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Understanding and Reducing Appearance Anxiety for Social Media Users: A Study Using Ecological Momentary Assessment and Ecological Momentary Intervention.

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Title: Understanding and Reducing Appearance Anxiety for Social Media Users: A Study Using Ecological Momentary Assessment and Ecological Momentary Intervention.
Authors: Chen, Rong (AUTHOR), Bai, Jin Tong (AUTHOR), Liu, Yue (AUTHOR), Asif, Muhammad (AUTHOR)
Source: Depression & Anxiety (1091-4269). 6/15/2026, Vol. 2026, p1-15. 15p.
Subjects: Ecological momentary assessments (Clinical psychology), Self-compassion, Mental health, Social media, Structural equation modeling, Research protocols, Anxiety
Abstract: Appearance anxiety for social media users (AASMU) is emotional distress linked to social media use (SMU), negatively affecting mental and physical health. However, little is known about the dynamic relationship between AASMU and SMU, and effective interventions. Study 1 used Ecological Momentary Assessment (EMA) with 206 participants completing daily surveys for 20 days. Dynamic structural equation modeling (DSEM) revealed that AASMU tended to persist from 1 day to the next (β = 1.45) and that higher levels of AASMU and SMU often occurred together on the same day (β = 2.57). A higher level of self‐compassion (SC) or a healthier lifestyle moderated this relationship, providing resilience against SMU's negative effects (β = −0.40 or −0.41). Study 2 utilized an ecological momentary intervention (EMI) with 200 participants, where the intervention group read SC statements daily. Results showed a significant reduction in both the mean level (β = −0.05) and intra‐individual variability of AASMU in the intervention group (β = −0.11), suggesting SC‐based EMI is an effective approach to reducing AASMU. [ABSTRACT FROM AUTHOR]
Copyright of Depression & Anxiety (1091-4269) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Label: Title
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  Data: Understanding and Reducing Appearance Anxiety for Social Media Users: A Study Using Ecological Momentary Assessment and Ecological Momentary Intervention.
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  Data: <searchLink fieldCode="AR" term="%22Chen%2C+Rong%22">Chen, Rong</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Bai%2C+Jin+Tong%22">Bai, Jin Tong</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Liu%2C+Yue%22">Liu, Yue</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Asif%2C+Muhammad%22">Asif, Muhammad</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Depression+%26+Anxiety+%281091-4269%29%22">Depression & Anxiety (1091-4269)</searchLink>. 6/15/2026, Vol. 2026, p1-15. 15p.
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  Data: <searchLink fieldCode="DE" term="%22Ecological+momentary+assessments+%28Clinical+psychology%29%22">Ecological momentary assessments (Clinical psychology)</searchLink><br /><searchLink fieldCode="DE" term="%22Self-compassion%22">Self-compassion</searchLink><br /><searchLink fieldCode="DE" term="%22Mental+health%22">Mental health</searchLink><br /><searchLink fieldCode="DE" term="%22Social+media%22">Social media</searchLink><br /><searchLink fieldCode="DE" term="%22Structural+equation+modeling%22">Structural equation modeling</searchLink><br /><searchLink fieldCode="DE" term="%22Research+protocols%22">Research protocols</searchLink><br /><searchLink fieldCode="DE" term="%22Anxiety%22">Anxiety</searchLink>
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  Label: Abstract
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  Data: Appearance anxiety for social media users (AASMU) is emotional distress linked to social media use (SMU), negatively affecting mental and physical health. However, little is known about the dynamic relationship between AASMU and SMU, and effective interventions. Study 1 used Ecological Momentary Assessment (EMA) with 206 participants completing daily surveys for 20 days. Dynamic structural equation modeling (DSEM) revealed that AASMU tended to persist from 1 day to the next (β = 1.45) and that higher levels of AASMU and SMU often occurred together on the same day (β = 2.57). A higher level of self‐compassion (SC) or a healthier lifestyle moderated this relationship, providing resilience against SMU's negative effects (β = −0.40 or −0.41). Study 2 utilized an ecological momentary intervention (EMI) with 200 participants, where the intervention group read SC statements daily. Results showed a significant reduction in both the mean level (β = −0.05) and intra‐individual variability of AASMU in the intervention group (β = −0.11), suggesting SC‐based EMI is an effective approach to reducing AASMU. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Depression & Anxiety (1091-4269) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=194581259
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        Value: 10.1155/da/7212945
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      – Code: eng
        Text: English
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      – SubjectFull: Ecological momentary assessments (Clinical psychology)
        Type: general
      – SubjectFull: Self-compassion
        Type: general
      – SubjectFull: Mental health
        Type: general
      – SubjectFull: Social media
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      – SubjectFull: Structural equation modeling
        Type: general
      – SubjectFull: Research protocols
        Type: general
      – SubjectFull: Anxiety
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      – TitleFull: Understanding and Reducing Appearance Anxiety for Social Media Users: A Study Using Ecological Momentary Assessment and Ecological Momentary Intervention.
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            NameFull: Chen, Rong
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            NameFull: Bai, Jin Tong
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            – D: 15
              M: 06
              Text: 6/15/2026
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              Y: 2026
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