In-house created questions.

<div><p>Body image dissatisfaction is consistently highlighted as a precursor for eating disorders, arising from several factors. One factor surrounds social expectations of being thin, which can be emphasised in certain physical activities, like dance. Whilst research is available for body image dissatisfaction among female dancers, literature has neglected the male demographic. The present study investigated seven predictors of body image dissatisfaction within male and female dancers, from a variety of genres. The study employed a non-experimental quantitative method, utilising an independent groups correlational design. The role of clothing practices, body ideal internalisation and sociocultural influences were investigated as predictors for body image dissatisfaction. Data from 180 participants (mean age = 23.7, SD = 7.51) was analysed from an online survey. Hierarchical multiple regression revealed that the model consisting of all predictors significantly accounted for over 60% of variance in body image dissatisfaction scores within all independent groups. The individual contribution of predictors differed between groups, with clothing practice being the only significant predictor in all four groups. Media pressure was a significant predictor within non-dancer groups only. This research highlights the importance of clothing practices, specifically tight-fitting garments within the dance environment and general population. Future research should investigate potential differences in the predictors between each level of dance.</p></div>

Publication Details

Journal
Figshare
Published
2024-11-07
DOI
https://doi.org/10.1371/journal.pone.0313142.s001
Primary Topic
Eating Disorders and Behaviors
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

In-house created questions.

Figshare
Eating Disorders and Behaviors
article

In-house created questions.

article en

Abstract

<div><p>Body image dissatisfaction is consistently highlighted as a precursor for eating disorders, arising from several factors. One factor surrounds social expectations of being thin, which can be emphasised in certain physical activities, like dance. Whilst research is available for body image dissatisfaction among female dancers, literature has neglected the male demographic. The present study investigated seven predictors of body image dissatisfaction within male and female dancers, from a variety of genres. The study employed a non-experimental quantitative method, utilising an independent groups correlational design. The role of clothing practices, body ideal internalisation and sociocultural influences were investigated as predictors for body image dissatisfaction. Data from 180 participants (mean age = 23.7, SD = 7.51) was analysed from an online survey. Hierarchical multiple regression revealed that the model consisting of all predictors significantly accounted for over 60% of variance in body image dissatisfaction scores within all independent groups. The individual contribution of predictors differed between groups, with clothing practice being the only significant predictor in all four groups. Media pressure was a significant predictor within non-dancer groups only. This research highlights the importance of clothing practices, specifically tight-fitting garments within the dance environment and general population. Future research should investigate potential differences in the predictors between each level of dance.</p></div>

Figshare
Gender equality
Openalex Percentile: Top 50%
Eating Disorders and Behaviors
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.