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. 2026 Jun 17;32(3):e70156. doi: 10.1111/ijn.70156

Uncovering Hidden Patterns of Stigma Amongst Older Men With Urinary Incontinence: A Latent Profile Analysis

ShiTing Wang 1, YuXuan Chen 2, HaoChong He 3,4, JianYou Lu 4,5,✉
PMCID: PMC13276010  PMID: 42310687

ABSTRACT

Background

Urinary incontinence (UI) stigma significantly impacts older men's mental well‐being, yet individual experiences vary. Current research frequently overlooks the heterogeneity of these stigma experiences. Addressing this gap, this study identifies stigma‐influencing factors and uncovers distinct subgroups to inform targeted psychological strategies.

Methods

A cross‐sectional study conducted from November 2023 to February 2024 included a convenience sample of 243 older men with urinary incontinence from two hospitals in Guangdong, China. Data were collected via a demographic questionnaire and the Stigma Scale for Chronic Illness. Latent profile analysis identified distinct stigma subgroups. Furthermore, Pearson correlation and multiple linear regression were utilized to evaluate demographic and clinical differences across subgroups and identify influencing factors.

Results

Education, UI severity and type and water/tea intake significantly influenced stigma (p < 0.05). LPA revealed the following four subgroups: (1) ‘High Self‐Stigma & High Perceived Stigma’ (34.4%); (2) ‘Internal‐Sensitive & External‐Resilient’ (40.2%); (3) ‘Moderate Stigma’ (15.0%); and (4) ‘Low Stigma’ (10.4%). Demographic and clinical characteristics differed significantly across these profiles.

Conclusion

Our findings suggest that older men with UI may exhibit four distinct stigma profiles. Recognizing these patterns could inform customized psychological support, potentially advancing a precision health approach aimed at improving care efficacy and quality of life.

Summary

What Is Already Known About This Topic?

  • Urinary incontinence is prevalent in older men and carries significant stigma, which impedes help‐seeking and reduces health‐related quality of life.

  • Current stigma assessments often treat the population as homogeneous, potentially masking subgroup differences.

  • Although variable stigma experiences among women with urinary incontinence are well‐documented, this heterogeneity is still underexplored in men.

What This Paper Adds:

  • Provides a person‐centred, heterogeneity‐informed perspective on stigma, moving beyond isolated risk factors

  • This study successfully identified four distinct stigma profiles, revealing previously unclassified heterogeneity in this population.

  • The four profiles exhibited significantly different clinical and demographic characteristics, providing precise targets for individualized psychological intervention.

The Implications of This Paper:

  • This study underscores the critical need to understand the latent profiles of urinary incontinence stigma to improve quality of life and intervention efficacy.

  • Future interventions must account for the key factors and subgroup differences identified.

  • Offers an empirical basis for developing stratified and tailored psychosocial interventions for this population

1. Introduction

Urinary incontinence (UI) has emerged as a significant public health issue that adversely affects the health‐related quality of life (HRQoL) of older men. Globally, the condition is estimated to affect approximately 15%–35% of men aged 65 and older (Milutinović et al. 2025). Beyond physical discomfort, UI is associated with a considerable psychosocial burden—stigma has been identified as a key factor that hinders help‐seeking behaviour and diminishes HRQoL (Yang et al. 2023; Stites et al. 2022). As Pisano et al. (2020) highlighted, men often delay seeking medical care due to ‘misconceptions about masculinity,’ resulting in more advanced disease stages at the time of clinical presentation. Further studies report that stigma may not only exacerbate UI symptoms and reduce quality of life but also contribute to social withdrawal, depression and anxiety (Wang et al. 2014; Li and Wang 2025). In addition, research by Drennan et al. (2011) underscores that incontinence management substantially increases the caregiving burden. Family caregivers frequently identify UI as more challenging to manage than behavioural symptoms and rank it among the most difficult aspects of home‐based care.

Given the serious consequences of stigma, early identification and intervention for men with urinary incontinence are crucial for improving clinical outcomes. However, current assessment approaches for stigma in this population primarily rely on interviews or total score strategies (Southall et al. 2017; Green 2024), which may overlook the heterogeneous nature of this group. Such homogeneous assessment methods are likely inadequate for fully capturing the diverse manifestations of stigma, potentially obscuring critical subgroup differences and thereby limiting the effectiveness and precision of subsequent interventions.

Latent profile analysis (LPA) has emerged as a person‐centred analytical approach that provides a robust framework for investigating heterogeneity within complex psychosocial constructs (Huang et al. 2025). Unlike traditional variable‐centred methods, LPA identifies latent, qualitative subgroups based on multiple observed indicators, thereby offering a more accurate representation of the natural classification structure within populations. Evidence suggests that distinct subtypes of illness‐related stigma exist among older women with UI, necessitating tailored intervention strategies for different subgroups (Wang et al. 2025; J. H. Wu, Wu, et al. 2025). It is hypothesized that distinct subtypes of stigma, characterized by varying psychosocial profiles, also exist among older men with UI. Furthermore, the experience and expression of stigma in this population are shaped by a complex interplay of gender‐specific social norms, psychological coping styles and health‐related behaviours (Yu et al. 2024; Bai et al. 2017).

