Participatory health research under COVID-19 restrictions in Bauchi State, Nigeria: Feasibility of cellular teleconferencing for virtual discussions with community groups in a low-resource setting

Introduction During the COVID-19 pandemic, researchers have used Internet-based applications to conduct virtual group meetings, but this is not feasible in low-resource settings. In a community health research project in Bauchi State, Nigeria, COVID-19 restrictions precluded planned face-to-face meetings with community groups. We tested the feasibility of using cellular teleconferencing for these meetings. Methods In an initial exercise, we used cellular teleconferencing to conduct six male and six female community focus group discussions. Informed by this experience, we conducted cellular teleconferences with 10 male and 10 female groups of community leaders, in different communities, to discuss progress with previously formulated action plans. Ahead of each teleconference call, a call coordinator contacted individual participants to seek consent and confirm availability. The coordinator connected the facilitator, the reporter, and the participants on each conference call, and audio-recorded the call. Each call lasted less than 1 h. Field notes and debriefing meetings with field teams supported the assessment of feasibility of the teleconference meetings. Results Cellular teleconferencing was feasible and inexpensive. Using multiple handsets at the base allowed more participants in a call. Guidelines for facilitators and participants developed after the initial meetings were helpful, as were reminder calls ahead of the meeting. Connecting women participants was challenging. Facilitators needed extra practice to support group interactions without eye contact and body language signals. Conclusions With careful preparation and training, cellular teleconferencing can be a feasible and inexpensive method of conducting group discussions in a low-resource setting.

Promise and peril-defining ethical telehealth practice from the clinician and patient perspective: A qualitative study

Objectives We undertook a qualitative study to examine and compare the experience of ethical principles by telehealth practitioners and patients in relation to service delivery theory. The study was conducted prior to and during the recent global increase in the use of telehealth services due to the COVID-19 pandemic, Methods We conducted semi-structured interviews with 20 telehealth practitioners and patients using constructionist grounded theory methods to collect and analyse data. Twenty-five axial coded data categories were then unified and aligned through selective coding with the Beauchamp and Childress (2013) framework of biomedical ethics. The groups were then compared. Results Thirteen categories aligned to the ethical framework were identified for practitioners and 12 for patients. Variance existed between the groups. Practitioner results were non-maleficence 4/13 or (31%), beneficence 4/13 (31%), professional–patient relationships 3/12 (22%), autonomy 1/13 (8%) and justice 1/13 (8%). Patient data results were non-maleficence 4/12 (33%), professional–patient relationships 3/12 (33%), autonomy 2/12 (18%), beneficence 1/12 (8%) and justice 1/12 (8%). Conclusions Ethical principles are experienced differently between telehealth practitioners and patients. These differences can impact the quality and safety of care. Practitioners feel telehealth provides better care overall than patients do. Patients felt telehealth may force a greater share of costs and burdens onto them and reduce equity. Both patients and practitioners felt telehealth can be more harmful than face-to-face service delivery when it creates new or increased risk of harms. Building sufficient trust and mutual understanding are equally important to patients as privacy and confidentiality.

Digitally enabled flash glucose monitoring for inpatients with COVID-19: Feasibility and pilot implementation in a teaching NHS Hospital in the UK

Background COVID-19 placed significant challenges on healthcare systems. People with diabetes are at high risk of severe COVID-19 with poor outcomes. We describe the first reported use of inpatient digital flash glucose monitoring devices in a UK NHS hospital to support management of people with diabetes hospitalized for COVID-19. Methods Inpatients at University Hospitals Coventry & Warwickshire (UHCW) NHS Trust with COVID-19 and diabetes were considered for digitally enabled flash glucose monitoring during their hospitalization. Glucose monitoring data were analysed, and potential associations were explored between relevant parameters, including time in hypoglycaemia, hyperglycaemia, and in range, glycated haemoglobin (HbA1c), average glucose, body mass index (BMI), and length of stay. Results During this pilot, digital flash glucose monitoring devices were offered to 25 inpatients, of whom 20 (type 2/type 1: 19/1; mean age: 70.6 years; mean HbA1c: 68.2 mmol/mol; mean BMI: 28.2 kg/m2) accepted and used these (80% uptake). In total, over 2788 h of flash glucose monitoring were recorded for these inpatients with COVID-19 and diabetes. Length of stay was not associated with any of the studied variables (all p-values >0.05). Percentage of time in hyperglycaemia exhibited significant associations with both percentage of time in hypoglycaemia and percentage of time in range, as well as with HbA1c (all p-values <0.05). The average glucose was significantly associated with percentage of time in hypoglycaemia, percentage of time in range, and HbA1c (all p-values <0.05). Discussion We report the first pilot inpatient use of digital flash glucose monitors in an NHS hospital to support care of inpatients with diabetes and COVID-19. Overall, there are strong arguments for the inpatient use of these devices in the COVID-19 setting, and the findings of this pilot demonstrate feasibility of this digitally enabled approach and support wider use for inpatients with diabetes and COVID-19.

