A 2022 Survey of Commercially Available Smartphone Apps for Sleep
Bibliographic record
Abstract
•Most sleep apps available to consumers are designed to enhance sleep by reducing sleep latency with auditory stimuli.•While most sleep apps do not have peer-reviewed evidence supporting the specific app, most do use types of enhancement that are backed by scientific evidence.•Sleep apps are widely available, low to no cost, and mostly focus on helping the consumer fall sleep faster using sounds.•Sleep apps could be considered a possible strategy for patients and consumers to improve their sleep, although more validation of these apps is recommended. •Most sleep apps available to consumers are designed to enhance sleep by reducing sleep latency with auditory stimuli.•While most sleep apps do not have peer-reviewed evidence supporting the specific app, most do use types of enhancement that are backed by scientific evidence.•Sleep apps are widely available, low to no cost, and mostly focus on helping the consumer fall sleep faster using sounds.•Sleep apps could be considered a possible strategy for patients and consumers to improve their sleep, although more validation of these apps is recommended.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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; both teacher heads agree on what is shown here.
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".