

The concept of digital health literacy is rooted in broader theories of health literacy and digital competence.³⁸ The typology of health literacy, functional, communicative, and critical, provides a foundational understanding of how individuals engage with health information at varying levels of complexity. This framework has been adapted for the digital context, particularly by Norman & Skinner,³⁹ who developed the eHealth Literacy Model. This model outlines six core literacies: traditional literacy, health literacy, information literacy, scientific literacy, media literacy, and computer literacy. These competencies are necessary for individuals, including health professionals, to effectively search for, understand, and apply digital health information.

In implementation contexts, especially in low-resource health systems, digital health literacy among health workers is also influenced by workplace learning, adult education theories, and socio-technical system thinking. For instance, Vygotsky's socio-cultural theory, as reviewed by Rahmatirad,⁴⁰ emphasises the role of interaction and context in knowledge acquisition, which is particularly relevant for community health workers and nurses who learn digital skills informally, often through peer support or on-the-job exposure. Additionally, the Technology Acceptance Model (TAM) has been used to explain how perceived usefulness and ease of use shape attitudes toward digital tools.⁴¹ In more recent studies, the Unified Theory of Acceptance and Use of Technology (UTAUT) has been applied to healthcare workers, highlighting the roles of performance expectancy, effort expectancy, and facilitating conditions.⁴²

Empirical literature review

Understanding digital health literacy among health workers

DHL, a concept that extends traditional health literacy into digital contexts, refers to the ability to search, evaluate, and use health information from electronic resources to address health-related problems.^43,44 For healthcare professionals, DHL includes not only technical skills but also the cognitive, communicative, and evaluative competencies needed to engage effectively with digital health tools.⁴⁵

High DHL among health workers is associated with better access to reliable digital health content, improved patient communication, and more efficient clinical workflows.⁴⁶ It also plays a foundational role in supporting the digital transformation of health systems, particularly in the integration of electronic health records and telehealth.⁴⁷ Health professionals with higher DHL levels are better positioned to support patients in making informed decisions, thereby promoting equity in care access and outcomes.⁴³

Empirical studies have identified significant variation in DHL across contexts. While studies from Iran, Nepal, and Australia generally report high levels of DHL among health workers,^44,47 research from Ethiopia reveals lower literacy levels, particularly among staff in rural or resource-constrained settings.⁴⁶ In these contexts, limited access to digital devices, lack of training, and negative attitudes toward digital tools were noted as key barriers.

Several factors influence DHL, including education level, access to digital infrastructure, digital training, job designation, and attitudes toward technology.^46,48 For example, healthcare workers with advanced degrees or prior ICT training consistently demonstrate stronger DHL. Younger professionals and those with more exposure to digital platforms also tend to score higher in digital literacy domains.⁴⁷

Despite these insights, challenges remain. Even in settings where operational skills are high, gaps persist in evaluating the reliability and relevance of online health content.⁴³ In addition, many studies rely on self-reported measures, raising concerns about the accuracy of reported DHL levels. There is also a lack of validated, standardised tools tailored to healthcare providers, limiting comparability across studies.⁴⁵

Digital health literacy and health outcomes

DHL is increasingly recognised as a key determinant of health, influencing not only individuals’ access to and understanding of digital health information but also their capacity to make informed decisions and manage health effectively. It encompasses a range of competencies, including the ability to locate, evaluate, and apply digital health information for personal or patient-related care.^49,50 Several studies have confirmed that higher DHL is associated with positive psychosocial outcomes, including increased empowerment, reduced psychological distress, and improved satisfaction in healthcare interactions. For example, older adults with high DHL reported greater satisfaction and less perceived strain during medical encounters.⁴⁹

Furthermore, individuals with better DHL have shown improved self-management behaviours in chronic disease contexts, including COPD, HIV, and diabetes. These include increased likelihood of engaging in preventive behaviours, adherence to treatment plans, and more active participation in decision-making.^49,50 In contrast, low DHL has been linked to poorer self-care, reduced use of online patient portals, and difficulties navigating digital health services, which may exacerbate health inequities and limit the effectiveness of care coordination.

Although the evidence base is growing, much of it relies on self-reported DHL measures, such as eHEALS, which may overestimate actual competencies. Moreover, evidence on the direct impact of DHL on long-term health outcomes in underrepresented populations remains limited. Nevertheless, the emerging consensus suggests that investing in DHL could enhance health behaviours, psychosocial well-being, and equitable access to care, reinforcing its status as a ‘super determinant of health’ in digitalised health systems.^51,52

Digital health literacy and health disparities

DHL plays a critical role in shaping access to healthcare and mediating health equity. DHL encompasses both digital competencies and the ability to manage one's health in a digital environment.^9,53 As health services increasingly move online, DHL has become a central player in navigating patient portals, telemedicine, and mobile health tools.⁵⁴

However, gaps in DHL can reinforce or widen existing health disparities. Older adults, individuals with low incomes or limited education, and rural populations are consistently shown to have lower DHL levels, often due to limited access, inadequate infrastructure, or a lack of digital skills.^53,55 For example, individuals aged over 75 are up to four times more likely to have low DHL than their younger counterparts,⁵⁵ and similar patterns are seen among women and those dependent on others to access digital tools.

