Adult (over aged 18 years) participants from Romania, Greece, Netherlands, Indonesia, Ghana, and Venezuela were approached in the collaborating clinics and invited to participate. Two participant groups per country were interviewed, one comprising actual or former TB patients and one of the TB medical staff experts. Experts had to have worked in a TB clinic on a daily basis for at least 3 years. Participants were recruited through purposive sampling by investigators visiting different medical facilities specializing in TB care. The target size was 2 to 6 participants per focus group as all participants were highly involved with the topic of TB and discussion in larger groups was not recommended [17].

The study was performed in two parts. The first phase consisted of a short questionnaire to collect demographic data and basic internet and mobile use statistics by asking the experience, in years and number of hours per day, spent using the internet and smartphones and a numbered scale on which participants ordered activities performed in order of frequency (with 5 being most frequent and 1 least frequent). Activities were defined as communication (eg, WhatsApp, Facebook Messenger), social media (eg, Facebook, Instagram), utilities (eg, banking, weather), work, games, and health/medical.

The second part consisted of semistructured focus group interviews with questions as conversation starters. The researchers allowed the interviewees to have a conversation around a specific question and asked follow-up questions for clarification. Questions were designed to repeatedly ask the same subject in different ways and at different time points during the interview to achieve data saturation irrespective of time needed. In order to adhere to qualitative reporting standards, the consolidated criteria for reporting qualitative research (COREQ) checklist was used [18].

In order to minimize the risk of bias, the researcher conducting the interviews had no previous history with the patients or medical staff involved and conducted the interviews in a private room, patients separated from medical staff. Interviews were conducted in the participants’ native tongues or in a language they felt comfortable in, transcribed verbatim, and translated by a native speaker with proficiency in English.

In order to develop a globally acceptable app that can be used in different settings, interviews targeted diverse countries with different cultures, socioeconomic statuses, and TB populations. Thus, 6 countries, Romania, Ghana, Indonesia, Greece, the Netherlands, and Venezuela, were chosen to have a mix of geography, socioeconomic statuses, health care systems, and TB profiles (Multimedia Appendix 1).

The focus groups followed a semistructured framework based on the theory of planned behavior (Textbox 1). This psychological theory proposes that intention—in our case, use of eHealth—has a number of determinants. The original work describes three main determinants, and these were used in order not only to stay true to the framework, but also to guide interviews in a simple, efficient manner. The first is the attitude toward the behavior, defined by the strength of the attitude and the evaluation of the outcome, favorable or unfavorable. The second is the subjective norm, or beliefs about the normative expectations of others: perceived social pressure to perform or preclude from the behavior. The last is the perceived ease or difficulty of performing the behavior and is based on past experience as well as anticipated factors that might facilitate or impede a specific behavior [14]. The last domain, preferred features, was added to further stratify user preferences.

The study was approved by the ethics committee of the initiating institute, the University Medical Centrum Groningen (METc 2017/448), and the medical facilities of each country participating in the study. All focus group participants signed informed consent expressing their volition to participate in the study.

A thematic approach using ATLAS.ti 8 (ATLAS.ti Scientific Software Development GmbH) was used to analyze the transcripts by one investigator (IM); this was reviewed by the supervisory authors. After major themes were identified in response to the questions asked and the theory of planned behavior framework, the transcriptions were indexed using topic coding (Textbox 2). Codes were assigned to phrases addressing an issue in the positive or negative (eg, “Maybe if we use an app, [the process] would be made simpler” versus “[eHealth] would give us double the job”) and were assigned whenever a quote was repeated by other participants in the focus group but not by the same participant. For clarification purposes, see definitions in Multimedia Appendix 2. All of the coding was performed by two independent authors (IM, CL). Conflicts were resolved by discussions between the coders with the aid of one of the supervisors (YS).

Descriptive statistics were used to present quantitative results. Medians and interquartile ranges were used to present internet and mobile experience. Codes were reported as a total and per domain, and themes were reported as proportions of the total.

A total of 29 patients and 32 medical staff members responded to the questionnaire and participated in the focus group. Four patients were former TB patients and had finished their treatment within 6 months of the interview, with the majority being current patients. Ages ranged between 23 and 63 years for patients and 30 and 60 years for medical staff. Gender distribution was mostly male (20/29, 68%) among patients and mostly female (26/32, 81%) among medical staff; 65% (19/29) of patients and 68% (22/32) of medical staff lived in urban environments. Education levels were lower in patients groups than in the medical staff group: among patients, the highest level of education was a bachelor’s degree, and among medical staff, the highest level was doctorate (PhD).

General internet and mobile internet use was almost half within the patient group compared with the medical staff (Figure 1): average years of experience using the internet was 6.1 (range 1-16) person-years versus 13.9 (range 5-35) person-years. All medical staff had used the internet, whereas 31% (9/29) of patients had never been online. Concerning mobile phone use, staff median experience was 7.4 (range 0.3-15) person-years versus 3.4 (range 0-10) person-years for patients; 44% (13/29) of patients had never used mobile data and 34% (10/29) had never used a smartphone. Of all patient groups, the least tech savvy were the Romanians and the most were from Venezuela. From the medical staff groups, participants from Ghana had the least experience with the internet and mobile, and participants from the Netherlands had the most. Internet and mobile use in hours per day were lower for people from the low- and middle-income countries than the high-income countries, but this correlation was observed only in the patient groups and not in the expert groups.