Therefore, this study aims to identify distinct subtypes of illness‐related stigma among older men with UI by applying LPA. This approach transcends isolated examinations of risk factors, thereby providing a novel perspective for elucidating the complex psychosocial structure of UI‐related stigma. The findings are anticipated to provide an empirical foundation for developing stratified, precision psychosocial interventions in the future.

2. Methods

2.1. Study Design

This descriptive cross‐sectional study was conducted in accordance with the STROBE guidelines.

2.2. Settings and Samples

This study recruited participants through a three‐stage random sampling process to ensure representativeness. First, two hospitals were randomly selected from five tertiary hospitals in Guangdong, China between November 2023 and February 2024, using a random number table. Next, wards were randomly chosen from the urology and geriatrics departments of these hospitals. Finally, all eligible male inpatients aged 60 or older in the selected wards were screened and systematically enrolled based on a predetermined random sequence.

Eligibility criteria included the following: (1) males aged 60 years or older; (2) clinical diagnosis of urinary incontinence confirmed by a physician according to International Continence Society criteria (Abrams et al. 2003); and (3) cognitive competence with adequate communication abilities to complete questionnaires independently or with minimal assistance. The enrolment procedure is detailed in Figure 1. Initial screening identified 478 potential participants, of whom 248 met the inclusion criteria and completed the questionnaires. After excluding incomplete responses, 243 participants provided valid data for final analysis.

FIGURE 1.

FIGURE 1

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Participants screening flowchart.

2.3. Power Analysis and Sample Size Calculation

The sample size calculation was based on the objective of estimating the prevalence of stigma among older men with UI in the study setting. A two‐tailed test was used with a significance level (α) of 0.05, an anticipated standard deviation of 30 and a margin of error of 5. Using PASS 15 software (NCSS, LLC 2026) for sample size calculation yielded a minimum required sample of 139 participants. Accounting for an anticipated 20% dropout rate, a minimum of 170 participants was required. Ultimately, 243 eligible patients were enrolled in the study.

2.4. Instruments

2.4.1. Sociodemographic and Clinical Characteristics

A structured questionnaire was developed based on a comprehensive review of relevant literature to collect data on sociodemographic and clinical characteristics (Lu et al. 2022; He et al. 2024). Sociodemographic variables included age, education level, income level and marital status. Clinical variables comprised obesity (defined as BMI > 30 kg/m2), history of constipation (frequency) and the presence of comorbidities including stroke, diabetes, coronary heart disease, prostatic hyperplasia and hypertrophy and hypertension. Health behaviours such as water intake, tea consumption, smoking, drinking and spicy food flavour were also documented. In addition, UI‐specific characteristics, including UI type, UI severity and frequency of micturition, were systematically recorded.

2.4.2. Stigma Assessment

The level of stigma was assessed using the Stigma Scale for Chronic Illness (SSCI), originally developed by Rao et al. (2009). This scale is grounded in the Patient‐Reported Outcomes Measurement Information System (PROMIS) framework and is designed to measure stigma across various chronic conditions. It comprises 24 items categorized into two subscales: self‐stigma (13 items) and perceived stigma (11 items). Responses are recorded on a 5‐point Likert scale ranging from 1 (never) to 5 (always). Total scores range from 24 to 120, with higher scores indicating higher levels of stigma. In this study, we used the Chinese version of the SSCI, adapted by Deng et al. (2017). This version has demonstrated excellent reliability and validity in previous studies, with a reported Cronbach's α coefficient of 0.95 (Deng et al. 2017). The scale‐level content validity index (S‐CVI) was 0.932, and the item‐level content validity indices (I‐CVI) ranged from 0.800 to 1.000 (Deng et al. 2017).

2.4.3. Incontinence Severity Index

UI severity was assessed using the Incontinence Severity Index (ISI), an epidemiological instrument introduced by Sandvik and colleagues (Sandvik et al. 2000). This index consists of two core items: (1) frequency of urinary leakage, with responses ranging from ‘less than once a month’ to ‘every day and/or night,’ and (2) volume of urine loss per episode, rated as ‘drops,’ ‘small splashes,’ or ‘more.’ A composite score is derived by multiplying the numerical values assigned to the responses of both questions. Based on established cutoffs, severity was classified into the following four levels: mild (scores 1–2), moderate (3–6), severe (7–9) and extremely severe (10–12). The ISI underwent a standard forward‐backward translation process to ensure cross‐cultural validity (Wild et al. 2005). This involved independent forward translations by two medical experts, synthesis, back‐translation by an independent bilingual translator and final review by an expert committee. The Chinese version demonstrated acceptable internal consistency in the current study (Cronbach's α = 0.62).

2.5. Data Collection

Prior to data collection, the study objectives and procedures were explained to all potential participants, and written informed consent was obtained. Each participant was assigned a unique identifier to anonymize the data. To minimize participant stress and potential bias, the principal investigator remained blinded to individual participation status throughout the study. Questionnaires were administered in paper‐and‐pencil format. For participants with limited literacy, researchers read each item aloud and recorded responses accordingly. Those who agreed to participate submitted completed questionnaires along with signed consent forms, while individuals who declined were asked to return blank documents. To ensure data quality, a validation protocol was implemented. This included a trap question to identify random responding. Questionnaires were excluded if the completion time was less than 5 min or exceeded 30 min or if consistent response patterns were observed across all items. All collected data underwent double‐entry verification before being transferred to statistical software.