These disparities have significant consequences. Limited access to DHL can impede the ability to schedule appointments, understand treatment options, and engage in health-promoting behaviours. Conversely, higher DHL is positively associated with improved self-rated health, mental well-being, and physical activity.⁵⁴ Among older adults, DHL contributes to reduced depressive symptoms and supports greater engagement with health services.

Efforts to reduce the digital divide must therefore consider both individual-level interventions, such as targeted education and training, and structural strategies, including improving internet access, designing inclusive technologies, and maintaining face-to-face options for those unable to use digital tools. Policies promoting digital inclusion are crucial to ensure that digital health advancements do not exacerbate existing inequalities, but instead foster equitable health outcomes across populations.^9,53

Literature gap

While existing studies have established strong links between DHL and outcomes, much of this evidence is derived from high-income settings, with limited empirical data from low-resource contexts, such as Tanzania. Few studies examine DHL among health workers, despite their central role in delivering and mediating digital health services. Moreover, the intersection of DHL with health disparities shapes access and use of digital tools, which remains underexplored in the sub-Saharan African context.

Methodology

Study design

This study employed a qualitative descriptive design to explore the DHL of frontline health workers in Tanzania. The design was chosen to facilitate an in-depth understanding of participants’ lived experiences, perceptions, and contextual challenges related to the use of digital health tools in primary care.

Research team and reflexivity

All interviews were conducted by the researcher in the field of health informatics at the University of Dodoma. He has extensive training and experience in qualitative health systems research and the implementation of digital health solutions. The researcher had no prior personal or professional relationship with the participants. Participants were introduced to the study through their facility's in-charges, and each was informed that the researcher was conducting academic research on digital health literacy among frontline health workers.

The researcher maintained a reflexive stance throughout the study, recognising his interest in digital health system adoption and potential bias toward the benefits of digitalisation. Field notes were used to document reflections after each interview to minimise interpretive bias.

Study setting

The study was conducted purposively in the Dodoma region of Tanzania, with contrasting urban and rural primary healthcare contexts. The region has been part of recent digital health initiatives, including the implementation of electronic immunisation registries, mobile health reporting systems, and digital referral platforms. Within the region, three public primary healthcare facilities, two from urban areas and one from a rural area, were selected to ensure diversity in digital infrastructure, service levels, and staff composition.

Study population and sampling

Thirty health workers participated in this study, selected from urban (Dodoma Municipal) and rural (Bahi and Chamwino) public primary healthcare facilities (Supplemental Appendix 1). A purposive sampling strategy was used to capture diverse experiences across cadres, facility types, and exposure to digital systems. This method was chosen because it allows for the selection of participants who are most knowledgeable about the use of digital tools in primary care, thereby yielding rich, contextually relevant data.

The sample comprised 14 nurses, 9 clinical officers, and 7 community health workers, providing representation across cadres, facility contexts, and levels of exposure to digital systems. Participants were recruited face-to-face through facility in-charges and invited to participate voluntarily. This purposive approach was chosen to ensure the inclusion of individuals directly engaged with digital tools for patient care or health data reporting.

Sampling continued concurrently with data analysis, and recruitment ceased when data saturation was reached, that is, when additional interviews no longer generated new themes or insights. This point was reached after the 28th interview; two further interviews were conducted to confirm saturation. Thus, the final sample of 30 was determined by saturation rather than a fixed target, providing both depth and diversity of perspectives.

Inclusion criteria were: (i) current employment in a primary healthcare facility in the Dodoma region; (ii) direct involvement in patient care and/or data reporting; and (iii) use of at least one digital health tool within the previous six months.

Data collection

Data were collected through semi-structured, in-depth interviews conducted between March and April 2025. The semi-structured interview guide (Supplemental Appendix 2) contained open-ended questions with prompts aligned to the study objectives. The guide was pilot-tested with two health workers outside the study facilities to refine clarity and sequencing.

Interviews were conducted over a four-week period, with approximately three to four interviews held per day, depending on participant availability. Each session lasted between 30 and 60 minutes. The interviews were conducted in either Kiswahili or English, depending on the participants’ preference. All interviews were audio-recorded with consent, transcribed verbatim, and translated as necessary. Translations were checked to ensure conceptual accuracy. Field notes were used to capture nonverbal cues and contextual observations, complementing the transcripts.

Data analysis

Data were analysed thematically following Braun and Clarke's⁵⁶ six-phase framework: familiarisation, coding, theme development, review, definition, and reporting. NVivo 15 software (QSR International) was used to manage and support the analysis process. Within NVivo, the coding tool was applied to organise and label meaningful text segments, and the node classification function helped group similar codes into broader themes. The word frequency query was used to identify recurrent concepts and terminology, while the matrix coding query facilitated comparison of themes across participant cadres and facility types. These tools collectively enhanced transparency, consistency, and depth in the analysis.

