Systematic Review of Algorithm-Guided Depression Treatment Trials

A systematic review by Deni Rkman, published in 2026, synthesizes evidence from seven randomized controlled trials encompassing over 3,500 participants. It compares algorithm-guided treatment to treatment as usual for major depressive disorder, reporting outcomes like time to remission and treatment adherence.

Use Cases

• Compare time to remission outcomes between algorithm-guided treatment and treatment as usual groups across the seven included trials.
• Analyze the proportion of patients achieving remission and response as reported in the systematic review's results.
• Assess adherence to treatment protocols, a key finding noted in the review's results section.
• Investigate reported outcome differences in studies involving comorbid populations, as mentioned in the results.

Strengths

• Based on a systematic review of seven randomized controlled trials, a rigorous study design.
• Aggregates data from over 3,500 participants across the included studies.
• Follows PRISMA 2020 guidelines for systematic review methodology.

Limitations

• The dataset is a 32.1 KB DOCX document, not a structured data table, limiting direct computational analysis.
• The underlying data from the seven original trials is not provided, only the review's synthesis.
• The review's search was conducted up to June 2025, potentially missing very recent studies.

Provenance

Source

Deni Rkman via figshare.

Collection Method

Systematic review of randomized controlled trials from PubMed, Scopus, Embase, PsychInfo, and the Cochrane Library.

Time Range

Literature search up to June 2025.

Freshness

Last updated on 2026-03-25.