2.6. Statistical Analysis

Data analysis was performed using IBM SPSS Statistics (Version 26.0) for general statistical testing and Mplus (Version 8.3) for latent variable modelling. The analytical approach encompassed multiple stages, beginning with univariate analyses to identify variables associated with total stigma scores using independent t‐tests, one‐way ANOVA and chi‐square tests. Variables demonstrating significant associations (p < 0.05) were retained for subsequent modelling. To address potential confounding, a directed acyclic graph (DAG) was constructed using DAGitty software (Textor et al. 2011), informed by existing literature (Lu et al. 2022; He et al. 2024) and univariate results. This framework identified the minimal sufficient adjustment set for multivariable analysis (Figure 2). The association between key predictors (education level, UI type, UI severity, water intake and tea consumption) and total stigma scores was examined through hierarchical multivariable linear regression. Three sequential models were specified: an unadjusted model (Model 1), a model adjusting for demographic and clinical factors (Model 2: age, income level and obesity) and a fully adjusted model incorporating additional clinical and behavioural factors (Model 3: hypertension, frequency of micturition, drinking, spicy food flavour, coronary heart disease, history of constipation, smoking and stroke).

FIGURE 2.

FIGURE 2

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Directed acyclic graph of stigma in participants.

Latent profile analysis (LPA) was implemented in Mplus to identify distinct stigma subgroups based on SSCI responses. Models with increasing profile numbers were evaluated using multiple fit indices: Akaike information criterion (AIC), Bayesian information criterion (BIC), sample‐size adjusted BIC (aBIC), entropy, Lo–Mendell–Rubin adjusted likelihood ratio test (LMR‐A‐LRT) and bootstrap likelihood ratio test (BLRT) (Robertson and Kaptein 2016; Burnham and Anderson 2004). Model selection considered statistical fit, theoretical interpretability and parsimony (Lo et al. 2001). Cross‐group comparisons among the identified latent profiles employed ANOVA/t‐tests for continuous variables and chi‐square tests for categorical variables, with Pearson correlation assessing bivariate relationships (Stull 2013). A two‐sided p value < 0.05 defined statistical significance throughout the analysis.

2.6.1. Ethical Considerations

The study adhered to the ethical principles outlined in the Declaration of Helsinki and received approval from The Ethics Committee of the First Affiliated Hospital of Guangdong Pharmaceutical University (2023‐11T50). All participants were fully informed about the study’s purpose, procedures and their rights, including anonymity and confidentiality of responses, voluntary participation and the right to withdraw at any time without penalty. Written informed consent was obtained from all participants prior to their involvement.

3. Results

3.1. Participant Characteristics

The mean scores for the total stigma scale, self‐stigma subscale and perceived stigma subscale were 83.82 ± 12.27, 48.60 ± 7.12 and 35.23 ± 6.12, respectively. A total of 243 older male participants were included in this study, with a mean age of 75.87 ± 8.63 years. The detailed sociodemographic and clinical characteristics of the participants are summarized in Table 1. Statistically significant differences (p < 0.05) were observed across groups defined by educational level, water intake, smoking status, alcohol use, presence of diabetes and UI‐related characteristics (type, severity and frequency). Furthermore, significant differences in total stigma and perceived stigma scores were associated with educational level. Similarly, significant differences in all three stigma scores (total, self and perceived) were associated with income level.

TABLE 1.

Participants with different characteristics univariate analysis of SSCI.

Variable Classification Number (%) Total stigma (x ± s) Self‐stigma (x ± s) Perceive stigma (x ± s)
Age, year 60–80 150 83.74 ± 11.63 48.75 ± 7.00 34.99 ± 5.75
Over 80 93 83.96 ± 13.30 48.34 ± 7.35 35.61 ± 6.67
t/z −0.13 0.43 −0.78
p 0.894 0.664 0.439
Education level Below elementary 57 78.81 ± 16.55 45.25 ± 9.19 33.56 ± 8.10
Middle school 165 84.93 ± 10.17 49.30 ± 5.89 35.63 ± 5.40
High school or above 21 88.71 ± 10.00 52.14 ± 6.57 36.57 ± 4.28
F 7.49 10.49 3.03
p < 0.001 < 0.001 0.050
Income level, CNY < 3000 34 87.59 ± 11.23 50.41 ± 6.70 37.18 ± 5.83
3000–5000 135 84.79 ± 10.97 49.21 ± 6.38 35.59 ± 5.74
5000–7000 43 81.00 ± 13.60 46.79 ± 7.52 34.21 ± 6.70
> 7000 31 79.39 ± 15.07 46.45 ± 9.18 32.94 ± 6.54
F 3.57 3.00 3.24
p 0.015 0.031 0.023
Marital status Married 184 83.19 ± 12.51 48.12 ± 7.20 35.07 ± 6.30
Single 59 85.80 ± 11.36 50.08 ± 6.73 35.71 ± 5.52
t/z −1.42 −1.85 −0.70
p 0.156 0.065 0.485

