Evidence map›Paper›PMID 37292260›Full record

ArticleHeliyon2023

Factors influencing tobacco use behaviour initiation - From the perspective of the Capability, Opportunity, Motivation- Behaviour (COM-B) Model.

R Lakshmi, John Romate, Eslavath Rajkumar, Allen Joshua George, Maria Wajid

Open access · goldAbstract read
In one paragraph

Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
3.7field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 19 citations in OpenAlex.

  1. The role of the orbitofrontal cortex in smoking cue-reactivity in onset phase of smoking behavior, a fMRI study in adolescents.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2026
    Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Determinants of Smoking Among University Students in Northern Iraq.Journal of research in health sciences · 2025
    Article
  7. Article
  8. Article
  9. Article
  10. Unveiling the Bleak Reality of Tobacco Control Policies and Two-Tier Model for Mitigation.Indian journal of community medicine : official publication of Indian Association of Preventive & Social Medicine
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 4 institutions in 1 country.

R LakshmiDepartment of Applied Psychology, Central University of Tamil Nadu, Thiruvarur, India.
John RomateDepartment of Psychology, Central University of Karnataka, Kalaburagi, India.
Eslavath RajkumarDepartment of Psychology, Central University of Karnataka, Kalaburagi, India.
Allen Joshua GeorgeDepartment of Humanities and Applied Sciences Indian Institute of Management, Ranchi, India.
Maria WajidSt Joseph's University, Bengaluru, India.
Central University of Karnataka · INCentral University of Tamil Nadu · INIndian Institute of Management Ranchi · INSt Joseph's University, Bengaluru, India

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Non-communicable diseases such as ischemic heart disease, cancer, diabetes, and chronic respiratory diseases are the leading causes of death worldwide, and are associated with tobacco use. The ultimate goal of health professionals and researchers working to combat smoking's extremely harmful health effects is to prevent smoking initiation. Nearly 5500 new smokers are added each day, for a total of almost 2 million new smokers each year. The COM-B model's primary goal is to determine what needs to be done for a behaviour change to occur. Behaviour modification requires an understanding of the factors that drive behaviour. Aim: The current qualitative study intends to explore the factors affecting tobacco use initiation (TUI) using the COM-B model, given the relevance of investigating the factors affecting TUI and the model. Methods: The present qualitative study has used a directed content analysis approach. Seventeen participants who reported having started any kind of tobacco in the last six months were recruited in the study using a purposive sampling method to understand the factors affecting TUI. The data was collected through interviews, and all of the participants were from the Hyderabad-Karnataka region of Karnataka, India (a state which has been reported as having the highest prevalence of cigarette smoking in India). Results: Directed content analysis revealed six categories: psychological capabilities affecting TUI (lack of knowledge about adverse health effects of tobacco, behavioural control, and poor academic performance), physical capabilities affecting TUI (lack of better physical resilience), physical opportunities favouring TUI (tobacco advertisements, easy access of tobacco products, and favourite star smoke on screen), social opportunities favouring TUI (peer influence, tobacco use by parents, tradition of hospitality, tobacco use as a normal behaviour, and toxic masculinity), automatic motivation causal factors of TUI (affect regulation, risk taking behaviours and tobacco use for pleasure) and reflective motivation causal factors of TUI (perceived benefits of tobacco, risk perception, perceived stress, and compensatory health beliefs). Conclusion: Identifying the factors that influence TUI may help to limit or prevent people from smoking their first cigarette. Given the importance of preventing TUI, the findings of this study indicated the factors that influence TUI, which can be valuable in improving behaviour change processes.

Indexed as

The COM-B model DomainsTobacco use initiationTobacco users

Identifiers

PMID37292260
PMCPMC10245169
OpenAlexW4377018971

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.