0376 Trajectories of Natural Product and Over-the-Counter Sleep Aid Users: A Five Year Follow-Up
Bibliographic record
Abstract
Natural products (NP) and over-the-counter (OTC) sleep aids are widely used despite limited evidence on their risks and benefits. Given the heterogeneity of help-seeking behaviors, variable patterns of NP and OTC use are expected. However, self-medicating patterns of NP and OTC use have not been studied over an extended time period. Therefore, the aim of this study was to investigate trajectories and predictors of sleep-related self-medicating patterns in a Canadian population-based sample. Data were derived from a longitudinal study on the natural history of insomnia. Participants were 3416 adults (mean age = 49.7 (±14.7); 62% women, 56% good sleepers, 44% insomnia symptoms/syndrome). Self-reported usage frequency data (i.e. nights/week of use) were extracted from a sub-population of NP (n=794) and OTC (n=606) users across seven time-points over five years. Latent class growth modeling for count data (SAS PROJ TRAJ) was used to identify distinct temporal trajectories of NP and OTC use. Preliminary associations between class membership and baseline participant characteristics were assessed using a one-way ANOVA or the χ2 test. Sampling weights were applied to all analyses to ensure population representativeness and to adjust for partial non-response. NP usage frequencies were classified into five latent-class trajectories: minimal user (30%), moderate user (37%), intermittent-decreasing user (9%), intermittent-increasing user (14%) and high user (10%). For OTC use, four latent-class trajectories were identified: intermittent user (17%), minimal user (53%), rebound user (20%) and high user (10%). Across NP and OTC sleep aids, high users were older, more likely to use prescription sleep medications, had poorer sleep quality, greater insomnia severity and depressive symptoms and were less likely to be a good sleeper compared to minimal users. However, only NP high users were more likely to consult health professionals about their sleep. Temporal trajectories of NP and OTC usage frequencies highlight heterogeneous patterns of chronic self-medicating practices, particularly among NP users. Such patterns could potentially inform the transition to prescribed sleep medication use. Research is supported by the Canadian Institutes of Health Research (MOP#115103).
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".