1. Introduction
In recent years, online personality assessments have gained popularity, helping individuals understand themselves and their behaviors, aiding personal growth. Adolescents, in a critical phase of socialization and self-identity, often turn to such tools for self-help when facing psychological challenges [1]. Labeling, a common socialization process, involves defining individuals or groups with specific traits rather than treating them as unique. Self-labeling [2] allows individuals to present themselves differently in various contexts. Over the past five years, discussions on self-labeling's impact on mental health, particularly depression and anxiety, have intensified, though its negative effects remain debated [3].
During the COVID-19 pandemic, the popularity of astrology on social media brought the Barnum effect [4] to the forefront. This study posits that the manifestation and development of the Barnum effect share commonalities with the concept of labeling. Existing research shows that the use of the Myers-Briggs Type Indicator (MBTI) can influence individual mental health through the sequential mediation of the Barnum effect: promoting adolescent self-identity, enhancing subjective well-being, and reducing anxiety and depression [5].
This study aims to explore whether online personality assessments affect the development of adolescent interpersonal relationships and whether the use of online personality assessments can influence mental health (stress, anxiety, and depression) through the mediating role of interpersonal relationships. Additionally, it constructs a relevant questionnaire on labeling phenomena.
2. Study 1
2.1. Participants
Sample 1: Participants were randomly selected based on two criteria: "use of online personality assessments" and "depth of understanding." Four levels were created, with two participants from each level, totaling eight (average age 18±2). These participants helped determine preliminary scale dimensions.
Sample 2: A questionnaire was distributed randomly via Wenjuanxing, collecting 575 responses. Participants included 212 aged below 15, 114 aged 15-18, 153 aged 18-21, and 96 above 21. Of these, 135 were male (23.46%) and 440 were female (76.52%).
2.2. Dimension confirmation
Based on psychometric requirements, the scale items were constructed through two methods: interviews and literature review. The final dimensions were determined by statistical analysis.
2.2.1. Interviews
In the initial stage, one-on-one interviews were conducted to gather attitudes toward online personality assessments. Questions included views on assessments, agreement with results, summarizing personality in 2-3 words, applicability of adjectives, interest in related memes, and self-introduction based on assessment dimensions. Interviews, conducted via voice or text, lasted 45 minutes on average, with participants informed and consenting beforehand.
2.2.2. Literature review
Due to the small number of interviewees, we reviewed recent research on labeling and self-labeling stigmatization. We identified prerequisites for labeling from online personality assessments [6]: (1) experience with tests, (2) understanding results, and (3) accepting interpretations as "accurate." To refine the scale, we referenced Lopez et al.'s Barnum Sensitivity Level Scale and Conscious Behavioral Response Scale [4], and Yim et al.'s [7] self-report method. The scale dimensions were simplified to: (1) actions in specific situations, (2) agreement with assessment interpretations, and (3) belief in possessing certain traits. Based on interviews and literature, the dimensions were preliminarily set as social behavior performance, emotional response tendency, and self-cognitive evaluation.
2.3. Item development and adjustment
Initially, seven items were developed for each dimension, totaling 21 items, using a 5-point Likert scale (1= completely disagree, 5= completely agree). Participants were asked to answer based on their actual situation. The final scale included 10 items for social behavior performance, 9 items for emotional response tendency, and 10 items for self-cognitive evaluation, totaling 29 items.
2.4. Measurement tools
2.4.1. Self-labeling questionnaire
The self-labeling questionnaire developed in this study consists of 29 items, including dimensions of social behavior, emotional response tendency, and self-cognitive evaluation. All items were scored on a 5-point Likert scale, from 1 (completely disagree) to 5 (completely agree). Higher scores indicate stronger self-labeling.
2.4.2. Interpersonal relationship scale
The interpersonal relationship scale used in this study was developed by Zheng Richang et al. in 1999, consisting of 28 items across four dimensions: conversation, friendship, social interaction, and heterosexual interaction. In this study, the Cronbach's α coefficient was 0.912.
