Question · asked by 1 review
Hypnosis vs relaxation: Adverse events
- Population
- People aged 12 years and over with painful TMD lasting 3 months or longer
- Intervention
- Hypnosis
- Comparison
- relaxation
- Outcome
- Adverse events
What each review found
Include earlier review versions| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Hypnosis vs Relaxation Adverse events · People aged 12 years and over with painful TMD lasting 3 months or longer Psychological therapies for temporomandibular disorders (TMDs) (2022) · Cochrane All outcomes | Abrahamsen 2011: one participant who received hypnosis was admitted to a psychiatric hospital during the intervention; per study authors this was unrelated to the study treatment. | 1 study | GRADE not reported |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Psychological therapies for temporomandibular disorders (TMDs) 2022 · Cochrane All outcomes | 2021-10 | Not listed | Not assessed |
Related questions
The same intervention and outcome, asked in another population or against another comparator.
- Hypnosis vs WAIT LIST · people with conversion disorder according to DSM‐IV or ICD‐10 criteria · 1 review
- Hypnosis vs diazepam · people with conversion disorder according to DSM‐IV or ICD‐10 criteria · 1 review
- Hypnosis vs No hypnosis (no hypnotic intervention) · Children undergoing dental and orthodontic treatment (Gokli 1994; Trakyali 2008) · 1 review
- Hypnosis vs Inhalation sedation with nitrous oxide and oxygen · Children aged 10 to 16 years undergoing orthodontic extractions (Braithwaite 2005) · 1 review
- Hypnosis vs No hypnosis (no hypnotic intervention) · Children and adolescents (0 to 16 years) needing dental treatment · 0 reviews
- Hypnosis vs Sedation (sedative agent alone) · Children and adolescents (0 to 16 years) needing dental treatment · 0 reviews
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.