Mobile Health Apps for Improvement of Tuberculosis Treatment: Descriptive Review

Climate change, its impact on emerging infectious diseases and new technologies to combat the challenge

ABSTRACTImproved sanitation, increased access to health care, and advances in preventive and clinical medicine have reduced the mortality and morbidity rates of several infectious diseases. However, recent outbreaks of several emerging infectious diseases (EIDs) have caused substantial mortality and morbidity, and the frequency of these outbreaks is likely to increase due to pathogen, environmental, and population effects driven by climate change. Extreme or persistent changes in temperature, precipitation, humidity, and air pollution associated with climate change can, for example, expand the size of EID reservoirs, increase host-pathogen and cross-species host contacts to promote transmission or spillover events, and degrade the overall health of susceptible host populations leading to new EID outbreaks. It is therefore vital to establish global strategies to track and model potential responses of candidate EIDs to project their future behaviour and guide research efforts on early detection and diagnosis technologies and vaccine development efforts for these targets. Multi-disciplinary collaborations are demanding to develop effective inter-continental surveillance and modelling platforms that employ artificial intelligence to mitigate climate change effects on EID outbreaks. In this review, we discuss how climate change has increased the risk of EIDs and describe novel approaches to improve surveillance of emerging pathogens that pose the risk for EID outbreaks, new and existing measures that could be used to contain or reduce the risk of future EID outbreaks, and new methods to improve EID tracking during further outbreaks to limit disease transmission.

Effect of a Mobile Health-Based Remote Interaction Management Intervention on the Quality of Life and Self-Management Behavior of Patients With Low Anterior Resection Syndrome: Randomized Controlled Trial

BACKGROUND

People who undergo sphincter-preserving surgery have high rates of anorectal functional disturbances, known as low anterior resection syndrome (LARS). LARS negatively affects patients' quality of life (QoL) and increases their need for self-management behaviors. Therefore, approaches to enhance self-management behavior and QoL are vital.

OBJECTIVE

This study aims to assess the effectiveness of a remote digital management intervention designed to enhance the QoL and self-management behavior of patients with LARS.

METHODS

From July 2022 to May 2023, we conducted a single-blinded randomized controlled trial and recruited 120 patients with LARS in a tertiary hospital in Hefei, China. All patients were randomly assigned to the intervention group (using the "e-bowel safety" applet and monthly motivational interviewing) or the control group (usual care and an information booklet). Our team provided a 3-month intervention and followed up with all patients for an additional 3 months. The primary outcome was patient QoL measured using the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30. The secondary outcomes were evaluated using the Bowel Symptoms Self-Management Behaviors Questionnaire, LARS score, and Perceived Social Support Scale. Data collection occurred at study enrollment, the end of the 3-month intervention, and the 3-month follow-up. Generalized estimating equations were used to analyze changes in all outcome variables.

RESULTS

In the end, 111 patients completed the study. In the intervention group, 5 patients withdrew; 4 patients withdrew in the control group. Patients in the intervention group had significantly larger improvements in the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 total score (mean difference 11.51; 95% CI 10.68-12.35; Cohen d=1.73) and Bowel Symptoms Self-Management Behaviors Questionnaire total score (mean difference 8.80; 95% CI 8.28-9.32; Cohen d=1.94) than those in the control group. This improvement effect remained stable at 3-month follow-up (mean difference 14.47; 95% CI 13.65-15.30; Cohen d=1.58 and mean difference 8.85; 95% CI 8.25-9.42; Cohen d=2.23). The LARS score total score had significantly larger decreases after intervention (mean difference -3.28; 95% CI -4.03 to -2.54; Cohen d=-0.39) and at 3-month follow-up (mean difference -6.69; 95% CI -7.45 to -5.93; Cohen d=-0.69). The Perceived Social Support Scale total score had significantly larger improvements after intervention (mean difference 0.47; 95% CI 0.22-0.71; Cohen d=1.81).

CONCLUSIONS

Our preliminary findings suggest that the mobile health-based remote interaction management intervention significantly enhanced the self-management behaviors and QoL of patients with LARS, and the effect was sustained. Mobile health-based remote interventions become an effective method to improve health outcomes for many patients with LARS.

TRIAL REGISTRATION

Chinese Clinical Trial Registry ChiCTR2200061317; https://tinyurl.com/tmmvpq3.

Innovative Approaches to Enhance and Measure Medication Adherence in Chronic Disease Management: A Review

Medication non-adherence is a problem that affects up to 50% of patients with chronic diseases. The result is a failure to achieve therapeutic goals and an increased burden on the healthcare system. It is, therefore, highly appropriate to develop models to assess patient adherence to prescribed therapy. To date, there are many methods for doing this. However, several tools have been developed that subjectively or objectively, directly or indirectly, assess the level of patient adherence. Electronic medication packaging devices are among the most rapidly evolving methods of measuring adherence. Other emerging technologies include the use of artificial intelligence algorithms and ingestible biosensors. The former is being used to create applications for mobile phones and laptops. The latter appears to be the least susceptible to the risk of overestimating adherence but remains very expensive. Here, we present recent developments in measuring patient adherence, and provide details of achievements in objective methods for assessing adherence, such as electronic monitoring devices, video-observed therapy, and ingestible biosensors. A dedicated section on using artificial intelligence and machine learning in adherence measurement and reviewing questionnaires and scales used in specific diseases is also included. Methods are discussed along with their advantages and potential limitations. This article aimed to review current measures and future initiatives to improve patient medication adherence.