2.4.3. Depression-Anxiety-Stress Scale
The Depression-Anxiety-Stress Scale was developed by Lovibond et al. in 1995 and revised by Gong Xiang et al. in 2010. The scale consists of 21 items, including three subscales: depression, anxiety, and stress. In this study, the Cronbach's α coefficient was 0.943, with subscale coefficients of 0.894 (depression), 0.866 (anxiety), and 0.830 (stress).
2.5. Results
2.5.1. Item analysis
First, an item-total correlation analysis was conducted on all valid questionnaires (totaling 218). The results (Table 1) showed that all items were significantly correlated with the total score (P < 0.01), indicating good discrimination of the questionnaire.
Table 1: Labeling scale item-total correlation analysis
Spurious correlation | Net correlation | Spurious correlation | Net correlation | Spurious correlation | Net correlation | |||
1 | 0.477** | 0.422** | 11 | 0.589** | 0.543** | 21 | 0.618** | 0.580** |
2 | 0.551** | 0.499** | 12 | 0.581** | 0.545** | 22 | 0.304** | 0.255** |
3 | 0.511** | 0.450** | 13 | 0.565** | 0.515** | 23 | 0.280** | 0.222** |
4 | 0.701** | 0.667** | 14 | 0.508** | 0.455** | 24 | 0.292** | 0.229** |
5 | 0.481** | 0.431** | 15 | 0.625** | 0.583** | 25 | 0.605** | 0.566** |
6 | 0.366** | 0.304** | 16 | 0.726** | 0.690** | 26 | 0.557** | 0.513** |
7 | 0.445** | 0.380** | 17 | 0.653** | 0.609** | 27 | 0.636** | 0.601** |
8 | 0.386** | 0.325** | 18 | 0.673** | 0.632** | 28 | 0.358** | 0.301** |
9 | 0.593** | 0.552** | 19 | 0.640** | 0.596** | 29 | 0.562** | 0.522** |
10 | 0.591** | 0.540** | 20 | 0.515** | 0.473** |
2.5.2. Reliability analysis
The Cronbach's α coefficient of the self-labeling questionnaire was 0.908, with sub-dimension coefficients of 0.788 (social behavior performance), 0.848 (emotional response tendency), and 0.765 (self-cognitive evaluation), indicating good reliability.
2.5.3. Validity analysis and exploratory factor analysis
An exploratory factor analysis was performed on valid questionnaires. The Bartlett's test (χ²=2322.885, P<0.001) and KMO measure (0.891) confirmed the data's suitability for analysis. Principal component analysis with varimax rotation was applied to the component matrix. Items with dual or no loadings were removed iteratively, resulting in 24 items with a cumulative variance contribution of 47.76%. Four factors emerged: Factor 1 (9 items, "cognitive emotion"), Factor 2 (6 items, "interpersonal reactivity"), Factor 3 (5 items, "social performance"), and Factor 4 (4 items, "cognitive appraisal").
3. Study 2
3.1. Mediation effect analysis
This study aims to explore the impact of self-labeling on individual mental health development. Based on a review of relevant literature and theoretical research, interpersonal relationships were used as the mediating variable, and it was predicted that self-labeling would affect adolescents' mental health (depression, anxiety, and stress) through interpersonal relationships.
3.1.1. Labeling and mental health
In recent years, adolescents have used personality assessments to better understand themselves and others, and to seek psychological counseling and help when necessary [8]. Taking the popular online personality assessment MBTI [9] as an example, recent literature and research show that the use of MBTI can influence individual mental health through the Barnum effect and self-identity, enhancing subjective well-being and reducing anxiety and depression [5].
