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Article ; Online: Notes from the Field: Firearm Homicide Rates, by Race and Ethnicity - United States, 2019-2022.

Kegler, Scott R / Simon, Thomas R / Sumner, Steven A

MMWR. Morbidity and mortality weekly report

2023 Volume 72, Issue 42, Page(s) 1149–1150

MeSH term(s)	Humans ; Ethnicity ; Firearms ; Homicide ; Suicide ; United States/epidemiology ; Wounds, Gunshot
Language	English
Publishing date	2023-10-20
Publishing country	United States
Document type	Journal Article
ZDB-ID	412775-4
ISSN	1545-861X ; 0149-2195
ISSN (online)	1545-861X
ISSN	0149-2195
DOI	10.15585/mmwr.mm7242a4
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Article: A Social-Ecological Approach to Modeling Sense of Virtual Community (SOVC) in Livestreaming Communities.

Kairam, Sanjay R / Mercado, Melissa C / Sumner, Steven A

Proceedings of the ACM on human-computer interaction

2023 Volume 6, Issue CSCW2 Article No 356, Page(s) 1–35

Abstract: Participation in communities is essential to individual mental and physical health and can yield further benefits for members. With a growing amount of time spent participating in virtual communities, it's increasingly important that we understand how ... ...

Abstract	Participation in communities is essential to individual mental and physical health and can yield further benefits for members. With a growing amount of time spent participating in virtual communities, it's increasingly important that we understand how the community experience manifests in and varies across these online spaces. In this paper, we investigate Sense of Virtual Community (SOVC) in the context of live-streaming communities. Through a survey of 1,944 Twitch viewers, we identify that community experiences on Twitch vary along two primary dimensions:
Language	English
Publishing date	2023-06-25
Publishing country	United States
Document type	Journal Article
ISSN	2573-0142
ISSN	2573-0142
DOI	10.1145/3555081
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Article ; Online: Business and property types experiencing excess violent crime: a micro-spatial analysis.

Bowen, Daniel A / Anthony, Kurtis M / Sumner, Steven A

Journal of injury & violence research

2021 Volume 14, Issue 1, Page(s) 1–10

Abstract: Background: Beyond alcohol retail establishments, most business and property types receive limited attention in studies of violent crime. We sought to provide a comprehensive examination of which properties experience the most violent crime in a city ... ...

Abstract	Background: Beyond alcohol retail establishments, most business and property types receive limited attention in studies of violent crime. We sought to provide a comprehensive examination of which properties experience the most violent crime in a city and how that violence is distributed throughout a city. Methods: For a large urban city, we merged violent incident data from police reports with municipal tax assessor data from 2012-2017 and tabulated patterns of violent crime for 15 commercial and public property types. To describe outlier establishments, we calculated the proportion of individual parcels within each property-type that experienced more than 5 times the average number of crimes for that property-type and also mapped the 25 parcels with the highest number of violent incidents to explore what proportion of violent crime in these block groups were contributed by the outlier establishments. Results: While the hotel/lodging property-type experienced the highest number of violent crimes per parcel (2.72), each property-type had outlier establishments experiencing more than 5 times the average number of violent crimes per business. Twelve of 15 property-types (80%) had establishments with more than 10 times the mean number of violent incidents. The 25 parcels with the most violent crime comprised a wide variety of establishments, ranging from a shopping center, grocery store, gas station, motel, public park, vacant lot, public street, office building, transit station, hospital, pharmacy, school, community center, and movie theatre, and were distributed across the city. Eight of the 25 parcels with the highest amount of violent crime, accounted for 50% or more of the violent crime within a 400-meter buffer. Conclusions: All property-types had outlier establishments experiencing elevated counts of violent crimes. Furthermore, the 25 most violent properties in the city demonstrated remarkable diversity in property-type. Further studies assessing the risk of violent crime among additional property-types may aid in violence prevention.
MeSH term(s)	Commerce ; Crime ; Humans ; Police ; Spatial Analysis ; Violence
Language	English
Publishing date	2021-11-17
Publishing country	Iran
Document type	Journal Article
ZDB-ID	2573562-7
ISSN	2008-4072 ; 2008-4072
ISSN (online)	2008-4072
ISSN	2008-4072
DOI	10.5249/jivr.v14i1.1566
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Article ; Online: Emerging Trends of Self-Harm Using Sodium Nitrite in an Online Suicide Community: Observational Study Using Natural Language Processing Analysis.

