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Cited by 53Impact of Technology on AdolescentsHealth disparities and outcomesPhysical Activity and Health

Social Media Use and Its Link to Physical Health Indicators

Open access
Lee, David S., Jiang, Tao, Crocker, Jennifer, Way, Baldwin M.·2022·Cyberpsychology, Behavior, and Social Networking
DOI 10.1089/cyber.2021.0188PMC PMC8864418
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Abstract

Social media use has become an integral part of many young adults' daily lives. Although much research has examined how social media use relates to psychological well-being, little is known about how it relates to physical health. To address this knowledge gap, the present research investigated how the amount of social media people use relates to various indices of physical health. Young adults provided a blood sample that was analyzed for C-reactive protein (CRP), a marker of chronic inflammation. They also completed self-report measures of social media use, somatic symptoms, illness-related physician or health center visits, and whether they sought medical care for infection-related illnesses in the last 3 months. Social media use was positively correlated with higher levels of CRP, more somatic symptoms, and more visits to the doctor or health centers for an illness. Although directionally consistent, the correlation with likelihood of seeking medical care for infection-related illnesses was nonsignificant ( p = 0.061). All of these results held after controlling for factors such as sociodemographic information and depressive symptoms. Given the prevalence of social media use in daily life, these findings underscore the need for more research examining how social media use relates to physical health.

AI snapshot

Written from the paper’s full text.

TL;DR

In a college sample, social media use across four platforms was positively associated with higher C-reactive protein (CRP), more somatic symptoms, and more illness-related medical visits, but not significantly with seeking care for infection-related illness (p = 0.061). These associations generally held after controlling for sociodemographic factors, health behaviors, depressive symptoms, and birth control pill use.

Key findings

  • Social media use was associated with elevated CRP: zero-order r = 0.21, p ≤ 0.01; regression βs ranged from 0.17 to 0.20 across models (Model 1 β = 0.20, p = 0.007; Model 4 β = 0.17, p = 0.019).
  • Social media use was associated with more frequent somatic symptoms: β = 0.18, p = 0.006, 95% CI = 0.05–0.30; results remained after adjusting for depressive symptoms (p = 0.01).
  • Social media use was associated with more illness-related visits to a doctor or health center in the past 3 months: β = 0.19, p = 0.005, 95% CI = 0.06–0.32; results remained after adjusting for depressive symptoms (p = 0.007).
  • The link to seeking medical care for a cold, flu, or infection was nonsignificant but directionally consistent: Wald coefficient = 3.50, odds ratio = 1.38, 95% CI = 0.99–1.77, p = 0.061; after depressive symptoms, p = 0.054.

Methods

  • Cross-sectional study of 251 undergraduates at a large Midwestern university (123 females; Mage = 19.40, SD = 2.23; 60.8% White, 27.7% Asian/Pacific Islander, 5.8% African American, 3.5% Hispanic/Latin American, 2.2% Other), conducted October 2018–February 2019. Participants provided finger-stick blood samples for CRP; 28 (11%) opted out and were excluded from CRP analyses, leaving n = 219 for CRP and n = 249 for other analyses.
  • Social media use was averaged across four platforms (Snapchat, Instagram, Twitter, Facebook) using daily-time categories (α = 0.57, M = 2.37, SD = 0.85). Outcomes were CRP from dried blood spots, PHQ-15 somatic symptoms (α = 0.90, M = 2.03, SD = 0.72, log-transformed), illness-related medical visits in the last 3 months (M = 0.79, SD = 1.53, log-transformed), and whether participants sought care for a cold, flu, or infection (n = 80 yes).
  • Analyses used multiple regression with sequential covariates: sociodemographic factors, health behaviors, depressive symptoms, and birth control pill use; logistic regression was used for infection-related care seeking. A power analysis based on f² = 0.09 indicated n = 200 provides 90% power at α = 0.05.

Limitations

  • The paper states the cross-sectional design limits causal or temporal inferences; reverse direction cannot be ruled out, such as people with undermined health using social media more.
  • The paper states effect sizes were small (0.17 < βs < 0.20), so clinical or practical significance is uncertain, and the aggregate amount of social media use does not capture how people use social media.
  • Evident from the text: the social media use composite had low reliability (α = 0.57), and the authors caution that the nonlinear response scale warrants cautious interpretation.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1089/cyber.2021.0188

Cites

57 of 57 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 64 cited sources checked · 0 supported · 0 flagged

  • Findingown data
    § Abstract

    Social media use was positively associated with more visits to the health center or doctor's office for an illness in the past 3 months.

