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Record W4416537759 · doi:10.1186/s12889-025-24971-8

Student perspectives on smoking and second-hand smoke in Qatar: a participatory photovoice study in a multicultural university context

2025· article· en· W4416537759 on OpenAlexaff
Shannan MacNevin, Mashael Al Naemi, Yasin M. Yasin, Haruna Musa Moda, Ahmad AlMulla, Dana Abougazar, Raniah Farooq, Amiel Panda, Ayesha Sideeqa, Kryzchan Zapanta

Bibliographic record

VenueBMC Public Health · 2025
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsPhotovoiceThematic analysisPublic healthContext (archaeology)Community-based participatory researchQualitative researchParticipatory action researchBiostatisticsPopulation

Abstract

fetched live from OpenAlex

BACKGROUND: Tobacco use among university students presents a persistent public health challenge, particularly in settings where smoking is socially normalized despite strong regulatory frameworks. Qatar, with its multicultural population and progressive tobacco laws, offers a unique context for exploring these dynamics. However, little research has examined how young adults in the region experience and navigate smoking behaviours in everyday life. The study explores how university students’ perception and experience of smoking and second-hand smoke exposure, and examined barriers and facilitators to cessation within their academic and social environments. METHODS: A qualitative study using photovoice methodology was conducted within a community-based participatory research framework. Undergraduate students aged 18–24 at a large national university in Qatar were recruited via purposive and snowball sampling. After a preparatory workshop, participants captured photographs representing their experiences with smoking or second-hand smoke, followed by semi-structured, photo-elicitation interviews. Data were analysed using thematic analysis of interview transcripts and photographs using a collaborative coding process. Credibility was strengthened through triangulation of visual and narrative data, member checking, and peer debriefing. RESULTS: Twenty-two students (12 females, 10 males; 9 smokers, 13 non-smokers) participated. Thematic analysis revealed five interrelated themes: (1) health awareness and personal triggers (2), social and cultural influences (3), environmental and economic consequences (4), prevention, cessation, and support, and (5) policy and behavioural regulation. Although students were aware of the health risks of tobacco use, many continued to smoke due to stress relief, peer influence, and cultural normalization. Environmental concerns such as litter and second-hand smoke exposure were widespread but inconsistently acted upon. Most participants expressed interest in quitting but reported limited awareness or trust in available cessation resources. Institutional policies were inconsistently enforced and undermined by contradictory role modelling from faculty and peers. CONCLUSIONS: University students in Qatar described smoking behaviours shaped by emotional triggers, academic stress, peer influence, and cultural normalization. Despite awareness of health risks, smoking persisted. Participants reported widespread exposure to second-hand smoke, limited trust in cessation resources, and inconsistent enforcement of institutional policies across campus settings. TRIAL REGISTRATION: Not applicable.

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)0.006
metaresearch head score (Gemma)0.004
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 score0.011
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0110.004
Scholarly communication0.0030.002
Open science0.0010.004
Research integrity0.0030.003
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 head0.109
GPT teacher head0.389
Teacher spread0.281 · 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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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