Evidence map›Paper›PMID 31362763›Full record

ArticleHealth and quality of life outcomes2019

Attitudes toward and beliefs about obese persons across Hong Kong and Taiwan: wording effects and measurement invariance.

Meng-Che Tsai, Carol Strong, Janet D Latner, Yi-Ching Lin, Amir H Pakpour, Chung-Ying Lin, Shu-Mei Wang

Open access · goldAbstract readValidation Study
In one paragraph

Article in Health and quality of life outcomes, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
5.9field-weighted citation impact, top 4% 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

19 citing papers in PubMed, 34 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Weightism in Asia: A Narrative Review and Implications for Practice.Journal of obesity & metabolic syndrome · 2024
    Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. 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

7 authors at 5 institutions in 5 countries.

Meng-Che TsaiDepartment of Pediatrics, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
Carol StrongDepartment of Public Health, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
Janet D LatnerDepartment of Psychology, University of Hawaii at Manoa, Honolulu, Hawaii, USA.
Yi-Ching LinDepartment of Early Childhood and Family Education, College of Education, National Taipei University of Education, Taipei, Taiwan.
Amir H PakpourSocial Determinants of Health Research Center, Qazvin University of Medical Sciences, Qazvin, Iran.
Chung-Ying LinDepartment of Rehabilitation Sciences, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University, 11 Yuk Choi Rd, Hung Hom, Hong Kong. cylin36933@gmail.com.ORCID http://orcid.org/0000-0002-2129-4242
Shu-Mei WangDepartment of Rehabilitation Sciences, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University, 11 Yuk Choi Rd, Hung Hom, Hong Kong.
Hong Kong Polytechnic University · HKNational Cheng Kung University Hospital · TWNational Taipei University of Education · TWQazvin University of Medical Sciences · IRUniversity of Hawaiʻi at Mānoa · US

Funding

Department of Rehabilitation Sciences, The Hong Kong Polytechnic University startup fund
6 · The paper itself

Abstract

backgroundThe psychosocial consequences of obesity are important but often underrated. The Attitudes Toward Obese Persons (ATOP) and Beliefs About Obese Persons (BAOP) scales used to measure weight-related bias have little psychometric information, especially in East Asian contexts. The objective of this study was to use rigorous statistical methods to demonstrate the psychometric properties of these two instruments in Hong Kong and Taiwanese college students.

methodsA convenience sample of 707 students was recruited from the universities in Hong Kong and Taiwan. Several competing confirmatory factor analyses (CFAs) were conducted to confirm the factorial structure of the ATOP and BAOP. The best fit models for the ATOP and BAOP were chosen for the examination of the measurement invariance across subcultures. We then compared configurable models with or without loading and/or intercept constrained before correlating the latent constructs between the best models for the ATOP and BAOP.

resultsThe comparison in multiple CFAs found that the model with one factor and two correlated-wording-method factors outperformed the other models for both the ATOP and BOAP. However, the internal consistency was suboptimal (ATOP: α = .56 to .80; BTOP: α = .57 to .65) and the measurement invariance was somewhat unsupported among the Hong Kong and Taiwan samples. Moreover, after controlling wording effects, the latent construct of the ATOP was moderately associated with that of BAOP (r = .356; p < .001).

conclusionChinese versions of the ATOP and BAOP can be treated as a unidimensional factor for use in Hong Kong and Taiwan university students. However, further refinements of both instruments may be needed before using them to capture the social attitudes and beliefs toward obesity individuals, which is expected to advance our understanding of weight-related bias in East Asian contexts.

Indexed as

AttitudeAdultCross-Sectional StudiesFactor Analysis, StatisticalFemaleHong KongHumansMaleObesityQuality of LifeSurveys and QuestionnairesTaiwanTranslationsYoung AdultCross-culturePsychometricsWeight biasWeight stigmaYoung adults

Identifiers

PMID31362763
PMCPMC6668070
OpenAlexW2965611583

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.