Obesity

(BMI > 30 kg/m2)

 Yes 220 83.69 ± 12.66 48.55 ± 7.23 35.14 ± 6.29
No 23 85.09 ± 7.65 49.00 ± 6.14 36.09 ± 4.06
t/z 0.52 0.28 1.00
p 0.605 0.776 0.322
Stroke Yes 98 86.11 ± 11.28 49.78 ± 6.38 36.34 ± 5.94
No 145 82.28 ± 12.70 47.80 ± 7.50 34.48 ± 6.14
t/z −2.42 −2.14 −2.35
p 0.016 0.034 0.020
Diabetes Yes 83 82.23 ± 13.91 47.39 ± 7.76 34.84 ± 6.81
No 160 84.65 ± 11.28 49.23 ± 6.71 35.42 ± 5.73
t/z 1.46 1.92 0.70
p 0.145 0.056 0.483
Water intake 0–1000 mL 22 64.18 ± 12.58 37.82 ± 7.71 26.36 ± 5.22
1000–2000 mL 178 85.66 ± 10.89 49.74 ± 6.36 35.93 ± 5.67
Over 2000 mL 43 86.26 ± 8.09 49.40 ± 4.99 36.86 ± 4.51
F 41.41 35.69 32.53
p < 0.001 < 0.001 < 0.001
Smoking Yes 112 85.15 ± 9.32 49.70 ± 5.94 35.46 ± 4.82
No 131 82.69 ± 14.26 47.66 ± 7.90 35.03 ± 7.05
t/z −1.62 −2.29 −0.55
p 0.107 0.023 0.580
Drinking Yes 67 85.60 ± 6.76 49.61 ± 4.64 35.99 ± 4.28
No 176 83.15 ± 13.76 48.21 ± 7.84 34.94 ± 6.67
t/z −1.85 −1.71 −1.44
p 0.066 0.088 0.150
Coronary heart disease Yes 67 81.96 ± 13.39 47.69 ± 7.51 34.27 ± 6.66
No 176 84.53 ± 11.77 48.94 ± 6.96 35.59 ± 5.88
t/z 1.47 1.23 1.51
p 0.143 0.220 0.132
Prostatic hyperplasia and hypertrophy Yes 124 83.74 ± 13.24 85.11 ± 12.04 35.64 ± 6.54
No 119 83.91 ± 11.22 48.94 ± 6.54 34.97 ± 5.76
t/z 0.10 0.74 −0.65
p 0.916 0.461 0.517
Hypertension Yes 139 84.50 ± 12.84 49.04 ± 7.32 35.46 ± 6.40
No 104 82.91 ± 11.46 48.00 ± 6.84 34.91 ± 5.72
t/z −1.00 −1.13 −0.69
p 0.318 0.259 0.491
History of constipation (frequency) Never 102 85.34 ± 9.29 49.86 ± 5.40 35.48 ± 5.32
Occasionally 117 82.91 ± 13.71 47.62 ± 7.83 35.28 ± 6.61
Frequently 24 81.83 ± 15.41 47.96 ± 9.15 33.88 ± 6.84
F 1.43 2.84 0.68
p 0.241 0.060 0.509
UI type SUI 30 69.80 ± 15.52 82.68 ± 12.14 86.75 ± 9.57
UUI 50 40.87 ± 9.02 47.42 ± 6.53 50.38 ± 5.80
MUI 163 28.93 ± 6.87 35.26 ± 6.31 36.37 ± 5.17
F 30.42 28.86 22.01
p < 0.001 < 0.001 < 0.001
UI severity Slight 58 77.90 ± 15.19 48.60 ± 7.12 32.60 ± 6.98
Moderate 85 83.88 ± 12.41 45.29 ± 8.80 35.42 ± 6.22
Severe 78 87.22 ± 8.75 48.46 ± 7.13 36.65 ± 5.10
Extremely severe 22 87.18 ± 7.71 50.86 ± 4.90 36.32 ± 4.54
F 7.63 7.45 5.53
p < 0.001 < 0.001 0.001
Frequency of micturition 2–3 times a day 37 83.05 ± 12.10 47.81 ± 7.24 35.24 ± 5.76
3–5 times a day 92 81.04 ± 14.21 47.33 ± 8.40 33.72 ± 6.78
More than 5 times 114 86.32 ± 10.01 49.88 ± 5.65 36.44 ± 5.40
F 4.94 3.61 5.22
p 0.008 0.029 0.006
Tea consumption Yes 84 86.71 ± 8.58 50.17 ± 5.11 36.55 ± 4.86
No 159 82.30 ± 13.60 47.77 ± 7.87 34.53 ± 6.59
t/z −3.09 −2.87 −2.71
p 0.002 0.005 0.007
Spicy food flavour Yes 8 85.38 ± 4.90 49.62 ± 3.46 35.75 ± 3.33
No 235 83.77 ± 12.44 48.56 ± 7.22 35.21 ± 6.19
t/z −0.36 −0.41 −0.25
p 0.717 0.679 0.806
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Abbreviations: CNY, Chinese Yuan, the official currency of the People's Republic of China; MUI, mixed urinary incontinence, referring to any combination of SUI and UUI; SUI, stress urinary incontinence, referring to urine loss during movement, exertion or generally during increased abdominal pressure; UUI, urgency urinary incontinence, referring to urine loss concomitant or immediately following an urgency episode.