3.1.2. Interpersonal relationships as the mediating variable
Interpersonal relationships have long been regarded as a type of interaction and behavioral tendency between individuals and others, influenced by different types of objects, and have a significant impact on mental health [10]. This study uses interpersonal relationships as the mediating variable to explore whether self-labeling behavior affects individual mental health (depression, anxiety, and stress) through the mediating effect of interpersonal relationships.
3.1.3. Mediation model construction
In summary, this study uses the four dimensions of self-labeling (cognitive-emotion, interpersonal reactivity, social performance, and cognitive appraisal) as independent variables, interpersonal relationships as the mediating variable, and the three dimensions of mental health (depression, anxiety, and stress) as dependent variables to construct a simple mediation model, as shown in Figure 1 to Figure 4.
Figure 1: Simple mediation model of interpersonal relationships on cognitive emotion and mental health relationships
Figure 2: Simple mediation model of interpersonal relationships on social performance and mental health relationships
Figure 3: Simple mediation model of interpersonal relationships on interpersonal reactivity and mental health relationships
Figure 4: Simple mediation model of interpersonal relationships on cognitive appraisal and mental health relationships
3.2. Results
3.2.1. Correlation analysis
A correlation analysis was conducted between the four dimensions of the self-labeling scale and the interpersonal relationship scale and the three subscales of the Depression-Anxiety-Stress Scale. The results are shown in Table 2.
Table 2: Correlation between self-labeling scale and interpersonal relationship scale and Depression-Anxiety-Stress Scale
Interpersonal Relationship | Depression | Anxiety | Stress | |
cognitive-emotion | 0.177** | 0.091 | 0.060 | 0.120 |
interpersonal reactivity | 0.029 | 0.000 | 0.047 | 0.061 |
social performance | 0.072 | 0.122 | 0.145* | 0.162* |
cognitive appraisal | -0.024 | -0.022 | 0.033 | 0.067 |
Interpersonal Relationship | - | 0.652** | 0.651** | 0.655** |
3.2.2. Simple mediation analysis of interpersonal relationships
The simple mediation model tested the relationships between factors. The "cognitive-emotion" dimension significantly influenced interpersonal relationships [β= 0.185, 95% CI= (0.047, 0.323)] but had no direct effect on depression, anxiety, or stress. Interpersonal relationships significantly impacted depression [β=1.009], anxiety [β=0.927], and stress [β=0.902].
Using the Bootstrap method (5000 times), the "cognitive-emotion" dimension indirectly influenced depression [95% CI= (0.030, 0.347)], anxiety [95%CI= (0.025, 0.317)], and stress [95% CI= (0.020, 0.321)] through interpersonal relationships, showing significant mediation.
Similar analyses for "interpersonal reactivity," "social performance," and "cognitive appraisal" revealed no significant mediation effects.
The same method was applied to the remaining three dimensions: "interpersonal reactivity," "social performance," and "cognitive appraisal." The results are as follows:
• The "interpersonal reactivity" dimension had no significant effect on interpersonal relationships [β= 0.023, 95% CI= (-0.081, 0.127)], depression [β= -0.023, 95% CI= (-0.144, 0.099)], anxiety [β= 0.030, 95% CI= (-0.081, 0.141)], or stress [β=0.045, 95%CI=(-0.064, 0.154)]. Interpersonal relationships significantly influenced depression [β= 1.003, 95% CI= (0.846, 1.160)], anxiety [β= 0.912, 95% CI=(0.769, 1.055)], and stress [β= 0.901, 95% CI=(0.761, 1.041)]. The indirect effects of the "interpersonal reactivity" dimension on depression [95% CI= (-0.073, 0.122)], anxiety [95% CI= (-0.068, 0.111)], and stress [95% CI=(-0.064, 0.111)] through interpersonal relationships were not significant, indicating no mediation effect.
