Evidence map›Paper›PMID 36465518›Full record

ArticleTobacco induced diseases2022

Effectiveness of an integrated smoking cessation service model on smoking status: A preliminary study.

Kamollabhu Thanomsat, Jintana Yunibhand, Sunida Preechawong

Open access · goldAbstract read
In one paragraph

Article in Tobacco induced diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.4field-weighted citation impact, top 40% 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

0 citing papers in PubMed, 4 citations in OpenAlex.

No citing paper in PubMed yet.

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

3 authors at 1 institution in 1 country.

Kamollabhu ThanomsatFaculty of Nursing, Chulalongkorn University, Bangkok, Thailand.
Jintana YunibhandFaculty of Nursing, Chulalongkorn University, Bangkok, Thailand.
Sunida PreechawongFaculty of Nursing, Chulalongkorn University, Bangkok, Thailand.
Chulalongkorn University · TH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionSmoking cessation has been considered a benefit for smokers. This study aimed to investigate the effect of an integrated smoking cessation service model (ISCSM) on enhancing cessation among smokers in a community setting.

methodsThe participants were 144 smokers allocated into two groups, experimental and control with 72 participants each. The ISCSM comprised two sessions: 1) smoking cessation service design and training smoking cessation capacity for the Community Health Workers (CHWs) by nurses; and 2) integrated smoking cessation service delivery. The CHWs offered brief advice for smoking cessation for smokers through home visits under supervision by nurses, then referred to proactive multisession intensive telephone counselling that was behavioral therapy with follow-up. In contrast, the control group received Thai therapy, which was mouthwash. The 7-day point prevalence abstinence (PPA) was assessed 30 days after the quit date. The probability of quitting between the experimental and control groups was calculated by the risk ratio (RR). Propensity score matching was performed to analyze the treatment effect after balancing the covariate factors.

resultsThe probability of quitting smoking successfully among the participants in the experimental group was 7.5 times higher than the control group (χ

conclusionsThe findings of this study indicate that the ISCSM is an efficient, powerful intervention for enhancing smoking cessation.

Indexed as

integratedsmoking cessationsmoking status

Identifiers

PMID36465518
PMCPMC9677954
OpenAlexW4309754320

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.