"An app is just available at all times"-the process and outcomes of converting the Georgia Tuberculosis Reference Guide into a mobile application

BACKGROUND

The physical, paper-based Georgia TB Reference Guide has served as the clinical reference handbook on tuberculosis (TB) diagnostic and treatment guidelines for the state of Georgia in the United States. Supported by the Georgia Department of Public Health, the production of the 112-page palm-sized booklet was previously led by a team of Georgia-based TB experts at Emory University and printed every three-five years with updates to clinical management guidelines and TB consult contact information. However, the costs associated with editorial printing combined with delays in updating a static printed booklet with revised guidance hampered the utility of the tool. Considering the barriers with paper-based production and based on the beneficial use of apps to support the dissemination of clinical management guidance in other settings, the booklet was converted into a mobile application. This paper describes the process of developing a mobile app version of the Georgia TB Reference Guide in an easy-to-update and readily available format.

METHODS

We employed a user-centered design approach to develop the app, including a series of qualitative interviews and quantitative surveys. Participants included a mix of state officials and local TB experts. First, initial foundational interviews were conducted to conceptualize current utilization practices of both the paper and PDF versions of the tool. Second, the findings from the initial interviews were organized thematically and informed the design of the app, which was then beta tested by a round of previously unsampled TB experts as well as a re-sample from the initial interviews. Third, the designs were coded into developmental phases and beta tested among users of the current Georgia TB Reference Guide. Fourth, the app was published and downloaded by a pre-selected group of local users who provided answers to a follow-up survey after using the app for one month. Fifth, user growth, self-reported demographics, and app usage between February and July 2022 were recorded through automatic data metrics built into the app.

RESULTS

The paper copy Georgia TB Reference Guide usage themes included commonly referenced content, navigation paths, and desired features and content. The themes were converted into features and designs such as prioritizing commonly reviewed topics and guide customization with bookmarks and notes. Iterations of the designs were driven by feedback from TB experts and included home page featured content, improving content readability, and improving the search feature. The follow-up survey revealed a 90% preference for the app over the paper version of the guide. In the six months following the app's release, the app was downloaded by 281 individuals in the United States. The majority of downloads were in Georgia and the app also expanded organically to 19 other states.

CONCLUSION

The experience of converting the Georgia TB Reference Guide offers specific and effective steps to converting a medical reference guide into a mobile application tool that is readily available, easy to use, and easy to update. The organic dissemination of the app beyond the state of Georgia's borders within the first six months of app launch underscores desire among TB healthcare professionals for high-quality digital reference content outside the state. This experience offers clear outlines for replication in other contexts and demonstrates the utility of similar mobile medical reference tools.

Experience of Older Patients with COPD Using Disease Management Apps: A Qualitative Study

(1) Background: Digital medicine is developing in the management of chronic diseases in older people, but there is still a lack of information on the use of disease management apps in older patients with COPD. This study aims to explore the views and experience of older patients with COPD on disease management apps to provide a basis for the development and promotion of apps for geriatric diseases. (2) Methods: A descriptive qualitative research method was used. Older patients with COPD (N = 32) with experience using disease management apps participated in semi-structured interviews. Thematic analysis was used to analyze the data. (3) Results: Seven themes were defined: (a) feeling curious and worried when facing disease management apps for the first time; (b) actively overcoming barriers to use; (c) gradually becoming independent by continuous online learning; (d) feeling safe in the virtual environment; (e) gradually feeling new value in online interactions; (f) relying on disease management apps under long-term use; (g) expecting disease management apps to meet personalized needs. (4) Conclusions: The adoption and use of disease management apps by older people is a gradual process of acceptance, and they can obtain a wide range of benefits in health and life.

Usability testing of a mobile health application to support individuals with active tuberculosis: a mixed methods study

Poor adherence to tuberculosis (TB) treatment leads to further disease transmission, worsened outcomes, and the development of drug resistance. Digital adherence technologies may facilitate a more patient-centered approach for improving TB treatment outcomes than current strategies. The objective of this study was to evaluate and explore improving usability of the TB Treatment Support Tools (TB-TST) mobile application. We used an iterative convergent mixed-method design consisting of two quantitative surveys and a qualitative think-aloud interview. Testing was conducted in three testing cycles consisting of a total of 16 interviews and 26 surveys. Results were thematically analyzed and reported to the development team during weekly team meetings. Participants rated the TB-TSTs application as having high usability and the iterative approach resulted in several refinements to the application in response to participant feedback. These refinements were well received during qualitative interviews but did not result in a statistically significant improvement in usability testing scores between cycles. Using an iterative convergent mixed-method design was an effective method for refining our mHealth application. Data collected from think-aloud interviews, the MAUQ, and the Health-ITUES identified key areas of application design that needed refinement.

