SRS 2025 Gender Differences in Stigma Internalization and STBs
Gender Differences in Stigma Internalization and Suicidal Thoughts and Behaviors: A Three-Step Theory (3ST) Perspective
Sabrina Yanan Jiang | Macau University of Science and Technology
Yu Li | Hong Kong Baptist University (Beijing Normal)
Hi, I'm Shunyan. Thanks for blowing my Google Blogger!
Content
- Presenter's Information
- Manuscript Abstracts
- Presentation Transcript (will be added after the presentation)
- References & Data
About Shunyan Lyu (Presenter)
ORCID | ResearchGate | Twitter: @Shunyan_Lyu | BlueSky: @shunyanlyu.bsky.social | LinkedIn
Shunyan Lyu is a M.Ed. of Education student at Thompson Rivers University, B.C., Canada. He serves as a Graduate Research Assistant at the School of Education. He is looking forward to continuing his research in a Ph.D. program related to social psychology or educational psychology.
He holds a B.Sc. in Applied Psychology from Hong Kong Baptist University. Following his undergraduate studies, he worked as a Research Assistant for the Applied Psychology Program at HKBU United International College for five months.
Personal Academic Email: barrylyucc@outlook.com | Institutional Email: lyus23@mytru.ca
Shunyan's prior research explored suicide stigma and its influence on suicidal ideation and behaviours.
Currently, his research interests encompass stereotype threats, academic help-seeking, community-engaged research, and universal design of learning within post-secondary settings.
Abstracts
Background
Stigma internalization, the transformative process from perceived stigma to internalized stigma, can contribute to negative mental health outcomes, and even suicidal thoughts and behaviours (STBs). Previous research suggests that gender may influence the impact of stigma internalization on STBs. This study aims to examine gender differences in the relationship between stigma internalization and STBs through the lens of the Three-Step Theory (3ST).
Methods
A total of 1974 Chinese college students (mean age, 22.27 years; 66.13% female) participated in this study by completing self-report measures assessing suicide stigma, help-seeking stigma, hopelessness, unbearable pain, connectedness, and STBs.
Findings
Multi-group SEM analyses revealed significant gender differences in the relationship between stigma internalization and STBs. In the male group, stigma’s effects on STBs were fully mediated by stigma internalization. In contrast, in the female group, stigma’s effects on STBs were partially mediated by stigma internalization.
Conclusions
These findings suggested gender differences in the internalization process of stigma. This study considered how these findings relate to specialized stigma reduction strategies in the context of campus suicide prevention.
Keywords: gender differences; perceived stigma; internalized stigma; stigma reduction; suicide prevention
Research Highlights
- For females, perceived stigma—even if not internalized—can still influence STBs due to stereotype threats, possibly linked to greater interpersonal sensitivity.
- For males, the primary pathway operates through self-stigma internalization, suggesting that suicide interventions for men should directly challenge internal beliefs of weakness and failure.
- Highlights the dual mechanism of stigma impact: both stigma internalization and stereotype threats led by perceived stigma play key roles in suicide vulnerability.
Lay Abstract
Suicide remains a serious concern among young people, and stigma—how society labels and judges those who struggle with mental health—can make things worse. This study looked at nearly 2,000 Chinese college students to understand how stigma might lead to suicidal thoughts and behaviors, and whether this process works differently for males and females.
We found that how stigma affects students depends on gender. For male students, stigma becomes dangerous when it is turned inward. That is, when they believe negative stereotypes about suicide or mental health apply to themselves, it can increase their emotional pain and hopelessness—key factors that may lead to suicidal thoughts or actions. This suggests that breaking down internal feelings of shame and weakness is especially important in helping men.
For female students, we found something different. Even if they don’t fully believe or accept the negative stereotypes, simply being exposed to stigma can still hurt their mental well-being. This may be because women are more sensitive to how they are judged by others, and may experience stress from trying to avoid being seen in a negative light. This type of stress, known as "stereotype threat," can be just as harmful as internalized stigma.
Overall, our findings show that both the internalization of stigma and the fear of judgment from others play major roles in how young people experience suicidal thoughts. But the way these processes work is different for men and women. Understanding these gender-specific pathways can help schools and mental health professionals create better, more personalized strategies for suicide prevention that truly support the unique needs of young people.
Presentation Transcript
[Will be added after the presentation.]
