Identifying Unmet Needs in Major Depressive Disorder Using a Computer-Assisted Alternative to Conventional Thematic Analysis: Qualitative Interview Study With Psychiatrists.

BACKGROUND: The development of digital health tools that are clinically relevant requires a deep understanding of the unmet needs of stakeholders, such as clinicians and patients. One way to reveal unforeseen stakeholder needs is through qualitative research, including stakeholder interviews. However, conventional qualitative data analytical approaches are time-consuming and resource-intensive, rendering them untenable in many industry settings where digital tools are conceived of and developed. Thus, a more time-efficient process for identifying clinically relevant target needs for digital tool development is needed. OBJECTIVE: The objective of this study was to address the need for an accessible, simple, and time-efficient alternative to conventional thematic analysis of qualitative research data through text analysis of semistructured interview transcripts. In addition, we sought to identify important themes across expert psychiatrist advisor interview transcripts to efficiently reveal areas for the development of digital tools that target unmet clinical needs. METHODS: We conducted 10 (1-hour-long) semistructured interviews with US-based psychiatrists treating major depressive disorder. The interviews were conducted using an interview guide that comprised open-ended questions predesigned to (1) understand the clinicians' experience of the care management process and (2) understand the clinicians' perceptions of the patients' experience of the care management process. We then implemented a hybrid analytical approach that combines computer-assisted text analyses with deductive analyses as an alternative to conventional qualitative thematic analysis to identify word combination frequencies, content categories, and broad themes characterizing unmet needs in the care management process. RESULTS: Using this hybrid computer-assisted analytical approach, we were able to identify several key areas that are of interest to clinicians in the context of major depressive disorder and would be appropriate targets for digital tool development. CONCLUSIONS: A hybrid approach to qualitative research combining computer-assisted techniques with deductive techniques provides a time-efficient approach to identifying unmet needs, targets, and relevant themes to inform digital tool development. This can increase the likelihood that useful and practical tools are built and implemented to ultimately improve health outcomes for patients.

Opportunities for digital health technology: identifying unmet needs for bipolar misdiagnosis and depression care management.

Introduction: Digital health technologies (DHTs) driven by artificial intelligence applications, particularly those including predictive models derived with machine learning methods, have garnered substantial attention and financial investment in recent years. Yet, there is little evidence of widespread adoption and scant proof of gains in patient health outcomes. One factor of this paradox is the disconnect between DHT developers and digital health ecosystem stakeholders, which can result in developing technologies that are highly sophisticated but clinically irrelevant. Here, we aimed to uncover challenges faced by psychiatrists treating patients with major depressive disorder (MDD). Specifically, we focused on challenges psychiatrists raised about bipolar disorder (BD) misdiagnosis. Methods: We conducted semi-structured interviews with 10 United States-based psychiatrists. We applied text and thematic analysis to the resulting interview transcripts. Results: Three main themes emerged: (1) BD is often misdiagnosed, (2) information crucial to evaluating BD is often occluded from clinical observation, and (3) BD misdiagnosis has important treatment implications. Discussion: Using upstream stakeholder engagement methods, we were able to identify a narrow, unforeseen, and clinically relevant problem. We propose an organizing framework for development of digital tools based upon clinician-identified unmet need.

Randomized Controlled Trial of Automated Directly Observed Therapy for Measurement and Support of PrEP Adherence Among Young Men Who have Sex with Men.

Measurement of adherence to oral pre-exposure prophylaxis (PrEP) in real-time has been challenging. We developed DOT Diary, a smartphone application that combines automated directly observed therapy with a PrEP adherence visualization toolkit, and tested its ability to measure PrEP adherence and to increase adherence among a diverse cohort of young men who have sex with men (MSM). We enrolled 100 MSM in San Francisco and Atlanta and randomly assigned them 2:1 to DOT Diary versus standard of care. Concordance between DOT Diary measurement and drug levels in dried blood spots was substantial, with 91.0% and 85.3% concordance between DOT Diary and emtricitabine-triphosphate and tenofovir-diphosphate, respectively. There was no significant difference in the proportion of participants with detectable PrEP drug levels at 24 weeks between study arms. These results suggest DOT Diary is substantially better than self-reported measures of adherence, but additional interventions are needed to improve PrEP adherence over time.

RESUMEN: La medición de la adherencia a la profilaxis oral previa a la exposición (PrEP) en tiempo real ha constituido un desafío. Hemos desarrollado DOT Diary, una aplicación para teléfonos inteligentes que combina la terapia automatizada observada de forma directa con un kit de herramientas para visualizar la adherencia a la PrEP, y testeamos su capacidad para medir la adherencia a la PrEP, así como para aumentar la adherencia entre una cohorte variada de hombres jóvenes que tienen sexo con hombres (HSH). Reclutamos a 100 HSH en San Francisco y Atlanta y los asignamos aleatoriamente 2:1 a DOT Diary con respecto a la asistencia estándar. La concordancia entre la medición del DOT Diary y los niveles de fármacos en gotas de sangre seca fue sustancial, con un 91,0% y un 85,3% de concordancia entre el uso del DOT Diary y el de emtricitabina-trifosfato y tenofovir-difosfato, respectivamente. No hubo diferencias significativas en la proporción de participantes con niveles detectables del fármaco de la PrEP a las 24 semanas entre los brazos del estudio. Estos resultados sugieren que DOT Diary es sustancialmente superior a las medidas de adherencia que se notifican de forma personal, aunque hacen falta intervenciones adicionales para mejorar la adherencia a la PrEP a largo plazo.

Technology for Measuring and Monitoring Treatment Compliance Remotely.

Medication non-adherence during clinical trials is an ongoing challenge that can result in insufficient safety and efficacy data. For patients with Parkinson's disease and other neurological disorders, symptomatology such as forgetfulness compounds traditional obstacles to adherence. Today, sponsors and clinical study sites can call upon various technology tools that improve adherence by monitoring and confirming dosage in near real-time. These tools have the potential to improve the quality of data gleaned from these studies.