• The "social performance" dimension had no significant effect on interpersonal relationships [β= 0.064, 95% CI= (-0.055, 0.182)], but significantly influenced stress [β= 0.141, 95% CI= (0.019, 0.264)]. It had no significant effect on depression [β= 0.103, 95% CI= (-0.035, 0.242)] or anxiety [β= 0.123, 95% CI=(-0.003, 0.248)]. Interpersonal relationships significantly influenced depression [β= 0.994, 95% CI= (0.837, 1.150)], anxiety [β= 0.903, 95% CI= (0.761, 1.045)], and stress [β= 0.891, 95% CI= (0.753, 1.030)]. The indirect effects of the "social performance" dimension on depression [95% CI= (-0.080, 0.202)], anxiety [95% CI= (-0.071, 0.182)], and stress [95% CI= (-0.072, 0.176)] through interpersonal relationships were not significant, but the direct effect on stress [95% CI= (0.019, 0.264)] was significant, indicating no mediation effect.
• The "cognitive appraisal" dimension had no significant effect on interpersonal relationships [β= -0.024, 95% CI= (-0.161, 0.112)], depression [β= -0.010, 95% CI= (-0.170, 0.150)], anxiety [β= 0.070, 95% CI= (-0.076, 0.215)], or stress [β= 0.115, 95% CI= (-0.027, 0.257)]. Interpersonal relationships significantly influenced depression [β= 1.002, 95% CI= (0.845, 1.159)], anxiety [β= 0.915, 95% CI= (0.772, 1.057)], and stress [β= 0.906, 95% CI= (0.766, 1.045)]. The indirect effects of the "cognitive appraisal" dimension on depression [95% CI= (-0.173, 0.123)], anxiety [95% CI= (-0.160, 0.119)], and stress [95% CI= (-0.152, 0.114)] through interpersonal relationships were not significant, indicating no mediation effect.
In summary, the following effective mediation models were obtained (Figures 5-6):
Figure 5: Simple mediation model of interpersonal relationships on cognitive-emotion and mental health relationships
Figure 6: Simple mediation model of interpersonal relationships on social performance and mental health relationships
4. Conclusion
This study found that interpersonal relationships fully mediate the link between the cognitive-affective aspect of self-labeling and mental health, while partially mediating the relationship between the social performance aspect and mental health. This supports the hypothesis that the cognitive-affective aspect influences interpersonal relationships, while the social performance aspect directly impacts mental health stress levels. Interpersonal relationships significantly mediate the cognitive-affective aspect's effect on mental health, with self-labeling in this area affecting interpersonal relationships, which in turn influence mental health (depression, anxiety, stress). Accepting online personality assessment results may provide psychological benefits through user feedback, impacting emotional processes [11]. Social networks and online memes also shape interpersonal relationships beyond real-life contexts [12]. Additionally, the social performance aspect significantly affects mental health stress, as labels and language influence identity formation [13], shaping attitudes and behaviors. Therefore, individuals should use personality assessments as tools for self-awareness, interpreting results rationally rather than definitively.
Recent research on self-labeling has focused on stigmatization [14], mental health discrimination [15], and cultural differences [16, 17], with limited exploration of self-labeling from online personality assessments. Other studies have analyzed text features or used longitudinal tracking to examine labels' impact on mental health [18, 19]. This study employed a cross-sectional survey, limiting insights into how self-labeling affects interpersonal relationships and mental health over time or at key developmental stages. The survey was conducted during final exams, potentially skewing results due to participants' stress. Future research could use technology to analyze social media posts for deeper insights into user behavior. Additionally, improving the scale's representativeness by adding more items could better explore self-labeling's formation and its effects on interpersonal relationships and mental health.
References
[1]. Rickwood, D. J., Deane, F. P., and Wilson, C. J. (2007). When and how do young people seek professional help for mental health problems? Med. J. Aust. 187, pp.35–39.
[2]. Moses, Tally. 2009. Self-Labeling and Its Effects among Adolescents Diagnosed with Mental Disorders. Social Science & Medicine, 68(3):570–78.
