Determinants of Young Men’s Help-Seeking Behavior: Insights From a National Australian Survey

Abstract

Young men face unique barriers to accessing health care, contributing to poor health outcomes. We used data from 188 Australian men aged 18–34 years, who participated in a nationally representative cross-sectional survey, to examine the relationships between health literacy, health empowerment, social support, loneliness, and barriers to health care. Structural equation modeling was used to examine direct and indirect associations, adjusting for sociodemographic factors and health status. Loneliness and health literacy were consistently associated with barriers to help-seeking. Higher health literacy was linked to lower barriers (β = −0.26, p = .001), whereas higher loneliness was associated with higher barriers (β = 0.24, p = .007). Higher health empowerment was associated with lower concrete barriers and distrust of caregivers (β = −0.20, p = .007), and loneliness was found to be indirectly associated with concrete barriers and distrust of caregivers through health empowerment (β = 0.07, p = .024). Social support was not associated with barriers to help-seeking. These findings underscore the importance of health literacy and loneliness as consistent determinants of help-seeking and highlight the role of health empowerment in reducing practical and interpersonal access barriers. The results can inform the design of interventions to improve health care engagement among young men.

Keywords

young men help-seeking behavior loneliness health literacy

On average, men experience nearly 5 fewer years of healthy life than women and face higher rates of mortality from preventable diseases and suicide (Australian Institute of Health and Welfare, 2020, 2022, 2023; Pirkis et al., 2016; World Health Organization, 2018, 2021). Across global contexts, including Australia, the European Union, the United Kingdom, the United States, and countries in Asia and Africa, men consistently demonstrate reduced engagement with health services and lower rates of help-seeking behavior (Australian Institute of Health and Welfare, 2023; Rosu et al., 2017; Smits et al., 2018; Tong et al., 2011; Wang et al., 2013; World Health Organization, 2018; Yeatman et al., 2018). A pattern of delayed and reduced engagement with health care is a crucial factor contributing to men’s poorer health outcomes, with studies highlighting later diagnoses and reduced use of preventive and mental health services among men (Australian Institute of Health and Welfare, 2023; P. Baker, 2016; Clarke et al., 2013; Juel & Christensen, 2008; Lyratzopoulos et al., 2013; Mursa et al., 2022; Schlichthorst et al., 2016). Deepening our understanding of factors that may influence how men engage with health services is important for enhancing the health system’s capacity to support men’s health.

Age has been identified as a significant factor influencing men’s health help-seeking preferences and behaviors (McGraw et al., 2021; Palmer et al., 2025; Schlichthorst et al., 2016). Notably, attitudes and behaviors that reduce opportunities for engagement with health services appear to be prominent among young men, potentially contributing to lifelong disengagement from health care services (Palmer et al., 2024, 2025; J. A. Smith et al., 2006). Despite experiencing high rates of psychological distress and suicide, young men have among the lowest rates of professional help-seeking for mental health of any group across the lifespan (D. Baker & Rice, 2017; Burke & McKeon, 2007; Rickwood et al., 2005; B. Smith et al., 2023; Vincent et al., 2018). Understanding and addressing the factors that affect young men’s engagement with health services is therefore essential for improving both immediate and long-term health outcomes (Marcell et al., 2007; B. Smith et al., 2023; J. A. Smith et al., 2006; Vincent et al., 2018).

Young men’s help-seeking behaviors are influenced by a multifaceted set of determinants operating across socioecological levels (Palmer et al., 2024). Among these determinants, qualitative studies have highlighted the importance of psychosocial factors in shaping help-seeking behaviors. For instance, a study by Lynch et al. (2018) involving 17 young men in Ireland aged 18 to 24 years found that low health literacy, including difficulty identifying symptoms and understanding the need for treatment, was a significant barrier to accessing mental health services. The study found that concerns about losing status and facing ostracism from peers further discouraged help-seeking. Conversely, having knowledge of other men’s help-seeking behaviors and receiving social support from peers were seen as key facilitators (Lynch et al., 2018). These findings are illustrative of the broader qualitative literature, highlighting health literacy and social support as important determinants of young men’s help-seeking (Palmer et al., 2024).