Das, Sudeshna / Walker, Drew / Rajwal, Swati / Lakamana, Sahithi / Sumner, Steven A / Mack, Karin A / Kaczkowski, Wojciech / Sarker, Abeed

JMIR mental health

2024 Volume 11, Page(s) e53730

Abstract: Background: There is growing concern around the use of sodium nitrite (SN) as an emerging means of suicide, particularly among younger people. Given the limited information on the topic from traditional public health surveillance sources, we studied ... ...

Abstract	Background: There is growing concern around the use of sodium nitrite (SN) as an emerging means of suicide, particularly among younger people. Given the limited information on the topic from traditional public health surveillance sources, we studied posts made to an online suicide discussion forum, "Sanctioned Suicide," which is a primary source of information on the use and procurement of SN. Objective: This study aims to determine the trends in SN purchase and use, as obtained via data mining from subscriber posts on the forum. We also aim to determine the substances and topics commonly co-occurring with SN, as well as the geographical distribution of users and sources of SN. Methods: We collected all publicly available from the site's inception in March 2018 to October 2022. Using data-driven methods, including natural language processing and machine learning, we analyzed the trends in SN mentions over time, including the locations of SN consumers and the sources from which SN is procured. We developed a transformer-based source and location classifier to determine the geographical distribution of the sources of SN. Results: Posts pertaining to SN show a rise in popularity, and there were statistically significant correlations between real-life use of SN and suicidal intent when compared to data from the Centers for Disease Control and Prevention (CDC) Wide-Ranging Online Data for Epidemiologic Research (⍴=0.727; P<.001) and the National Poison Data System (⍴=0.866; P=.001). We observed frequent co-mentions of antiemetics, benzodiazepines, and acid regulators with SN. Our proposed machine learning-based source and location classifier can detect potential sources of SN with an accuracy of 72.92% and showed consumption in the United States and elsewhere. Conclusions: Vital information about SN and other emerging mechanisms of suicide can be obtained from online forums.
MeSH term(s)	Humans ; Natural Language Processing ; Self-Injurious Behavior/epidemiology ; Sodium Nitrite ; Suicide/trends ; Suicide/psychology ; Adult ; Internet ; Male ; Female ; Social Media ; Young Adult
Chemical Substances	Sodium Nitrite (M0KG633D4F)
Language	English
Publishing date	2024-05-02
Publishing country	Canada
Document type	Journal Article ; Observational Study ; Research Support, Non-U.S. Gov't
ZDB-ID	2798262-2
ISSN	2368-7959 ; 2368-7959
ISSN (online)	2368-7959
ISSN	2368-7959
DOI	10.2196/53730
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Article ; Online: Estimating national and state-level suicide deaths using a novel online symptom search data source.

Sumner, Steven A / Alic, Alen / Law, Royal K / Idaikkadar, Nimi / Patel, Nimesh

Journal of affective disorders

2023 Volume 342, Page(s) 63–68

Abstract: Background: Suicide mortality data are a critical source of information for understanding suicide-related trends in the United States. However, official suicide mortality data experience significant delays. The Google Symptom Search Dataset (SSD), a ... ...

Abstract	Background: Suicide mortality data are a critical source of information for understanding suicide-related trends in the United States. However, official suicide mortality data experience significant delays. The Google Symptom Search Dataset (SSD), a novel population-level data source derived from online search behavior, has not been evaluated for its utility in predicting suicide mortality trends. Methods: We identified five mental health related variables (suicidal ideation, self-harm, depression, major depressive disorder, and pain) from the SSD. Daily search trends for these symptoms were utilized to estimate national and state suicide counts in 2020, the most recent year for which data was available, via a linear regression model. We compared the performance of this model to a baseline autoregressive integrated moving average (ARIMA) model and a model including all 422 symptoms (All Symptoms) in the SSD. Results: Our Mental Health Model estimated the national number of suicide deaths with an error of -3.86 %, compared to an error of 7.17 % and 28.49 % for the ARIMA baseline and All Symptoms models. At the state level, 70 % (N = 35) of states had a prediction error of <10 % with the Mental Health Model, with accuracy generally favoring larger population states with higher number of suicide deaths. Conclusion: The Google SSD is a new real-time data source that can be used to make accurate predictions of suicide mortality monthly trends at the national level. Additional research is needed to optimize state level predictions for states with low suicide counts.
MeSH term(s)	Humans ; United States/epidemiology ; Depressive Disorder, Major ; Information Sources ; Suicide/psychology ; Suicidal Ideation ; Self-Injurious Behavior
Language	English
Publishing date	2023-09-11
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	135449-8
ISSN	1573-2517 ; 0165-0327
ISSN (online)	1573-2517
ISSN	0165-0327
DOI	10.1016/j.jad.2023.08.141
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Article ; Online: Trends in stigmatizing language about addiction: A longitudinal analysis of multiple public communication channels.