[3]. Harari, L., Oselin, S. S., & Link, B. G. (2023). The Power of Self-Labels: Examining Self-Esteem Consequences for Youth with Mental Health Problems. Journal of Health and Social Behavior, 64(4), 578-592.
[4]. Lopez, K. R. B., Gaticales, N. P., Provido, A. V. C., Santelices, S. M. B., and Arcinas, M. M. (2021). Social contagion of astrology in the social media amid COVID-19 pandemic.
[5]. Hua, J., & Zhou, Y.X. (2023). Personality assessment usage and mental health among Chinese adolescents: A sequential mediation model of the Barnum effect and ego identity. Frontiers in Psychology, 14.
[6]. Defoe, I. N., Rap, S. E., & Romer, D. (2022). Adolescents’ own views on their risk behaviors, and the potential effects of being labeled as risk-takers: A commentary and review. Frontiers in Psychology, 13.
[7]. Yim, O., & Kang, S. K. (2024). One Label Doesn’t Fit All: Self-Labeling Practices Within the Chinese Immigrant Community in Canada. American Behavioral Scientist.
[8]. Das, A., Sharma, M. K., Kashyap, H., and Gupta, S. (2022). Fixating on the future: an overview of increased astrology use. Int. J. Soc. Psychiatry 68, 925–932.
[9]. Myers, I. B., McCaulley, M. H., et al. (1985). Manual: A Guide to the Development and Use of the Myers-Briggs Type Indicator. California: Consulting Psychologists Press.
[10]. Zheng, M., Guo, X., Chen, Z., Deng, J., & Hu, M. (2023). Association between interpersonal relations and anxiety, depression symptoms, and suicidal ideation among middle school students. Frontiers in Public Health, 11.
[11]. Grieve, R., March, E., & Watkinson, J. (2020). Inauthentic self-presentation on Facebook as a function of vulnerable narcissism and lower self-esteem. Computers in Human Behavior, 102, 144-150.
[12]. Molly Buchanan& Marvin D. Krohn. (2018). Does it matter if those who matter don’t mind?Effects of gang versus delinquent peer group membership on labeling processes.
[13]. Mousavi, S. B., Lecic-Tosevski, D., et al. (2020). To be able, or disable, that is the question: A critical discussion on how language affects the stigma and self-determination in people with parability. International Journal of Social Psychiatry, 66(5), 424-430.
[14]. Joelle Pasman. (2011) The Consequences of Labeling Mental Illnesses on the Self-concept: A Review of the Literature and Future Directions. Social Cosmos – URN:NBN:NL:UI:10-1-101264.
[15]. Time to Change. 2021. “Time to Change: Let’s End Mental Health Discrimination.” https://www.timeto-change.org.uk.
[16]. Grover, S., Shouan, A., & Sahoo, S. (2020). Labels used for persons with severe mental illness and their stigma experience in North India. Asian Journal of Psychiatry, 48.
[17]. Siegel, J. A., & Calogero, R. M. (2021). Measurement of Feminist Identity and Attitudes Over the Past Half Century: A Critical Review and Call for Further Research. Sex Roles, 85(5-6), 248-270.
[18]. Dubreucq, J., Plasse, J., & Franck, N. (2021). Self-stigma in Serious Mental Illness: A Systematic Review of Frequency, Correlates, and Consequences. Schizophrenia Bulletin, 47(5), 1261-1287.
[19]. Horsfield, P., Stolzenburg, S., et al. (2019). Self-labeling as having a mental or physical illness: the effects of stigma and implications for help-seeking. Social Psychiatry and Psychiatric Epidemiology, 55(7), 907-916.
Cite this article
Hu,X. (2025). Adolescent Online Personality Labeling and Mental Health: The Mediating Effect of Interpersonal Relationships. Lecture Notes in Education Psychology and Public Media,86,94-101.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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References
[1]. Rickwood, D. J., Deane, F. P., and Wilson, C. J. (2007). When and how do young people seek professional help for mental health problems? Med. J. Aust. 187, pp.35–39.