Implementation bottlenecks of real time medication monitoring (evriMED) for improving adherence to anti-TB drugs among people with tuberculosis in Kilimanjaro, Tanzania

Introduction

Digital Adherence Tools (DATs), which include real-time medication monitoring and Short Message Service (SMS) reminders, have been reported to improve medication adherence among people with Tuberculosis (TB). Recently, in limited resource settings, DATs have been described as a promising tool to monitor patients' medication behaviour. We aimed to determine implementation bottlenecks of real-time medication monitoring using the evriMED device.

Method

We conducted a research study using a mixed-methods approach, involving both people with TB s and directly observed treatment (DOT) providers who participated in the REMIND-TB trial and utilized the evriMED devices. EvriMED is a medication dispenser with internet connectivity that can send real-time SMS reminders. To gather data, we extracted reports from the Wisepill dashboard, specifically the client status report. This report documented the activity status of all devices, including communication and battery status. Additionally, we conducted in-depth interviews with people with TB and TB care providers who were involved in implementing the Remind TB trial in the Kilimanjaro region. These interviews were guided by the MIDI (Measurement Instrument for Determinants of Innovation), which helps identify the factors influencing the implementation of innovations such as evriMED.

Results

Out of the initial 281 participants who were given devices, 245 completed the 6-month follow-up period. The findings indicate that at month 6, most of the devices (49%) reported battery-related challenges. Additionally, forty devices (14%) had reported more than one incidence of losing communication. Through interviews with participants, we observed that evriMED was perceived as user-friendly, and the people with TB reported high satisfaction as the device facilitated improved medication intake. TB care providers also said that evriMED was a relevant tool to be used by the people with TB. However, during the in-depth interview certain implementation bottlenecks were identified, including network issues, limited training, and low technology knowledge among TB care providers, who found the procedure of using the evriMED to be time-consuming.

Conclusion

Implementation of evriMED was perceived as user-friendly and highly satisfactory by people with TB. Certain implementation bottlenecks were identified as potential barriers to the use of devices. These bottlenecks include network issues, limited training, battery-related challenges and low technological knowledge among TB care providers, which may have contributed to communication loss. Further research may be needed to address these limitations and develop effective strategies to facilitate the successful implementation of evriMED as a tool for improving medication intake among people with TB.

Utilization of digital tools to enhance COVID-19 and tuberculosis testing and linkage to care: A cross-sectional evaluation study among Bodaboda motorbike riders in the Nairobi Metropolis, Kenya

Kenya has registered over 300,000 cases of COVID-19 and is a high-burden tuberculosis country. Tuberculosis diagnosis was significantly disrupted by the pandemic. Access to timely diagnosis, which is key to effective management of tuberculosis and COVID-19, can be expanded and made more efficient through integrated screening. Decentralized testing at community level further increases access, especially for underserved populations, and requires robust systems for data and process management. This study delivered integrated COVID-19 and tuberculosis testing to commercial motorbike (Bodaboda) riders, a population at increased risk of both diseases with limited access to services, in four counties: Nairobi, Kiambu, Machakos and Kajiado. Testing sheds were established where riders congregate, with demand creation carried out by the Bodaboda association. Integrated symptom screening for tuberculosis and COVID-19 was conducted through a digital questionnaire which automatically flagged participants who should be tested for either, or both, diseases. Rapid antigen-detecting tests (Ag-RDTs) for COVID-19 were conducted onsite, while sputum samples were collected and transported to laboratories for tuberculosis diagnosis. End-to-end patient data were captured using digital tools. 5663 participants enrolled in the study, 4946 of whom were tested for COVID-19. Ag-RDT positivity rate was 1% but fluctuated widely across counties in line with broader regional trends. Among a subset tested by PCR, positivity was greater in individuals flagged as high risk by the digital tool (8% compared with 4% overall). Of 355 participants tested for tuberculosis, 7 were positive, with the resulting prevalence rate higher than the national average. Over 40% of riders had elevated blood pressure or abnormal sugar levels. The digital tool successfully captured complete end-to-end data for 95% of all participants. This study revealed high rates of undetected disease among Bodaboda riders and demonstrated that integrated diagnosis can be delivered effectively in communities, with the support of digital tools, to maximize access.

Effect of mobile health reminders on tuberculosis treatment outcomes in Shanghai, China: A prospective cohort study

Background

Poor adherence increases the risk of unfavorable outcomes for tuberculosis (TB) patients. Mobile health (mHealth) reminders become promising approaches to support TB patients' treatment. But their effects on TB treatment outcomes remain controversial. In this prospective cohort study, we evaluated the effect of the reminder application (app) and the smart pillbox on TB treatment outcomes compared with the standard care in Shanghai, China.