    “Social media use was positively correlated with higher levels of CRP, more somatic symptoms, and more visits to the doctor or health centers for an illness.”
    • Also stated in: § Results · hedged
      “Consistent with our hypothesis, multiple regression analyses indicated that social media use was positively associated with more visits to the health center or doctor's office for an illness in the past 3 months (β = 0.19, p = 0.005, 95 percent CI = 0.06–0.32).”
    Quote in the paperSubstantial claim
  • Findingown data
    § Abstract

    Social media use was positively associated with more frequent somatic symptoms in the past month.

    “Social media use was positively correlated with higher levels of CRP, more somatic symptoms, and more visits to the doctor or health centers for an illness.”
    • Also stated in: § Results · plain
      “Controlling for sociodemographic factors, as predicted, social media use was associated with more frequent somatic symptoms experienced in the past month (β = 0.18, p = 0.006, 95 percent confidence interval [CI] = 0.05–0.30).”
    Quote in the paperSubstantial claim
  • Findingown data
    § Abstract

    Social media use was positively associated with higher levels of C-reactive protein (CRP) in young adults, after controlling for sociodemographic factors, health behaviors, depressive symptoms, and birth control use.

    “Social media use was positively correlated with higher levels of CRP, more somatic symptoms, and more visits to the doctor or health centers for an illness.”
    • Also stated in: § Results · plain
      “Consistent with our hypothesis, social media use was associated with elevated levels of CRP in Model 1 (β = 0.20, p = 0.007), Model 2 (β = 0.17, p = 0.023), Model 3 (β = 0.19, p = 0.011), and Model 4 (β = 0.17, p = 0.019).”
    Quote in the paperSubstantial claim
  • Findingown data
    § Discussion

    This study documented an aggregate association between overall amount of social media use and physical health.

    “this study documented an aggregate association between overall amount of social media use and physical health.”
    Quote in the paperSubstantial claim
  • Findingown data
    § Discussion

    The effect sizes found in this study are small (0.17 < βs < 0.20).

    “the effect sizes found in this study are small (0.17 < βs < 0.20)”
    Quote in the paperSubstantial claim
  • May combine two claims. 12
  • Classified as probably not a substantial claim. 30
  • The quote only partly states this claim. 1

  • May combine two claims.

    Findingown data
    § Abstract

    The association between social media use and seeking medical care for any cold, flu, or infection in the last 3 months was positive but not statistically significant (OR = 1.38, p = 0.061).

    “Although directionally consistent, the correlation with likelihood of seeking medical care for infection-related illnesses was nonsignificant (p = 0.061).”
    • Also stated in: § Results · plain
      “In addition, a logistic regression analysis revealed a nonsignificant, but directionally consistent link between social media use and seeking medical care for any sort of cold, flu, or infection in the last 3 months (Wald coefficient = 3.50, odds ratio = 1.38, 95 percent CI = 0.99–1.77, p = 0.061).”
    Quote in the paperNot a substantial claim

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    Study design and conductreasoning
    § Methods

    Before data collection, the authors decided to exclude participants who reported at the end of the study that they did not take the study seriously at all.

    “To ensure validity of questionnaire responses, at the end of the study, participants were instructed to report the extent to which they took the study seriously (1 = not at all seriously, 5 = very seriously). Before data collection, we decided to exclude participants who responded “not at all seriously.””
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data
    § Methods

    A power analysis based on a small-to-medium effect size (f2 = 0.09) indicated that a sample size of 200 provides 90 percent power (α = 0.05) to detect a significant effect, and the authors aimed to recruit 250 participants.

    “A power analysis using G*Power based on a small-to-medium effect size (f2 = 0.09) between social media use and each of our dependent variables indicated that a sample size of 200 provides 90 percent power (α = 0.05) to detect a significant effect; we intentionally oversampled and aimed to recruit 250 participants to account for participants who opt out of providing blood samples.”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [7] 7. Liu D, Baumeister RF, Yang CC, et al. Digital communication media use and psychological well-being: a meta-analysis. Journal of Computer-Mediated Communication 2019; 24:259–273. [Google Scholar] source

      Not checked in the free run.

    • cites [42] 42. Appel M, Marker C, Gnambs T. Are social media ruining our lives? A review of meta-analytic evidence. Review of General Psychology 2020; 24:60–74. [Google Scholar] source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data
    § Methods

    Twenty-eight participants (11 percent) opted out of providing blood samples and were excluded from CRP analyses but included in other analyses.