3.2. Multivariable Analysis of Stigma Correlates

Multivariable linear regression analysis revealed significant associations between education level, UI type, UI severity, daily water intake, tea consumption and stigma scores (Table 2). In the unadjusted Model 1, completion of middle school (β = 6.126) and high school or above (β = 9.907) were associated with significantly higher stigma scores compared to the below elementary reference group. Both stress urinary incontinence (SUI; β = 12.880) and urge urinary incontinence (UUI; β = 16.955) demonstrated significantly elevated scores compared to mixed urinary incontinence. A graded positive association was observed between UI severity and stigma scores, with moderate (β = 5.986), severe (β = 9.321) and extremely severe (β = 9.285) groups all showing significantly higher scores than the slight UI group. Higher daily water intake was significantly associated with increased stigma scores, with both the 1000–2000 mL/day (β = 21.481) and > 2000 mL/day (β = 22.074) groups demonstrating substantially higher scores than the < 1000 mL/day reference group. Tea consumption was also associated with higher stigma scores compared to nonconsumption (β = 4.419). In Model 2, adjusted for demographic and clinical covariates (age, income level and obesity), all associations remained statistically significant with largely consistent effect sizes. The association for tea consumption strengthened slightly (β = 5.022). After comprehensive adjustment for additional clinical and behavioural covariates in Model 3 (hypertension, frequency of micturition, drinking, spicy food flavour, coronary heart disease, history of constipation, smoking and stroke), all key variables maintained significant associations with total stigma scores (all p < 0.05).

TABLE 2.

Multivariable Linear regression models for stigma scores.

Model 1 Model 2 Model 3
Variables β (95% CI) p β (95% CI) p β (95% CI) p
Education level
Below elementary 0.000 (Reference) 0.000 (Reference) 0.000 (Reference)
Middle school 6.126 (2.509, 9.743) 0.001 6.758 (3.031, 10.485) < 0.001 5.509 (1.691, 9.327) 0.005
High school or above 9.907 (3.897, 15.917) 0.001 9.424 (3.351, 15.498) 0.003 8.346 (2.224, 14.468) 0.008
UI type
MUI 0.000 (Reference) 0.000 (Reference) 0.000 (Reference)
SUI 12.880 (7.874, 17.886) < 0.001 12.687 (7.665, 17.709) < 0.001 11.248 (6.101, 16.395) < 0.001
UUI 16.955 (12.649, 21.261) < 0.001 16.989 (12.700, 21.278) < 0.001 15.867 (11.439, 20.295) < 0.001
UI severity
Slight 0.000 (Reference) 0.000 (Reference) 0.000 (Reference)
Moderate 5.986 (2.029, 9.942) 0.003 5.403 (1.476, 9.330) 0.007 5.205 (1.271, 9.140) 0.010
Severe 9.321 (5.294, 13.349) < 0.001 9.221 (5.237, 13.205) < 0.001 8.587 (4.588, 12.586) < 0.001
Extremely severe 9.285 (3.468, 15.102) 0.002 9.203 (3.370, 15.035) 0.002 7.499 (1.582, 13.415) 0.013
Water intake
0–1000 mL 0.000 (Reference) 0.000 (Reference) 0.000 (Reference)
1000–2000 mL 21.481 (16.752, 26.210) < 0.001 21.870 (17.233, 26.507) < 0.001 21.499 (16.558, 26.440) < 0.001
Over 2000 mL 22.074 (16.589, 27.559) < 0.001 22.252 (16.874, 27.631) < 0.001 21.807 (16.056, 27.558) < 0.001
Tea consumption
No 0.000 (Reference) 0.000 (Reference) 0.000 (Reference)
Yes 4.419 (1.201, 7.637) 0.007 5.022 (1.844, 8.201) 0.002 4.407 (1.143, 7.672) 0.008
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3.3. Latent Profile Analysis

Latent profile models ranging from one to five profiles were estimated. The corresponding model fit indices are presented in Table 3. The AIC and BIC values decreased consistently from the 1‐ to 4‐profile models, indicating improved model fit with increasing complexity. Entropy values for the 2‐ and 4‐profile models were high (≥ 0.80), indicating acceptable classification accuracy and clear profile separation. The BLRT was significant (p < 0.05) for the 2‐, 3‐ and 4‐profile models, supporting the superiority of each k‐profile model over the corresponding k‐1 model. The consistent decrease in both AIC (from 1117.837 to 1062.223) and BIC (from 1142.280 to 1107.633) for the 2‐ to 4‐profile models suggested a favourable balance between parsimony and fit. However, for the 5‐profile model, the BIC value (1420.76) increased compared to the 4‐profile model (1107.633), suggesting potential overfitting despite a lower AIC (1319.4). Based on the combination of statistical indices (particularly the BIC increase in the 5‐profile model), high entropy (0.82 for the 4‐profile model) and substantive interpretability, the 4‐profile model was selected as the optimal solution.

