User Outcomes for an App-Delivered Hypnosis Intervention for Menopausal Hot Flashes: Retrospective Analysis
Bibliographic record
Abstract
Background Hypnotherapy has been shown to be a safe, nonhormonal intervention effective for treating menopausal hot flashes. However, women experiencing hot flashes may face accessibility barriers to in-person hypnotherapy. To solve this issue, a smartphone app has been created to deliver hypnotherapy. The Evia app delivers audio-recorded hypnotherapy and has the potential to help individuals experiencing hot flashes. Objective This study aims to determine user outcomes in hot flash frequency and severity for users of the Evia app. Methods This study is a retrospective analysis of a dataset of Evia app users. Participants were divided into 2 groups for analysis. The first group reported daytime hot flashes and night sweats, while the second group was asked to report only daytime hot flashes. The participants in the first group (daytime hot flashes and night sweats) were 139 women with ≥3 daily hot flashes who downloaded the Evia app between November 6, 2021, and June 9, 2022, with a baseline mean of 8.330 (SD 3.977) daily hot flashes. The participants in the second group (daytime hot flashes) were 271 women with ≥3 daily hot flashes who downloaded the Evia app between June 10, 2022, and February 5, 2024, with a baseline mean of 6.040 (SD 3.282) daily hot flashes. The Evia program included a 5-week program for all participants with daily tasks such as educational readings, hypnotic inductions, and daily hot-flash tracking. The app uses audio-recorded hypnosis and mental imagery for coolness, such as imagery for a cool breeze, snow, or calmness. Results A clinically significant reduction, defined as a 50% reduction, in daily hot flashes was experienced by 76.3% (106/139) of the women with hot flashes and night sweats and 56.8% (154/271) of the women with daily hot flashes from baseline to their last logged Evia app survey. On average, the women with hot flashes and night sweats experienced a reduction of 61.4% (SD 33.185%) in their hot flashes experienced at day and night while using the Evia app, and the women with daily hot flashes experienced a reduction of 45.2% (SD 42.567%) in their daytime hot flashes. In both groups, there was a large, statistically significant difference in the average number of daily hot flashes from baseline to end point (women with hot flashes and night sweats: Cohen d=1.28; t138=15.055; P<.001; women with daily hot flashes: Cohen d=0.82; t270=13.555; P<.001). Conclusions Hypnotherapy is an efficacious intervention for hot flashes, with the potential to improve women’s lives by reducing hot flashes without hormonal or pharmacological intervention. This study takes the first step in evaluating the efficacy of an app-delivered hypnosis intervention for menopausal hot flashes, demonstrating the Evia app provides a promising app delivery of hypnotherapy with potential to increase accessibility to hypnotherapy.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".