Global Public Interests and Dynamic Trends in Osteoporosis From 2004 to 2019: Infodemiology Study
Bibliographic record
Abstract
BACKGROUND: With the prolonging of human life expectancy and subsequent population aging, osteoporosis (OP) has become an important public health issue. OBJECTIVE: This study aimed to understand the global public search interests and dynamic trends in "osteoporosis" using the data derived from Google Trends. METHODS: An online search was performed using the term "osteoporosis" in Google Trends from January 1, 2004, to December 31, 2019, under the category "Health." Cosinor analysis was used to test the seasonality of relative search volume (RSV) for "osteoporosis." An analysis was conducted to investigate the public search topic rising in RSV for "osteoporosis." RESULTS: There was a descending trend of global RSV for "osteoporosis" from January 2004 to December 2014, and a slowly increasing trend from January 2015 to December 2019. Cosinor analysis showed significant seasonal variations in global RSV for "osteoporosis" (P=.01), with a peak in March and a trough in September. In addition, similar decreasing trends of RSV for "osteoporosis" were found in Australia, New Zealand, Ireland, and Canada from January 2004 to December 2019. Cosinor test revealed significant seasonal variations in RSV for "osteoporosis" in Australia, New Zealand, Canada, Ireland, UK, and USA (all P<.001). Furthermore, public search rising topics related to "osteoporosis" included denosumab, fracture risk assessment tool, bone density, osteopenia, osteoarthritis, and risk factor. CONCLUSIONS: Our study provided evidence about the public search interest and dynamic trends in OP using web-based data, which would be helpful for public health and policy making.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".