References & Data
P2: Background
Berardelli, I., Rogante, E., Sarubbi, S., Erbuto, D., Cifrodelli, M., Concolato, C., ... & Pompili, M. (2022). Is lethality different between males and females? Clinical and gender differences in inpatient suicide attempters. International Journal of Environmental Research and Public Health, 19(20), 13309. https://doi.org/10.3390/ijerph192013309
Bommersbach, T. J., Rosenheck, R. A., Petrakis, I. L., & Rhee, T. G. (2022). Why are women more likely to attempt suicide than men? Analysis of lifetime suicide attempts among US adults in a nationally representative sample. Journal of Affective Disorders, 311, 157-164. https://doi.org/10.1016/j.jad.2022.05.096
Freeman, A., Mergl, R., Kohls, E., Székely, A., Gusmao, R., Arensman, E., Koburger, N., Hegerl, U., & Rummel-Kluge, C. (2017). A cross-national study on gender differences in suicide intent. BMC Psychiatry, 17, 1-11. https://doi.org/10.1186/s12888-017-1398-8
Li, R., Deng, R., Song, T., Xiao, Y., Wang, Q., Fang, Z., ... & Chen, Y. (2024). Gender-specific factors of suicidal ideation among high school students in Yunnan province, China: A machine learning approach. Journal of Affective Disorders, 364, 157-166. https://doi.org/10.1016/j.jad.2024.08.072
Xu, H., Zhang, W., Wang, X., Yuan, J., Tang, X., Yin, Y., ... & Tian, D. (2015). Prevalence and influence factors of suicidal ideation among females and males in Northwestern urban China: a population-based epidemiological study. BMC Public Health, 15, 1-13. https://doi.org/10.1186/s12889-015-2257-5
P3: Background
Corrigan, P. W., Schmidt, A., Bink, A. B., Nieweglowski, K., Al-Khouja, M. A., Qin, S., & Discont, S. (2017). Changing public stigma with continuum beliefs. Journal of Mental Health, 26(5), 411-418. https://doi.org/10.1080/09638237.2016.1207224
Fox, A. B., Earnshaw, V. A., Taverna, E. C., & Vogt, D. (2018). Conceptualizing and measuring mental illness stigma: The mental illness stigma framework and critical review of measures. Stigma and Health, 3(4), 348-376. https://doi.org/10.1037%2Fsah0000104
Schultner, D. T., Lindström, B. R., Cikara, M., & Amodio, D. M. (2024). Transmission of social bias through observational learning. Science Advances, 10(26), eadk2030. https://doi.org/10.1126/sciadv.adk2030
P4: Background
Livingston, J. D., & Boyd, J. E. (2010). Correlates and consequences of internalized stigma for people living with mental illness: A systematic review and meta-analysis. Social Science & Medicine, 71(12), 2150-2161. https://doi.org/10.1016/j.socscimed.2010.09.030
Pfeiffer, S., & In-Albon, T. (2023). Gender specificity of self-stigma, public stigma, and help-seeking sources of mental disorders in youths. Stigma and Health, 8(1), 124–132. https://doi.org/10.1037/sah0000366
Sattler, K. M., Deane, F. P., Tapsell, L., & Kelly, P. J. (2018). Gender differences in the relationship of weight-based stigmatisation with motivation to exercise and physical activity in overweight individuals. Health Psychology Open, 5(1). https://doi.org/10.1177/2055102918759691
Trompeter, N., Rafferty, L., Dyball, D., McKenzie, A., Greenberg, N., Fear, N. T., & Stevelink, S. A. (2024). Gender differences in structural and attitudinal barriers to mental healthcare in UK Armed Forces personnel and veterans with self-reported mental health problems. Social Psychiatry and Psychiatric Epidemiology, 59(5), 827-837. https://doi.org/10.1007/s00127-023-02567-0
P5: Background
Hall, J. A., & Schmid Mast, M. (2008). Are women always more interpersonally sensitive than men? Impact of goals and content domain. Personality and Social Psychology Bulletin, 34(1), 144-155. https://doi.org/10.1177/0146167207309192
