Evidence map›Paper›PMID 36424977›Full record

ArticleFrontiers in public health2022

A content analysis of e-cigarette marketing on social media: Findings from the Tobacco Enforcement and Reporting Movement (TERM) in India, Indonesia and Mexico.

Nandita Murukutla, Melina S Magsumbol, Hana Raskin, Sharan Kuganesan, Silvia Dini, Carlos Martinez-Mejia, Rachfiansyah, Benjamin Gonzalez Rubio Aguilar

Abstract read
In one paragraph

Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  4. Tobacco Control Scale (TCS) for Tobacco Control Policy Analysis of India.Asian Pacific journal of cancer prevention : APJCP · 2025
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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

8 authors.

Nandita MurukutlaPolicy Advocacy and Communication Division, Vital Strategies, New York, NY, United States.
Melina S MagsumbolPolicy Advocacy and Communication Division, Vital Strategies, New York, NY, United States.
Hana RaskinPolicy Advocacy and Communication Division, Vital Strategies, New York, NY, United States.
Sharan KuganesanPolicy Advocacy and Communication Division, Vital Strategies, New York, NY, United States.
Silvia DiniPolicy Advocacy and Communication Division, Vital Strategies, New York, NY, United States.
Carlos Martinez-MejiaPolicy Advocacy and Communication Division, Vital Strategies, New York, NY, United States.
RachfiansyahPolicy Advocacy and Communication Division, Vital Strategies, New York, NY, United States.
Benjamin Gonzalez Rubio AguilarPolicy Advocacy and Communication Division, Vital Strategies, New York, NY, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The use of e-cigarettes is proliferating globally, especially among youth and even children. Marketing is a known risk factor for e-cigarette initiation, yet little is known of e-cigarette marketing on social media in low- and middle-income countries. This study compares e-cigarette social media marketing in India, Indonesia, and Mexico, three such countries with different regulatory environments. Methods: Instances of e-cigarette marketing on social media platforms were identified via the Tobacco Enforcement and Reporting Movement (TERM), a digital tobacco marketing monitoring system. Through systematic keyword-based searches, all tobacco marketing posts observed between 15 December 2021 and 16 March 2022 were included in the analysis. The final sample included 1,437 e-cigarette-related posts on Instagram, Facebook, Twitter, YouTube, and TikTok, which were systematically content analyzed by independent coders after inter-reliability (Cohen's Kappa K > 0.79) was established using a theory-derived codebook. The final data is represented in percentages and frequencies for ease of presentation. Results: We observed e-cigarette marketing online in all countries studied, yet there was variation in the volume of marketing and types of accounts identified. In India, where e-cigarettes were comprehensively banned, we identified 90 (6%) posts; in Mexico, where e-cigarettes were partially restricted, 318 (22%) posts were observed; and in Indonesia, where there were no restrictions, 1,029 (72%) posts were observed. In both India and Mexico, marketing originated from retailer accounts (100%), whereas in Indonesia, it was primarily product brand accounts (86%). Across countries, e-cigarettes were mostly marketed directly to sell products (India: 99%, Indonesia: 69% and Mexico: 93%), though the sales channels varied. Product features, including e-liquid flavors, device colors and technical specifications, was the most prominent message framing (India: 86%; Mexico: 73%; Indonesia: 58%). Harm reduction messaging was most popular in Mexico (8%) and was not common in Indonesia (0.3%) or India (0%). Conclusion: Our study provides important insights for tobacco control stakeholders on the evolving nature of e-cigarette marketing in low- and middle-income countries. It underscores the presence of e-cigarette marketing, including in countries where comprehensive regulations exist, and suggests the importance of continuous monitoring to keep up with industry practices and strengthen tobacco control stakeholder efforts to counter them.

Indexed as

Electronic Nicotine Delivery SystemsSocial MediaAdolescentChildHumansIndonesiaMarketingMexicoReproducibility of ResultsTobacco Productsdigital monitoringe-cigarette marketingelectronic nicotine delivery systems (ENDS)FCTCsocial media

Identifiers

PMID36424977
PMCPMC9679495

What OpenQuestion holds

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Registered trials

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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.