    “Twenty-eight (11 percent) opted out; these participants were excluded whenever we conducted analyses with the CRP variable, but were included for other analyses.a”
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    Premisecitation
    § Introduction

    Xue and colleagues (2018) found that excessive use of WeChat was associated with lower self-reported health.

    “For example, Xue and colleagues (2018) found that excessive use of WeChat (the most popular social media platform in China) was associated with lower self-reported health.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Xue and colleagues (2018)

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    Study design and conductcitation
    § Results

    CRP values over 10 μg/mL (n = 5; <2 percent) were excluded because they may indicate the presence of an acute infection.

    “First, individuals with CRP values over 10 μg/mL (n = 5; < 2 percent) were excluded because these values may indicate the presence of an acute infection.49”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [49] 49. Pearson TA, Mensah GA, Alexander RW, et al. Markers of inflammation and cardiovascular disease: application to clinical and public health practice: a statement for healthcare professionals from the centers for disease control and prevention and the American Heart Association. Circulation 2003; 107:499–511. [DOI] [PubMed] [Google Scholar] source

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    Premisecitation
    § Introduction

    The displacement hypothesis posits that time spent on social media may have detrimental effects by displacing activities beneficial to well-being and health, such as sleep, exercise, or face-to-face interactions.

    “This perspective aligns with the displacement hypothesis, which posits that time spent on social media may have detrimental effects by displacing activities that are beneficial to well-being and health—for example, sleep, exercise, or face-to-face interactions.7,26”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [7] 7. Liu D, Baumeister RF, Yang CC, et al. Digital communication media use and psychological well-being: a meta-analysis. Journal of Computer-Mediated Communication 2019; 24:259–273. [Google Scholar] source

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  • Classified as probably not a substantial claim. May combine two claims.

    Premisecitation
    § Introduction

    Stress can undermine health by increasing the number and severity of somatic symptoms, the probability of infection and severity of symptoms following exposure to a cold virus, and systemic inflammation.

    “Stress can undermine health in many ways, for example, by increasing the number and severity of somatic symptoms,31 the probability of infection and the severity of symptoms following exposure to a cold virus,32 and systemic inflammation.33”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites [31] 31. Beutel ME, Wiltink J, Kerahrodi JG, et al. Somatic symptom load in men and women from middle to high age in the Gutenberg Health Study-association with psychosocial and somatic factors. Scientific Reports 2019; 9:1–9. [DOI] [PMC free article] [PubMed] [Google Scholar] source

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    Study design and conductnone given
    § Results

    Two participants who indicated at the end of the study that they did not take the study seriously at all were excluded.

    “Second, two participants who indicated at the end of the study that they “did not take the study seriously at all” were excluded.”
    Quote in the paperNot a substantial claim

  • The quote only partly states this claim.

    Study design and conductown data
    § Results

    Controlling for depressive symptoms did not substantively change the association between social media use and seeking medical care for infection (p = 0.054).

    “Controlling for depressive symptoms did not substantively change the results (p = 0.054).”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductcitation
    § Methods

    The analyses controlled for sociodemographic factors, health behaviors, depressive symptoms, and birth control pill use based on prior work.

    “Based on prior work,12,45,46 we controlled for extraneous factors associated with inflammation.”
    • Also stated in: § Methods · plain
      “We also controlled for depressive symptoms using the Center for Epidemiological Studies Depression Scale (α = 0.93, M = 1.05, SD = 0.69)47 and birth control pill use (0 = no, 1 = yes [n = 58]), as they can influence inflammation levels.45,48”
    Quote in the paperSubstantial claim0 of 4 sources checked
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      Not checked in the free run.

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    Study design and conductown data
    § Methods

    The CRP assay had a coefficient of variation of 2.05 percent and an interassay coefficient of variation of 4.94 percent.

    “The assay coefficient of variation (CV) was 2.05 percent and interassay CV was 4.94 percent (M = 1.73, SD = 4.25).”
    Quote in the paperNot a substantial claim

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    Premisecitation
    § Introduction

    New communication norms and demands arising from hyperconnectivity can lead to communication overload and higher levels of stress.

