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Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease

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Personalized Digital Solutions for Mental Health.

Jorge Ropero¹, Kerstin Denecke², Octavio Rivera-Romero^1,3

¹Department of Electronic Technology, Universidad de Sevilla, Seville, Spain.

Studies in Health Technology and Informatics

|October 23, 2023

Summary

Personalized digital mental health solutions show promise, but personalization factors are often unspecified. Guidelines are needed for effective data collection and tailored user experiences in mental healthcare.

Keywords:

Digital health Mental health Personalized health mHealth

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Area of Science:

Digital health
Mental healthcare
Personalization strategies

Background:

Mental health is a global healthcare concern.
Digital solutions offer significant support for mental health disorders.
Personalization enhances the effectiveness of digital mental health interventions.

Purpose of the Study:

To identify personalization factors in digital mental health solutions.
To understand data collection methods for personalization.
To review existing personalized digital mental health tools.

Main Methods:

Building upon a prior mHealth review.
Expanding analysis to the specific domain of mental health.
Analyzing ten digital mental health solutions.

Main Results:

Analyzed solutions target diverse mental health conditions.
Personalization factors are frequently not explicitly stated in research.
Commonly used personalization factors include age, gender, user preferences, and behavior.

Conclusions:

A wide range of mental health conditions are addressed by digital solutions.
Methods for data collection include in-app questionnaires, self-reports, and usage data.
Development of guidelines for personalized digital mental health solutions is recommended.