Are cannabis prevalence estimates comparable across countries and regions? A cross-cultural validation using search engine query data

Predicting the Number of GHB-Related Toxicologic Admissions Using Google Trends Data

In the era of novel psychoactive substances (NPS), the internet became a relevant source of information and purchase for those who consume psychoactive drugs. Parallelly, a growing body of research aim to utilize web search metrics (most commonly by relying on Google Trends data) in the prediction of substance use-related trends, including epidemiological forecasting. The main goal of the current study was to assess the utility of web search queries in the prediction of Gamma-hydroxybutyrate (GHB)-related toxicologic admissions in Hungary by performing additive decomposition of time series to identify trend and seasonal components. Monthly data identified GHB-related search volume representing nationwide web interest towards this substance was found to be a significant covariate of admission rates; the seasonal component showed two peaks in the admission rates: one in December/January and another one in May, whereas more admissions on the weekends were observed as compared to weekday data in Hungary. By taking into account the subtle effect sizes of this study, these results suggest that Google Trends data may be useful in forecasting toxicologic admissions on a monthly level, yet a number of limitations should be considered when interpreting these associations. Web search metrics can therefore be used for early warning purposes in the field of toxicology as well. An external validation approach is also suggested by the authors.

Hey Google! will New Zealand vote to legalise cannabis? Using Google Trends data to predict the outcome of the 2020 New Zealand cannabis referendum

BACKGROUND

New Zealand held a referendum on the legalisation of recreational cannabis in October 2020. Polls preceding the referendum provided contrasting outcomes. We investigated whether internet search data from Google Trends could provide an alternative estimate of the referendum outcome.

METHODS

We assessed various methods for accessing Google Trends data, downloading search probability data for google.com searches from New Zealand via trends.google.com, PyTrends and Google Trends Extended for Health. We used daily data for the three months prior to the final referendum date, and hourly data for the final week. We defined two smaller time frames each from daily and hourly data, allowing comparisons over the entire time frames, and progressively closer to the end. Using the selected keyword combination of 'cannabis referendum yes/no' we calculated the proportions of 'yes' and 'no' searches for each time frame/data source combination, aiming for a prediction within 2% of the final result.

RESULTS

Data from different sources varied slightly. The method used to aggregate search probabilities over the selected time frame (mean/median) resulted in changes in the predicted outcome for hourly-, but not daily data. On 20 October we predicted the 'no' vote at 51.9%-55.4% for daily-, and 60% for hourly data when aggregated using the median, but only 49% for mean hourly data. Hourly data performed poorly at predicting the final 51.2% 'no' result, while predictions based on mean daily data for the full voting period provided the best prediction, differing by 0.1-0.2%.

CONCLUSION

Predictions based on Google Trends data broadly agreed with polling predictions, but the exact method used affected the eventual prediction. While polls are subject to influence from methodological considerations (e.g., sampling), it is clear that Google Trends data can be used to make a prediction, but do not present a magic bullet solution to polling problems.

Utility of Web search query data in testing theoretical assumptions about mephedrone

OBJECTIVE

With growing access to the Internet, people who use drugs and traffickers started to obtain information about novel psychoactive substances (NPS) via online platforms. This paper aims to analyze whether a decreasing Web interest in formerly banned substances-cocaine, heroin, and MDMA-and the legislative status of mephedrone predict Web interest about this NPS.

METHODS

Google Trends was used to measure changes of Web interest on cocaine, heroin, MDMA, and mephedrone. Google search results for mephedrone within the same time frame were analyzed and categorized.

RESULTS

Web interest about classic drugs found to be more persistent. Regarding geographical distribution, location of Web searches for heroin and cocaine was less centralized. Illicit status of mephedrone was a negative predictor of its Web search query rates. The connection between mephedrone-related Web search rates and legislative status of this substance was significantly mediated by ecstasy-related Web search queries, the number of documentaries, and forum/blog entries about mephedrone.

CONCLUSIONS

The results might provide support for the hypothesis that mephedrone's popularity was highly correlated with its legal status as well as it functioned as a potential substitute for MDMA. Google Trends was found to be a useful tool for testing theoretical assumptions about NPS.

Forecasting state-level premature deaths from alcohol, drugs, and suicides using Google Trends data

BACKGROUND

Vital statistics on the number of, alcohol-induced death (AICD) drug-induced death (DICD), and suicides at the local-level are only available after a substantial lag of up to two years after the events occur. We (1) investigate how well Google Trends search data explain variation in state-level rates in the US, and (2) use this method to forecast these rates of death for 2015 as official data are not yet available.

METHODS

We tested the degree to which Google Trends data on 27 terms can be fit to CDC data using L₁-regularization on AICD, DICD, and suicide. Using Google Trends data, we forecast 2015 AICD, DICD, and suicide rates.

RESULTS

L₁-regularization fit the pre-2015 data much better than the alternative model using state-level unemployment and income variables. Google Trends data account for substantial variation in growth of state-level rates of death: 30.9% for AICD, 23.9% for DICD, and 21.8% for suicide rates. Every state except Hawaii is forecasted to increase in all three of these rates in 2015.

