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Abstract 64: Multilevel Barriers and Facilitators of Smoking Cessation in People Living With HIV in Vietnam: A Qualitative Analysis

2023· article· en· W4379012141 on OpenAlexaff
Thanh Hoang, Claire VT Nguyen, Gloria Guevera Alvarez, Trang Nguyen, Nam Nguyen, Louise Adermark, Nawi Ng, Donna Shelley, Mari Armstrong‐Hough

Bibliographic record

VenueCancer Epidemiology Biomarkers & Prevention · 2023
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsYork University
Fundersnot available
KeywordsSmoking cessationFacilitatorMedicineThematic analysisQualitative researchFamily medicineHuman immunodeficiency virus (HIV)PsychologySocial psychology

Abstract

fetched live from OpenAlex

Abstract Purpose: In Vietnam, tobacco smoking is highly prevalent among people living with HIV (PLWH) and increases their risk of cancer, cardiovascular disease, and life-threatening opportunistic infections. However, research on effective tobacco use treatment (TUT) for PLWH is lacking. To fill this gap, we aimed to identify multilevel barriers and facilitators (B&Fs) of smoking cessation and their implications for TUT implementation for PLWH in Hanoi, Vietnam. Methods: We conducted individual in-depth interviews with 24 patients and 13 healthcare providers at three HIV outpatient clinics (OPCs) in Hanoi to explore B&Fs of smoking cessation at the patient, provider, and system level. Two coders carried out a two-phase abductive thematic analysis using Atlas.ti and guided by the Theoretical Domains Framework. Results: Participants described several patient-level barriers to smoking cessation: limited knowledge, misperceptions about smoking harms, lack of familiarity with cessation aids, exposure to environments in which smoking is common, emotional issues (i.e., stress/depression), substance use, and social norms that promote male smoking and tie smoking to masculinity. Both patients and providers described self-determination to quit as a major facilitator of smoking cessation (Everything can be overcome if there is determination). Patients reported that strong determination to quit is influenced by concerns about the harms of smoking; family support and pressure to quit; and the potential for improving health of themselves and their family and for reducing tobacco-related expenses from tobacco purchases. Provide-reported barriers included a lack of resources and capabilities to assess and intervene on smoking behaviour at the OPCs, and at the system level affordable and accessible tobacco products. However, providers endorsed the importance of supporting patients to quit and were optimistic about tailoring and integrating TUT into OPCs if they were equipped with training, personnel, and financial support. Trust and patient-provider solid relationships were potential facilitators of cessation. Conclusion: The study suggested the need to intervene at patient, provider, and system levels to increase engagement among PLWH in smoking cessation treatment. Provider training, patient education and resources are needed to facilitate treatment. Findings also suggest a need to tailor existing treatment options developed in other contexts to this population and setting. Citation Format: Thanh Hoang, Claire VT Nguyen, Gloria Guevera Alvarez, Trang Nguyen, Nam Nguyen, Louise Adermark, Nawi Ng, Donna Shelley, Mari Armstrong-Hough. Multilevel Barriers and Facilitators of Smoking Cessation in People Living With HIV in Vietnam: A Qualitative Analysis [abstract]. In: Proceedings of the 11th Annual Symposium on Global Cancer Research; Closing the Research-to-Implementation Gap; 2023 Apr 4-6. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(6_Suppl):Abstract nr 64.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0050.003
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.062
GPT teacher head0.412
Teacher spread0.351 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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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Citations1
Published2023
Admission routes1
Has abstractyes

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