Breast Cancer Screening Participation and Internet Search Activity in a Japanese Population: Decade-Long Time-Series Study
Bibliographic record
Abstract
Background: Breast cancer is a major health concern in various countries. Routine mammography screening has been shown to reduce breast cancer mortality, and Japan has set national targets to improve screening participation and increase public attention. However, collecting nationwide data on public attention and activity is not easy. Google Trends can reveal changes in societal interest, yet there are no reports on the relationship between internet search volume and nationwide participation rates in Japan. Objective: This study aims to reveal and discuss the relationship between public awareness and actual behavior in breast cancer screening by examining trends in internet search volume for the keyword "breast cancer screening" and participation rates over a decade-long period. Methods: This time-series study evaluated the association between internet search volume and breast cancer screening participation behavior among women aged 60-69 years in Japan from 2009 to 2019. Relative search volume (RSV) data for the search term "breast cancer screening (nyuugan-kenshin)" were extracted from Google Trends as internet search volume. Breast cancer screening and further assessment participation rates were based on government municipal screening data. Joinpoint regression analyses were conducted with weighted BIC to evaluate the time trends. An ethics review was not required because all data were open. Results: The RSV for "breast cancer screening (nyuugan-kenshin)" peaked in June 2017 (100) and showed clear spikes in June 2016 (94), September (69), and October (77) 2015. No RSVs above 60 were observed except around these three specific periods, and the average RSV for the entire period was 30.7 (SD 16.2). Two statistically significant joinpoints were detected, rising in December 2013 and falling in June 2017. Screening participation rates showed a temporary increase in 2015 in a slowly decreasing trend, and no joinpoints were detected. Further assessment participation rates showed a temporary spike in 2015 in the middle of an increasing trend, with a statistically significant point of slowing increase detected in 2015. Post hoc manual searches revealed that Japanese celebrities' breast cancer diagnoses were announced on the relevant dates, and many Japanese media reports were found. Conclusions: This study found a notable association between internet search activity and celebrity cancer media reports and a temporal association with screening participation in breast cancer screening in Japan. Celebrity cancer media reports triggered internet searches for cancer screening, but this did not lead to long-term changes in screening participation behavior. This finding suggests what information needs to be provided to citizens to encourage participation in screening.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.000 |
| 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".