The positive effects of social support appear to be most pronounced in contexts where peers and family members consider male help-seeking as legitimate and acceptable and endorse it as behavior that is congruent with masculine values (Palmer et al., 2024). This role of social support underscores the potential compounding impact of loneliness, a related but distinct component of social well-being (Lim et al., 2023; K. P. Smith & Christakis, 2008) with established links to health outcomes and health service engagement (Geboers et al., 2016; Vasan et al., 2023). Recent Australian population-level research shows that severe loneliness in men is associated with lower health literacy and health empowerment and less favorable attitudes toward preventive health practices (Lim et al., 2025). These findings raise concerns given the high prevalence of loneliness among young men (Australian Institute of Health and Welfare, 2025; Ending Loneliness Together, 2023) and highlight the need to better understand how loneliness interacts with other psychosocial determinants to influence help-seeking.

While qualitative research has identified a range of factors that influence young men’s help-seeking, it remains unclear how these factors interact or their relative influence on help-seeking behaviors. Quantitative research in this area is also limited (Palmer et al., 2024). In one of the few quantitative studies, Boman and Walker (2010) investigated the role of general self-efficacy (GSE) in moderating the relationship between conformity to masculinity norms and perceived barriers to health care among 118 Australian university students (mean age 23.7 years). Their findings suggested that GSE might mitigate some of the barriers to help-seeking behaviors, highlighting the potential of psychological constructs like self-efficacy to shape health care engagement in young men (Boman & Walker, 2010).

These findings raise important questions about the related concept of health empowerment and its role in young men’s help-seeking. Health empowerment extends the principles of self-efficacy into a health care context, emphasizing the skills and participatory behaviors necessary to navigate health care systems effectively (Wallerstein, 1992). Health empowerment is associated with improved health behaviors and outcomes (Laverack, 2006; Náfrádi et al., 2017; Wallerstein, 1992) and is closely connected with psychosocial factors that may influence young men’s help-seeking, with studies showing that higher health empowerment is associated with greater health literacy, stronger social connections, and lower levels of loneliness (Çiftci et al., 2023; Demirel & Ayaz-Alkaya, 2024; Lin et al., 2019).

Health empowerment offers a theoretical and empirically grounded mechanism linking psychosocial factors to help-seeking by young men. For instance, loneliness has been consistently associated with heightened hypervigilance to threat, diminished trust in others, and reduced confidence in navigating social interactions (Cacioppo & Hawkley, 2009; Hawkley & Cacioppo, 2010). This may erode a young man’s sense of control and capability in health care contexts, increasing the likelihood of perceiving help-seeking as difficult, unsafe, or unmanageable (Cacioppo & Hawkley, 2009; Hawkley & Cacioppo, 2010; Lim et al., 2025). Low health literacy may similarly reduce an individual’s ability to recognize symptoms, evaluate treatment options, and communicate effectively with providers, reducing perceived capacity to act on health concerns and lowering confidence in engaging with health care (Mursa et al., 2024; Oliffe et al., 2020). In contrast, social support may strengthen health empowerment by reinforcing self-efficacy, providing encouragement, modeling adaptive help-seeking, and signaling that accessing care is legitimate and acceptable (Palmer et al., 2024). Together, these pathways suggest that loneliness, health literacy, and social support may shape young men’s perceived help-seeking barriers in part through their influence on health empowerment.

The described literature highlights a range of intrapersonal and social factors that may, in direct or combined ways, influence young men’s help-seeking behaviors. It is notable that, while qualitative studies have revealed a range of potential determinants of men’s help-seeking, quantitative research is limited and has largely concentrated on a narrow set of variables, such as masculine attitudes and self-stigma, without examining broader psychosocial factors (Palmer et al., 2024). Further, much of this research has been limited in scope, focusing primarily on population subgroups, such as university students or young men already engaged with health care (Palmer et al., 2024).