McLaren, Nilay / Jones, Christopher M / Noonan, Rita / Idaikkadar, Nimi / Sumner, Steven A

Drug and alcohol dependence

2023 Volume 245, Page(s) 109807

Abstract: Introduction: Stigma associated with substance use and addiction is a major barrier to overdose prevention. Although stigma reduction is a key goal of federal strategies to prevent overdose, there is limited data to assess progress made in reducing use ... ...

Abstract	Introduction: Stigma associated with substance use and addiction is a major barrier to overdose prevention. Although stigma reduction is a key goal of federal strategies to prevent overdose, there is limited data to assess progress made in reducing use of stigmatizing language about addiction. Methods: Using language guidelines published by the federal National Institute on Drug Abuse (NIDA), we examined trends in use of stigmatizing terms about addiction across four popular public communication modalities: news articles, blogs, Twitter, and Reddit. We calculate percent changes in the rates of articles/posts using stigmatizing terms over a five-year period (2017-2021) by fitting a linear trendline and assess statistically significant trends using the Mann-Kendall test. Results: The rate of articles containing stigmatizing language decreased over the past five years for news articles (-68.2 %, p < 0.001) and blogs (-33.6 %, p < 0.001). Among social media platforms, the rate of posts using stigmatizing language increased (Twitter [43.5 %, p = 0.01]) or remained stable (Reddit [3.1 %, p = 0.29]). In absolute terms, news articles had the highest rate of articles containing stigmatizing terms over the five-year period (324.9 articles per million) compared to 132.3, 18.3, and 138.6 posts per million for blogs, Twitter, and Reddit, respectively. Conclusions: Use of stigmatizing language about addiction appears to have decreased across more traditional, longer-format communication modalities such as news articles. Additional work is needed to reduce use of stigmatizing language on social media.
MeSH term(s)	Humans ; Language ; Social Stigma ; Communication ; Behavior, Addictive ; Substance-Related Disorders ; Social Media ; Drug Overdose
Language	English
Publishing date	2023-02-13
Publishing country	Ireland
Document type	Journal Article
ZDB-ID	519918-9
ISSN	1879-0046 ; 0376-8716
ISSN (online)	1879-0046
ISSN	0376-8716
DOI	10.1016/j.drugalcdep.2023.109807
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Article ; Online: Temporal Trends in Online Posts About Vaping of Cannabis Products.

Sumner, Steven A / Haegerich, Tamara M / Jones, Christopher M

Journal of addiction medicine

2020 Volume 15, Issue 2, Page(s) 173–174

MeSH term(s)	Cannabis/adverse effects ; Electronic Nicotine Delivery Systems ; Humans ; Marijuana Smoking ; Social Media ; Vaping/adverse effects
Language	English
Publishing date	2020-07-22
Publishing country	Netherlands
Document type	Letter
ISSN	1935-3227
ISSN (online)	1935-3227
DOI	10.1097/ADM.0000000000000709
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Article ; Online: Adherence to suicide reporting guidelines by news shared on a social networking platform.

Sumner, Steven A / Burke, Moira / Kooti, Farshad

Proceedings of the National Academy of Sciences of the United States of America

2020 Volume 117, Issue 28, Page(s) 16267–16272

Abstract: Rates of suicide in the United States are at a more than 20-y high. Suicide contagion, or spread of suicide-related thoughts and behaviors through exposure to sensationalized and harmful content is a well-recognized phenomenon. Health authorities have ... ...