TABLE 3.

Fit statistics for the latent profile analysis.

LogLik AIC BIC SABIC Entropy LMR‐A‐LRT BLRT p Profile probabilities
1 −688.602 1385.204 1399.176 1386.497 1 NA NA 1
2 −551.919 1117.837 1142.288 1120.099 0.983 273.367 0.010 88.2%/11.8%
3 −531.310 1082.620 1117.550 1085.852 0.771 41.217 0.010 48.2%/11.2%/40.6%
4 −518.112 1062.223 1107.633 1066.425 0.820 26.396 0.010 15%/10.4%/40.2%/34.4%
5 −514.542 1061.085 1116.974 1066.256 0.754 7.138 0.069 25.7%/15%/10.4%/19.3%/29.6%
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Analyses of variance revealed statistically significant differences across the four latent profiles on the self‐stigma subscale, perceived stigma subscale and total SSCI score (all p < 0.001). See Supplementary Material 2. The characteristic scores of the four latent profiles on the SSCI subscales are presented in Supplementary Material 1. Profile 4 (34.4% of the sample) demonstrated above‐average scores on both self‐stigma and perceived stigma subscales and was labelled the ‘High‐Self‐Stigma & High Perceived Stigma’ profile. Profile 3 (40.2%) exhibited moderately elevated self‐stigma scores alongside perceived stigma scores near the average, being termed the ‘Moderate Self‐Stigma & Moderate Perceived’ profile. Profile 1 (15.0%) showed scores near the mean on both subscales and was designated as ‘Internal‐Sensitive & External‐Resilient.’ Profile 2 (10.4%) consistently displayed the lowest scores across both subscales and was categorized as the ‘Low Stigma’ profile.

3.4. Characteristics Across Stigma Profiles

Statistical analyses revealed significant associations between latent profile membership and participant characteristics (all p < 0.05 by chi‐square tests). The heatmap illustrates varying strengths of association between the latent profiles and key behavioural and clinical variables. The strongest correlations were observed with water intake (r = 0.356), UI type (r = 0.302) and educational level (r = 0.228), indicating these factors are significantly linked to profile differentiation. The strength of these categorical relationships was quantified using Pearson coefficients (Supplementary Material 3), with chord diagrams visually representing the bivariate associations between profiles and key variables (Supplementary Material 4). Distinct characteristic patterns emerged across profiles: the ‘High‐Self‐Stigma & High Perceived Stigma’ profile demonstrated significant associations with very high daytime urinary frequency (more than 5 times/day, 41.2%), severe UI (39.7%), tea consumption (39.3%) and higher diabetes prevalence (34.9%), along with the highest proportion of nonsmokers (38.9%) and second‐highest proportion of nondrinkers (36.4%) (Supplementary Material 4A); the ‘Internal‐Sensitive & External‐Resilient’ profile correlated strongly with very severe UI (50.0%), urge urinary incontinence (UUI) (44.8%), high water intake (> 2000 mL/day, 51.2%), smoking (55.4%) and drinking (62.7%) (Supplementary Material 4B); the ‘Low Stigma’ profile was predominantly characterized by low water intake (0–1000 mL/day, 54.5%) and a low frequency of micturition (2–3 times/day, 8.1%) (Supplementary Material 4C); while the ‘Moderate Self‐Stigma & Moderate Perceived’ profile showed significant associations with a low frequency of micturition (2–3 times/day, 18.9%), low water intake (0–1000 mL/day, 31.8%) and higher educational attainment (high school or above, 23.8%) (Supplementary Material 4D).

4. Discussion

This study identified independent factors influencing stigma among older men with UI through multivariate linear regression analysis. Results indicate that educational level, UI type, UI severity, water intake and tea consumption are all significant predictors of stigma. These associations remained robust after stepwise adjustment for multiple covariates, demonstrating strong reliability. Notably, higher educational level was associated with greater stigma scores, potentially stemming from heightened self‐image and societal expectations within this group, rendering them more sensitive to the disability caused by UI symptoms (Hack et al. 2020). Among UI types, UUI exhibited the strongest association with stigma. This may be due to the characteristic nature of UUI, which involves sudden, intense urges to urinate that are difficult to delay (Drennan et al. 2011). The unpredictability and urgency of symptoms make it more likely for patients to experience embarrassing and anxiety‐inducing episodes of incontinence in public settings, thereby increasing their psychological burden (Drennan et al. 2011; Konstantinou et al. 2025). Furthermore, increased UI severity showed a significant positive correlation with embarrassment scores, indicating that the symptom burden itself is a core driver. Water intake was significantly positively correlated with stigma, potentially reflecting patients' increased fluid consumption behaviour, which objectively heightens leakage risk and psychological stress (Shoham et al. 2021). Tea consumption, as a modifiable behavioural factor, showed significant associations, suggesting that caffeine's physiological stimulation of the bladder may exacerbate symptom perception and psychological distress—a finding corroborated by Andrea Staack's research (Staack et al. 2022).