    “For example, new communication norms and demands arising from hyperconnectivity (e.g., the need to check or respond to social media posts constantly) can lead to communication overload and higher levels of stress.28–30”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites [28] 28. Reinecke L, Aufenanger S, Beutel ME, et al. Digital stress over the life span: the effects of communication load and internet multitasking on perceived stress and psychological health impairments in a German probability sample. Media Psychology 2017; 20:90–115. [Google Scholar] source

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    Premisecitation
    § Introduction

    Elevated levels of CRP are associated with increased risk for chronic diseases, including cardiovascular disease, cancers, and depression.

    “In particular, elevated levels of CRP are associated with increased risk for chronic diseases, including cardiovascular disease, cancers, and depression.36,37”
    Quote in the paperSubstantial claim0 of 2 sources checked
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    Premisecitation
    § Introduction

    Chronic inflammation is a potent driver of disease.

    “Chronic inflammation is a potent driver of disease.35”
    Quote in the paperNot a substantial claim0 of 1 sources checked
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    Premisecitation
    § Introduction

    Americans average about 144 minutes per day on social media, more time than they spend exercising, directly socializing with others, or eating.

    “A recent survey indicates that Americans average about 144 minutes per day on social media1; more time than they spend exercising, directly socializing with others, or eating.2”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [1] 1. Statista. Daily time spent on social networking by internet users worldwide from 2012 to 2019. https://www.statista.com/statistics/433871/daily-social-media-usage-worldwide/ (accessed Jun. 2021).

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    Premisecitation
    § Introduction

    Generation Z (people born in the late 1990s and early 2000s) spend about 6 hours a day texting, online, and on social media and report being online on a "near-constant" basis.

    “Social media usage is particularly high among Generation Z (i.e., people born in the late 1990s and early 2000s) who spend about 6 hours a day texting, online, and on social media3 and report being online on a “near-constant” basis.4”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [3] 3. Twenge JM, Martin GN, Spitzberg BH. Trends in U.S. adolescents' media use, 1976–2016: the rise of digital media, the decline of TV, and the (near) demise of print. Psychology of Popular Media Culture 2018; 8:329–345. [Google Scholar] source

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    Premisecitation
    § Methods

    Emerging work recommends measuring social media use across multiple platforms because people use them for different purposes and in different amounts.

    “Second, emerging work recommends measuring social media use across multiple platforms because people use them for different purposes and in different amounts.43”
    Quote in the paperNot a substantial claim0 of 1 sources checked
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    Premisecitation
    § Introduction

    Hyperconnectivity-the permanent availability of and connectivity to peers, media content, and online services through social media-can increase stress.

    “Second, several scholars contend that hyperconnectivity—the permanent availability of and connectivity to peers, media content, and online services through social media—can increase stress.17,27,28”
    Quote in the paperNot a substantial claim0 of 3 sources checked
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      Not checked in the free run.

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      Not checked in the free run.

  • May combine two claims.

    Premisecitation
    § Introduction

    The sample was college students because it is the age group most actively engaged with social media.

    “We tested this hypothesis in a college student sample because it is the age group most actively engaged with social media.34”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [34] 34. Perrin A, Anderson M. (2018). Share of US adults using social media, including Facebook, is mostly unchanged since 2018. https://www.pewresearch.org/fact-tank/2019/04/10/share-of-u-s-adults-using-social-media-including-facebook-is-mostly-unchanged-since-2018/ (accessed Aug. 2020).

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    Study design and conductown data
    § Methods

    Dropping the menstrual cramps item from the PHQ-15 did not alter the results.

    “Because over half of our sample comprised male participants, we dropped one item that measured menstrual cramps from analyses. Including this item in the analyses did not alter the results.”
    Quote in the paperNot a substantial claim

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    Premisecitation
    § Introduction

    Lee and Way (2021) discovered that among older adults with low self-esteem, social media use predicted higher levels of CRP and IL-6.

    “More recently, Lee and Way (2021) discovered that among older adults with low self-esteem, social media use predicted higher levels of C-reactive protein (CRP) and interleukin (IL)-6—biomarkers of chronic inflammation.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Lee and Way (2021)

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    Premisecitation
    § Introduction

    Lower quality or quantity of sleep is linked to poorer physical health, including elevated risks for cardiovascular disease, hypertension, and early mortality.

    “A substantial body of evidence indicates that lower quality or quantity of sleep is linked to poorer physical health,20–22 including elevated risks for cardiovascular disease,23 hypertension,24 and early mortality.25”
    Quote in the paperSubstantial claim0 of 5 sources checked
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    Study design and conductnone given
    § Results

    Including all excluded participants in the analyses did not substantively change any results.