Abstract	Rates of suicide in the United States are at a more than 20-y high. Suicide contagion, or spread of suicide-related thoughts and behaviors through exposure to sensationalized and harmful content is a well-recognized phenomenon. Health authorities have published guidelines for news media reporting on suicide to help prevent contagion; however, uptake of recommendations remains limited. A key barrier to widespread voluntary uptake of suicide-reporting guidelines is that more sensational content is perceived to be more engaging to readers and thus enhances publisher visibility and engagement; however, no empirical information exists on the actual influence of adherence to safe-reporting practices on reader engagement. Hence, we conducted a study to analyze adherence to suicide-reporting guidelines on news shared on social media and to assess how adherence affects reader engagement. Our analysis of Facebook data revealed that harmful elements were prevalent in news articles about suicide shared on social media while the presence of protective elements was generally rare. Contrary to popular perception, closer adherence to safe-reporting practices was associated with a greater likelihood of an article being reshared (adjusted odds ratio [AOR] = 1.19, 95% confidence interval [CI] = 1.10 to 1.27) and receiving positive engagement ("love" reactions) (AOR = 1.20, 95% CI = 1.13 to 1.26). Mean safe-reporting scores were lower in the US than other English-speaking nations and variation existed by publisher characteristics. Our results provide empirical evidence that improved adherence to suicide-reporting guidelines may benefit not only the health of individuals, but also support publisher goals of reach and engagement.
MeSH term(s)	Guideline Adherence/standards ; Guideline Adherence/statistics & numerical data ; Guidelines as Topic ; Humans ; Odds Ratio ; Social Media/standards ; Social Media/statistics & numerical data ; Social Networking ; Suicide/psychology ; United States/epidemiology ; Suicide Prevention
Language	English
Publishing date	2020-07-06
Publishing country	United States
Document type	Journal Article
ZDB-ID	209104-5
ISSN	1091-6490 ; 0027-8424
ISSN (online)	1091-6490
ISSN	0027-8424
DOI	10.1073/pnas.2001230117
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Article ; Online: Concerns among people who use opioids during the COVID-19 pandemic: a natural language processing analysis of social media posts.

Sarker, Abeed / Nataraj, Nisha / Siu, Wesley / Li, Sabrina / Jones, Christopher M / Sumner, Steven A

Substance abuse treatment, prevention, and policy

2022 Volume 17, Issue 1, Page(s) 16

Abstract: Background: Timely data from official sources regarding the impact of the COVID-19 pandemic on people who use prescription and illegal opioids is lacking. We conducted a large-scale, natural language processing (NLP) analysis of conversations on opioid- ... ...

Abstract	Background: Timely data from official sources regarding the impact of the COVID-19 pandemic on people who use prescription and illegal opioids is lacking. We conducted a large-scale, natural language processing (NLP) analysis of conversations on opioid-related drug forums to better understand concerns among people who use opioids. Methods: In this retrospective observational study, we analyzed posts from 14 opioid-related forums on the social network Reddit. We applied NLP to identify frequently mentioned substances and phrases, and grouped the phrases manually based on their contents into three broad key themes: (i) prescription and/or illegal opioid use; (ii) substance use disorder treatment access and care; and (iii) withdrawal. Phrases that were unmappable to any particular theme were discarded. We computed the frequencies of substance and theme mentions, and quantified their volumes over time. We compared changes in post volumes by key themes and substances between pre-COVID-19 (1/1/2019-2/29/2020) and COVID-19 (3/1/2020-11/30/2020) periods. Results: Seventy-seven thousand six hundred fifty-two and 119,168 posts were collected for the pre-COVID-19 and COVID-19 periods, respectively. By theme, posts about treatment and access to care increased by 300%, from 0.631 to 2.526 per 1000 posts between the pre-COVID-19 and COVID-19 periods. Conversations about withdrawal increased by 812% between the same periods (0.026 to 0.235 per 1,000 posts). Posts about drug use did not increase (0.219 to 0.218 per 1,000 posts). By substance, among medications for opioid use disorder, methadone had the largest increase in conversations (20.751 to 56.313 per 1,000 posts; 171.4% increase). Among other medications, posts about diphenhydramine exhibited the largest increase (0.341 to 0.927 per 1,000 posts; 171.8% increase). Conclusions: Conversations on opioid-related forums among people who use opioids revealed increased concerns about treatment and access to care along with withdrawal following the emergence of COVID-19. Greater attention to social media data may help inform timely responses to the needs of people who use opioids during COVID-19.
MeSH term(s)	Analgesics, Opioid/therapeutic use ; COVID-19/epidemiology ; Humans ; Natural Language Processing ; Opioid-Related Disorders/drug therapy ; Opioid-Related Disorders/epidemiology ; Pandemics ; SARS-CoV-2 ; Social Media
Chemical Substances	Analgesics, Opioid
Language	English
Publishing date	2022-03-05
Publishing country	England
Document type	Journal Article ; Observational Study ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, P.H.S.
ZDB-ID	2222956-5
ISSN	1747-597X ; 1747-597X
ISSN (online)	1747-597X
ISSN	1747-597X
DOI	10.1186/s13011-022-00442-w
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Article ; Online: Using Transformer-Based Topic Modeling to Examine Discussions of Delta-8 Tetrahydrocannabinol: Content Analysis.

