State health policies and interest in PrEP: evidence from Google Trends

Strengthening the US Health Workforce to End the HIV Epidemic: Lessons Learned From 11 Ending the HIV Epidemic Jurisdictions

BACKGROUND

Supplements were awarded under the National Institutes of Health, ending the HIV epidemic (EHE) initiative to foster implementation science through community-engaged research. The objective of this study was to synthesize lessons learned, identify areas of research sufficiently studied, and present an agenda for future research on HIV health workforce development from a collaboration across 9 EHE projects in 11 jurisdictions in the United States.

METHODS

EHE supplement recipients completed a semistructured questionnaire to identify shared lessons learned about common themes of workforce development using the Consolidated Framework for Implementation Research and Expert Recommendation for Implementing Change frameworks. Data were synthesized to identify shared lessons learned, topic areas no longer in need of research, and next steps.

RESULTS

Project teams emphasized several strategies including clarifying roles and responsibilities, the need for dynamic training, and stigma mitigation as strategies to enhance the implementation of HIV prevention and treatment services. Strengthening organizational support through supportive supervision structures, ensuring sustainable funding, preventing turnover, addressing salary constraints, and establishing clear promotion and educational pathways were identified as useful workplace development strategies. Supplements identified lessons learned about deploying community engagement strategies to ensure communities were aware of HIV prevention and treatment services. Several areas sufficiently studied that can be deprioritized were identified and discussed.

CONCLUSION

A research agenda for workplace development moving forward is discussed with several recommendations to improve the implementation of HIV prevention and treatment programs.

Relationships between structural stigma, societal stigma, and minority stress among gender minority people

Structural stigma towards gender minority (GM; people whose current gender does not align with sex assigned at birth) people is an important contributor to minority stress (i.e., stress experienced due to one's marginalized GM identity), although existing variables are unclear in their inclusion of social norms, or societal stigma, as a key component of the construct. We examined potential variables representing structural stigma, including variables that are inclusive of societal stigma, to identify those that most strongly relate to minority stress outcomes. We tested variables identified in the literature as measures of structural stigma inclusive of societal stigma (LGBT + Business Climate Index, state voting behaviors, and Google Trends search data), the most commonly used structural stigma variable (State Policy Environment Tally), and proxy variables (region, population density) for comparison. The relationships between structural stigma and minority stress model outcomes were tested in a sample of GM participants from The Population Research in Identity and Disparities for Equality (PRIDE) Study (N = 2,094) 2019 Annual Questionnaire using a structural equation model (SEM). Lower structural stigma (i.e., higher LGBT Business Climate Index) was associated with lower experienced stigma (β= -0.260, p < .01) and lower anticipated stigma (β= -0.433, p < .001). Greater conservative voting behavior was associated with less experienced stigma (β= -0.103, p < .01). Living in a more densely populated county was also associated with lower anticipated stigma (β=-0.108, p < .001) and greater identity outness (β = 0.053, p < .05). Two of the identified structural stigma variables that were inclusive of societal stigma (i.e., LGBT + Business Climate Index, conservative voting behaviors) and one proxy variable (population density) were associated with minority stress outcomes. However, the most commonly used variable for structural stigma (State Policy Environment Tally) was not associated with any outcomes. The State LGBT + Business Climate Index showed the most promise for use as a structural stigma variable in future research. The application of this variable should be investigated further to explore its association with health outcomes and to inform efforts to reduce health equity barriers experienced by GM people through addressing structural stigma in a manner inclusive of societal stigma.

The Interest in Betting, Smoking, Alcohol, and Drugs in Malawi: Changing Trends between 2012-2022

Background

In recent years, the online gambling market has rapidly developed, and betting has become one of the most popular forms of gambling. The aim of this study was to analyse the interest of the Malawian population in terms related to betting, sports betting, alcohol, cigarettes, and some psychoactive drugs through the relative search volumes of Google Trends.

Methods

Internet search query data related to betting, sports betting, alcohol, cigarettes, and psychoactive drugs were obtained monthly from Google Trends for the period 2010-2022. Comparisons of interest levels in these topics were conducted in Malawi, and correlation coefficients were calculated.

Results

In Malawi, relative search volumes for betting and sports betting terms were the highest (average RSVs: 66% and 30%). It was found that from 2019 onwards, the interest in betting and sports-related search topics and keywords increased significantly (p < 0.001). Strong positive correlations were found between betting-related keywords and alcohol and gross domestic product (r = 0.831 and r = 0.901, p < 0.001). A positive correlation was found between betting and psychoactive drug-related terms (minimum r = 0.417, p < 0.01).

Conclusions

This study concludes that the interest of the Malawian population in betting has increased in recent years, while interest in psychoactive drugs and alcohol remains high. Gross domestic product is highly correlated with society's interest in betting. It was additionally found that Google Trends can be used as a tool to predict and monitor future risky behaviours, such as gambling disorder.

The application of artificial intelligence in health policy: a scoping review

BACKGROUND

Policymakers require precise and in-time information to make informed decisions in complex environments such as health systems. Artificial intelligence (AI) is a novel approach that makes collecting and analyzing data in complex systems more accessible. This study highlights recent research on AI's application and capabilities in health policymaking.

METHODS

We searched PubMed, Scopus, and the Web of Science databases to find relevant studies from 2000 to 2023, using the keywords "artificial intelligence" and "policymaking." We used Walt and Gilson's policy triangle framework for charting the data.

RESULTS

The results revealed that using AI in health policy paved the way for novel analyses and innovative solutions for intelligent decision-making and data collection, potentially enhancing policymaking capacities, particularly in the evaluation phase. It can also be employed to create innovative agendas with fewer political constraints and greater rationality, resulting in evidence-based policies. By creating new platforms and toolkits, AI also offers the chance to make judgments based on solid facts. The majority of the proposed AI solutions for health policy aim to improve decision-making rather than replace experts.

CONCLUSION

Numerous approaches exist for AI to influence the health policymaking process. Health systems can benefit from AI's potential to foster the meaningful use of evidence-based policymaking.

Infodemiologists Beware: Recent Changes to the Google Health Trends API Result in Incomparable Data as of 1 January 2022

In an ever-increasingly online world, many Internet users seek information from online search engines such as Google. Accessing such search activity allows infodemiologists a glimpse into the collective online mind. Tools such as Google Trends and Google Health Trends (GHT) can be used to gauge search activity in key geographical regions and for specific periods of time. Recently, Google implemented changes to the GHT platform. Evidence is provided here for an initial exploration of how this change impacted the data obtained from GHT. Comparing 177 weekly probabilities for short search sessions of 421 Freebase IDs in thirty geographies extracted from GHT both before and after the implemented change, a low correlation (median of all Spearman ρ = 0.262 [IQR 0.04; 0.53]) between these data was observed for the year 2022. In general, the extracted values are higher after the implemented changes, compared to the values extracted before the change. Future research using the GHT API should not attribute increases in GHT data from 1 January 2022 onward as being reflective of increased search activity for a specific keyword, but rather attribute it to the implemented change to the GHT sampling strategy.