Nonbinary positive body image: Quantitative measurement of intrapersonal and interpersonal variables and a proposed theoretical model
Notice bibliographique
Résumé
Positive body image refers to the ways in which individuals love, respect, and accept their bodies (Tylka & Wood-Barcalow, 2015). While much of the previous research on positive body image still places a focus on its relationship to binary gender identities and expressions, Ogle and colleagues (2023) began to fill this gap by conducting qualitative interviews on positive body image with a small group of nonbinary individuals. Several variables and processes of positive body image emerged from these interviews. The present honors thesis aimed to expand upon the work of Ogle et al. (2023) through quantitative measurement of the variables and processes found to support nonbinary positive body image identified in their study. Specifically, the present study posited a theoretical model for how peer support (LGBTQ community support and body acceptance by others), authentic gender expression (resistance to gender conformity, comfort in dress and appearance, and gender identity acceptance), positive body image factors (body appreciation, functionality appreciation, body image flexibility, appearance congruence, and broad conceptualization of beauty), and actions that support positive body image and overall health (mindful self-care and intuitive eating) connect with each other. The model posited that variables representing peer support would contribute to variables representing authentic gender expression, which would then relate to positive body image factors, which would then be associated with actions supporting positive body image and overall health. To test these hypotheses, 400 nonbinary adult participants from the U.S., U.K., Canada, and Australia were recruited through Prolific Academic to complete a Qualtrics survey, which included the Functional Appreciation Scale (FAS), the Body Appreciation Scale-2 (BAS-2), the Transgender Congruence Scale (TCS), the Broad Conceptualization of Beauty Scale (BCBS), the Body Image Flexibility and Inflexibility Scale (BIFIS), the Comfort and Conformity of Gender Expression Scale (CAGES), the LGBTQ Community Resilience Scale (CRIS), the Body Acceptance by Others Scale-3 (BAOS-2), the Mindful Self-Care Scale (MSCS), the Intuitive Eating Scale-3 (IES-3), and the Genderqueer Identity Scale (GIS). After screening, data from 389 participants were analyzed. Path analysis was then used to examine the model, which was then refined by removing nonsignificant paths and adding paths that were identified as significant through model modification indices. Overall, model fit indices supported the final model. LGBTQ community support was related to all authentic gender expression variables, certain positive body image variables (gender identity acceptance and body appreciation, and body image flexibility) and actions supporting mindful self-care and intuitive eating. To a lesser degree, body acceptance by others was connected to the variables representing authentic gender expression and to a greater extent connected to the variables representing positive body image variables and actions supporting positive body image and overall health. The authentic gender expression variables were associated with many positive body image variables, with gender identity acceptance relating to all positive body image variables. Of the positive body image variables, body image flexibility and body appreciation related to the actions supporting self-care and intuitive eating. These findings overall provide strong support for Ogle et al.’s (2023) initial study conclusions, and meaningfully build upon these conclusions by identifying specific ways in which specific components of positive body image, peer support, and gender identity connect to actions supporting positive body image among nonbinary persons.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».