[2]. Moses, Tally. 2009. Self-Labeling and Its Effects among Adolescents Diagnosed with Mental Disorders. Social Science & Medicine, 68(3):570–78.
[3]. Harari, L., Oselin, S. S., & Link, B. G. (2023). The Power of Self-Labels: Examining Self-Esteem Consequences for Youth with Mental Health Problems. Journal of Health and Social Behavior, 64(4), 578-592.
[4]. Lopez, K. R. B., Gaticales, N. P., Provido, A. V. C., Santelices, S. M. B., and Arcinas, M. M. (2021). Social contagion of astrology in the social media amid COVID-19 pandemic.
[5]. Hua, J., & Zhou, Y.X. (2023). Personality assessment usage and mental health among Chinese adolescents: A sequential mediation model of the Barnum effect and ego identity. Frontiers in Psychology, 14.
[6]. Defoe, I. N., Rap, S. E., & Romer, D. (2022). Adolescents’ own views on their risk behaviors, and the potential effects of being labeled as risk-takers: A commentary and review. Frontiers in Psychology, 13.
[7]. Yim, O., & Kang, S. K. (2024). One Label Doesn’t Fit All: Self-Labeling Practices Within the Chinese Immigrant Community in Canada. American Behavioral Scientist.
[8]. Das, A., Sharma, M. K., Kashyap, H., and Gupta, S. (2022). Fixating on the future: an overview of increased astrology use. Int. J. Soc. Psychiatry 68, 925–932.
[9]. Myers, I. B., McCaulley, M. H., et al. (1985). Manual: A Guide to the Development and Use of the Myers-Briggs Type Indicator. California: Consulting Psychologists Press.
[10]. Zheng, M., Guo, X., Chen, Z., Deng, J., & Hu, M. (2023). Association between interpersonal relations and anxiety, depression symptoms, and suicidal ideation among middle school students. Frontiers in Public Health, 11.
[11]. Grieve, R., March, E., & Watkinson, J. (2020). Inauthentic self-presentation on Facebook as a function of vulnerable narcissism and lower self-esteem. Computers in Human Behavior, 102, 144-150.
[12]. Molly Buchanan& Marvin D. Krohn. (2018). Does it matter if those who matter don’t mind?Effects of gang versus delinquent peer group membership on labeling processes.
[13]. Mousavi, S. B., Lecic-Tosevski, D., et al. (2020). To be able, or disable, that is the question: A critical discussion on how language affects the stigma and self-determination in people with parability. International Journal of Social Psychiatry, 66(5), 424-430.
[14]. Joelle Pasman. (2011) The Consequences of Labeling Mental Illnesses on the Self-concept: A Review of the Literature and Future Directions. Social Cosmos – URN:NBN:NL:UI:10-1-101264.
[15]. Time to Change. 2021. “Time to Change: Let’s End Mental Health Discrimination.” https://www.timeto-change.org.uk.
[16]. Grover, S., Shouan, A., & Sahoo, S. (2020). Labels used for persons with severe mental illness and their stigma experience in North India. Asian Journal of Psychiatry, 48.
[17]. Siegel, J. A., & Calogero, R. M. (2021). Measurement of Feminist Identity and Attitudes Over the Past Half Century: A Critical Review and Call for Further Research. Sex Roles, 85(5-6), 248-270.
[18]. Dubreucq, J., Plasse, J., & Franck, N. (2021). Self-stigma in Serious Mental Illness: A Systematic Review of Frequency, Correlates, and Consequences. Schizophrenia Bulletin, 47(5), 1261-1287.
[19]. Horsfield, P., Stolzenburg, S., et al. (2019). Self-labeling as having a mental or physical illness: the effects of stigma and implications for help-seeking. Social Psychiatry and Psychiatric Epidemiology, 55(7), 907-916.