The 20 patients who used the internet mostly used it for communication (median 4/6), followed by social media (median 4/6), utilities (median 3/6), medical/health (median 2/6), work (median 1/6), and games (median 1/6). For smartphones, the 18 patients ordered the categories the same, but with more patients using Messenger (median 4.5/6) and fewer using for social media and utilities (median 3/6). The 32 staff members used the internet mostly for communication and work (median 5/6); games were the least used (median 1/5). Medical staff use smartphones also mostly for communication (median 5/6), followed by social media (median 4/6), and work (4/6).

The final yield was 13 focus group interviews, two per country, with 2 focus groups conducted with Dutch medical staff as the TB clinic and at the Municipal Health Center Groningen (a type of outpatient clinic) are geographically separated. The duration of interviews ranged between 25 and 45 minutes.

By domain, attitude toward behavior contained the most quotes (339), with preferred features containing the least (161). By far the most discussed topic was the potential of eHealth to improve information and/or education concerning TB among patients, the public, and even medical staff (144 quotes). The countries that mentioned this aspect the most were Venezuela (55 quotes) and the Netherlands (31 quotes).

A summary of the most frequent themes/codes and example quotations can be found in Multimedia Appendix 2.

The attitude toward behavior domain contained 5 codes, with a total yield of 339 quotations out of the total 911 quotations (37.2%), the most of all domains. Even though experience varied between patients and medical staff, both groups explained that their outlook concerning implementing eHealth in TB was overwhelmingly positive (292/339, 86.1%), with the most expected impact in the information and communication fields.

Participants also offered examples of specific ways in which eHealth could improve TB management.

Participants felt that speed, convenience, flexibility, and the ability to communicate and obtain information over long distances were very important factors contributing to a positive outcome.

Although the expected outcome is mostly positive, some challenges have been identified, such as a need for personal contact. Interestingly, within the same focus group, one person believed an app would enhance contact and others did not.

Furthermore, patients mentioned a need for trustworthy sources of information, and some medical staff were concerned about patients intruding on their personal time if the app were to be on their personal phones or of doubling the workload (traditional system and eHealth).

The subjective norm domain contained 6 codes with 22.8% (208/911) of the total quotations. All groups felt there is a certain degree of pressure to perform the behavior as they felt the status quo should be improved, and they thought eHealth could be a useful tool for such improvement. Participants described gaps especially in communication and information access that would encourage them to use a trusted eHealth app.

Concerning the particular use of eHealth in TB and the perceived subjective norm concerning the general public, patients spoke about stigma and how eHealth, through education, could solve such problems.

Participants believed either that eHealth would be easy to implement or that it is possible but that ease of implementation will depend on certain factors, most frequently technology savviness.

Participants also mentioned lack of resources as possible impediments to eHealth implementation. Lower income countries tended to mention more often a lack of physical resources, such as electricity, network coverage, or hardware (computers, phones), whereas higher income countries were worried about the lack of human resources needed to manage a potential extra burden of eHealth.

Perceived ease or difficulty toward behavior contained 9 codes and 22.2% (203/911) of the total quotations. A minority of participants expressed they didn’t think they could use a new app, quoting reasons such as illiteracy or lack of time. Most either said they would have no problems integrating a new app within their digital routines or that they would require certain facilitators that would promote adoption (eg, have a simple interface, contain a training module).

Participants identified steps that are mandatory to perform in order to have an easy-to-use app, such as privacy or localizing the app.

Facilitators concerning implementation, such as financial incentives in the form of extra staff or equipment or offering the app for free were also identified, especially since some participants expressly mentioned the financial difficulties some patients are in.

Some participants expressed a desire to be trained in how to use the app or for a demo module to be presented as they believe this would facilitate quick adoption.

Concerning the app itself, participants believed ease of use would be furthered by a simple and friendly user interface, by adding a community-building module (either for the patients or for medical staff), adding a training module, and using videos to transmit information.

Preferred features contained 7 codes with 17.6% (161/911) of the total quotations. Concerning information media, most participants expressed a preference for video, followed by images, text, and a gamification component, such as quizzes, to enhance the user experience.

Participants would rather use the app for treatment (38/61) than for diagnosis (17/61) or prevention (19/61), and they would want a notification or reminding system implemented to encourage treatment adherence and follow-up.

Using a health behavior framework for market research [19], this study explored attitudes toward eHealth implementation in TB. Semistructured focus group interviews were performed worldwide with medical staff and patients to better understand key motivators, challenges, facilitators, and user preferences for implementing new eHealth solutions. A number of important insights have been gathered, as has a prioritization of features to be implemented, which can be used when planning new eHealth apps for TB. Overall, both patients and TB experts have expressed enthusiasm at the potential of eHealth, with an overwhelming consensus that the first domains where it could be useful are information and communication.

