Teenage Body Image Perception, Body-shaping Behavior, and Body Composition With Respect to Use of “Fitspiration”: Exploratory Investigation Study
Notice bibliographique
Résumé
Background: The social media trend #fitspiration aims to positively impact its users' health, but studies have shown detrimental effects, as it mainly involves stereotypical and barely achievable body images and health behaviors. During puberty, adolescents form their identity and body image, making it essential to examine social media's influence on their health. Objective: The exploratory investigation study, part of the mixed methods study in the project FIVE (#Fitspiration Image Verification), sought initial insights into how #fitspiration consumption may affect adolescents' body image perception, dieting, and exercise behaviors. Methods: In total, 86 adolescents (N=310, age range 14-18 years; n=42 females) attending upper secondary schools in Eastern Austria took part in an online questionnaire concerning the use of #fitspiration, body image perception, and body-shaping behaviors (dieting and working out) and bioelectrical impedance measurements to assess body composition. Participants have been classified as #fitspiration users (n=27), nonusers (n=51), and former users (n=8). We compared body image perceptions and body-shaping behaviors of #fitspiration user groups sex-specifically with the fat mass index (FMI) and the fat-free mass index (FFMI). Results: The results indicated that the amount of muscularity was of greater importance for all participants than thinness because, and even though the majority were of normal weight (76/86, 88%) and had an average to high FFMI (62/86, 92%), only 6% (5/86) of all participants thought that their amount of muscle mass was appropriate, while 43% (37/86) of all participants rated their body weight as okay. However, this outcome seemed to be of greater significance for #fitspiration users, especially males. While male participants seemed to be more dissatisfied with their amount of muscularity and worked out more often (female: 24/42, 57%, male: 35/44, 80%), female participants seemed to be more dissatisfied with their body weight and were dieting (female: 10/42, 24%; male: 6/44, 14%). Generally, none of the #fitspiration users (0/27, 0%) answered that her or his amount of muscle mass was okay, although all of them had an average or high FFMI (27/27, 100%). Participants assessed their body weight and body fat more precisely (54/86, 63% matched FMI) than their muscle mass (27/86, 31% matched FFMI). Conclusions: Our findings regarding the body ideals of adolescents are in line with the results of large-scale cross-sectional studies, indicating that they aspire to achieve a toned (and, for females, thin) body. The fact that none of the #fitspiration users were satisfied with their level of muscle mass raises the question of whether #fitspiration may perpetuate this ideal. The line between eating disorders and body dysmorphia might be very thin, especially during puberty. Therefore, our findings can be used to raise awareness of the speculated impact of #fitspiration on adolescents as a source for body ideals and consequently for body image perception and body-shaping behavior.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».