A primarily deductive approach was employed, with coding and theme development guided by the study's research objectives. Within each broad theme, inductive coding was used to identify patterns and sub-themes emerging from participants’ accounts. This allowed the analysis to remain grounded in the data while ensuring alignment with the study's conceptual focus. To enhance credibility, two researchers independently coded a subset of transcripts and resolved differences through discussion.

Trustworthiness

The study adhered to the principles of credibility, dependability, transferability, and confirmability. Credibility was ensured through prolonged engagement with the data, triangulation of sources (interviews and field notes), and peer debriefing. A detailed description of the setting and participants enhances the study's transferability. An audit trail of coding decisions, thematic maps, and analytic memos supports dependability and confirmability.

Reporting standards

The study followed the Consolidated Criteria for Reporting Qualitative Research (COREQ) checklist to ensure transparency and completeness in reporting qualitative data (Supplemental Appendix 3).

Ethical considerations

Ethical approval for this study was granted by the University of Dodoma Research Ethics Committee. Although the clearance number was not formally issued, written authorisation was obtained before fieldwork commenced. The study adhered to ethical principles of voluntary participation, confidentiality, and informed consent.

Before each interview, participants were informed of the study's purpose, their right to withdraw at any stage without penalty, and the measures taken to protect their identity. Written informed consent was obtained from all participants. To ensure confidentiality, pseudonyms were assigned and all identifying information was removed during transcription. Audio recordings and transcripts were stored in password-protected files accessible only to the research team. Interviews were recorded using digital audio devices and analysed using NVivo 15 qualitative analysis software.

Findings

This section presents the findings from in-depth interviews with 30 primary healthcare workers drawn from six public facilities across urban and rural districts in the Dodoma region. Participants included nurses, clinical officers, and community health workers, all of whom had experience using at least one digital health tool in the six months preceding the study. These tools included electronic immunisation registries, mobile health applications, SMS-based reporting systems, and digital referral platforms. Using thematic analysis, three major themes emerged aligned with the study objectives: (1) conceptual understanding of digital health literacy, (2) influence of digital health literacy on service delivery, and (3) contextual disparities shaping digital health literacy.

Conceptual understanding of digital health literacy

Participants expressed varied understandings of what digital health literacy entails, shaped largely by their exposure to digital systems, cadre, and prior training. While nearly all participants acknowledged the increasing importance of digital tools in health service delivery, their interpretation of DHL ranged from basic operational familiarity to more advanced, integrative conceptions that included the use of information and communication.

Functional versus applied understanding

A large proportion of participants described DHL primarily in terms of operational skills, the ability to operate digital devices, navigate software, and enter patient data correctly. As one clinical officer explained:

Digital health literacy, to me, is about being able to use the system to register patients, update records, and submit monthly reports. Without that skill, it is hard to do our job now. (HW07)

For others, especially those who had received structured training or worked in facilities with better support, the concept extended beyond routine input. They emphasised the ability to interpret digital information for clinical decision-making, patient education, and improving service delivery:

It is not just about entering data. DHL means understanding what the data tells you, like identifying which diseases are common this month and acting on it. (HW15)

Blurred boundaries with general ICT literacy

Some community health workers and older staff members conflated DHL with general computer literacy or familiarity with social media platforms. One participant noted:

I first learned how to use WhatsApp and Facebook before I touched GoTHOMIS. So I thought digital literacy meant using any device well, even outside work. (HW19)

This view illustrates a gap in conceptual clarity, where DHL was sometimes equated with basic digital familiarity rather than competencies related to health-specific technologies or information systems.

Learning through practice and peer support

Across both urban and rural settings, several participants reported that their understanding of DHL had evolved through on-the-job learning and peer collaboration. Formal training was noted to be limited, but learning by doing helped clarify what DHL is involved in real-life contexts:

At first, I was only copying what others were doing. However, over time, I learned what to check for to ensure the record is complete and that the diagnosis codes make sense. That is when I felt I understood the system. (HW02)

Urban–rural and cadre-level differences

Urban-based workers, especially those in district-level facilities, tended to articulate a broader understanding of DHL, often referring to health data analysis, online guideline access, or the use of dashboards. In contrast, rural workers more frequently focused on data entry and system navigation. Differences were also evident across cadres: nurses and clinical officers generally reported higher familiarity with clinical documentation tools, while community health workers expressed less confidence, often relying on verbal instructions or paper-based methods when digital systems failed.

Influence of digital health literacy on service delivery

Participants described DHL as central to their ability to deliver efficient, accurate, and person-centred care. Their narratives revealed that DHL influenced how they documented clinical information, interpreted digital records, communicated with patients, and responded to the needs of the health system. The level of DHL, often developed informally, directly influenced both the quality of care and the efficiency of service delivery.