Hunger, J. M., Major, B., Blodorn, A., & Miller, C. T. (2015). Weighed down by stigma: How weight‐based social identity threat contributes to weight gain and poor health. Social and Personality Psychology Compass, 9(6), 255-268. https://doi.org/10.1111/spc3.12172
Holzinger, A., Floris, F., Schomerus, G., Carta, M. G., & Angermeyer, M. C. (2012). Gender differences in public beliefs and attitudes about mental disorder in Western countries: A systematic review of population studies. Epidemiology and Psychiatric Sciences, 21(1), 73–85. https://doi.org/10.1017/S2045796011000552
P6: Theoretical Framework | P7: Current Study
Klonsky, E. D., & May, A. M. (2014). Differentiating suicide attempters from suicide ideators: A critical frontier for suicidology research. Suicide and Life‐Threatening Behavior, 44(1), 1-5. https://doi.org/10.1111/sltb.12068
Klonsky, E. D., Pachkowski, M. C., Shahnaz, A., & May, A. M. (2021). The three-step theory of suicide: Description, evidence, and some useful points of clarification. Preventive Medicine, 152, 106549. https://doi.org/10.1016/j.ypmed.2021.106549
P8: T-tests
t | df | p | |||||
---|---|---|---|---|---|---|---|
PSS | -0.936 | 1582 | 0.350 | ||||
ISS | 0.186 | 1582 | 0.852 | ||||
PHSS | 0.227 | 1340 | 0.821 | ||||
IHSS | -2.356 | 1340 | 0.019 | ||||
UP | 3.772 | 1972 | < .001 | ᵃ | |||
HO | 5.192 | 1972 | < .001 | ||||
CO | 3.604 | 1972 | < .001 | ᵃ | |||
SD | 4.266 | 1972 | < .001 | ᵃ | |||
SA | 3.590 | 1972 | < .001 | ||||
Note. Student's t-test. | |||||||
ᵃ Brown-Forsythe test is significant (p < .05), suggesting a violation of the equal variance assumption |
P9: Correlations
Variable | PSS | ISS | PHSS | IHSS | UP | HO | CO | SD | SA | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
PSS | Pearson's r | — | |||||||||||||||||||
p-value | — | ||||||||||||||||||||
ISS | Pearson's r | 0.789 | — | ||||||||||||||||||
p-value | < .001 | — | |||||||||||||||||||
PHSS | Pearson's r | 0.572 | 0.525 | — | |||||||||||||||||
p-value | < .001 | < .001 | — | ||||||||||||||||||
IHSS | Pearson's r | 0.540 | 0.582 | 0.730 | — | ||||||||||||||||
p-value | < .001 | < .001 | < .001 | — | |||||||||||||||||
UP | Pearson's r | 0.555 | 0.569 | 0.540 | 0.555 | — | |||||||||||||||
p-value | < .001 | < .001 | < .001 | < .001 | — | ||||||||||||||||
HO | Pearson's r | 0.418 | 0.394 | 0.475 | 0.448 | 0.578 | — | ||||||||||||||
p-value | < .001 | < .001 | < .001 | < .001 | < .001 | — | |||||||||||||||
CO | Pearson's r | 0.556 | 0.543 | 0.599 | 0.590 | 0.700 | 0.663 | — | |||||||||||||
p-value | < .001 | < .001 | < .001 | < .001 | < .001 | < .001 | — | ||||||||||||||
SD | Pearson's r | 0.514 | 0.521 | 0.516 | 0.509 | 0.697 | 0.558 | 0.709 | — | ||||||||||||
p-value | < .001 | < .001 | < .001 | < .001 | < .001 | < .001 | < .001 | — | |||||||||||||
SA | Pearson's r | 0.520 | 0.535 | 0.499 | 0.496 | 0.688 | 0.530 | 0.654 | 0.826 | — | |||||||||||
p-value | < .001 | < .001 | < .001 | < .001 | < .001 | < .001 | < .001 | < .001 | — | ||||||||||||
P10:
Measurement model: CFI = .939; IFI = .939; SRMR = .030; RMSEA = .069, 95% CI [.065, .072]
P11:
Measurement model: CFI = .978; IFI = .978; SRMR = .030; RMSEA = .062, 95% CI [.055, .070]
P12:
Measurement model: CFI = .939; IFI = .939; SRMR = .046; RMSEA = .070, 95% CI [.066, .073]
P13:
Measurement model: CFI = .978; IFI = .978; SRMR = .030; RMSEA = .063, 95% CI [.055, .070]
[4th Annual Suicide Research Symposium - April 23rd, 2025]
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