Evidence map›Paper›PMID 39724203›Full record

ArticlePloS one2024

How does habit strength affect reactions to warning labels? evidence from Chinese consumers' choices of carbonated beverages.

Yulian Ding, Yue Yang, Yangyang Sun, Kevin Chen, Lianfeng Hu

Abstract read
In one paragraph

Article in PloS one, 2024. 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
–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

0 citing papers in PubMed.

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

5 authors.

Yulian DingInstitute of Western China Economic Research, Southwestern University of Finance and Economics, Chengdu, China.ORCID 0000-0002-4553-3383
Yue YangInstitute of Western China Economic Research, Southwestern University of Finance and Economics, Chengdu, China.
Yangyang SunZhejiang Province Key Think Tank: Institute of Ecological Civilization, Zhejiang A&F University, Hangzhou, China.ORCID 0000-0003-0742-1417
Kevin ChenCenter for Agricultural and Rural Development, Zhejiang University, Hangzhou, China.
Lianfeng HuIndustry Planning Division, Chengdu Municipal Bureau of Economic and Information Technology, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Effectively regulating the excessive consumption of sugar-sweetened beverages (SSBs) has been an important task for public health authorities around the world. The rapid increase in SSB consumption in China necessitates robust regulations. This study employed a choice experiment to simulate the market scenario in which a text warning label was presented on SSBs. We draw a sample of 1200 participants from five major cities across China to analyze the warning label's effectiveness in reducing urban consumers' purchases of SSBs, with a particular emphasis on how an individual's habit strength affects their reaction to the warning label. Our analysis unveiled varying levels of habit strength among respondents: 35.33% showed weak habits, 56.25% displayed moderate habits, and 8.42% demonstrated strong habits. The random parameters logit model results showed a significant overall decrease in SSB purchases when a warning label was present, indicated by a significant negative coefficient associated with the label. However, when examining the impact of warning labels across different habit strengths, a significant effect was observed only in the moderate habit group. Furthermore, within this group, the warning label was more effective for those with correct health knowledge and who were not overweight or obese.

Indexed as

Carbonated BeveragesChoice BehaviorConsumer BehaviorFood LabelingAdultChinaEast Asian PeopleFemaleHabitsHumansMaleMiddle AgedProduct LabelingSugar-Sweetened BeveragesYoung Adult

Identifiers

PMID39724203
PMCPMC11671022

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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.