Enabling accurate data capture and continuity of care

Participants frequently emphasised that adequate DHL allowed them to maintain complete and accurate patient records, which in turn improved follow-up and reduced repetition of services. Several nurses and clinical officers reported using digital tools to check patient history, avoid drug duplication, and follow up on chronic cases:

When you know how to use the system well, it helps a lot with continuity. I can see what the patient was given last month and avoid repeating the same drug unnecessarily. (HW04)

In contrast, participants with limited DHL admitted to entering minimal data, skipping non-mandatory fields, or reverting to paper documentation during system downtime, practices that risked data loss and reduced service quality.

Supporting clinical decision-making and planning

Many health workers highlighted that DHL helped them not just record information but also interpret it. This was especially common among staff working in urban facilities or those who had undergone refresher training. For instance:

I usually check the dashboard to see if malaria cases are increasing. Then we plan health talks for that. (HW13)

Others reported using the digital system to access national treatment guidelines or calculate vaccine coverage during immunisation drives, though this was less common in rural settings.

Improving patient communication and education

Several participants noted that improved digital health literacy enabled them to better explain clinical information to patients. Younger staff, in particular, felt more confident using the system to support health education during consultations. A nurse from an urban facility explained:

When a patient asks when they last took medication or came for review, I just check in the system and tell them directly. It helps avoid confusion. (HW15)

Similarly, others used DHL to confirm scheduled referrals or reassure patients about service availability:

Sometimes a mother asks if her child has already given a vaccine. I can check the records and show her the date. It builds trust. (HW06)

However, older staff or those less familiar with the system expressed hesitation when using digital tools during patient interactions:

I am not confident opening the screen in front of the patient. If I make a mistake, it is embarrassing. I prefer to write down what I need first. (HW10)

In rural settings, participants also raised the challenge of language barriers in patient communication, noting that although the system is in English, many patients prefer explanations in Kiswahili, which necessitates an additional step for interpretation.

Most patients do not understand what is on the screen, so I still explain it in Kiswahili. But the system helps me be sure I am giving the right dates and instructions. (HW20)

These examples illustrate the supportive role of DHL in enhancing patient-provider communication, particularly in areas such as medication tracking, follow-up verification, and health education.

Workarounds in low-literacy or low-resource contexts

Participants from rural facilities reported improvising when digital literacy or infrastructure limitations prevented them from using the system effectively. Some would note down information on paper during busy periods and enter it later. Others relied on colleagues who were more comfortable with the system:

When I am unsure, I just call the nurse who handles the records well. We sit together and enter the information after patients leave. (HW20)

These informal coping mechanisms ensured service continuity but also indicated dependency and inefficiency stemming from low DHL.

Increased workload and digital fatigue

Several health workers reported that the limited DHL extended task completion time, particularly when navigating updates or system changes. This often compounded fatigue during busy shifts:

The new version is confusing. I have to click more screens just to do what was one page before. It slows us down, especially if you did not get training. (HW08)

This concern was more pronounced among staff who lacked ongoing technical support, and it affected their motivation to engage fully with digital documentation.

Contextual disparities shaping digital health literacy

A complex mix of contextual factors, including geographic setting, professional cadre, education level, clinical competence, infrastructure, access to training, and organisational culture, shaped participants’ digital health literacy (DHL). While most participants recognised the importance of DHL in improving service delivery, the extent to which they were able to develop and apply these skills varied considerably across rural and urban settings, as well as between cadres.

Professional background

Participants’ professional backgrounds reflected a broad range of qualifications and experience: 60% held diploma-level qualifications, 30% had bachelor's degrees, and 10% possessed certificate-level training. Work experience ranged from 2 to 24 years (mean = 11 years), with nurses generally reporting longer service histories than clinical and community health officers. Those with higher formal education and longer professional experience tended to demonstrate stronger confidence in using digital systems, citing greater familiarity with health information technologies and documentation standards. Conversely, staff with limited training or shorter work experience often relied on peers for guidance or used digital tools primarily for data entry rather than for clinical decision support.

Urban–rural infrastructure gaps

Workers in rural facilities consistently reported challenges in accessing and using digital health tools due to unreliable infrastructure. Limited computers, poor internet connectivity, and power outages were common in the Bahi and Chamwino districts:

We have one computer shared by three people. Sometimes the battery is low or the power is gone. You end up postponing everything. (HW06)

This contrasted with urban-based participants, who described more stable infrastructure and greater availability of devices, allowing for more consistent use of digital systems and thus more opportunities to build DHL.

Disparities in training exposure and follow-up

Participants’ narratives highlighted that DHL was closely linked to the availability and quality of training. Rural workers were more likely to report missing out on formal training opportunities or receiving only brief introductions without follow-up:

They trained the in-charge only. The rest of us just learned from watching or being told what to do. (HW11)

By contrast, urban facilities had more regular training schedules and support from district health offices. Workers in Dodoma Municipal reported receiving system updates and even refresher courses:

We were trained on both GoTHOMIS and the immunisation app. The district sends someone when updates come. (HW01)

This disparity not only affected individual DHL levels but also contributed to feelings of exclusion among rural staff.

Cadre-specific variations in confidence and usage

Nurses and clinical officers were generally more confident and frequent users of digital tools, particularly those related to patient registration, referrals, or reporting. Community health workers and lab technicians were less exposed to systems like GOTHOMIS and more likely to use parallel paper-based tools.