In this study, we aim to address these gaps by using population-level data to examine the influences of social support, loneliness, health literacy, and health empowerment on perceived barriers to help-seeking among young men. In doing so, we seek to build a broader conceptual framework, grounded in the existing literature, that explores whether health empowerment may serve as a mechanism through which psychosocial factors shape help-seeking barriers. By examining both the direct and indirect pathways, we aim to contribute to a more comprehensive understanding of the determinants influencing young men’s health care engagement and provide insights to inform targeted intervention development.

Methods

Study Design

This study uses data from a national cross-sectional survey of Australian men. Ethics approval was acquired from the Monash University Human Research Ethics Committee (Approval No. 27289). The reporting of the study is based on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines (Von Elm et al., 2007).

Participants and Sampling

Participants were recruited through the Life in Australia (LiA) panel (Dove & Smith, 2021). This panel consists of a probabilistic sample of approximately 4,000 Australian adults recruited through random digit dialing with a 30:70 distribution between landline and mobile phone numbers (Kaczmirek et al., 2019). To be eligible for the LiA panel, participants had to be aged 18 years or older, speak English, and have access to a telephone and an internet connection.

All men in the LiA panel (N = 1.409) received an invitation through email and text message to participate in the survey, with follow-up phone calls to those who did not respond. The invitations included an information statement about the study, and participants confirmed their consent by choosing to complete the survey. Participants were given a $10 gift-card for taking the survey. The online survey was conducted during March 2021.

Survey Measures

The survey (see Supplementary File 1) was developed by Healthy Male, which is a national men’s health organization funded by the Australian Department of Health and Aging. Survey measures were selected based on consultation with medical and allied health advisors, as well as a review of Australian and international men’s health surveys.

Participants provided their age, residential postcode (used to determine SEIFA; Australian Bureau of Statistics, 2018), marital status, educational background, occupation, and country of birth. Participants were also asked about any disabilities and chronic physical or mental health conditions they might have.

Social support was measured with the Multidimensional Scale of Perceived Social Support, which consists of 12 items and has good internal reliability and satisfactory construct validity (Zimet et al., 1990). Loneliness was assessed using the 3-item version of the revised UCLA loneliness scale (UCLA-3), which demonstrates acceptable internal reliability and both discriminant and concurrent validity (Hughes et al., 2004). Health literacy was evaluated using the 16-item European Health Literacy Survey Questionnaire (HLS-EU-Q16; Sørensen et al., 2013), selected for its suitability to general population contexts as opposed to health care-specific settings. This questionnaire emphasizes public health dimensions of health literacy, such as disease prevention and health promotion, and demonstrates a robust scale structure and strong concurrent validity in multiple populations. Health empowerment was measured using the 8-item Perceived Health Competence scale (M. Smith et al., 1995), which also demonstrates internal reliability and construct validity.

Barriers to help-seeking were measured using the 31-item Barriers to Help-Seeking Scale (BHSS; Mansfield et al., 2005). Using a 7-point scale, the BHSS asks participants to rate the significance of different reasons for not seeking help. These reasons are categorized into five subscales: need for control and self-reliance; concrete barriers and distrust of caregivers; minimizing problems and resignation; privacy concerns; and emotional control. Higher scores on the BHHS indicate higher levels of barriers to help-seeking. Each subscale demonstrated robust internal reliability (see Table 2)

Statistical Analysis

Survey data were weighted using enrollment weights derived through design and post-stratification procedures to align the LiA sample with Australian population benchmarks (Kaczmirek et al., 2019). Generalized regression methods were applied for weighting, using non-linear optimization to minimize weight variability while matching known population totals (Deville et al., 1993; Dove & Smith, 2021). Weighting was based on the Australian Bureau of Statistics Census profile (2020; Dove & Smith, 2021) accounting for demographic variables, including age, country of birth, geographic location, educational level, Socioeconomic Index for Areas (SEIFA) score (a postcode-based socioeconomic index), telephone access, and duration at current place of residence (Australian Bureau of Statistics, 2020). Weighting was calculated for the full LiA male panel and was not recalibrated for the 18 to 34-year-old subsample used in the present analysis.