    “Including all excluded participants in the analyses did not substantively change any results.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation
    § Discussion

    SNS addiction (e.g., preoccupation with social media, excessive use) is associated with lower well-being and depression, which can predict worse physical health.

    “SNS addiction (e.g., preoccupation with social media, excessive use) is associated with lower well-being and depression,14,58 which can predict worse physical health.59”
    Quote in the paperNot a substantial claim0 of 3 sources checked
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    Study design and conductnone given
    § Conclusion

    An average score of 2 on the social media measure can roughly be interpreted as spending about 44 minutes to 2 hours on social media daily, but the nonlinear scale warrants cautious interpretation.

    “While an average score of 2 on this measure can roughly be interpreted as spending about 44 minutes to 2 hours on social media daily, the nonlinear scale used in this measure warrants a cautious interpretation.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation
    § Discussion

    People use social media platforms to have intimate conversations and exchange social support, to participate in groups and organizations, and to cultivate diverse types of relationships.

    “people use social media platforms to have intimate conversations and exchange social support,54 to participate in groups and organizations (e.g., Facebook groups), and to cultivate diverse types of relationships.”
    Quote in the paperNot a substantial claim0 of 3 sources checked
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    • cites [53] 53. Cohen S, Doyle WJ, Skoner DP, et al. Social ties and susceptibility to the common cold. JAMA 1997; 277:1940–1944. [PubMed] [Google Scholar] source

      Not checked in the free run.

    • cites [54] 54. Park J, Lee DS, Shablack H, et al. When perceptions defy reality: the role of actual and perceived Facebook social support in depression. Journal of Affective Disorders 2016; 200:37–44. [DOI] [PubMed] [Google Scholar] source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Study design and conductreasoning
    § Discussion

    We cannot rule out the possibility that people with undermined health may use social media more.

    “we cannot rule out the possibility that people with undermined health may use social media more (e.g., to seek health information or distraction from their dysphoria).”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationcitation
    § Discussion

    Our findings highlight the potential role of social media use in the context of social relationships and physical health research.

    “Broadly, our findings highlight the potential role of social media use in the context of social relationships and physical health research.50,51”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [50] 50. Cohen S. Social relationships and health. American Psychologist 2004; 59:676–684. [DOI] [PubMed] [Google Scholar] source

      Not checked in the free run.

    • cites [51] 51. Uchino BN. Social support and health: a review of physiological processes potentially underlying links to disease outcomes. Journal of Behavioral Medicine 2006; 29:377–387. [DOI] [PubMed] [Google Scholar] source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Premisecitation
    § Discussion

    The ways in which people use social media can influence their well-being.

    “the ways in which they use social media can also influence their well-being,60,61”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [60] 60. Verduyn P, Lee DS, Park J, et al. Passive Facebook usage undermines affective well-being: experimental and longitudinal evidence. Journal of Experimental Psychology: General 2015; 144:480–488. [DOI] [PubMed] [Google Scholar] source

      Not checked in the free run.

    • cites [61] 61. Clark JL, Algoe SB, Green MC. Social network sites and well-being: the role of social connection. Current Directions in Psychological Science 2018; 27:32–37. [Google Scholar] Associated Data This section collects any data citations, data availability statements, or supplementary materials included in this article. source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

    Premisecitation
    § Discussion

    People use social media for a variety of reasons.

    “people use social media for a variety of reasons”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [60] 60. Verduyn P, Lee DS, Park J, et al. Passive Facebook usage undermines affective well-being: experimental and longitudinal evidence. Journal of Experimental Psychology: General 2015; 144:480–488. [DOI] [PubMed] [Google Scholar] source

      Not checked in the free run.

    • cites [61] 61. Clark JL, Algoe SB, Green MC. Social network sites and well-being: the role of social connection. Current Directions in Psychological Science 2018; 27:32–37. [Google Scholar] Associated Data This section collects any data citations, data availability statements, or supplementary materials included in this article. source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Study design and conductreasoning
    § Discussion

    The broad metric of amount of social media use does not provide any insight into how people use social media.

    “this broad metric does not provide any insight into how people use social media.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Premisecitation
    § Discussion

    Traditional measures of social integration and interaction have salubrious health effects.

    “especially given the salubrious health effects typically seen with traditional measures of social integration and interaction (e.g., Social Network Index).53”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [53] 53. Cohen S, Doyle WJ, Skoner DP, et al. Social ties and susceptibility to the common cold. JAMA 1997; 277:1940–1944. [PubMed] [Google Scholar] source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given
    § Discussion

    It is unclear how much participants engaged in problematic social media use in this study.