We write our outreach reports on paper and give them to the nurse to enter later. I have never logged into the system myself. (HW18)

These differences reflected both role-based system access and assumptions within facilities about who ‘should’ be using digital tools.

Language, age, and digital confidence

Participants pointed to age and language proficiency as additional barriers. Older staff often expressed anxiety or mistrust of digital systems, sometimes preferring to delegate tasks to younger colleagues. One participant observed:

The older ones say they cannot type or they are afraid to spoil something. So they ask us to do it for them. (HW10)

Language barriers also emerged in facilities where the user interface was in English and some staff were more comfortable in Kiswahili.

Organisational culture and leadership

Finally, some facilities fostered stronger digital literacy by encouraging teamwork, mentorship, and openness to learning. These places often had active in-charges or digital champions who supported the use of the system. Others, however, had passive leadership, leading to low morale and inconsistent system engagement.

Here, if you do not understand, you just struggle. No one checks, and you might enter wrong data without knowing. (HW14)

Where supportive cultures existed, even staff with initially low DHL showed steady improvement through practice and guidance.

Discussion

This study aimed to investigate how primary healthcare workers in Tanzania perceive digital health literacy (DHL), its impact on their ability to deliver care, and the contextual disparities that influence DHL across various settings.

Interpretation of findings

Understanding of digital health literacy

Participants’ definitions of DHL ranged from basic operational competencies (example, navigating digital forms) to more integrated concepts involving decision-making and patient education. This variation aligns with Norman and Skinner's³⁹ outline in the eHealth Literacy Model, which posits that different layers of literacy, ranging from technical to critical, contribute to overall digital competence. Similar to findings by Tegegne et al.⁴⁶ in Ethiopia, Tanzanian health workers with limited formal ICT training tended to equate DHL with basic system use, whereas others with more exposure understood DHL as a skill set that supports clinical reasoning and communication.

The tendency among community health workers and older participants to conflate DHL with general ICT or social media use mirrors findings from Alipour and Payandeh,⁴³ who reported similar conceptual ambiguity in low-resource settings. This suggests a need for greater clarity in framing DHL among frontline staff, particularly through training and policy documents. However, the study also highlighted that peer learning and informal mentorship are key enablers of DHL development, an observation consistent with Rahmatirad's⁴⁰ review of Vygotskian learning theories, which emphasise the social nature of skill acquisition.

Influence of DHL on service delivery

Participants across all settings reported that DHL influenced their ability to document, interpret, and communicate health information. Health workers with higher DHL felt more confident in retrieving patient history, checking referrals, and using data to guide outreach activities, aligning with findings from Kuek and Hakkennes⁴⁷ and Longhini et al.,⁴⁵ who linked DHL to improved data quality and service planning. The current study extends this evidence by showing how DHL also affects the provider-patient relationship. For instance, some participants used digital systems to verify treatment schedules or explain follow-up dates, tangible actions that enhanced trust and communication.

However, older workers and those in rural areas described system fatigue, delays in navigation, or fear of errors when using digital tools in front of patients. These experiences align with the technological anxiety observed in studies by Kemp et al.⁵³ and Rousseau et al.,⁵⁵ particularly among underserved groups with limited access to technology. Such findings underscore the need for tailored DHL interventions that account not only for technical gaps but also for individual differences in confidence and communication styles.

Contextual disparities shaping DHL

The study found that urban–rural differences in infrastructure, training opportunities, and supervisory support were key determinants of DHL. Urban health workers benefited from more reliable electricity, better device availability, and closer links with district health teams. Rural workers, on the other hand, faced frequent power cuts, shared computers, and limited access to follow-up training. These findings align with evidence from studies in Tanzania^28,29 and other regions in sub-Saharan Africa,¹⁶ which suggests that addressing systemic inequalities is crucial to ensure digital health interventions do not exacerbate, but rather mitigate, disparities.

In addition to infrastructure, cadre, and age, these factors also shaped DHL. Nurses and clinical officers typically had more exposure to formal training and system use, while community health workers, despite their crucial outreach role, were often sidelined from digital documentation processes. This pattern aligns with Tegegne et al.,⁴⁶ who found that job designation predicted DHL levels among health workers in Ethiopia. The marginalisation of CHWs from digital tools in Tanzania may reduce the effectiveness of community-level interventions, particularly where referral systems or mobile data reporting are involved.

The study also highlighted the role of organisational culture. Facilities with supportive leadership and collaborative staff were more likely to see informal learning and mentorship flourish. This supports Wosny et al.'s³³ findings that institutional support and digital champions can compensate for the limitations of formal training.

