Dataset Handle: 20.500.14123/1741

Supplementary Material for the Paper "Finding the Best Match - A Case Study on the (Text-)Feature and Model Choice in Digital Mental Health Interventions"

Archiving without access
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Chronological data

Date of availability in catalog2025-01-22
Available from / since 2025-01-22

Language of the resource

English

Related external resources

Supplement to DOI: 10.1007/s41666-023-00148-z
Zantvoort, K., Scharfenberger, J., Boß, L., Lehr, D., & Funk, B. (2023). Finding the Best Match — a Case Study on the (Text‑) Feature and Model Choice in Digital Mental Health Interventions. Journal of Healthcare Informatics Research, 7(4), 447-479. Artikel 00148.

Related PubData resources

Supplement to

Resource
Dissertation
Machine Learning Dropout Predictions for Personalizing Digital Mental Health Interventions
Zantvoort, Kirsten
2025 | DOI: 10.48548/pubdata-1596

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Author

Other contributors

Abstract

This document serves as supplement for the paper "Finding the Best Match – A Case Study on the (Text-)Feature and Model Choice in Digital Mental Health Interventions". The researchers analyzed nearly 16.000 open-text answers from 849 German-speaking users in a Digital Mental Health Intervention (DMHI) for stress. The archived document represents a short overview of the data.

Resource type

Dataset

Kinds of Data

Context Materials / Supporting information

Methods

Summary
Description
Aggregation

Thematic classification

Digital Health

Keywords

Maschinelles Lernen; Natural Language Processing; Digitale Gesundheit; Mentale Gesundheit; Intervention; Gesundheitsdaten; Stress; Machine Learning; Natural Language Processing; Digital Health; Mental Health; Intervention; Health Data; Stress

Notes

The supplementary material is available for download. Please visit the article linked below to gain access. You will find the document in the chapter "Supplementary information".