Methods

We recruited new pulmonary TB (PTB) patients diagnosed between April and November 2019 who were aged 18 or above, treated with the first-line regimen (2HREZ/4HR), and registered at Songjiang CDC (Shanghai). All eligible patients were invited to choose the standard care, the reminder app, or the smart pillbox to support their treatment. Cox proportional hazard model was fitted to assess the effect of mHealth reminders on treatment success.

Results

260 of 324 eligible patients enrolled with 88 using standard care, 82 the reminder app, and 90 the smart pillbox, followed for a total of 77,430 days. 175 (67.3%) participants were male. The median age was 32 (interquartile range [IQR] 25 to 50) years. A total of 44,785 doses were scheduled for 172 patients in the mHealth reminder groups during the study period. 44,604 (99.6%) doses were taken with 39,280 (87.7%) monitored by the mHealth reminders. A significant time-dependent downward linear trend was observed in the monthly proportion of dose intake (p < 0.001). 247 (95%) patients were successfully treated. The median treatment duration of successfully treated patients in the standard care group was 360 (IQR 283-369) days, significantly longer than those in the reminder app group (296, IQR 204-365, days) and the smart pillbox group (280, IQR 198-365, days) (both p < 0.01). Using the reminder app and the smart pillbox was associated with 1.58 times and 1.63 times increase in the possibility of treatment success compared with the standard care, respectively (both p < 0.01).

Conclusion

The reminder app and the smart pillbox interventions were acceptable and improved the treatment outcomes compared with the standard care under the programmatic setting in Shanghai, China. More high-level evidence is expected to confirm the effect of mHealth reminders on TB treatment outcomes.

Infection tracking in travellers using a mobile app (ITIT): The pilot study

BACKGROUND

Current surveillance of travellers' health captures only a small proportion of illness events. We aimed to evaluate the usability and feasibility of using an app to enable travellers to self-report illness.

METHOD

This pilot study assesses a novel mobile application called Infection Tracking in Travellers (ITIT) that records travel-related symptoms with associated geolocation and weather data. Participants were recruited in three Swiss travel clinics between December 2021 and March 2022. A feedback survey was used to examine app ease of use, and data from the app was used to examine travel and illness patterns as a proof-of-concept for the larger ITIT study.

RESULTS

Participants were recruited from Zürich, Basel, and Geneva, with 37 individuals completing a total of 394 questionnaires in 116 locations in Asia, Africa, the Americas, and Europe. Illness symptoms were reported by 41% of participants, 67% of which were respiratory. The post travel questionnaire showed that all participants found the app easy to use and 63% said they would recommend it to others. Several users provided suggestions for improved usability.

CONCLUSION

The app fulfilled its function as a research tool linking infection symptoms with geolocation and climate data.

Pharmacokinetics and pharmacodynamics of anti-tuberculosis drugs: An evaluation of in vitro, in vivo methodologies and human studies

There has been an increased interest in pharmacokinetics and pharmacodynamics (PKPD) of anti-tuberculosis drugs. A better understanding of the relationship between drug exposure, antimicrobial kill and acquired drug resistance is essential not only to optimize current treatment regimens but also to design appropriately dosed regimens with new anti-tuberculosis drugs. Although the interest in PKPD has resulted in an increased number of studies, the actual bench-to-bedside translation is somewhat limited. One of the reasons could be differences in methodologies and outcome assessments that makes it difficult to compare the studies. In this paper we summarize most relevant in vitro, in vivo, in silico and human PKPD studies performed to optimize the drug dose and regimens for treatment of tuberculosis. The in vitro assessment focuses on MIC determination, static time-kill kinetics, and dynamic hollow fibre infection models to investigate acquisition of resistance and killing of Mycobacterium tuberculosis populations in various metabolic states. The in vivo assessment focuses on the various animal models, routes of infection, PK at the site of infection, PD read-outs, biomarkers and differences in treatment outcome evaluation (relapse and death). For human PKPD we focus on early bactericidal activity studies and inclusion of PK and therapeutic drug monitoring in clinical trials. Modelling and simulation approaches that are used to evaluate and link the different data types will be discussed. We also describe the concept of different studies, study design, importance of uniform reporting including microbiological and clinical outcome assessments, and modelling approaches. We aim to encourage researchers to consider methods of assessing and reporting PKPD of anti-tuberculosis drugs when designing studies. This will improve appropriate comparison between studies and accelerate the progress in the field.

