Systematic Review and Network Meta-analysis of Cognitive and/or Behavioral Therapies (CBT) for Tinnitus
Bibliographic record
Abstract
OBJECTIVE: To evaluate the efficacy of cognitive and/or behavioral therapies in improving health-related quality of life (HRQOL), depression, and anxiety associated with tinnitus. DATA SOURCES: EMBASE, MEDLINE, PubMed, PsycINFO, and the Cochrane Registry were used to identify English studies from database inception until February 2018. STUDY SELECTION: Randomized controlled trials (RCTs) comparing cognitive and/or behavioral therapies to one another or to waitlist controls for the treatment of tinnitus were included. DATA EXTRACTION: Quality and risk were assessed using GRADE and Cochrane's Risk of Bias tool respectively. DATA SYNTHESIS: Pairwise meta-analysis (12 RCTs: 1,144 patients) compared psychological interventions to waitlist controls. Outcomes were measured using standardized mean differences (SMDs) and 95% confidence intervals (CI). I and subgroup analyses were used to assess heterogeneity. Network meta-analysis (NMA) (19 RCTS: 1,543 patients) compared psychological therapies head-to-head. Treatment effects were presented by network diagrams, interval plots, and ranking diagrams indicating SMDs with 95% CI. Direct and indirect results were further assessed by inconsistency plots. CONCLUSIONS: Results are consistent with previously published guidelines indicating that CBT is an effective therapy for tinnitus. While guided self-administered forms of CBT had larger effect sizes (SMD: 3.44; 95% CI: -0.022, 7.09; I: 99%) on tinnitus HRQOL, only face-to-face CBT was shown to make statistically significant improvements (SMD: 0.75; 95% CI: 0.53, 0.97; I: 0%). Guided self-administered CBT had the highest likelihood of being ranked first in improving tinnitus HRQOL (75%), depression (83%), and anxiety (87%), though statistically insignificant. This NMA is the first of its kind in this therapeutic area and provides new insights on the effects of different forms of cognitive and/or behavioral therapies for tinnitus.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.029 | 0.078 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.040 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".