[HTML][HTML] From smartphone data to clinically relevant predictions: A systematic review of digital phenotyping methods in depression

IE Leaning, N Ikani, HS Savage, A Leow… - Neuroscience & …, 2024 - Elsevier
Background Smartphone-based digital phenotyping enables potentially clinically relevant
information to be collected as individuals go about their day. This could improve monitoring …

Use of voice-based conversational artificial intelligence for basal insulin prescription management among patients with type 2 diabetes: a randomized clinical trial

A Nayak, S Vakili, K Nayak, M Nikolov… - JAMA Network …, 2023 - jamanetwork.com
Importance Optimizing insulin therapy for patients with type 2 diabetes can be challenging
given the need for frequent dose adjustments. Most patients receive suboptimal doses and …

[HTML][HTML] Big data in oncology nursing research: state of the science

CS Harris, RA Pozzar, Y Conley, M Eicher… - Seminars in Oncology …, 2023 - Elsevier
Objective To review the state of oncology nursing science as it pertains to big data. The
authors aim to define and characterize big data, describe key considerations for accessing …

[HTML][HTML] Evaluating a remote monitoring program for respiratory diseases: prospective observational study

MA Althobiani, Y Ranjan, J Jacob, M Orini… - JMIR Formative …, 2023 - formative.jmir.org
Background Patients with chronic respiratory diseases and those in the postdischarge
period following hospitalization because of COVID-19 are particularly vulnerable, and little is …

[HTML][HTML] Challenges in using mHealth data from smartphones and wearable devices to predict depression symptom severity: retrospective analysis

S Sun, AA Folarin, Y Zhang, N Cummins… - Journal of medical …, 2023 - jmir.org
Background Major depressive disorder (MDD) affects millions of people worldwide, but
timely treatment is not often received owing in part to inaccurate subjective recall and …

[HTML][HTML] A global research priority agenda to advance public health responses to fatty liver disease

JV Lazarus, HE Mark, AM Allen, JP Arab, P Carrieri… - Journal of …, 2023 - Elsevier
Background & aims An estimated 38% of adults worldwide have non-alcoholic fatty liver
disease (NAFLD). From individual impacts to widespread public health and economic …

[HTML][HTML] Longitudinal Assessment of Seasonal Impacts and Depression Associations on Circadian Rhythm Using Multimodal Wearable Sensing: Retrospective …

Y Zhang, AA Folarin, S Sun, N Cummins… - Journal of Medical …, 2024 - jmir.org
Background Previous mobile health (mHealth) studies have revealed significant links
between depression and circadian rhythm features measured via wearables. However, the …

[HTML][HTML] Value of Engagement in Digital Health Technology Research: Evidence Across 6 Unique Cohort Studies

SM Goodday, E Karlin, A Brooks, C Chapman… - Journal of Medical …, 2024 - jmir.org
Background Wearable digital health technologies and mobile apps (personal digital health
technologies [DHTs]) hold great promise for transforming health research and care …

[HTML][HTML] Feasibility Study on Menstrual Cycles With Fitbit Device (FEMFIT): Prospective Observational Cohort Study

AL Lang, RL Bruhn, M Fehling… - JMIR mHealth and …, 2024 - mhealth.jmir.org
Background: Despite its importance to women's reproductive health and its impact on
women's daily lives, the menstrual cycle, its regulation, and its impact on health remain …

[HTML][HTML] Patient Experience of Digitalized Follow-up of Antidepressant Treatment in Psychiatric Outpatient Care: Qualitative Analysis

M Hamlin, J Holmén, E Wentz, H Aiff, L Ali… - JMIR Mental …, 2023 - mental.jmir.org
Background Nonadherence to pharmaceutical antidepressant treatment is common among
patients with depression. Digitalized follow-up (ie, self-monitoring systems through mobile …