Open health data: Mapping the ecosystem

Background Governments around the world own multiple datasets related to the policy domain of health. Datasets range from vaccination rates to the availability of health care practitioners in a region to the outcomes of certain surgeries. Health is believed to be a promising subject in the case of open government data policies. However, the specific properties of health data such as its sensibilities regarding privacy, ethics, and ownership encompass particular conditions either enabling or preventing datasets to become freely and easily accessible for everyone. Objective and methods This paper aims to map the ecosystem of open health data. By analyzing the foundations of health data and the commonalities of open data ecosystems via literature analysis, the socio-technical environment in which health data managed by governments are opened up or potentially stay closed is created. After its theoretical development, the open health data ecosystem is tested via a case study concerning the Data for Better Health initiative from the government of Belgium. Results Creation and assessment of an open health data ecosystem consisting of stakeholders, interests, information policies, and data preparation activities. Conclusions The policy domain of health includes de-identification activities, bioethical assessments, and the specific role of data providers within its open data ecosystem. However, the concept of open data does not always fully apply to the topic of health. Such several health datasets may be findable via government portals but not directly accessible. Differentiation within types of health data and data user capacities are recommendable for future research.

Barriers to eHealth adoption in routine antenatal care practices: Perspectives of expectant mothers in Uganda – A qualitative study using the unified theory of acceptance and use of technology model

Current empirical evidence suggests that successful adoption of eHealth systems improves maternal health outcomes, yet there are still existing gaps in adopting such systems in Uganda. Service delivery in maternal health is operating in a spectrum of inadequacy, hence eHealth adoption cannot ensue. This study set out to explore the challenges that impede eHealth adoption in women's routine antenatal care practices in Uganda. A qualitative approach using semi-structured interviews was employed to document challenges. These challenges were classified based on a unified theory of acceptance and use of technology constructs. One hundred and fifteen expectant mothers, aged between 18 and 49 years, who spoke either English or Luganda were included in the study that took place between January to May 2019. Thematic analysis using template analysis was adopted to analyse qualitative responses. Challenges were categorised based on five principal unified theories of acceptance and use of technology constructs namely: performance expectancy, effort expectancy, social influence, facilitating conditions and behavioural intention. Facilitating conditions had more influence on technology acceptance and adoption than the other four constructs. Specifically, the lack of training prior to using the system, technical support, computers and smart phones had a downhill effect on adoption. Subsequently, the cost of data services, internet intermittency, and the lack of systems that bridge the gap between mothers and health providers further hindered technology uptake. In conclusion, strategies such as co-development, training end-users, garnering support at the national and hospital levels should be advocated to improve user acceptance of technology.

Use of home pulse oximetry with daily short message service messages for monitoring outpatients with COVID-19: The patient's experience

Studies have shown COVID-19 patients may have a low oxygen saturation (SpO2) independent of visible respiratory distress, a phenomenon termed “silent hypoxia.” Silent hypoxia creates uncertainty in the outpatient setting for clinicians and patients alike. In this study, we examined the potential for pulse oximeters in identifying early signs of clinical deterioration. We report descriptive results on COVID-positive patients’ experiences with a comprehensive home monitoring tool comprised of home SpO2 measurements with a novel symptom-tracking short message service/text messaging application. Of patients who required hospitalization, 83% sought care as a result of low pulse oximeter readings. Nearly all patients who did not require hospitalization reported that having a pulse oximeter provided them with the confidence to stay at home. Essentially all patients found a home pulse oximeter useful. Keeping COVID-19-positive patients at home reduces the potential for disease spread and prevents unnecessary costs and strain on the healthcare system.