The findings reveal clear disparities in digital health literacy among urban and rural health workers, as well as across different cadres. Addressing these requires a multi-level response. At the organisational level, facilities should institutionalise regular, on-site refresher sessions and mentorship programmes led by digitally competent ‘peer champions’. At the policy level, the Ministry of Health and district authorities could integrate DHL indicators into supervision tools and allocate dedicated digital support staff for rural facilities. Furthermore, integrating digital health modules into pre-service and in-service training curricula can systematically strengthen competence. Tailored user interfaces in Kiswahili and offline functionality would also enhance inclusion in low-resource contexts. These actions collectively translate the study's findings into feasible steps for equitable capacity building.

Contributions and policy implications

This study contributes context-specific evidence on DHL in a region where empirical data remain scarce. It highlights that improving DHL is not only a technical matter but also a question of equity, infrastructure, and support. For policymakers, this suggests that investments in digital health infrastructure should be accompanied by sustained, context-sensitive capacity building, not just during rollout but as part of ongoing professional development.

Building on these insights, it becomes evident that enhancing digital health literacy demands more than policy recognition or short-term training initiatives. It requires coordinated, practical actions that address the individual, organisational, and systemic factors influencing how health workers engage with digital tools. The following strategies outline feasible approaches to strengthen digital health literacy and promote equitable participation across primary healthcare settings.

Structured and continuous training

Regular refresher sessions and on-site mentorship can enhance and sustain digital competence among healthcare workers. Continuous professional development ensures that staff remain confident in using evolving digital tools and systems.^17,47

Peer learning and digital champions

Establishing peer-mentor networks within facilities encourages shared learning and mutual support. Identifying ‘digital champions’ among staff can help maintain motivation, strengthen skills, and promote a culture of digital confidence.³³

Infrastructure improvement

Reliable internet connectivity and consistent power supply are essential for equitable digital access, particularly in rural and resource-limited areas. Investing in basic infrastructure creates the foundation for effective use of digital health tools.²⁰

System localisation

Adapting digital systems to local needs enhances usability and inclusion. Interfaces designed in Kiswahili, along with simplified dashboards, help bridge language and literacy barriers, allowing all cadres to engage effectively with digital platforms.²⁹

Policy integration and accountability

Integrating DHL indicators into routine supervision and performance evaluation frameworks strengthens accountability and ensures sustainability. Recognition of DHL as a core competency can drive resource allocation and foster long-term institutional commitment.

Limitations

As a qualitative study based on purposive sampling in a single region, the findings are not generalisable to all Tanzanian health workers. Perspectives from private facilities, regional hospitals, and patients themselves were not included. Nonetheless, the insights are analytically generalisable and relevant to similar primary care contexts across the country.

Conclusion

This study examined how primary healthcare workers in Tanzania perceive and apply digital health literacy in their daily practice, and how contextual factors influence its development. Findings indicate that while digital health literacy is increasingly recognised as essential to effective service delivery, its interpretation and application remain uneven across cadres and settings. Health workers in urban facilities and higher clinical roles were more likely to associate DHL with data-informed decision-making and patient communication, while those in rural areas or with less exposure focused on basic system navigation. Disparities in infrastructure, training, and organisational support continue to influence DHL capacity, particularly for community health workers. These insights underscore the need for practical, inclusive strategies to enhance DHL as a core competency within Tanzania's primary healthcare system.

Supplemental Material

sj-docx-1-dhj-10.1177_20552076251396986 - Supplemental material for Exploring digital health literacy among Tanzanian primary care workers: A qualitative study

Supplemental material, sj-docx-1-dhj-10.1177_20552076251396986 for Exploring digital health literacy among Tanzanian primary care workers: A qualitative study by Augustino Mwogosi in DIGITAL HEALTH

Supplemental Material

sj-docx-2-dhj-10.1177_20552076251396986 - Supplemental material for Exploring digital health literacy among Tanzanian primary care workers: A qualitative study

Supplemental material, sj-docx-2-dhj-10.1177_20552076251396986 for Exploring digital health literacy among Tanzanian primary care workers: A qualitative study by Augustino Mwogosi in DIGITAL HEALTH

Footnotes

Acknowledgements

The author thanks the participating healthcare workers for their time and valuable insights. Gratitude is also extended to district health officials in Dodoma for facilitating access to study sites.

ORCID iD

Augustino Mwogosi

Ethical approval and informed consent

The study received ethical clearance from the University of Dodoma Research Ethics Committee. Written informed consent was obtained from all participants prior to interviews.

Consent to participate

Written informed consent was obtained from all participants.

Consent for publication

Not applicable-the study does not include identifiable personal data, images, or videos of individuals.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Declaration of conflicting interest

The author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data availability statement

Due to the nature of qualitative data and privacy considerations, full interview transcripts are not publicly available. Selected anonymised excerpts supporting the study's findings are available from the author upon reasonable request.

Supplemental material

Supplemental material for this article is available online.

References

Shahid

Shoker

Chu

, et al. Impact of low health literacy on patients’ health outcomes: a multicenter cohort study. BMC Health Serv Res 2022; 22: 1148.

Coughlin

Vernon

Hatzigeorgiou

, et al. Health literacy, social determinants of health, and disease prevention and control. J Environ Health Sci 2020; 6: 3061.

van der Gaag

Heijmans

Spoiala

, et al. The importance of health literacy for self-management: a scoping review of reviews. Chronic Illn 2022; 18: 234–254.

