Toward clinical digital phenotyping: a timely opportunity to consider purpose, quality, and safety

Abstract

The use of data generated passively by personal electronic devices, such as smartphones, to measure human function in health and disease has generated significant research interest. Particularly in psychiatry, objective, continuous quantitation using patients’ own devices may result in clinically useful markers that can be used to refine diagnostic processes, tailor treatment choices, improve condition monitoring for actionable outcomes, such as early signs of relapse, and develop new intervention models. If a principal goal for digital phenotyping is clinical improvement, research needs to attend now to factors that will help or hinder future clinical adoption. We identify four opportunities for research directed toward this goal: exploring intermediate outcomes and underlying disease mechanisms; focusing on purposes that are likely to be used in clinical practice; anticipating quality and safety barriers to adoption; and exploring the potential for digital personalized medicine arising from the integration of digital phenotyping and digital interventions. Clinical relevance also means explicitly addressing consumer needs, preferences, and acceptability as the ultimate users of digital phenotyping interventions. There is a risk that, without such considerations, the potential benefits of digital phenotyping are delayed or not realized because approaches that are feasible for application in healthcare, and the evidence required to support clinical commissioning, are not developed. Practical steps to accelerate this research agenda include the further development of digital phenotyping technology platforms focusing on scalability and equity, establishing shared data repositories and common data standards, and fostering multidisciplinary collaborations between clinical stakeholders (including patients), computer scientists, and researchers.

Harnessing consumer smartphone and wearable sensors for clinical cancer research

“…Third, ethical challenges must be confronted in using mobile sensor data 62 , 63 . These include ensuring that patients understand the risks and benefits of collecting and sharing these data and that risks related to privacy and data security are minimized.…”

“…Interventions such as those to support pain management, address cognitive impairment, or reduce stress can be delivered via smartphone apps, and collecting concurrent sensor data can enable researchers to evaluate app use patterns and behavioral changes in response to intervention content 45 , 60 . Furthermore, sensor data can be used to tailor intervention content, dose, or timing, setting attainable individualized goals and delivering prompts at the right time, when participants are receptive to intervention messages or in need of support 63 . Finally, sensor data themselves can be leveraged to develop n-of-1 interventions, helping individual patients identify patterns and recognize how their activity, sleep, or other behaviors affect their health.…”

Digital phenotyping for assessment and prediction of mental health outcomes: a scoping review protocol

“…Current reviews do not develop or apply existing frameworks of digital phenotyping (ie, frameworks of relationships between behaviours, digital traces/sensors and health conditions, eg, suggested by Mohr et al 12 or Garcia-Ceja et al 13) to highlight gaps, identify potential digital markers and generate new hypotheses. Huckvale, K. et al, 14 provide a general overview and mapping of digital phenotyping to clinical application, that is, prevention, screening, monitoring and treatment but do not attempt to map associations between digital markers and mental health outcomes. Fraccaro, P. et al 15 map the associations between digital markers and mental health outcomes; however, this review was limited to geolocation data and specific serious mental illness (ie, bipolar disorder and schizophrenia).…”

Digital Phenotyping in Bipolar Disorder: Which Integration with Clinical Endophenotypes and Biomarkers?

“…In the last two decades, the rapid expansion of digital technology, particularly the ubiquity of smartphones reaching up to 77% of US population out of around 95% of US population who reported owning a mobile phone, could make them a potential real-time digital platform for the diagnosis, monitoring, and relapse detention of psychiatric diseases, including BD [ 2 , 8 , 45 , 46 ]. In fact, there is a plethora of data that is generated and recorded during the interaction between an individual and his/her smartphone or personal device, some data that might occur with minimal participation (active) whilst other data with little or no burden for them (passive) [ 8 , 47 ].…”

“…In this context, digital phenotyping could significantly improve the early identification and intervention in potentially life-threatening conditions, including fluctuations in suicidal ideation and thoughts of death [ 50 ], the dimension of the affective instability comprising emotional intensity, emotional lability, and ability to control shifts in mood [ 8 , 49 ]. Moreover, it may be a valid tool for clinical characterization, course of illness (i.e., detection of subgroups of BD patients), prediction of critical outcomes in illness course (i.e., relapse, recurrence, resilience), to early detecting, monitoring and predicting treatment response, non-response, remission, and treatment tolerance (i.e., identification of predictors of side effects) as well as a prediction tool for the identification of high-risk BD subjects [ 8 , 19 , 21 , 45 ]. At this regard, it may help clinicians as well in refining the clinical response phenotype and could translate into the personalization of lithium treatment [ 38 ].…”