Dataset Handle: 20.500.14123/1743

Supplementary Material for the Paper "The Promise and Challenges of Computer Mouse Trajectories in DMHIs - A Feasibility Study on Pre-Treatment Dropout Predictions"

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Chronological data

Date of availability in catalog2025-01-23
Available from / since 2025-01-23

Language of the resource

English

Related external resources

Supplement to Zantvoort, K., Matthiesen, J. J., Bjurner, P., Bendix, M., Funk, B., & Kaldo, V. (Preprint). The Promise and Challenges of Computer Mouse Trajectories in DMHIs - A Feasibility Study on Pre-Treatment Dropout Predictions.

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Abstract

Empirical evidence suggests that how one moves their mouse holds information on motivation and attention, both valuable aspects otherwise difficult to measure at scale. Further, mouse trajectories can already be collected on pre-treatment questionnaires, making them a promising candidate for early predictions informing treatment allocation. Therefore, this study investigates how to gather and process mouse trajectory data on questionnaires in Digital Mental Health Interventions (DMHI). As a feasibility study, the researchers collected mouse trajectory data from 183 patients filling out a pre-intervention depression questionnaire.

Resource type

Dataset

Kinds of Data

Programs and Applications
Context Materials / Supporting information

Methods

Description
Programming / Script-based data collection

Thematic classification

Nutzerverhalten

Keywords

Data Science; Computermaus; Nutzerverhalten; Prognose; Digitale Gesundheit; Mentale Gesundheit; Intervention; Motivation; Aufmerksamkeit; Algorithmus; Data Science; Computer Mouse; User Behavior; Prediction; Digital Health; Mental Health; Intervention; Motivation; Attention; Algorithm