Bivariate associations between variables were examined using a Pearson correlation matrix. This included the total and subscale scores for barriers to help-seeking, psychosocial factors (health literacy, loneliness, health empowerment, and social support), relevant sociodemographic (country of birth and SEIFA quintile), and health status characteristics (disability status and mental and physical health status). Correlations were calculated separately for the total BHSS score and each of the five subscales.

Subsequent multivariable linear regression analyses were conducted to assess the associations between psychosocial factors and barriers to help-seeking. Each regression model was adjusted for relevant sociodemographic and health status variables, using forced-entry linear regression to account for potential confounding factors. Separate models were run for the total BHSS score and for each of the five BHSS subscales as dependent variables.

Structural equation modeling (SEM) was used to examine the direct associations between the psychosocial variables and barriers to help-seeking and to explore whether health empowerment functioned as a potential pathway linking health literacy, social support, and loneliness to these barriers. Six separate SEMs were specified, one for the total BHSS score and one for each of the five subscales as dependent variables. The model structure remained consistent across all six models; only the dependent variable (total or subscale barrier score) varied. Each model estimated direct paths from psychosocial variables to help-seeking barriers, as well as indirect paths from health literacy, social support, and loneliness to help-seeking barriers via health empowerment. All models were also adjusted for relevant sociodemographic and health status variables. All SEM models were estimated using maximum likelihood estimation in R’s lavaan package (Rosseel, 2012). Model fit was assessed using Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Comparative Fit Index (CFI), Tucker–Lewis Index (TLI), Root Mean Square Error of Approximation (RMSEA), and Standardized Root Mean Square Residual (SRMR). As all six SEMs were just-identified (df = 0), these indices indicate a perfect fit (CFI = 1.00, TLI = 1.00, RMSEA = 0.00, SRMR = 0.00), though this is not interpretable in the conventional sense. Multicollinearity was assessed using variance inflation factors (VIFs) across linear regression models corresponding to each SEM outcome. All VIFs ranged from 1.05 to 1.65, indicating low multicollinearity.

Statistical analyses were performed using R statistical computing software (version 4.4.1; R Core Team, 2024), within RStudio (Posit team, 2024). Missing data ranged from 1.6% to 8.5% across variables, with the highest proportion observed for the total barriers to help-seeking score. Correlation analyses were conducted using pairwise deletion, and listwise deletion was used for regression analyses and SEM. Although no formal sensitivity analysis was conducted, missing data were within an acceptable range (<10%; Bennett, 2001) and patterns of associations were consistent across analytic approaches.

Results

Sample Characteristics

Of the 1,409 men invited to participate in the survey, 1,282 completed the survey (91.0%). For this analysis, we selected the subset of 188 young men aged 18 to 34 years. Sociodemographic and health status characteristics for this group are presented in Table 1.

Table 1.

Sociodemographic and Health Characteristics of Survey Participants, 18 to 34 Years (n = 188).

Demographic and health factors	n (%)
Residential location
Urban	142 (76.5)
Rural	42 (22.3)
Marital status
Never married	91 (48.4)
Married/partner	90 (47.9)
Divorced/widowed	2 (1.1)
SEIFA quintile
Q1 (lowest)	23 (12.2)
Q2	26 (13.8)
Q3	37 (19.7)
Q4	40 (21.3)
Q5 (highest)	57 (30.3)
Education
University	93 (49.5)
Vocational	36 (19.1)
High school	54 (28.7)
Occupation
Manager/professional	104 (55.3)
Trades/manual	28 (14.9)
Sales/service	37 (19.7)
Other	16 (8.5)
Country of birth
English speaking	143 (76.1)
Non-English speaking	42 (22.3)
Disability
Living with a disability	24 (12.8)
Not living with a disability	161 (85.6)
Chronic disease^a
Physical condition	45 (23.9)
Mental condition	29 (15.4)
No chronic disease	132 (70.2)

Note. Variables with totals less than 188 are due to missing data, which ranged from 1.6% to 2.7%, with the highest proportions observed for education level, SEIFA quintile, and marital status. SEIFA = Socioeconomic Index for Areas, a postcode-based index of socioeconomic position. Quintiles indicate relative socioeconomic position, with lower quintiles reflecting greater disadvantage.