The attitude toward eHealth domain contained the most codes. We interpreted this result in the context of participants having already formed an opinion on this subject and welcomed the opportunity to discuss it in depth. The domain presents encouraging results, with 67% (229/339) of codes expressing a positive expectation about eHealth capabilities. Participants overwhelmingly felt there is a lack of knowledge about TB among patients, the general public, and even among medical practitioners. These findings are mirrored by a systematic review that concluded there is a lack of knowledge among medical practitioners concerning national or internal TB guidelines within 14 non-European countries [20] and by multiple studies identifying knowledge gaps among patients [21-23]. Furthermore, a recent review highlighted that many apps offer inaccurate information [24]. Participants expect that an eHealth solution would be used to educate and provide accurate, secure, and friendly information.

The subjective norm describes the most important pressure to adopt eHealth as the lack of information and communication, felt across the board. Participants described a lack of clear, open communication channels both between patients and medical staff and between different specialties involved in TB management. Multiple studies have linked lack of patient-medical staff relationships to poorer outcomes in TB [25-27], concluded that communication methods should be tailored [28], or called for improving collaborations between medical staff involved in TB care [29]. Participants in our study would not only welcome online TB-related communities but also believe that communication could be improved through an app and that, in itself, would improve TB management and the stigma felt at the moment. On the other hand, a challenge identified was the need for human, personal contact, identified especially by a minority of Dutch participants (2).

Concerning perceived ease or difficulty of use, most participants felt they could implement a new app easily, although some participants mentioned a fear that a new app would be time consuming.

One important factor that could influence adoption was identified as technology savviness, linked to age and experience with use; however, some participants felt that training could bridge this gap. Indeed, one study using video directly observed therapy noted that “Older participants in particular enjoyed learning to use a smartphone” [30]. A facilitator mentioned by some participants is localization, translating the app in the local language. A minority of participants quoted illiteracy as a barrier to regular app use.

On a local level, interviewees from countries with a resource paucity, such as Venezuela or Greece, expressed a need for extra human or physical resources. Most participants agreed that an app should be free. Interestingly, concerning technology accessibility, opinions varied widely, from “even if they are illiterate they use the internet, google, even if they can’t write their own signature, they can go online” to “they probably have 1 smartphone per family and they don’t use the internet all the time.”

From a development perspective, the only truly mandatory feature to be implemented would be privacy/security, as this was a concern expressed in multiple interviews, both by experts and patients. A recent systematic review performed by the authors (unpublished) highlighted that within 7 studies that quantified this aspect, there were zero privacy breaches for a pooled 71 patients.

Participants mentioned other features, such as a treatment module with asynchronous video therapy, reminders, and a diagnosis module with an emphasis on self-diagnosing education in order to hasten hospital visits. Participants also expressed a desire to have a gamification component and believed video would best facilitate app adoption.

Textbox 3 summarizes recommendations for developing a new eHealth app for TB.

There are few studies exploring user attitudes for eHealth in TB. A study from Mozambique exploring text messaging found, as our study did, that messaging should be used for reminders and motivational texts in order to increase retention and that the main obstacle would be privacy assurance [31]. Another study involving focus group interviews with medical staff for a chronic obstructive pulmonary disease telerehabilitation app found that education and skill training are highly essential to support successful implementation [32]. A study from Saudi Arabia showed that perceived usefulness and perceived ease are significant factors to performing the behavior, results corroborated by our study [33]. Furthermore, a recent systematic review (unpublished) performed by the main authors revealed that already implemented eHealth apps focused rarely on education, despite it being one of the two major needs felt by the participants within the focus groups.

This study offers a more diverse perspective on eHealth use in TB by conducting interviews in 6 countries on 4 different continents to gain a more global perspective for a potential app that could be universally applicable.

Purposive sampling was used, which might have selected participants already more open to new technology. Furthermore, individual interviews might have elicited different results as they have less risk of bias and are more in-depth. The theory of planned behavior is a useful tool to gauge decision making with the caveat that it does not take in account socioeconomic, religious, and gender-based factors.

This study was conducted in 6 different settings, offering a better understanding of what populations across the globe might decide concerning adopting eHealth in TB management. TB patients and TB experts were approached, thus covering the potential user base for future eHealth solutions. The theory of planned behavior is a simple, elegant way to conduct focus group interviews and understand decision-making processes. Two independent authors coded the interviews, thus limiting bias.

This study used focus group interviews performed in 6 countries in order to gauge perceptions about eHealth use in TB management and draw recommendations for further implementation. Participants in all 6 countries are enthusiastic about eHealth, and most users expect a potential app to be helpful. There is a global need to improve information access and communication, and participants feel that eHealth could help bridge this gap. Most themes resounded in all countries interviewed, but certain particularities, such as a large proportion of asylum seekers or lack of infrastructure or training, should be addressed when trying to implement eHealth in specific settings. Despite individual preferences, the global sentiment is that eHealth is a promising field of research that will be well received with the potential to enhance multiple aspects of TB care, with an emphasis on the need to communicate and educate.