Question · asked by 0 reviews
Music‐based therapeutic interventions vs usual care: Anxiety
- Population
- cancer patients
- Intervention
- Music‐based therapeutic interventions
- Comparison
- usual care
- Outcome
- Anxiety
What each review found
Current versions onlyNo studies found 0 · 0%GRADE not reported 0 · 0%Very low 1 · 33.3%Low 2 · 66.7%Moderate 0 · 0%High 0 · 0%
| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Music interventions vs standard care Anxiety · cancer patients Music interventions for improving psychological and physical outcomes in people with cancer (2016) · Cochrane Headline outcomes onlyearlier version CD006911.PUB3, superseded | no estimate extracted | 13 studies · 1028 participants | Low |
Music interventions vs standard care Anxiety (STAI) Scale from: 20 to 80. · cancer patients Music interventions for improving psychological and physical outcomes in people with cancer (2011) · Cochrane Headline outcomes onlyearlier version CD006911.PUB2, superseded | no estimate extracted | 7 studies · 430 participants | Low |
Music interventions vs standard care Anxiety (non‐STAI (full version) measures) · cancer patients Music interventions for improving psychological and physical outcomes in people with cancer (2011) · Cochrane Headline outcomes onlyearlier version CD006911.PUB2, superseded | no estimate extracted | 6 studies · 469 participants | Very low |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Music interventions for improving psychological and physical outcomes in people with cancer 2021 · Cochrane Headline outcomes only | Not reported | Not extracted | Not assessed |
Related questions
The same intervention and outcome, asked in another population or against another comparator.
- Music‐based therapeutic interventions vs usual care · patients with preoperative anxiety · 1 review
How reviews are matched to this question
Reviews word the same question differently. Four decision models (TypeSafe's Jev, Liquid AI's d1-ultra, SubQ Snap and Baseten's Elephant) judged each wording of the population, intervention, comparator and outcome against the others; two wordings count as the same when at least three of them agree and none clearly disagrees, and findings count as this question only when all four elements match. Timing, setting and subgroup never split a question: they are shown on each finding.