Participants reporting at least one physical or mental condition. The full list of conditions is provided in Supplementary File 1.

As shown in Table 2, participants reported moderate levels of health empowerment (M = 27.45, SD = 4.88) and social support (M = 5.12, SD = 1.06) with higher scores indicating greater perceived competence in managing health-related tasks and greater perceived social support. On average, health literacy scores fell within the lower end of the “sufficient” range (M = 13.32, SD = 2.94), with some participants scoring within the “inadequate” or “problematic” range. Participants reported moderate levels of loneliness (M = 5.62, SD = 1.89), with scores ranging from “low” to “severe.” Minimizing problems and resignation (M = 3.80, SD = 1.39) and the need for emotional control (M = 3.08, SD = 1.52) were the most prominent barriers to help-seeking, followed by privacy concerns (M = 2.75, SD = 1.33), concrete barriers and distrust of caregivers (M = 2.59, SD = 1.27) and need for control and self-reliance (M = 2.46, SD = 1.30).

Table 2.

Psychosocial Factors and Barriers to Help-Seeking Among Young Men.

Psychosocial factor/barrier	Mean (SD)	Range*	Cronbach’s α	Missing (n, %)
Health Empowerment	27.45 (4.88)	10–40	0.84	5 (2.66)
Health Literacy	13.32 (2.94)	0–16	0.83	12 (6.38)
Loneliness	5.62 (1.89)	3–9	0.81	15 (7.98)
Social Support	5.12 (1.06)	1.67–7	0.92	13 (6.9)
Total barriers	88.27 (33.63)	31–194	0.95	16 (8.51)
Need for Control and Self-Reliance	2.46 (1.30)	1–6.20	0.92	11 (5.85)
Minimizing Problems and Resignation	3.80 (1.39)	1–7	0.87	11 (5.85)
Concrete Barriers and Distrust of Caregivers	2.59 (1.27)	1–6.33	0.81	7 (3.72)
Privacy	2.75 (1.33)	1–6.20	0.79	10 (5.32)
Emotional Control	3.08 (1.52)	1–6.50	0.83	7 (3.72)

Note. SD = standard deviation. *Range represents the minimum and maximum scores for each variable. Higher scores indicate higher levels of each variable. Health literacy scores are categorized as inadequate (0–8), problematic (9–12), or sufficient (13–16). Loneliness scores are classified as low (3–5), moderate (6–7), or severe (8–9).

Associations Between Psychosocial Factors and Help-Seeking Barriers

The correlation matrix of psychosocial variables with help-seeking barriers is presented in Table 3. Loneliness was positively correlated with total barriers (r = 0.27, p < .001), indicating a weak to moderate relationship, and with all barrier subscales except for the minimizing problems and resignation subscale (r = 0.15, p = .06). There were notable subscale correlations between loneliness and concrete barriers and distrust of caregivers (r = 0.29, p < .001; weak to moderate) and emotional control (r = 0.25, p = .001; weak). Health literacy was negatively correlated with total barriers (r = −0.32, p < .001; moderate) and all subscales, with the strongest correlations observed for concrete barriers and distrust of caregivers (r = −0.33, p < .001; moderate) and privacy (r = −0.29, p < .001; weak to moderate). Health empowerment was also negatively correlated with total barriers (r = −0.23, p = .003; weak), and with all subscales except for minimizing problems and resignation (r = −0.03, p = .712). The strongest correlation was observed for concrete barriers and distrust of caregivers (r = −0.32, p < .001; moderate). Social support was not correlated with total barriers (r = −0.09, p = .27) or any of the subscales.

Table 3.

Correlation Matrix of Psychosocial Variables and Help-Seeking Barriers.

