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Neuroticism Magnifies the Detrimental Association between Social Media Addiction Symptoms and Wellbeing in Women, but Not in Men: a three-Way Moderation Model

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Abstract

Addiction symptoms in relation to the use of social networking sites (SNS) can be associated with reduced wellbeing. However, the mechanisms that can control this association have not been fully characterized, despite their relevance to effective treatment of individuals presenting SNS addiction symptoms. In this study we hypothesize that sex and neuroticism, which are important determinants of how people evaluate and respond to addiction symptoms, moderate this association. To examine these assertions, we employed hierarchical linear and logistic regression techniques to analyze data collected with a cross-sectional survey of 215 Israeli college students who use SNS. Results lend support to the hypothesized negative association between SNS addiction symptoms and wellbeing (as well as potentially being at-risk for low mood/ mild depression), and the ideas that (1) this association is augmented by neuroticism, and (2) that the augmentation is stronger for women than for men. They demonstrated that the sexes may differ in their SNS addiction-wellbeing associations: while men had similar addiction symptoms -wellbeing associations across neuroticism levels, women with high levels of neuroticism presented much steeper associations compared to women with low neuroticism. This provides an interesting account of possible “telescoping effect”, the idea that addicted women present a more severe clinical profile compared to men, in the case of technology-“addictions”.

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Funding

The authors report no extramural funding for this project.

Author information

Authors and Affiliations

  1. Department of Psychology, University of Southern California, Los Angeles, CA, USA

    Ofir Turel & Natalie “Tasha” Poppa

  2. Department of Information Systems and Decision Sciences, California State University, Fullerton, 800 N. State College Blvd., Fullerton, CA, 92834, USA

    Ofir Turel

  3. College of Management Academic Studies, Rishon LeZion, Israel

    Oren Gil-Or

Authors
  1. Ofir Turel
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  2. Natalie “Tasha” Poppa
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  3. Oren Gil-Or
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Corresponding author

Correspondence to Ofir Turel.

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Conflict of Interest

The authors have no potential conflict of interest pertaining to this Psychiatric Quarterly submission.

Ethical Approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. This article does not contain any studies with animals performed by any of the authors.

Informed Consent

Informed consent was obtained from all individual participants included in the study.

Appendices

Appendix 1: Scales and their Psychometric Properties

The survey was completed in the Hebrew language. The psychometric properties of the scales are given in Table 2, which also outlines the items in the English language. Table 3 provides the correlations between the constructs.

The wellbeing and neuroticism scales had validated adaptations to Hebrew, which were adapted in this study. The SNS addiction symptoms scale and some of the control variables were translated to Hebrew using a forward-backward translation process with two fluent bilingual researchers. The Hebrew scales were tested for face- and content-validity by presenting them together with the original English scales to a panel of 15 bilingual academicians who use SNS. No changes were made based on their feedback, and the content validity of the scales was affirmed via individual interviews with panel members. All scales (the newly translated and the ones with established translations) were then pilot tested with a sample of 30 Israeli students. They were judged to be reliable (all αs > 0.81) and loaded on the expected latent variables (all loadings >0.6) in confirmatory factor analysis (CFA) models.

SNS Addiction Symptoms

SNS addiction as manifested via addiction symptoms was captured with the Hebrew translation of the 6-item Bergen Facebook Addiction Scale (BFAS, see [10]) using a 1–5 Likert scales (1 = very rarely, and 5 = very often). In this scale, each item captured the frequency of one key core symptom of addiction (salience, tolerance, mood modification, relapse, withdrawal, and conflict). This scale has been shown to work well in various International samples, including in adolescents, students and adults [41], and has been successfully translated to various languages [42]. Recently, a cutoff of 19 was suggested as a differentiator between people at-risk of SNS addiction and those with low or no risk of such addiction [8]. We use the scale here as continuous, i.e., encapsulating the level of addiction-like symptoms, as well as for producing the at-risk vs. no/low risk of SNS addiction classification using the abovementioned cutoff. As a continuous scale, it was consistent and reliable (see Table 2). It also presented good fit to the assumed factor structure in a CFA procedure in AMOS 24 [χ2(9) = 25.3, CFI = 0.94, IFI = 0.95, RMSEA = 0.059 with p-close = 0.34, SRMR = 0.031] and all loadings were over 0.58 and significant at p < 0.001. Hence, it was reasonable to use composite (imputed) scores from the CFA procedure in the regression analysis.

Neuroticism

Neuroticism was captured with three items from the Big Five inventory- short version (BFI-S) [39] as adapted in the Hebrew translation of the full Big Five inventory (https://www.ocf.berkeley.edu/~johnlab/pdfs/BFI-Hebrew.pdf). Items were rated on a 7-point Likert scale (1 = does not apply to me at all, 7 = applies to me perfectly). The scale was consistent and reliable (see Table 2). A CFA procedure in AMOS 24 was estimated together with the other two factors, it demonstrated good fit to the assumed factor structure [χ2(74) = 111.8, CFI = 0.96, IFI = 0.96, RMSEA = 0.052 with p-close = 0.41, SRMR = 0.054]; all loading were over 0.59 and significant (p < 0.001). Hence, a composite score from the CFA analysis was used in the regression models.

