Photo-Editing Scale: Development and Validation of a New Self-Report Scale of Photo-Editing Behaviors Among Chinese Females

IF 3 Q1 PSYCHOLOGY, MULTIDISCIPLINARY

Human Behavior and Emerging Technologies Pub Date : 2025-09-15 DOI:10.1155/hbe2/3064810

Jinghao Feng, Simin Xu, Zeguang Wang, Yin Xu

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Abstract

A comprehensive measurement encompassing all photo-editing techniques to assess photo-editing behaviors remains absent. Based on 621 Chinese females, we developed and validated a self-report scale to measure photo-editing behaviors among Chinese females. In Study 1, experts classified photo-editing techniques from mainstream apps into categories based on their functionalities. Initial items for the Photo-Editing Scale (PES), comprising two subscales designed to measure the frequency and extent of participants’ photo-editing behaviors, were developed. The final items of PES were determined via factor analyses. In Study 2, the validity and reliability of both subscales were examined. Findings revealed that each subscale, containing eight items associated with one factor, exhibited satisfactory internal consistency (McDonald^’s omega = 0.91 for Photo-Editing Extent subscale; McDonald^’s omega = 0.85 for Photo-Editing Frequency subscale), test–retest reliability, as well as discriminant, predictive, and convergent validity. The newly developed PES may help us better understand the photo-editing behaviors and their impact on various mental health issues.

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照片编辑行为量表：一种新的中国女性照片编辑行为自我报告量表的编制与验证

一个全面的测量包括所有的照片编辑技术来评估照片编辑行为仍然缺乏。基于621名中国女性，我们开发并验证了一个自我报告量表来衡量中国女性的照片编辑行为。在研究1中，专家们根据功能将主流应用程序中的照片编辑技术分类。照片编辑量表（PES）的初始项目包括两个子量表，旨在衡量参与者的照片编辑行为的频率和程度。PES最终项目通过因子分析确定。在研究2中，对两个分量表的效度和信度进行了检验。结果显示，每个子量表包含八个项目，与一个因素相关，具有令人满意的内部一致性（照片编辑程度子量表的麦当劳ω = 0.91，照片编辑频率子量表的麦当劳ω = 0.85），测试-重测信度，以及判别效度，预测效度和收敛效度。新开发的PES可以帮助我们更好地了解照片编辑行为及其对各种心理健康问题的影响。

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来源期刊

Human Behavior and Emerging Technologies Social Sciences-Social Sciences (all)

CiteScore

17.20

自引率

8.70%

发文量

期刊介绍： Human Behavior and Emerging Technologies is an interdisciplinary journal dedicated to publishing high-impact research that enhances understanding of the complex interactions between diverse human behavior and emerging digital technologies.