Liu

Wang

Liu

, et al. What is the meaning of health literacy? A systematic review and qualitative synthesis. Fam Med Community Health 2020; 8: e000351.

Fitzpatrick

. Improving health literacy using the power of digital communications to achieve better health outcomes for patients and practitioners. Front Digit Health 2023; 5: 1264780.

Ban

Kim

Seomun

. Digital health literacy: a concept analysis. Digit Health 2024; 10: 20552076241287894.

Causio

Gandolfi

Kaur

, et al. Impact of Digital Health Interventions on Health Literacy: A Systematic Review with Quality Appraisal. 2025. Epub ahead of print 1 March 2025. DOI: 10.1101/2025.02.27.25323025.

Bejaković

Mrnjavac

. The characteristics and role of digital literacy in an effective health protection. Heliyon 2024; 10: e29737.

Dong

Pan

, et al. Associations between digital literacy, health literacy, and digital health behaviors among rural residents: evidence from zhejiang, China. Int J Equity Health 2024; 23: 68.

10.

Young

Nesbitt

. Increasing the capacity of primary care through enabling technology. J Gen Intern Med 2017; 32: 398–403.

11.

Piera-Jiménez

Dedeu

Pagliari

, et al. Strengthening primary health care in Europe with digital solutions. Aten Primaria 2024; 56: 102904.

12.

Awosiku

Gbemisola

Oyediran

, et al. Role of digital health technologies in improving health financing and universal health coverage in Sub-Saharan Africa: a comprehensive narrative review. Front Digit Health 2025; 7: 1391500.

13.

Ahmed

Okesanya

Olaleke

, et al. Integrating digital health innovations to achieve universal health coverage: promoting health outcomes and quality through global public health equity. Healthcare 2025; 13: 1060.

14.

Bekerian

Osback

. Navigating the digital landscape: challenges and barriers to effective information use on the internet. Encyclopedia 2024; 4: 1665–1680.

15.

Badr

Motulsky

Denis

J-L

. Digital health technologies and inequalities: a scoping review of potential impacts and policy recommendations. Health Policy (New York) 2024; 146: 105122.

16.

Fang

Nie

. Inequalities in digital literacy: exploring the disparity in tangible outcomes of internet use among college students in China. Front Commun (Lausanne) 2025; 10: 1601240.

17.

Alotaibi

Wilson

Traynor

. Enhancing digital readiness and capability in healthcare: a systematic review of interventions, barriers, and facilitators. BMC Health Serv Res 2025; 25: 500.

18.

do Nascimento

IJB

Abdulazeem

Vasanthan

, et al. Barriers and facilitators to utilizing digital health technologies by healthcare professionals. NPJ Digit Med 2023; 6: 161.

19.

Mugauri

Chimsimbe

Shambira

, et al. A decade of designing and implementing electronic health records in Sub-Saharan Africa: a scoping review. Glob Health Action 2025; 18: 2492913.

20.

Adepoju

I-OO

Albersen

BJA

Brouwere

, et al. Mhealth for clinical decision-making in sub-saharan Africa: a scoping review. JMIR Mhealth Uhealth 2017; 5: e38.

21.

Betjeman

Soghoian

Foran

. Mhealth in sub-saharan Africa. Int J Telemed Appl 2013; 2013: 1–7.

22.

Simbini

Adimado

Adjorlolo

, et al. Digital Health Interventions (DHIs) for Health Systems Strengthening in Sub-Saharan Africa: Insights from Ethiopia, Ghana, and Zimbabwe. 2025. Epub ahead of print 25 April 2025. DOI: 10.1101/2025.04.22.25326213.

23.

Agboryah

B-ENM

Ndip

Ngomba

, et al. Factors associated with the use of digital health among healthcare workers in the Buea and Tiko health districts of Cameroon: a cross-sectional study. Pan Afr Med J 2024; 47: 51.

24.

Karamagi

Muneene

Droti

, et al. Ehealth or e-chaos: the use of digital health interventions for health systems strengthening in sub-saharan Africa over the last 10 years: a scoping review. J Glob Health 2022; 12: 4090.

25.

Ranjani

Nitika

Pradeepa

, et al. The role of digital health in tackling India’s diabetes epidemic. In: Diabetes digital health, telehealth, and artificial intelligence. Elsevier, 2024, pp.109–120. DOI: 10.1016/B978-0-443-13244-5.00022-5

26.

MoH. Digital health strategy:July 2019- June 2024, chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://www.healthdatacollaborative.org/fileadmin/uploads/hdc/Documents/Country_documents/Tanzania/Tanzania_Digital_Health_Strategy_2019_-2024.pdf (2019).

27.

PO-RALG. Status of facilities using GOTHOMIS . June 2025.

28.

Mambile

Mwogosi

. A comprehensive assessment of the government of Tanzania health operation management information system using participatory action research. Rec Manag J 2025; 35: 193–213.

29.

