Digital Health Technology Interventions for Multiple Sclerosis

A review dataset on non-pharmacological digital health technology interventions for people with Multiple Sclerosis. It was authored by Silvia Poli and last updated on January 21, 2026. The dataset emphasizes current use, intervention characteristics, sample details, and research gaps.

Use Cases

• Analyze intervention characteristics to identify common features of digital health technologies used for physical rehabilitation in MS.
• Review sample details across studies to assess demographic representation and recruitment strategies for pwMS.
• Map current use and research gaps to prioritize future clinical trials in cognitive rehabilitation for Multiple Sclerosis.
• Categorize studies by tags like Medicine Health And Life Sciences or Clinical Psychology to explore interdisciplinary research trends.

Strengths

• Data is current, with a last update timestamp of January 21, 2026.
• The dataset is sourced from the authoritative Harvard Dataverse repository.
• Covers multiple relevant domains as indicated by tags including Physical rehabilitation, Cognitive rehabilitation, and Clinical Psychology.

Limitations

• The dataset's size, row count, and column structure are unknown, limiting assessment of analytical scope.
• Sample data and file formats are unavailable, preventing evaluation of data structure and quality.
• The specific temporal coverage and geographic scope of the reviewed studies are not provided.

Provenance

Source

Harvard Dataverse

Collection Method

Compiled for a review of non-pharmacological digital health technology interventions.

Freshness

Last updated on 2026-01-21.