A Scoping Review on Accentuating the Pragmatism in the Implication of Mobile Health (mHealth) Technology for Tuberculosis Management in India

Background: India continues to share a colossal count of the global tuberculosis load, with a perturbing 19% spring in the reported cases in 2021. With the National Tuberculosis Elimination Program (NTEP) consolidated to bring this epidemic to an end by 2025, the rapidly growing mobile health technologies can be utilized to offer promising results. Even though the implementation of this novel strategy is escalating around the globe, its triumph is still sub optimal in India. Objectives: This scoping review intends to explore the available mobile health (mHealth) technologies and analyse the effectiveness of the same for tuberculosis management in India. Methods: An elaborate search in electronic databases, such as PubMed and Google scholar, using the key terms and focussing from the year 2015, provided very broad results focussing on mHealth interventions and their utilisation in TB management in India. Further selection of the inclusive publications was carried out based upon the eligibility requirements as formulated for this review, pertaining to the objective of this study. Results: The collaborate search yielded a total of 858 scientific research papers. After the filtering of the obtained results, a total of 45 articles were selected to be analysed for this review. Published manuscripts, articles in peer review and abstracts from reliable databases were included to obtain vast range of information. Conclusion: The extensive literature search showed a preponderance of mHealth intervention studies focusing on TB treatment and drug monitoring. There exists a paucity of mHealth applications targeted to educate the public and intercept this infectious disease. The scientific articles reviewed and analysed in this scoping review strongly recommend the demployment of mHealth applications to achieve the target of eradicating TB by 2025 in India.

Relational Agents for the Homeless with Tuberculosis Experience

In human–computer interaction (HCI) research, relational agents (RAs) are increasingly used to improve social support for vulnerable groups including people exposed to stigmas, alienation, and isolation. However, technical support for tuberculosis (TB) patients, one such vulnerable group, remains insufficient due to the nature of the infectious disease and difficulties in accessing the homeless community. To derive design considerations for developing RAs targeting homeless TB patients, we conducted an empirical study on the patients. Data were collected through participatory observations and interviews and were processed using deductive thematic analysis. The patients’ environmental and behavioral characteristics were classified, which showed that understanding these factors in the design of an RA is important because the patients’ perception, attitudes, and expectations towards the agent are shaped by (and also shape) their environmental and behavioral characteristics, which consequently affect the nature of relationships formed between them. Therefore, we drew the following design considerations: (1) protection of privacy is a prerequisite to the use of an RA for homeless TB patients and can be addressed from both short-term (technical) and long-term (sociotechnical) perspectives; (2) the homeless group emphasized affective support from the agent, suggesting that relationships per se are already valuable to people who have been socially isolated and stigmatized; (3) consideration of the past memories in selecting social cues can facilitate the exchange of affective expressions in user–agent interaction; and (4) an RA should clarify to its interlocuters its identity as a machine to avoid confusing people with low technological literacy.

Monitored Implementation of COVID-19 Rapid Antigen Screening at Taxi Ranks in Johannesburg, South Africa

Digital tools can support community-based decentralized testing initiatives to broaden access to COVID-19 diagnosis, especially in high-transmission settings. This operational study investigated the use of antigen-detecting rapid diagnostic tests (Ag-RDTs) for COVID-19 combined with an end-to-end digital health solution, in three taxi ranks in Johannesburg, South Africa. Members of the public were eligible if they were aged ≥18 years, could read, and had a cellphone. Over 15,000 participants, enrolled between June and September 2021, were screened for COVID-19 risk factors. A digital risk questionnaire identified 2061 (13%) participants as moderate risk and 2987 (19%) as high risk, based on symptoms and/or recent exposure to a known case. Of this group referred for testing, 3997 (79%) received Ag-RDTs, with positivity rates of 5.1% in the "high-risk" group and 0.8% in the "moderate-risk" group. A subset of 569 randomly selected participants received additional PCR testing. Sensitivity of the Ag-RDT in this setting was 40% (95% CI: 30.3%, 50.3%); most false negatives had high cycle threshold values (>25), hence low viral loads. Over 80% of participants who tested positive completed a 2-week phone-based follow-up questionnaire. Overall, the digital tool combined with Ag-RDTs enhanced community-based decentralized COVID-19 testing service delivery, reporting and follow-up.

The use of technology-based adherence monitoring in the treatment of hepatitis C virus

Direct-acting antivirals (DAAs) achieve high hepatitis C virus (HCV) cure rates and are forgiving to missed doses, but adherence–efficacy relationships have not been well defined. Traditional adherence measures (e.g. pill counts, self-report and pharmacy refills) over-estimate medication adherence. Newer technology-based tools have been used to provide more objective adherence data. Herein, electronic medication diaries (e-diaries), medication events monitoring system (MEMS^®) caps, electronic blister packs, electronic pill boxes, video-based directly observed therapy (vDOT), artificial intelligence platforms (AIPs), and ingestible sensor systems are described, and compared based on existing studies using DAA. Percent adherence, predictors of adherence, and HCV cure rates utilizing these technologies are included. DAA adherence with e-diaries was 95–96%, MEMS^® caps and ingestible biosensors were between 95% and 97%, blister pack weekly dosing ranged 73–98%, and daily dosing 73–94%, whereas electronic pill boxes ranged between 39% and 89%, vDOT was 98% and AIP 91–96%. Despite a wide range of adherence, high sustained virologic response (SVR) rates (86–100%) were observed across all studies utilizing these different technology-based tools. Current data support the forgiveness of DAA therapies to missed doses using tools that provide more quantitative adherence measures compared with self-report and provide insight on adherence–efficacy relationships for contemporary DAA.

