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Predictors of dieting and non-dieting approaches among adults living in Australia

Overview of attention for article published in BMC Public Health, February 2017
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Title
Predictors of dieting and non-dieting approaches among adults living in Australia
Published in
BMC Public Health, February 2017
DOI 10.1186/s12889-017-4131-0
Pubmed ID
Authors

Stuart Leske, Esben Strodl, Xiang-Yu Hou

Abstract

There is a dearth of research comparing why dieting and non-dieting approaches are adopted. A greater understanding of reasons underlying dieting and non-dieting attempts will help to identify target beliefs for interventions to support and motivate adults to attempt whatever approach they are willing and/or able to pursue. We investigated the predictors of dieting and non-dieting approaches in Australian adults using predictors that were identified in a previous qualitative study. We conducted a prospective study, with two waves of data collection occurring 4 weeks apart. At baseline, participants completed a questionnaire assessing constructs drawn from the theory of planned behaviour (attitude, subjective norm, and self-efficacy), past behaviour, non-planning, attributions for dieting failure, weight control beliefs, and dieting and non-dieting intentions. We used path modelling to analyse responses. At baseline, 719 adults (52.2% male) aged between 18 and 76 completed the questionnaire. Four weeks later, 64% of participants (n = 461) reported on their dieting and non-dieting behaviour in the past month. Past behaviour, attitude, subjective norm, and self-identity significantly predicted dieting intentions. Dieting intentions and past behaviour significantly predicted dieting behaviour, while non-planning and self-efficacy did not. The model explained 74.8% of the variance in intention and 52.9% of the variance in behaviour. While most findings were similar for the non-dieting model, subjective norms and self-identity did not predict intention, while self-efficacy and self-identity both predicted non-dieting behaviour directly. The non-dieting model explained 58.2% of the variance in intention and 37.5% of the variance in behaviour. The findings from this study provide support for the application of TPB and identity theory constructs in the context of both dieting and non-dieting behaviour. Self-efficacy and self-identity appear more relevant to non-dieting behaviour than dieting behaviour, while subjective norms was more influential in predicting dieting. Practitioners wishing to encourage either approach in their clients should attempt to modify the constructs that influence each approach.

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Mendeley readers

The data shown below were compiled from readership statistics for 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 77 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 16 21%
Student > Master 15 19%
Student > Ph. D. Student 12 16%
Researcher 7 9%
Student > Doctoral Student 4 5%
Other 8 10%
Unknown 15 19%
Readers by discipline Count As %
Psychology 17 22%
Nursing and Health Professions 11 14%
Medicine and Dentistry 8 10%
Agricultural and Biological Sciences 7 9%
Social Sciences 7 9%
Other 10 13%
Unknown 17 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 February 2017.
All research outputs
#4,941,820
of 9,093,370 outputs
Outputs from BMC Public Health
#5,476
of 7,381 outputs
Outputs of similar age
#149,232
of 255,143 outputs
Outputs of similar age from BMC Public Health
#132
of 172 outputs
Altmetric has tracked 9,093,370 research outputs across all sources so far. This one is in the 27th percentile – i.e., 27% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,381 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.8. This one is in the 17th percentile – i.e., 17% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 255,143 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 172 others from the same source and published within six weeks on either side of this one. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.