Variable	1	2	3	4	5	6	7	8	9	10
1. Total barriers	—	0.91**	0.70**	0.78**	0.80**	0.86**	−0.32**	0.27**	−0.23*	−0.09
2. Need for control and self-reliance		—	0.53**	0.64**	0.69**	0.77**	−0.22*	0.20*	−0.16*	−0.09
3. Minimizing problems and resignation			—	0.44**	0.36**	0.56**	−0.26*	0.15	−0.03	0.01
4. Concrete barriers and distrust of caregivers				—	0.63**	0.58**	−0.33**	0.29**	−0.32**	−0.07
5. Privacy					—	0.69**	−0.29**	0.20*	−0.24*	−0.05
6. Emotional control						—	−0.23*	0.25*	−0.15*	−0.17*
7. Health literacy							—	−0.18*	0.22*	0.22*
8. Loneliness								—	−0.40**	−0.48**
9. Health empowerment									—	0.18*
10. Social support										—

Note. Interpretation of correlation size follows Cohen (1988): r ≈ 0.10 (weak), 0.30 (moderate), 0.50 (strong).

p < .05; **p < .001.

Among the psychosocial factors, levels of health literacy were negatively correlated with loneliness (r = −0.18, p = .017; weak) and positively correlated with health empowerment (r = 0.22, p = .003; weak) and social support (r = 0.22, p = .004; weak). Levels of loneliness were negatively correlated with health empowerment (r = −0.40, p < .001; moderate) and social support (the r = −0.48, p < .001; moderate to strong). In addition, levels of health empowerment were positively correlated with social support (r = 0.18, p = .015; weak).

Multivariable regression analyses (Table 4) showed that health literacy was negatively associated with total barriers (β = −2.84, p = .002) and several subscales, including minimizing problems and resignation (β = −0.14, p < .001), concrete barriers and distrust of caregivers (β = −0.09, p = .003), privacy concerns (β = −0.11, p = .002), and emotional control (β = −0.10, p = .01). Loneliness was positively associated with total barriers (β = 4.29, p = .01) and specific subscales, such as minimizing problems and resignation (β = 0.19, p = .008), concrete barriers and distrust of caregivers (β = 0.11, p = .048), and emotional control (β = 0.16, p = .036). Health empowerment demonstrated a negative association with concrete barriers and distrust of caregivers (β = −0.05, p = .01) but was not associated with total barriers or other subscales. Social support was not associated with total barriers or any subscales.

Table 4.

Adjusted Associations Between Psychosocial Factors and Help-Seeking Barriers.

Psychosocial factor	Total barriers (β)	Help-seeking barriers subscales
Psychosocial factor	Total barriers (β)	Need for control & self-reliance (β)	Minimizing problems and resignation (β)	Concrete barriers and distrust of caregivers (β)	Privacy (β)	Emotional control (β)
Health empowerment	−0.67	−0.01	0.01	−0.05*	−0.04	−0.01
Health literacy	−2.84*	−0.06	−0.14**	−0.09*	−0.11*	−0.10*
Loneliness	4.29*	0.12	0.19*	0.11*	0.09	0.16*
Social support	2.53	0.02	0.23	0.18	0.10	−0.13

Note. Analyses adjusted for sociodemographic variables and health status. *p < .05; **p < .001.

Direct and Indirect Associations With Barriers to Help-Seeking

The SEMs show both the direct associations between psychosocial factors and help-seeking barriers, and the indirect associations between health literacy, social support, and loneliness and help-seeking barriers via health empowerment (see Supplementary File 2 for full results).

Health literacy was negatively associated with total barriers (β = −0.26, p = .001) and most subscales, including concrete barriers and distrust of caregivers (β = −0.23, p = .002), privacy concerns (β = −0.25, p = .001), minimizing problems (β = −0.30, p < .001), and emotional control (β = −0.21, p = .007). These associations are presented in Figure 1. However, an indirect effect of health literacy through health empowerment was not observed for total barriers or any subscales.

Figure 1.

Significant Direct Associations Between Health Literacy, and Help-Seeking Barriers.

Loneliness demonstrated a positive association with total barriers (β = 0.24, p = .007) and specific subscales, including minimizing problems (β = 0.26, p = .005), concrete barriers and distrust of caregivers (β = 0.17, p = .039), and emotional control (β = 0.20, p = .029). These associations are illustrated in Figure 2. In addition, a small indirect association between loneliness and concrete barriers and distrust of caregivers was observed through health empowerment (β = 0.07, p = .024), indicating that health empowerment may partially mediate this relationship.

