ArticleTobacco prevention & cessation2019
The effectiveness of family counselling on reducing exposure to secondhand smoke at home among pregnant women in Iran.
Article in Tobacco prevention & cessation, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.
- Smoking cessation in pregnancy: a systematic review and meta-analysis of vulnerability approaches and expectant father involvement.Public health reviews · 2026Pooled it
- The Effectiveness of a Structured Educational Intervention on Knowledge, Beliefs, and Self-Reported Practices of Pregnant Women Exposed to Thirdhand Smoke: A Randomized Controlled Trial.Brain and behavior · 2026Trial
- Second-hand smoke exposure among school children during COVID-19 in Jeddah.Journal of Taibah University Medical Sciences · 2025Article
- Prenatal passive smoking at home: The experiences of women in Thailand.Belitung nursing journal · 2024Article
- Article
- Prenatal harmful substances: Thai pregnant women's experiences.Belitung nursing journal · 2023Article
- The Effect of Couple's Motivational Interviewing on Exposure to Secondhand Smoke Among Pregnant Women at Home.Journal of family & reproductive health · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionPregnant women are often exposed to secondhand smoke that affects them and their child. Our aim was to determine the effectiveness of family counselling using the BASNEF model on reducing exposure to secondhand smoke at home among pregnant women.
methodsA quasi-experimental study was conducted on 103 pregnant women exposed to secondhand smoke. They were selected using a multi-stage cluster sampling method and allocated into intervention (50 people) and control (53 people) groups. Four family counseling sessions using the BASNEF model were held for the intervention group while the control group received routine care. The outcomes were measured before and at one month after the last session of counselling.
resultsIn the timeframe before the intervention, the number of days in which there was reported exposure to secondhand smoke was 5.08 ± 1.1 in the intervention group, significantly decreasing to 3.5 ± 1.6 after the intervention (p<0.001). No significant change was observed in the control group (p=0.1). Also, the mean scores of all constructs of the BASNEF model increased significantly after the intervention compared to those of the control group (p<0.05).
conclusionsFamily counseling had a positive effect on decreasing the exposure to secondhand smoke at home among a sample of pregnant women. The BASNEF model is useful for implementing educational care programs in these settings.
Indexed as
Identifiers
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Registered trials
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.