Mwogosi

. Revolutionizing primary health care in Tanzania: unravelling the contextual factors on electronic health record systems implementation for effective decision support. J Sci Technol Policy Manag 2024. Epub ahead of print 5 August 2024. DOI: 10.1108/JSTPM-11-2023-0205.

30.

Sukums

Simba

Kumalija

, et al. Avoiding pitfalls: Key insights and lessons learnt from customizing and rolling out a national web-based system in Tanzania. Electron J Inf Syst Dev Ctries 2021; 87: e12193.

31.

Mwogosi

. Telemedicine in Tanzania: a systematic literature review. J Health Organ Manag 2025; 39: 1290–1311.

32.

Agbeyangi

Suleman

. Advances and challenges in low-resource-environment software systems: a survey. Informatics 2024; 11: 90.

33.

Wosny

Strasser

Hastings

. Experience of health care professionals using digital tools in the hospital: qualitative systematic review. JMIR Hum Factors 2023; 10: e50357.

34.

Jeilani

Hussein

. Impact of digital health technologies adoption on healthcare workers’ performance and workload: perspective with DOI and TOE models. BMC Health Serv Res 2025; 25: 271.

35.

Mauro

Noto

Prenestini

, et al. Digital transformation in healthcare: assessing the role of digital technologies for managerial support processes. Technol Forecast Soc Change 2024; 209: 123781.

36.

Ferreira

Elvas

Correia

, et al. Empowering health professionals with digital skills to improve patient care and daily workflows. Healthcare 2025; 13: 329.

37.

Pellé

Rambaud-Althaus

D’Acremont

, et al. Electronic clinical decision support algorithms incorporating point-of-care diagnostic tests in low-resource settings: a target product profile. BMJ Glob Health 2020; 5: e002067.

38.

Nutbeam

. Health literacy as a public health goal: a challenge for contemporary health education and communication strategies into the 21st century. Health Promot Int 2000; 15: 259–267.

39.

Norman

Skinner

. Ehealth literacy: essential skills for consumer health in a networked world. J Med Internet Res 2006; 8: e9.

40.

Rahmatirad

. A review of socio-cultural theory. SIASAT 2020; 4: 23–31.

41.

Davis

. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q 1989; 13: 319.

42.

Venkatesh

Morris

Davis

, et al. User acceptance of information technology: toward a unified view. MIS Q 2003; 27: 425.

43.

Alipour

Payandeh

. Assessing the level of digital health literacy among healthcare workers of teaching hospitals in the southeast of Iran. Inform Med Unlocked 2022; 29: 100868.

44.

Regmi

Bhandary

. Factors associated with digital health literacy and attitude towards use of digital health technology among health workers of selected municipalities of lalitpur district: a mixed method study. Journal of General Practice and Emergency Medicine of Nepal 2024; 11: 52–57.

45.

Longhini

Rossettini

Palese

. Digital Health Competencies Among Health Care Professionals: Systematic Review. J Med Internet Res 2022; 24: e36414.

46.

Tegegne

Tilahun

Mamuye

, et al. Digital literacy level and associated factors among health professionals in a referral and teaching hospital: An implication for future digital health systems implementation. Front Public Health 2023; 11: 1130894.

47.

Kuek

Hakkennes

. Healthcare staff digital literacy levels and their attitudes towards information systems. Health Informatics J 2020; 26: 592–612.

48.

Holt

Overgaard

Engel

, et al. Health literacy, digital literacy and eHealth literacy in Danish nursing students at entry and graduate level: A cross sectional study. BMC Nurs 2020; 19: 22.

49.

Yuen

Winter

Savira

, et al. Digital health literacy and its association with sociodemographic characteristics, health resource use, and health outcomes: rapid review. Interact J Med Res 2024; 13: e46888.

50.

Arias

Wright

Waszak

Digital Health Systems in Africa: A convergence of opportunities, https://www.iqvia.com/-/media/iqvia/pdfs/mea/white-paper/iqvia-digital-health-system-maturity-in-africa.pdf (June 2023).

51.

Sørensen

. Fostering digital health literacy to enhance trust and improve health outcomes. Computer Methods and Programs in Biomedicine Update 2024; 5: 100140.

52.

Conard

. Best practices in digital health literacy. Int J Cardiol 2019; 292: 277–279.

53.

Kemp

Trigg

Beatty

, et al. Health literacy, digital health literacy and the implementation of digital health technologies in cancer care: the need for a strategic approach. Health Promot J Austr 2021; 32: 104–114.

54.

Tan

Chao

Jin

, et al. The association between digital health literacy and health inequalities among Chinese older adults: A multicenter cross-sectional study. Digit Health 2025; 11: 1–17.

55.

Rousseau

Gibbs

Garcia-Cabrera

, et al. A pioneering EMR-embedded digital health literacy tool reveals healthcare disparities for diverse older adults. J Am Geriatr Soc 2024; 72: S97–S104.

56.

Braun

Clarke

. Using thematic analysis in psychology. Qual Res Psychol 2006; 3: 77–101.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.02 MB