Figure 2.

Significant Direct and Indirect Associations Between Loneliness, Health Empowerment, and Help-Seeking Barriers.

A direct association was observed between health empowerment and the concrete barriers and distrust of caregivers subscale (β = −0.20, p = .007), indicating that young men with higher levels of health empowerment reported fewer concrete barriers to seeking help. However, health empowerment was not associated with total barriers or any other subscales.

Social support was not associated with total barriers or any subscales, either directly or indirectly.

Discussion

This study provides insights into the psychosocial determinants of young men’s barriers to help-seeking, identifying loneliness and health literacy as important factors, and highlighting health empowerment as having a direct relationship with concrete barriers and distrust of caregivers. These findings extend our understanding of the relative importance of these factors in shaping help-seeking behaviors.

The consistent association between loneliness and help-seeking barriers underscores its relevance to help-seeking. Young men experiencing greater loneliness reported higher total barriers and specific barriers, including minimizing problems and resignation, concrete barriers and distrust of caregivers, and emotional control. These findings suggest that loneliness may amplify practical, emotional, and relational challenges, discouraging help-seeking. This pattern is consistent with theoretical accounts linking loneliness to psychological states that may heighten perceptions of difficulty, danger, or stigma associated with accessing care (Cacioppo & Hawkley, 2009; Hawkley & Cacioppo, 2010). It was notable, that loneliness was not associated with control and self-reliance or privacy barriers, suggesting that these specific barriers are less influenced by feelings of relationship dissatisfaction and instead reflect broader personal or cultural attitudes toward autonomy and vulnerability.

The observed association between loneliness and higher help-seeking barriers among young men is consistent with established links between loneliness and poorer health behaviors (Lauder et al., 2006; Stickley et al., 2014) but differs from broader evidence indicating a positive association between loneliness and increased health care use (Christiansen et al., 2023; Sirois & Owens, 2023). Notably, evidence suggests that the health-seeking consequences of loneliness may be moderated by demographic factors, including gender and age: for example, loneliness predicts greater health care use among older women but not older men (Burns et al., 2020), and its association with primary care use is stronger in samples with a higher proportion of women (Sirois & Owens, 2023). The present findings add to existing evidence by showing that, among young men specifically, loneliness is associated with heightened barriers to help-seeking. This pattern highlights the importance of loneliness as a key determinant of health care engagement for young men and underscores the need for further research into the mechanisms through which loneliness shapes help-seeking in this demographic.

The importance of health literacy was affirmed in this study through its consistent negative associations with total barriers to help-seeking and all subscales except for control and self-reliance. These findings reinforce existing evidence that young men with higher health literacy are better able to identify symptoms, navigate health care systems, and access appropriate services (Mursa et al., 2024; Palmer et al., 2024). Lower privacy and emotional control barriers among men with higher health literacy suggest that increased understanding and confidence in health care contexts may reduce the perception that expressing vulnerability during help-seeking is problematic or unacceptable. However, the lack of an association with control and self-reliance suggests that health literacy may not influence masculine norms that emphasize autonomy. This finding contrasts with previous research suggesting that masculine traits such as self-reliance and emotional control may hinder the communicative and interactive aspects of health literacy, thereby discouraging men from openly discussing their health concerns (Milner et al., 2019).

The absence of an association between social support and barriers was unexpected, given its frequent identification in qualitative literature as a critical determinant of help-seeking (Palmer et al., 2024). One possible explanation is that the measure used in this study assessed the perceived availability of others who could provide emotional support and encouragement; the measure did not assess other recognized dimensions of social support such as practical assistance and information (Heaney & Israel, 2008), nor did it examine the normative attitudes within support networks that may have a bearing upon male help-seeking (Zimet et al., 1988). Research suggests that the impact of social support on young men’s help-seeking is highly context-dependent (Palmer et al., 2024). Support from individuals with negative perceptions of male help-seeking may act as a barrier, discouraging engagement, whereas support from those with positive attitudes can serve as a facilitator, encouraging help-seeking behavior (Nagai, 2015; Palmer et al., 2024). These nuances could explain the divergence between qualitative and quantitative findings and warrant further investigation.