Smith, Brandi Patrice / Hoots, Brooke / DePadilla, Lara / Roehler, Douglas R / Holland, Kristin M / Bowen, Daniel A / Sumner, Steven A

Journal of medical Internet research

2023 Volume 25, Page(s) e49469

Abstract: Background: Delta-8 tetrahydrocannabinol (THC) is a psychoactive cannabinoid found in small amounts naturally in the cannabis plant; it can also be synthetically produced in larger quantities from hemp-derived cannabidiol. Most states permit the sale of ...

Abstract	Background: Delta-8 tetrahydrocannabinol (THC) is a psychoactive cannabinoid found in small amounts naturally in the cannabis plant; it can also be synthetically produced in larger quantities from hemp-derived cannabidiol. Most states permit the sale of hemp and hemp-derived cannabidiol products; thus, hemp-derived delta-8 THC products have become widely available in many state hemp marketplaces, even where delta-9 THC, the most prominently occurring THC isomer in cannabis, is not currently legal. Health concerns related to the processing of delta-8 THC products and their psychoactive effects remain understudied. Objective: The goal of this study is to implement a novel topic modeling approach based on transformers, a state-of-the-art natural language processing architecture, to identify and describe emerging trends and topics of discussion about delta-8 THC from social media discourse, including potential symptoms and adverse health outcomes experienced by people using delta-8 THC products. Methods: Posts from January 2008 to December 2021 discussing delta-8 THC were isolated from cannabis-related drug forums on Reddit (Reddit Inc), a social media platform that hosts the largest web-based drug forums worldwide. Unsupervised topic modeling with state-of-the-art transformer-based models was used to cluster posts into topics and assign labels describing the kinds of issues being discussed with respect to delta-8 THC. Results were then validated by human subject matter experts. Results: There were 41,191 delta-8 THC posts identified and 81 topics isolated, the most prevalent being (1) discussion of specific brands or products, (2) comparison of delta-8 THC to other hemp-derived cannabinoids, and (3) safety warnings. About 5% (n=1220) of posts from the resulting topics included content discussing health-related symptoms such as anxiety, sleep disturbance, and breathing problems. Until 2020, Reddit posts contained fewer than 10 mentions of delta-8-THC for every 100,000 cannabis posts annually. However, in 2020, these rates increased by 13 times the 2019 rate (to 99.2 mentions per 100,000 cannabis posts) and continued to increase into 2021 (349.5 mentions per 100,000 cannabis posts). Conclusions: Our study provides insights into emerging public health concerns around delta-8 THC, a novel substance about which little is known. Furthermore, we demonstrate the use of transformer-based unsupervised learning approaches to derive intelligible topics from highly unstructured discussions of delta-8 THC, which may help improve the timeliness of identification of emerging health concerns related to new substances.
MeSH term(s)	Humans ; Cannabidiol ; Dronabinol ; Cannabis ; Anxiety ; Anxiety Disorders
Chemical Substances	Cannabidiol (19GBJ60SN5) ; Dronabinol (7J8897W37S)
Language	English
Publishing date	2023-12-21
Publishing country	Canada
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2028830-X
ISSN	1438-8871 ; 1438-8871
ISSN (online)	1438-8871
ISSN	1438-8871
DOI	10.2196/49469
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