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Record W6940865215 · doi:10.13016/dspace/7nkh-wvpp

2022 UMD-PRC Community Health Needs Assessment Report: Investigating Tobacco Use and Cessation Experiences of LGBTQ Youth and Young Adults in Prince George’s and Montgomery County, Maryland

2023· other· en· W6940865215 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity Libraries (University of Maryland) · 2023
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsnot available
FundersCenters for Disease Control and Prevention
KeywordsNeeds assessmentTobacco controlFocus groupTobacco useCommunity healthReproductive healthHealth literacyHealth promotionSmoking cessation

Abstract

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Funded by the Centers for Disease Control and Prevention (CDC), the current needs assessment was led by the University of Maryland Prevention Research Center (UMD-PRC) in conjunction with the UMD Center for Health Literacy and the Maryland Department of Health to better understand tobacco use among Black and Latino/a/x lesbian, gay, bisexual, transgender, queer, and other sexual and gender diverse (LGBTQ) youth and young adults in Prince George’s and Montgomery counties. The Maryland Department of Health and the University of Maryland Institutional Review Boards approved the project. The goals of the community needs assessment were to identify health needs among Black and Latino/a/x LGBTQ communities related to tobacco use, factors associated with health and tobacco use for these communities, and the strengths and resources available to address these needs and associated factors. The degree to which existing tobacco prevention and cessation health campaigns resonate with Black and Latino/a/x young adults was also assessed. Needs Assessment The needs assessment took place from April to September 2022 and included seven focus groups with Black and Latino/a/x LGBTQ people aged 18-30 with various histories of tobacco use, key informant interviews with community stakeholders, analysis of state-level health surveillance data, a review of county and state tobacco resources and programs, and a literature review of existing tobacco and cessation messaging focused on LGBTQ communities. The project’s Community Advisory Board (CAB) – comprised of Black, Latino/a/x, and LGBTQ-focused service providers and community members in Prince George’s and Montgomery counties – provided feedback the report. They also offered ideas regarding action items that resulted from the data. Results will inform upcoming project initiatives, including the development of a health communication campaign and community outreach programs. The assessment yielded the following findings: State Surveillance Data • We used data from the 2018-2019 Maryland Youth Risk Behavioral Survey/Youth Tobacco Survey (YRBS/YTS, aged ~13-18) and 2018-2019 Maryland Behavioral Risk Factor Surveillance System (BRFSS, aged 18 and older). • Our sample was restricted to participants from Prince George’s and Montgomery counties and analyzed to assess tobacco use behaviors by sexual orientation and gender identity, as well as correlates of these behaviors. • Results showed greater cigarette use, e-cigarette use, cigar use, and early initiation among LGBTa residents relative to cisgender, heterosexual residents (i.e., non-LGBT). • We did not observe differences in poor physical and mental health days between adult LGBT and non-LGBT respondents. • Among youth, all tobacco use behaviors were higher among LGBT youth who reported feeling sad or hopeless and experiences of bullying when compared to LGBT youth who did not experience these feelings and interactions. Focus Groups • Seven focus groups were conducted with residents aged 18-30 in Prince George’s and Montgomery counties (30 participants total). • Participants discussed using tobacco to cope with life stressors. • Focus group conversations highlighted the links between tobacco use, mental health, and discrimination. • Participants were unaware of most general or community-specific tobacco prevention and cessation resources. Stakeholders Interviews • Six key informant interviews were conducted with community service professionals from organizations serving LGBTQ, Black, and/or Latino/a/x residents in Prince George’s and Montgomery counties. • One organization reported an increase in tobacco use among clients since the start of the COVID-19 pandemic. • All stakeholders were interested in receiving tobacco prevention and cessation resources and support. • Stakeholder interviewers emphasized the mental health and substance use concerns among clients. Top Issues and Priorities Through stakeholder interviews, focus group discussions, and review of the literature and existing campaigns, the following priorities were established: • Tobacco use services do not appear to be a priority for local LGBTQ-serving organizations. • Tobacco prevention/cessation messaging and services should be paired with other topics, including mental health, stigma, coping, and peer pressure. • Our initial age range of focus (12-30 years) is too large to develop a single tailored communication health campaign; therefore, we will restrict our focus to Black and Latino/a/x youth aged 15-20. This decision was based on our literature review and focus group findings, but also to emphasize prevention and cessation early in the life course. • Communication channels for exposure to tobacco advertisements and prevention messages differed across both Black and Latino/a/x focus groups, suggesting channel preferences for our own tobacco messages. • Tobacco prevention and cessation campaign messages should be disseminated in traditional and digital formats that consider preferences and needs. • Smoking prevention and cessation messages for Black and Hispanic LGBTQ young adults must be carefully tailored to avoid stereotypes while appealing to cultural values. • The literature review shows a critical gap in existing research that tests and evaluates the effectiveness of tobacco and prevention control (TPC) messaging targeted at Black and Latino/a/x LGBTQ communities.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.491
Threshold uncertainty score0.941

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.017
GPT teacher head0.190
Teacher spread0.173 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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