The finding that higher health empowerment was linked to lower concrete barriers and distrust of caregivers suggests that empowered young men feel more capable of navigating practical and interpersonal challenges involved in seeking help. This builds on prior research identifying a link between general self-efficacy and lower barriers to help-seeking (Boman & Walker, 2010). In addition, a small indirect association between loneliness and concrete barriers and distrust of caregivers was observed through health empowerment, suggesting that health empowerment may buffer the relationship between loneliness and help-seeking. These findings provide support for the theoretically proposed role of empowerment as a mechanism affecting help-seeking and suggest that strategies to promote social connection in young men may have greater impacts on service usage if they incorporate elements that foster empowerment, such as skill development, role modeling and problem solving.

A key strength of this study is its use of probabilistic sampling, enhancing the representativeness of findings for young Australian men. However, several limitations should be acknowledged. The use of cross-sectional data means that directionality of associations cannot be confirmed. The exclusion of non-English speakers, individuals without internet or phone access and low representation of men from rural locations also likely reduced our ability to explore cultural and geographical factors that could influence help-seeking behaviors. In addition, the reliance on self-reported data introduces the potential for social desirability biases (Althubaiti, 2016). However, this risk is reduced by the anonymous data collection process (Larson, 2019).

This study highlights the important roles of loneliness, health literacy and health empowerment in shaping help-seeking among young men. Loneliness and health literacy were identified as consistent predictors of barriers to help-seeking, while the relationship between health empowerment on lower concrete barriers and distrust of caregivers adds an important dimension to the evidence base. The absence of associations with social support suggests that future research must consider the types of support received in relation to male help-seeking barriers and practices. By clarifying the interactions and relative importance of these factors, it provides valuable evidence to inform the development of targeted interventions. Addressing loneliness and enhancing both health literacy and health empowerment should be central to strategies aimed at reducing barriers and improving health care engagement among young men.

Supplemental Material

sj-docx-1-jmh-10.1177_15579883251412964 – Supplemental material for Determinants of Young Men’s Help-Seeking Behavior: Insights From a National Australian Survey

Supplemental material, sj-docx-1-jmh-10.1177_15579883251412964 for Determinants of Young Men’s Help-Seeking Behavior: Insights From a National Australian Survey by Robert Palmer, James Kite, Philayrath Phongsavan, Katherine B. Owen, Timothy J. Moss, Bernie Marshall and Ben J. Smith in American Journal of Men's Health

Supplemental Material

sj-docx-2-jmh-10.1177_15579883251412964 – Supplemental material for Determinants of Young Men’s Help-Seeking Behavior: Insights From a National Australian Survey

Supplemental material, sj-docx-2-jmh-10.1177_15579883251412964 for Determinants of Young Men’s Help-Seeking Behavior: Insights From a National Australian Survey by Robert Palmer, James Kite, Philayrath Phongsavan, Katherine B. Owen, Timothy J. Moss, Bernie Marshall and Ben J. Smith in American Journal of Men's Health

Footnotes

Acknowledgements

The authors would like to acknowledge Simon von Saldern, CEO of Healthy Male, and Nicole Halim for their contributions to the survey development. Contributions made by medical, nursing, and allied health advisors of Healthy Male in developing the survey are also gratefully acknowledged.

ORCID iD

Robert Palmer

Ethical Considerations

Ethics approval for this study was acquired from the Monash University Human Research Ethics Committee (Approval No. 27289) on 05/03/2021. All participants provided written informed consent prior to participation.

Consent to Participate

Participants provided written informed consent to take part in the study.

Consent for Publication

Participants provided written informed consent for the publication of the data presented in this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The authors wish to acknowledge the funding support for the lead author from the Men of Malvern and Healthy Male. Healthy Male, the organization which conducted this national survey, is funded by the Australian Department of Health.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The data underlying the results presented in this study will be made publicly available upon publication of this article in the Monash University Figshare Research Repository at DOI: 10.26180/28449137.

Supplemental Material

Supplemental material for this article is available online.

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