    “Although it is unclear how much our participants engaged in problematic social media use in this study”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationown data
    § Discussion

    By showing how the overall social media use variable was related to multiple health indicators, this study integrates and extends the nascent research on social media and physical health.

    “By showing how this overall social media use variable was related to multiple health indicators, this study integrates and extends the nascent research on social media and physical health.”
    Quote in the paperNot a substantial claim
35 of 35

  • The paper relies on this without support.

    Little research has examined how social media use is related to physical health.

    “However, little research has examined how social media use is related to physical health.”

  • The paper relies on this without support.

    Somatic symptoms are the leading cause of outpatient medical visits and are associated with substantial functional impairment, disability, and health care usage.

    “We also assessed somatic symptoms (e.g., headaches, chest or back pains), which are the leading cause of outpatient medical visits and associated with substantial functional impairment, disability, and health care usage.”

  • The paper relies on this without support.

    It is unclear to what extent elevated levels of biological markers (e.g., cortisol, IL-6) reflect current health status.

    “Although a few studies have used biological measures, it is unclear to what extent the elevated levels of biological markers (e.g., cortisol, IL-6) reflect current health status.”

  • The paper relies on this without support.

    This is the first study to demonstrate the association of social media use across several platforms with CRP, a chronic inflammatory and health marker, in a college sample.

    “To our knowledge, this is the first study to demonstrate the association of social media use across several platforms with CRP, a chronic inflammatory and health marker, in a college sample.”

  • The paper relies on this without support.

    Prior studies on social media use have primarily relied on self-report well-being measures, which can be vulnerable to demand characteristics.

    “prior studies on social media use have primarily relied on self-report well-being measures, which can be vulnerable to demand characteristics.”

  • The paper relies on this without support.

    Much of what people do on social media involves efforts to initiate, maintain, and develop relationships with others.

    “much of what they do on social media involves efforts to initiate, maintain, and develop relationships with others.”

  • The paper relies on this without support.

    Effect sizes in studies on social media use and psychological well-being typically range from −0.05 < rs < −0.15.

    “comparable to those typically found in studies on social media use and psychological well-being (−0.05 < rs < −0.15).”
7 of 7

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Prior cross-sectional studies have mostly found a positive association between screen time and somatic symptoms in children, adolescents, and young adults.

    “Prior cross-sectional studies have examined the relationship between screen time and somatic symptoms in children, adolescents, and young adults [60–66], with the majority finding a positive association between screen time and somatic symptoms.”

    From Screen time and mental health: a prospective analysis of the Adolescent Brain Cognitive Development (ABCD) Study (2024) · cites this paper as [64]

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Conflicting mean for depressive symptoms

    Minor

    The Methods report a depressive-symptoms mean of 1.05, whereas Table 1 reports 2.29 for the same variable. Both give its standard deviation as 0.69.

1 of 1

Cites

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Flagged first, then by citations

Cited by

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Related

Authors
Lee, D. S., Jiang, T., Crocker, J., & Way, B. M.
Affiliations
  • University at Buffalo, State University of New York (US)
  • The Ohio State University (US)
Corresponding author
Lee, David S.
ORCID
Venue
Cyberpsychology, Behavior, and Social Networking
Publisher
SAGE Publications
Published
2022-02
Volume
25
Issue
2
Pages
87-93
ISSN
  • 2152-2715 (ISSN-L)
  • 2152-2723
DOI
10.1089/cyber.2021.0188
PMC
PMC8864418
OpenAlex
W4206396399
Semantic Scholar
d73572dc2ce19aed18dfffb2b4d97b873c87f485
Cited by
53
References
57
Citations by year
2026: 11 · 2025: 13 · 2024: 14 · 2023: 11 · 2022: 4
FWCI
15.11
Type
journal article
Language
en
Open access
Licence
journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)
Locations
  • Cyberpsychology Behavior and Social Networking (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
  • Social Sciences › Health › Health disparities and outcomes
  • Health Sciences › Medicine › Physiology › Physical Activity and Health
Keywords
social media use, physical health, C-reactive protein, chronic inflammation, somatic symptoms, health care utilization, young adults, depressive symptoms
MeSH terms
Humans, Prevalence, Young Adult, Self Report, Social Media

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-08.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-08.

Statistics and arithmetic are recomputed, not judged.

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