Acceptance of an Informational Antituberculosis Chatbot Among Korean Adults: Mixed Methods Research

BACKGROUND

Tuberculosis (TB) is a highly infectious disease. Negative perceptions and insufficient knowledge have made its eradication difficult. Recently, mobile health care interventions, such as an anti-TB chatbot developed by the research team, have emerged in support of TB eradication programs. However, before the anti-TB chatbot is deployed, it is important to understand the factors that predict its acceptance by the population.

OBJECTIVE

This study aims to explore the acceptance of an anti-TB chatbot that provides information about the disease and its treatment to people vulnerable to TB in South Korea. Thus, we are investigating the factors that predict technology acceptance through qualitative research based on the interviews of patients with TB and homeless facility personnel. We are then verifying the extended Technology Acceptance Model (TAM) and predicting the factors associated with the acceptance of the chatbot.

METHODS

In study 1, we conducted interviews with potential chatbot users to extract the factors that predict user acceptance and constructed a conceptual framework based on the TAM. In total, 16 interviews with patients with TB and one focus group interview with 10 experts on TB were conducted. In study 2, we conducted surveys of potential chatbot users to validate the extended TAM. Survey participants were recruited among late-stage patients in TB facilities and members of web-based communities sharing TB information. A total of 123 responses were collected.

RESULTS

The results indicate that perceived ease of use and social influence were significantly predictive of perceived usefulness (P=.04 and P<.001, respectively). Perceived usefulness was predictive of the attitude toward the chatbot (P<.001), whereas perceived ease of use (P=.88) was not. Behavioral intention was positively predicted by attitude toward the chatbot and facilitating conditions (P<.001 and P=.03, respectively). The research model explained 55.4% of the variance in the use of anti-TB chatbots. The moderating effect of TB history was found in the relationship between attitude toward the chatbot and behavioral intention (P=.01) and between facilitating conditions and behavioral intention (P=.02).

CONCLUSIONS

This study can be used to inform future design of anti-TB chatbots and highlight the importance of services and the environment that empower people to use the technology.

Effect of mHealth intervention for pulmonary tuberculosis self-management based on the Integrated Theory of Health Behavior Change (ITHBC): a randomized controlled trial (Preprint)

Background

Improving the health self-management level of patients with tuberculosis (TB) is significant for reducing drug resistance, improving the cure rate, and controlling the prevalence of TB. Mobile health (mHealth) interventions based on behavioral science theories may be promising to achieve this goal.

Objective

This study aims to explore and conduct an mHealth intervention based on the Integrated Theory of Health Behavior Change (ITHBC) in patients with pulmonary TB to increase their ability of self-care management.

Methods

A prospective randomized controlled study was conducted from May to November 2020. A total of 114 patients who were admitted consecutively to the TB clinic of Harbin Chest Hospital, China from May 2020 to August 2020 were recruited by convenience sampling. Patients were divided into the control group and intervention group, and all received a 3-month intervention. Patients in the intervention group and the control group received routine medical and nursing care in the TB clinic, including the supervision of their medications. In addition, pharmacist-assisted mHealth (WeChat) intervention based on the ITHBC theory about TB management was provided to the intervention group. The primary outcome was self-management behavior, while the secondary outcomes were TB awareness, self-efficacy, social support, and degree of satisfaction with health education. The outcomes were measured using web-based self-designed and standard questionnaires administered at baseline and at the end point of the study. Intergroup data were assessed using the Mann-Whitney U test, whereas intragroup data were assessed with the Wilcoxon test (for paired samples).

Results

A total of 112 patients (59 in intervention group and 53 in control group) completed the study. After the intervention, a statistically significant increase was noted in the scores of each item of self-care management behaviors compared with the scores at the baseline (P<.001) in the intervention group. The scores of all self-care management behaviors of the control group were lower than those of all self-care management behaviors in the intervention group (all P<.05), except for the item “cover your mouth and nose when coughing or sneezing” (P=.23) and item “wash hands properly” (P=.60), which had no statistically significant difference from those in the intervention group. Compared with those at baseline, TB knowledge awareness, self-efficacy, social support, and degree of satisfaction with health education in the intervention group increased significantly (P<.001), and the intervention group had significantly higher scores than the control group (P<.001).

Conclusions

mHealth intervention for TB self-management based on ITHBC could deepen the understanding of patients with TB about their disease and improve their objective initiative and self-care management behaviors, which were beneficial for promoting compliance behavior and quality of prevention and control for pulmonary TB.

Trial Registration

Chinese Clinical Trial Registry ChiCTR2200055557; https://tinyurl.com/4ray3xnw

Mobile Tuberculosis Treatment Support Tools to Increase Treatment Success in Patients with Tuberculosis in Argentina: Protocol for a Randomized Controlled Trial

BACKGROUND

Tuberculosis (TB) is an urgent global health threat and the world's deadliest infectious disease despite being largely curable. A critical challenge is to ensure that patients adhere to the full course of treatment to prevent the continued spread of the disease and development of drug-resistant disease. Mobile health interventions hold promise to provide the required adherence support to improve TB treatment outcomes.