Based on the identified risk factors, this study employed latent profile analysis to reveal four distinct profiles among older men with UI, thereby deepening the understanding of UI stigma. The ‘Internal‐Sensitive & External‐Resilient’ profile was the most prevalent (40.2%), characterized by high self‐stigma but low perceived stigma. These participants experience substantial internal stigma while not strongly anticipating discrimination from others. This profile reflects a psychological coping mechanism particularly salient among older men with UI. Compared to younger populations, older men tend to adopt more internalized and emotionally restrained coping strategies, often treating health‐related distress as a private matter rather than a topic for open discussion (Xu et al. 2022). This tendency to internalize shame leads to high levels of self‐stigma while manifesting as low perceived external stigma. As noted by Lulu Liao et al. (2023), although UI is considered a ‘taboo’ subject by some, 69.2% of respondents still viewed it as a normal part of aging. The paradoxical combination of high internal sensitive and low external expectation observed in this profile suggests that these individuals may be less likely to seek help or disclose their concerns, potentially masking their psychological needs in clinical settings.

Comparative analysis of variable distribution across profiles revealed that the risk factors identified in the regression model exert distinct patterns of influence in different subgroups. For example, while higher educational attainment was a significant correlate of stigma in the overall regression model, its role varied across profiles: both the ‘Internal‐Sensitive & External‐Resilient’ and ‘High‐Self‐Stigma & High Perceived Stigma’ profiles contained higher proportions of individuals with secondary education or above. This suggests that education may potentially intensify self‐critical tendencies and internal shame in these groups, possibly through heightened health awareness or internalized social expectations (Calpe‐López et al. 2022). More importantly, the latent profile analysis uncovered clinically meaningful patterns arising from variable interactions: The ‘Internal‐Sensitive & External‐Resilient’ profile showed significant co‐occurrence of urge urinary incontinence (UUI), high symptom severity and frequent urination, suggesting that symptom uncontrollability may be the core mechanism driving internalized shame (Anderson et al. 2022). This group demonstrated seemingly paradoxical health behaviours: they exhibited the highest rates of both alcohol consumption (62.7%) and high water intake (> 2000 mL/day, 51.2%). Alcohol use may function as an emotional coping mechanism, yet its diuretic effect potentially worsens UI symptoms, establishing a self‐perpetuating cycle (Curyło et al. 2024). Conversely, high water intake may represent a psychological compensatory strategy to regain predictability by prescheduling voiding opportunities. While this behavioural adaptation reduces the risk of public incontinence episodes (contributing to low perceived stigma), it simultaneously increases internal hypervigilance and self‐criticism—a pattern reflected in their high rate of constipation (58.3%)—resulting in elevated self‐stigma (Zhang et al. 2024; De Rijk et al. 2022). Thus, this profile exemplifies a hidden psychological burden maintained through resource‐intensive self‐management strategies that preserve external functioning at considerable psychological cost (Drožđek et al. 2020).

The ‘High Self‐Stigma & High Perceived Stigma’ profile (34.4%) demonstrated multidimensional burden accumulation. Its clinical features—including severe UI, high urinary frequency and substantial diabetes comorbidity—directly corresponded with the risk factors identified in regression modelling, indicating a concentration of vulnerabilities (Batmani et al. 2021; Elstad et al. 2010). This pattern aligns with previous reports by Tai et al. (2021) and reflects a synergistic disease burden. Diabetes may exacerbate UI through multiple pathways, including diabetic neuropathy impacting bladder innervation and symptom overlap from polydipsia and polyuria, thereby complicating clinical management. Furthermore, multimorbidity causes patients to view their conditions as a collective burden, thereby amplifying their overall illness perception. This compounded identity significantly intensifies helplessness and diminishes self‐worth, thereby deepening both internal and perceived stigmatization (Pearl et al. 2024). Consequently, this group represents a priority population requiring comprehensive, multidisciplinary intensive interventions.

While the ‘Moderate Self‐Stigma & Moderate Perceived’ and ‘Low Stigma’ profiles share similar clinical characteristics, including low frequency of micturition and low water intake, they represent fundamentally distinct psychological adaptation pathways. These groups also differ significantly in their demographic composition. Notably, the ‘Moderate Self‐Stigma & Moderate Perceived’ group contains a substantially higher proportion of individuals with high school education or above compared to the ‘Low Stigma’ group. Previous findings indicate that individuals with higher e‐health literacy tend to experience less anxiety during health information acquisition (Kuzdas‐Sallaberger et al. 2025; Y. Wu, Zhang, and Zhao 2025), underscoring the connection between information processing capacity and psychological regulation. This suggests that the psychological challenges faced by the ‘Moderate Self‐Stigma & Moderate Perceived’ group likely reflect heightened health awareness and self‐reflective tendencies rather than cognitive deficits or health apathy. Conversely, the ‘Low Stigma’ profile demonstrates psychological resilience through its ability to frame symptoms as manageable issues rather than personal failures. This group shows a markedly lower proportion of frequency of micturition compared to the ‘Moderate Self‐Stigma & Moderate Perceived’ profile. Particularly among older men, frequent urination is often linked to erectile dysfunction (Elstad et al. 2010). Therefore, to reduce stigma, attention must be directed not only towards urinary leakage but also towards urinary frequency. This cognitive restructuring, coupled with effective self‐management strategies, is crucial for maintaining low stigma levels (Gökşin et al. 2020; Wu et al. 2024; Shi et al. 2025).