LIMITATIONS

The model predicts state, not local or individual behavior, and is dependent on continued availability of Google Trends data.

CONCLUSIONS

The method predicts state-level AICD, DICD, and suicide rates better than the alternative model. The study findings suggest that this methodology can be developed into a public health surveillance system for behavioral health-related causes of death. State-level predictions could be used to inform state interventions aimed at reducing AICD, DICD, and suicide.

Cannabis use and Drug Related Problems among Adolescents in 27 European Countries: The Utility of the Prevention Paradox

Aims

To study the prevalence of cannabis use and drug-related problems among European adolescents and the utility of the prevention paradox.

Methods

Survey data from the European School Survey Project on Alcohol and Other Drugs (ESPAD) in 2007 in the 27 countries with information about drug use and drug-related problems was used. We analysed the proportion of all drug-related problems that occurred in a high risk group and among others who had used cannabis in the previous 12 months. The cut-off for the high risk group was chosen to include 10-15 % of the most frequent cannabis users.

Results

The high risk groups accounted for a substantial, but a minority, of drug-related problems among boys as well as girls. A minority of those who had used cannabis reported any drug-related problem. The proportion of adolescents with drug-related problems and the average number of problems increased with frequency of cannabis use.

Conclusions

We find support for policy measures of more general character, supported by the prevention paradox. However, this does not exclude a policy supporting frequent drug users if they can be identified

State-level medical marijuana laws, marijuana use and perceived availability of marijuana among the general U.S. population

BACKGROUND

Little is known on how perceived availability of marijuana is associated with medical marijuana laws. We examined the relationship between medical marijuana laws (MML) and the prevalence of past-month marijuana use, with perceived availability of marijuana.

METHODS

Data were from respondents included in the National Survey of Drug Use and Health restricted use data portal 2004-2013. Multilevel logistic regression of individual-level data was used to test differences between MML and non-MML states and changes in prevalence of past-month marijuana use and perceived availability from before to after passage of MML among adolescents, young adults and older adults controlling for demographics.

RESULTS

Among adults 26+, past-month prevalence of marijuana use increased from 5.87% to 7.15% after MML passage (Adjusted Odds Ratio (AOR): 1.24 [1.16-1.31]), but no change in prevalence of use was found for 12-17 or 18-25 year-olds. Perceived availability of marijuana increased after MML was enacted among those 26+ but not in younger groups. Among all age groups, prevalence of marijuana use and perception of it being easily available was higher in states that would eventually pass MML by 2013 compared to those that had not. Perceived availability was significantly associated with increased risk of past-month marijuana use in all age groups.

CONCLUSION

Evidence suggests perceived availability as a driver of change in use of marijuana due to MML. To date, this has only occurred in adults 26+ and different scenarios that could explain this change need to be further explored.

The use of google trends in health care research: a systematic review

BACKGROUND

Google Trends is a novel, freely accessible tool that allows users to interact with Internet search data, which may provide deep insights into population behavior and health-related phenomena. However, there is limited knowledge about its potential uses and limitations. We therefore systematically reviewed health care literature using Google Trends to classify articles by topic and study aim; evaluate the methodology and validation of the tool; and address limitations for its use in research.

METHODS AND FINDINGS

PRISMA guidelines were followed. Two independent reviewers systematically identified studies utilizing Google Trends for health care research from MEDLINE and PubMed. Seventy studies met our inclusion criteria. Google Trends publications increased seven-fold from 2009 to 2013. Studies were classified into four topic domains: infectious disease (27% of articles), mental health and substance use (24%), other non-communicable diseases (16%), and general population behavior (33%). By use, 27% of articles utilized Google Trends for casual inference, 39% for description, and 34% for surveillance. Among surveillance studies, 92% were validated against a reference standard data source, and 80% of studies using correlation had a correlation statistic ≥0.70. Overall, 67% of articles provided a rationale for their search input. However, only 7% of articles were reproducible based on complete documentation of search strategy. We present a checklist to facilitate appropriate methodological documentation for future studies. A limitation of the study is the challenge of classifying heterogeneous studies utilizing a novel data source.

CONCLUSION

Google Trends is being used to study health phenomena in a variety of topic domains in myriad ways. However, poor documentation of methods precludes the reproducibility of the findings. Such documentation would enable other researchers to determine the consistency of results provided by Google Trends for a well-specified query over time. Furthermore, greater transparency can improve its reliability as a research tool.

Marijuana: current concepts(†)

Marijuana (cannabis) remains a controversial drug in the twenty-first century. This paper considers current research on use of Cannabis sativa and its constituents such as the cannabinoids. Topics reviewed include prevalence of cannabis (pot) use, other drugs consumed with pot, the endocannabinoid system, use of medicinal marijuana, medical adverse effects of cannabis, and psychiatric adverse effects of cannabis use. Treatment of cannabis withdrawal and dependence is difficult and remains mainly based on psychological therapy; current research on pharmacologic management of problems related to cannabis consumption is also considered. The potential role of specific cannabinoids for medical benefit will be revealed as the twenty-first century matures. However, potential dangerous adverse effects from smoking marijuana are well known and should be clearly taught to a public that is often confused by a media-driven, though false message and promise of benign pot consumption.