OBJECTIVE

This study aims to evaluate the effectiveness of the TB treatment support tools (TB-TSTs) intervention on treatment outcomes (success and default) and to assess patient and provider perceptions of the facilitators and barriers to TB-TSTs implementation.

METHODS

The TB-TSTs study is an open-label, randomized controlled trial with 2 parallel groups in which 400 adult patients newly diagnosed with TB will be randomly assigned to receive usual care or usual care plus TB-TSTs. Participants will be recruited on a rolling basis from 4 clinical sites in Argentina. The intervention consists of a smartphone progressive web app, a treatment supporter (eg, TB nurse, physician, or social worker), and a direct adherence test strip engineered for home use. Intervention group participants will report treatment progress and interact with a treatment supporter using the app and metabolite urine test strip. The primary outcome will be treatment success. Secondary outcomes will include treatment default rates, self-reported adherence, technology use, and usability. We will assess patients' and providers' perceptions of barriers to implementation and synthesize lessons learned. We hypothesize that the TB-TSTs intervention will be more effective because it allows patients and TB supporters to monitor and address issues in real time and provide tailored support. We will share the results with stakeholders and policy makers.

RESULTS

Enrollment began in November 2020, with a delayed start due to the COVID-19 pandemic, and complete enrollment is expected by approximately July 2022. Data collection and follow-up are expected to be completed 6 months after the last patient is enrolled. Results from the analyses based on the primary end points are expected to be submitted for publication within a year of data collection completion.

CONCLUSIONS

To our knowledge, this randomized controlled trial will be the first study to evaluate a patient-centered remote treatment support strategy using a mobile tool and a home-based direct drug metabolite test. The results will provide robust scientific evidence on the effectiveness, implementation, and adoption of mobile health tools. The findings have broader implications not only for TB adherence but also more generally for chronic disease management and will improve our understanding of how to support patients facing challenging treatment regimens.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04221789; https://clinicaltrials.gov/ct2/show/NCT04221789.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/28094.

Health Apps for Combating COVID-19: Descriptive Review and Taxonomy

BACKGROUND

Mobile phone apps have been leveraged to combat the spread of COVID-19. However, little is known about these technologies' characteristics, technical features, and various applications in health care when responding to this public health crisis. The lack of understanding has led developers and governments to make poor choices about apps' designs, which resulted in creating less useful apps that are overall less appealing to consumers due to their technical flaws.

OBJECTIVE

This review aims to identify, analyze, and categorize health apps related to COVID-19 that are currently available for consumers in app stores; in particular, it focuses on exploring their key technical features and classifying the purposes that these apps were designed to serve.

METHODS

A review of health apps was conducted using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines. The Apple Store and Google Play were searched between April 20 and September 11, 2020. An app was included if it was dedicated for this disease and was listed under the health and medical categories in these app stores. The descriptions of these apps were extracted from the apps' web pages and thematically analyzed via open coding to identify both their key technical features and overall purpose. The characteristics of the included apps were summarized and presented with descriptive statistics.

RESULTS

Of the 298 health apps that were initially retrieved, 115 met the inclusion criteria. A total of 29 technical features were found in our sample of apps, which were then categorized into five key purposes of apps related to COVID-19. A total of 77 (67%) apps were developed by governments or national authorities and for the purpose of promoting users to track their personal health (9/29, 31%). Other purposes included raising awareness on how to combat COVID-19 (8/29, 27%), managing exposure to COVID-19 (6/29, 20%), monitoring health by health care professionals (5/29, 17%), and conducting research studies (1/29, 3.5%).

CONCLUSIONS

This study provides an overview and taxonomy of the health apps currently available in the market to combat COVID-19 based on their differences in basic technical features and purpose. As most of the apps were provided by governments or national authorities, it indicates the essential role these apps have as tools in public health crisis management. By involving most of the population in self-tracking their personal health and providing them with the technology to self-assess, the role of these apps is deemed to be a key driver for a participatory approach to curtail the spread of COVID-19. Further effort is required from researchers to evaluate these apps' effectiveness and from governmental organizations to increase public awareness of these digital solutions.

Insights from participant engagement with the tuberculosis treatment support tools intervention: Thematic analysis of interactive messages to guide refinement to better meet end user needs

BACKGROUND

Tuberculosis (TB) is a largely curable disease, yet it remains one of the top ten causes of death globally. In response to known challenges to completing the long course of TB treatment, our study team developed the TB treatment support tools (TB-TSTs). The mobile application (app) is comprised of the following main components: 1) tracks treatment progress, 2) provides disease tailored information, 3) interactive communication between patients and treatment supporters, and 4) is linked with a direct adherence drug metabolite test.

OBJECTIVE

The objective of this study was to analyze the interactive communication between the patients and the treatment supporter during the TB-TSTs pilot testing to identify issues and guide intervention refinement.