Combining ecological momentary assessment, wrist-based eating detection, and dietary assessment to characterize dietary lapse: A multi-method study protocol

Objectives Behavioral obesity treatment (BOT) produces clinically significant weight loss and health benefits for many individuals with overweight/obesity. Yet, many individuals in BOT do not achieve clinically significant weight loss and/or experience weight regain. Lapses (i.e., eating that deviates from the BOT prescribed diet) could explain poor outcomes, but the behavior is understudied because it can be difficult to assess. We propose to study lapses using a multi-method approach, which allows us to identify objectively-measured characteristics of lapse behavior (e.g., eating rate, duration), examine the association between lapse and weight change, and estimate nutrition composition of lapse. Method We are recruiting participants (n = 40) with overweight/obesity to enroll in a 24-week BOT. Participants complete biweekly 7-day ecological momentary assessment (EMA) to self-report on eating behavior, including dietary lapses. Participants continuously wear the wrist-worn ActiGraph Link to characterize eating behavior. Participants complete 24-hour dietary recalls via structured interview at 6-week intervals to measure the composition of all food and beverages consumed. Results While data collection for this trial is still ongoing, we present data from three pilot participants who completed EMA and wore the ActiGraph to illustrate the feasibility, benefits, and challenges of this work. Conclusion This protocol will be the first multi-method study of dietary lapses in BOT. Upon completion, this will be one of the largest published studies of passive eating detection and EMA-reported lapse. The integration of EMA and passive sensing to characterize eating provides contextually rich data that will ultimately inform a nuanced understanding of lapse behavior and enable novel interventions. Trial registration: Registered clinical trial NCT03739151; URL: https://clinicaltrials.gov/ct2/show/NCT03739151

StopWatch: Pilot study for an Apple Watch application for youth with ADHD

Introduction To address the need for non-pharmacologic, scalable approaches for managing attention-deficit and hyperactivity disorder (ADHD) in young people, we report the results of a study of an application developed for a wearable device (Apple Watch) that was designed to track movement and provide visual and haptic feedback for ADHD. Methods Six-week, open label pilot study with structured rating scales ADHD and semi-structured qualitative interview. Apple Watch software application given to users that uses actigraphy and graphic interface as well as haptic feedback to provide feedback to users about level of movement during periods of intentional focus. Linear mixed models to estimate trajectories. Results Thirty-two participants entered the study. This application was associated with improvement in ADHD symptoms over the 6 weeks of the study. We observed an ADHD-Rating Scale change of β = −1.2 units/week (95% CI = −0.56 to −1.88, F = 13.4, P = .0004). Conclusions These positive clinical outcomes highlight the promise of such wearable applications for ADHD and the need to pursue their further development.

Systematic review of cost-effectiveness analysis of behavior change communication apps: Assessment of key methods

Objective Evidence backing the effectiveness of mobile health technology is growing, and behavior change communication applications (apps) are fast becoming a useful platform for behavioral health programs. However, data to support the cost-effectiveness of these interventions are limited. Suggestions for overcoming the low output of economic data include addressing the methodological challenges for conducting cost-effectiveness analysis of behavior change app programs. This study is a systematic review of cost-effectiveness analyses of behavior change communication apps and a documentation of the reported challenges for investigating their cost-effectiveness. Materials and methods Four academic databases: Medline (Ovid), CINAHL, EMBASE and Google Scholar, were searched. Eligibility criteria included original articles that use a cost-effectiveness evaluation method, published between 2008 and 2018, and in the English language. Results Out of the 60 potentially eligible studies, 6 used cost-effectiveness analysis method and met the inclusion criteria. Conclusion The evidence to support the cost-effectiveness of behavior change communication apps is insufficient, with all studies reporting significant study challenges for estimating program costs and outcomes. The main challenges included limited or lack of cost data, inappropriate cost measures, difficulty with identifying and quantifying app effectiveness, representing app effects as Quality-adjusted Life Years, and aggregating cost and effects into a single quantitative measure like Incremental Cost Effectiveness Ratio. These challenges highlight the need for comprehensive economic evaluation methods that balance app data quality issues with practical concerns. This would likely improve the usefulness of cost-effectiveness data for decisions on adoption, implementation, scalability, sustainability, and the benefits of broader healthcare investments.