Identifying distinct patterns of stigma characteristics among older men with UI holds significant clinical importance. By replacing generalized treatment approaches with targeted strategies, our findings may assist healthcare providers in developing psychosocial interventions tailored to the specific needs of each subgroup. For instance, individuals in the ‘Internal‐Sensitive & External‐Resilient’ profile may benefit from interventions targeting internal shame and fostering adaptive coping strategies (Chiu et al. 2020). Conversely, those in the ‘High Self‐Stigma & High Perceived Stigma’ profile require integrated medical and psychological support to manage multiple conditions and alleviate overall burden (He et al. 2024). This study may provide a tentative evidence base and could inform the direction of future psychosocial support systems for older men with UI.

4.1. Limitations

Several limitations should be noted. The cross‐sectional design precludes causal inferences between the identified variables and stigma profiles, while recruitment from only two hospitals in a single region limits the generalizability of the findings. Additionally, our data collection relied on self‐reported measures, which are susceptible to recall and social desirability biases. Furthermore, although the translated ISI showed acceptable internal consistency in our sample, it lacks rigorous, comprehensive psychometric validation. Future longitudinal studies are warranted to track the evolution of these stigma profiles in response to targeted interventions, alongside methodological research to fully validate the applied cross‐cultural instruments.

5. Conclusions

This study pinpointed key factors associated with stigma through regression analysis and, employing LPA, revealed significant heterogeneity in stigma experiences by identifying four distinct profiles: High‐Self‐Stigma & High Perceived Stigma, Internal‐Sensitive & External‐Resilient, Moderate Self‐Stigma & Moderate Perceived and Low Stigma. Future research may explore whether these profiles remain stable over time and how they might inform targeted support strategies in clinical practice.

Author Contributions

Conceptualization: J.Y.L. and S.T.W. Methodology: J.Y.L. and S.T.W. Formal analysis: H.C.H. and Y.X.C. Investigation: H.C.H., J.Y.L. and S.T.W. Administrative activities: Y.X.C. and H.C.H. Writing – original draft: Y.X.C., H.C.H. and J.Y.L. Writing – review and editing: S.T.W. and J.Y.L. Supervision: J.Y.L. Project administration: S.T.W. All authors read and approved the final manuscript. All authors read and approved the final manuscript.

Funding

The authors have nothing to report.

Disclosure

In this study, the authors utilized generative artificial intelligence (AI) tools, including Grammarly (Grammarly Inc) and OpenAI's ChatGPT (GPT‐4.5; OpenAI), to translate documents from Chinese to English. These tools were employed to support proofreading and improve the overall clarity and readability of the manuscript.

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Data S1: ijn70156‐sup‐0001‐Supporting_Information.docx. Supplementary Material 1. Latent profile indicators mean values for the four profiles. Note: B1–B24 refers to items 1 to 24 of the Stigma Scale.

Supplementary Material 2. Variability of dimension scores among profiles.

Supplementary Material 3. Correlation Heatmap between latent profiles and participant characteristics.

Supplementary Material 4 (A) Correlation between profile 1 and participant characteristics.

Supplementary Material 4 (B) Correlation between profile 2 and participant characteristics.

Supplementary Material 4 (C) Correlation between profile 3 and participant characteristics.

Supplementary Material 4 (D) Correlation between profile 4 and participant characteristics.

Note: The width of a string represents the strength of the association, quantified based on the probability of a specific feature appearing in a given profile.

IJN-32-e70156-s001.docx (1.2MB, docx)

Acknowledgements

The authors extend their sincere gratitude to all the participants who shared their personal experiences and stories, making this study possible. We also thank the nursing and medical staff of the participating hospitals for their support in participant recruitment and data collection.

Data Availability Statement

Prof. Lu had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Data S1: ijn70156‐sup‐0001‐Supporting_Information.docx. Supplementary Material 1. Latent profile indicators mean values for the four profiles. Note: B1–B24 refers to items 1 to 24 of the Stigma Scale.

Supplementary Material 2. Variability of dimension scores among profiles.

Supplementary Material 3. Correlation Heatmap between latent profiles and participant characteristics.

Supplementary Material 4 (A) Correlation between profile 1 and participant characteristics.

Supplementary Material 4 (B) Correlation between profile 2 and participant characteristics.

Supplementary Material 4 (C) Correlation between profile 3 and participant characteristics.

Supplementary Material 4 (D) Correlation between profile 4 and participant characteristics.

Note: The width of a string represents the strength of the association, quantified based on the probability of a specific feature appearing in a given profile.

IJN-32-e70156-s001.docx (1.2MB, docx)

Data Availability Statement

Prof. Lu had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Articles from International Journal of Nursing Practice are provided here courtesy of Wiley

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