METHODS

We used mixed methods to analyze the interactive communication data. The study was conducted at a pulmonary disease specialized hospital in Argentina. Of the 42 study participants enrolled in the pilot study, 21 were randomly assigned to use the TB-TSTs for 6-months during their TB treatment. The treatment supporter was a registered nurse from the regional level of the National TB program. We conducted thematic and content analysis of the messages in their original language, Spanish. We assessed the themes over time and by whom initiated the messages.

RESULTS

There were 2561 individual messages sent between the participants and treatment supporter. We identified 19 main themes: 7 were participant and 12 were treatment supporter initiated. Participant themes included missed report rationale, arranging in-person meeting, intervention support, TB treatment progress, disease/treatment questions, side effects and additional support. Treatment supporter themes included missed report inquiry, arranging in-person meeting, introduction and instructions, check-in's, positive reinforcement, treatment progress inquiry, test-strip issues, intervention orientation, initial side-effect check in, follow-up on side effects and photo quality issues. Messages and themes decreased over time with most occurring within the first 2 months of treatment.

CONCLUSIONS

Although there was a decrease in the number of messages and the theme types over the 6-month study participation, treatment adherence support remained needed throughout. Potential solutions are suggested for the main issues and recommendations are being used to guide refinement.

Patients and Medical Staff Attitudes Toward the Future Inclusion of eHealth in Tuberculosis Management: Perspectives From Six Countries Evaluated using a Qualitative Framework

Background

Digitally delivering healthcare services is very attractive for tuberculosis (TB) management as this disease has a complex diagnosis and lengthy management and involves multiple medical and nonmedical specialists. Especially in low- and middle-income countries, eHealth could potentially offer cost-effective solutions to bridge financial, social, time, and distance challenges.

Objective

The goal of the research is to understand what would make eHealth globally applicable and gain insight into different TB situations, opportunities, and challenges.

Methods

We performed focus group interviews with TB experts and patients from 6 different countries on 4 different continents. The focus group interviews followed the theory of planned behavior framework to offer structured recommendations for a versatile eHealth solution. The focus group interviews were preceded by a general demographic and technology use questionnaire. Questionnaire results were analyzed using basic statistics in Excel (Microsoft Corporation). Focus group interview data were analyzed using ATLAS.ti 8 (ATLAS.ti Scientific Software Development GmbH) by assigning codes to quotations and grouping codes into the 5 domains within the framework.

Results

A total of 29 patients and 32 medical staff members were included in our study. All medical staff had used the internet, whereas 31% (9/61) of patients had never been online. The codes with the most quotations were information in relation to eHealth (144 quotations) and communication (67 quotations). The consensus among all participants from all countries is that there are important communication and information gaps that could be bridged by an eHealth app. Participants from different countries also highlighted different challenges, such as a majority of asylum-seeker patients or lack of infrastructure that could be addressed with an eHealth app.

Conclusions

Within the 6 countries interviewed, there is high enthusiasm toward eHealth in TB. A potential app could first target information and communication gaps in TB, with additional modules aimed at setting-specific challenges.

Role of Treatment Adherence, Doctor-Patient Trust, and Communication in Predicting Treatment Effects Among Tuberculosis Patients: Difference Between Urban and Rural Areas

PURPOSE

China is the second highest tuberculosis (TB) burden in the world, and TB patients in the rural areas are about twice as many as urban patients. The purpose of present study was to explore the roles of medication adherence, doctor-patient trust and communication on treatment effects, and its inequality between urban and rural areas.

METHODS

There were 564 eligible TB patients, from four tuberculosis hospitals in China, participating in this cross-sectional study. They filled out questionnaires regarding socio-demographic characteristics, medication adherence, treatment effect, doctor-patient trust, and communication. The structural equation model (SEM) was applied to explore the hypotheses in this study. All statistical analysis was done by SPSS 25.0 and Mplus 7.0 statistical software.

RESULTS

This study included 267 (47.34%) urban and 297 (52.66%) rural eligible TB patients. The data fitted the research model well, and the urban TB patients reported better treatment effect than the rural ones (P=0.027). Overall, treatment adherence positively predicted treatment effect (Est.=0.353, P<0.001); doctor-patient communication positively influenced treatment adherence (Est.=0.214, P=0.002); and treatment adherence positively mediated the role of communication on treatment effect (Est.=0.076), 95% CI (0.026, 0.152). While in the grouping model, the urban patients' treatment effect was only influenced by adherence (Est.=0.286, P=0.003); for the rural patients, treatment adherence (Est.=0.464, P<0.001) and doctor-patient trust (Est.=0.382, P=0.019) directly predicted treatment effects, and treatment adherence positively mediated the role of doctor-patient communication on treatment effect (Est.=0.175, P=0.006).

CONCLUSION

The treatment effect of TB patients, from urban and rural China, was influenced by a different mechanism, among which rural TB patients need not only improve the treatment adherence but also establish good doctor-patient trust and communication to improve treatment effects. These findings provided a theoretical guide on treatment and control for rural TB patients.