Sex

Sex was measured with a direct two-choice question (women coded as 1).

Wellbeing

Wellbeing was captured with the WHO (World Health Organization) five item Wellbeing Index (WHO-5) [40]. This scale had a valid Hebrew version that was taken from the WHO website. People were asked to report on feelings over the last two weeks by using a six-point Likert scale (0 = at no time, 5 = all of the time). The scale was consistent and reliable (see Table 2), and presented good fit indices in a CFA procedure in AMOS 24 [χ2(5) = 12.7, CFI = 0.97, IFI = 0.97, RMSEA = 0.050 with p-close = 0.42, SRMR = 0.025] and all loadings were over 0.57 and significant at p < 0.001. Hence, its composite (imputed) scores from the CFA procedure were used in the regression analysis.

While the scale is meant to measure wellbeing, it has been suggested as a valid tool for initial screening (as a preliminary step before clinical interviews, not instead) for at-risk for depression. Those with scores (sum*4) of less than 50 were suggested to be at-risk for low-mood or mild-moderate depression [43] and those with a score below 28 were proposed to be at-risk for major depression [44]. While such classification is rudimentary, it has been shown to be a good predictor of actual clinical depression, with sensitivity of 93% and specificity of 64% and to do better at preliminarily screening for at-risk of depression compared with PHQ-9 and the General Health Questionnaire [45]. Subsequent studies also showed that WHO-5 is adequate at the detection of depression [46] and apathy [47] in elderly populations.

Demographic, control and descriptive variables

These included age [open ended, continuous quantitative], number of Facebook friends [1–9 Likert Scale, based on Ellison et al. [48], 71 = up to 10 friends, 9 = over 400 friends], frequency of Facebook use [1–6 Likert Scale, based on Turel, Bechara [49], 1 = less than once a month, 6 = over four times per day], time per day on Facebook [1–6 Likert Scale, based on Turel, Serenko [2], 1 = less than 10 min per day, 6 = over three hours per day], and education [1–5 Likert Scale, 1 = elementary school, 6 = doctorate].

Table 2 Scales, sources, descriptive statistics and reliability scores (n = 215) †
Full size table
Table 3 Correlation matrix
Full size table

Appendix 2: Detailed Statistical Procedures

Data were first tested for validity and reliability with multiple indictors: Cronbach alpha, Guttman split-half coefficients, corrected item-total correlations, percent of variance explained by the latent variables, and loadings and fit indices extracted from CFA models in AMOS 24. After establishing sufficient validity and reliability, composite factor scores were generated for all multiple-item scales in AMOS 24. These scores were used in a hierarchical regression model in SPSS 24, with wellbeing as the dependent variable. Because four of the control variables were operationalized as ordinal variables, and even though linear regression is not sensitive to the use of such variables as continuous ones, we tested which treatment is better using guidelines in: https://www3.nd.edu/~rwilliam/xsoc73994/OrdinalIndependent.pdf. Specifically, the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC) indices of models using each control as a continuous variable were contrasted with the same indices of models operationalizing these controls with dummy variables.

After establishing that the operationalization is adequate, variable entry order in the regression model was: (block 1) five control variables (Facebook friends, daily use frequency, daily use time, age and education), (block 2) the key predictor, namely SNS Addiction, (block 3) neuroticism and its interaction with SNS addiction, and (block 4) sex, two two-way interaction terms of sex, and the three way interaction term. In order to avoid distributional assumptions, bootstrapping with 500 re-samples and bias-corrected estimates were employed in the regression analysis. Next, for the linear regression model, analysis of differences between slopes of four groups [low (-1SD) vs. high (+1SD) neuroticism for men and women] was performed using tools in http://www.jeremydawson.co.uk/slopes.htm, which rely on Dawson, Richter [50]. Last, the moderation effects were plotted using the three-way interaction plotting facilities on the same website.

To supplement these analyses and enrich the findings, three additional analyses were performed. First, the binary variable representing the classification of people as at-risk vs. low/no risk of SNS addiction was used as a regressor (dummy variable, instead of continuous addiction symptoms score) in the full model. Given multicollinearity, the addiction classification interaction with neuroticism was excluded. Second, a logistic regression model with the same predictors as in the full model and with the binary classification of at-risk for low mood =1 and not =0 as the outcome variable was fit to the data. Third, a smaller model focusing only on SNS addiction symptoms as the predictor and the binary classification of at-risk for major depression as the outcome was fit to the data. This model was more restrictive in terms of predictors given the small number of subjects who met possible at-risk for major depression criteria.

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Turel, O., Poppa, N.“. & Gil-Or, O. Neuroticism Magnifies the Detrimental Association between Social Media Addiction Symptoms and Wellbeing in Women, but Not in Men: a three-Way Moderation Model. Psychiatr Q 89, 605–619 (2018). https://doi.org/10.1007/s11126-018-9563-x

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