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https://hdl.handle.net/20.500.14123/1742
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| Field | Value |
|---|---|
| Original Title | Supplementary Material for the Paper "Opening the black box - Effects of decision transparency on therapists' trust in and intended use of AI-based decision support systems in ICBTs" |
| Handle | 20.500.14123/1742 |
| Kinds of Data | Test Data (i.e. Educational, Psychical or Psychological Measurements) Context Materials / Supporting information |
| Resource Type | Dataset |
| Creator | Zantvoort, Kirsten  0000-0001-9876-054X (Institut für Wirtschaftsinformatik (IIS), Leuphana Universität Lüneburg  02w2y2t16)Bjurner, Pontus 0000-0002-4967-9128 (Karolinska Institutet 056d84691)Forsell, Erik 0000-0001-8236-4323 (Karolinska Institutet 056d84691)Wallert, John 0000-0002-1473-4916 (Karolinska Institutet 056d84691)Funk, Burkhardt 0000-0001-5855-2666 (Institut für Wirtschaftsinformatik (IIS), Leuphana Universität Lüneburg 02w2y2t16)Kaldo, Viktor 0000-0002-6443-5279 (Karolinska Institutet 056d84691) |
| Description of the Dataset | This study investigated the impact of local SHAP (SHapley Additive exPlanation) values on therapists’ perceptions of a Machine Learning-based Decision Support Tools (DST) in Internet-based Cognitive Behavioural Therapy (ICBT). The randomised experiment included 35 Swedish ICBT therapists who were each presented with a DST with six exemplary patient cases with SHAP values and six without them. The study measured therapists' understanding, trust, and perception of clinical usefulness through self-ratings at multiple stages. The primary hypothesis that adding SHAP values increased self-reported trust was confirmed by the findings (p=0.01, d=0.43 [0.07-0.76]). Further, the results suggested increased understanding, agreeance with, and the perceived usefulness of the DST predictions through SHAP values. |
| Methods | Experiment (Web-based) Description Programming / Script-based data collection |
| Keywords | Maschinelles Lernen; Data Science; Therapeutik; Kognitives Verhalten; Verhaltenstherapie; Entscheidungsfindung; Internetbasiert; Digitale Gesundheit; Mentale Gesundheit; Intervention; Machine Learning; Data Science; Therapeutics; Cognitive Behavior; Behavioral Therapy; Decision Making; Internet-based; Digital Health; Mental Health; Intervention |
| Thematic Classification | Digital Health |
| Language of the Resource | English |
| Date of Availability | 2025-01-23T06:16:38Z |
| Date of issue | 2025-01-23 |
| Archiving Facility | Medien- und Informationszentrum (Leuphana Universität Lüneburg 02w2y2t16) |
| Published by | Medien- und Informationszentrum, Leuphana Universität Lüneburg |
Related Resources
Superordinate Data Collection: Supplementary Material PhD Kirsten Zantvoort
| Field | Value |
|---|---|
| Participating Researchers | Zantvoort, Kirsten 0000-0001-9876-054X (Institut für Wirtschaftsinformatik (IIS), Leuphana Universität Lüneburg 02w2y2t16) |
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