Skip to main content
NCBI home page
Springer Nature - PMC COVID-19 Collection logoLink to Springer Nature - PMC COVID-19 Collection
. 2023 Mar 1:1–10. Online ahead of print. doi: 10.1007/s12144-023-04329-2

The relationships between perceived mental illness prevalence, mental illness stigma, and attitudes toward help-seeking

Luke Evans 1,2,✉, Alexander Chang 1, Jewell Dehon 1, Madison Streb 1, Madeline Bruce 1, Eddie Clark 1, Paul Handal 1
PMCID: PMC9975862  PMID: 37359578

Abstract

Previous research suggests that, despite the commonality of mental illness in the United States, the majority of U.S. individuals with mental illness do not seek treatment. One important factor that contributes to this lack of treatment utilization is mental illness stigma. Such stigma may result, in part, from many individuals in the U.S. underestimating the prevalence of mental illness. To test whether this is the case, 638 adults from across the U.S. completed measures related to perceived prevalence of mental illness, private stigma, perceived public stigma, and help-seeking. Findings indicated participants significantly underestimated the given-year prevalence rate of mental illness. The perceived given-year prevalence rate was significantly correlated with lower private stigma and more positive attitudes towards help-seeking. Personal stigma significantly predicted attitudes towards help-seeking. Findings also suggested that individuals who have received mental health services have a higher perceived prevalence rate of mental illness, as well as lower levels of personal stigma and more positive attitudes towards help-seeking. These findings support the notion that helping the general public recognize the true prevalence rate of mental illness could reduce personal mental illness stigma and facilitate help-seeking behaviors. However, future experimental studies are needed to test this hypothesis.

Keywords: Perceived prevalence, Mental illness stigma, Help-seeking behaviors

Nearly half (47.4%) of all individuals in the United States will meet criteria for a mental illness at some point in their lives (Kessler et al., 2007). Prior to the COVID-19 pandemic, the Substance Abuse and Mental Health Services Administration (SAMHSA; 2020) estimated that approximately 20.6% of U.S. adults (about 51.5 million individuals) meet criteria for a mental illness in a given year. However, the incidence of mental illness has increased since the onset of the COVID-19 pandemic. Ettman et al. (2020) found that the overall prevalence rate of depression increased significantly during the COVID-19 pandemic (from 24.7 to 52.4%), while Nochaiwong et al.’s (2021) meta-analysis found that prevalence rates for depression and anxiety in the United States were approximately 34.2% and 40.0%, respectively. Furthermore, Twenge and Joiner (2020) estimated that 70.4% of U.S. adults fit criteria for moderate to severe mental distress (as measured by the K6; Kessler et al., 2002), while Nochaiwong et al. (2021) indicated that 80.2% of adults in the Americas experienced psychological distress during the COVID-19 pandemic.

Yet, despite the widespread nature of mental illness, only 43.3% of U.S. adults with a mental illness receive treatment each year, indicating that millions of U.S. adults remain untreated (SAMHSA, 2020). In addition to costing the United States an estimated $300 billion per year (Hunt et al., 2016), untreated mental illness places a serious social and psychological burden on individuals with mental illness and their families, from psychological distress, negatively impacted relationships, social isolation, and suicide (Clarke et al., 2006; Gulati & Kelley, 2020; Kisely et al., 2006). Consequently, it is important to identify and address factors that might be preventing nearly 60% of individuals with mental illness from seeking treatment. The present study seeks to further investigate how perceived prevalence of mental illness may relate to two factors that have been shown to be related to help-seeking behaviors; mental illness stigma and attitudes towards help-seeking (Magaard et al., 2017).

Mental illness stigma in the United States

Research suggests that many U.S. individuals hold stigmatizing views about people with mental illness and limit their interaction with those who have mental illness (Parcesepe and Cabassa, 2013). Common stigmatizing views include the ideas that people with mental illnesses are dangerous, incompetent, prone to violence, and have mental illnesses because they did something wrong and being “punished” (Corrigan & Watson, 2002; Parcesepe & Cabassa, 2013). Although some research suggests that mental illness stigma is decreasing (e.g., Pescosolido et al., 2021), many individuals in the United States still hold stigmatizing views. For example, 49% of U.S. adults said they would not date someone with a mental illness, 33% agreed that people with mental illness scared them, and 39% indicated that they would view someone differently if they found out that they had a mental illness (APA, 2019).

Mental illness stigma is often conceptualized as existing at two broad levels: public stigma (i.e., negative beliefs about mental illness that exist at the societal/communal level) and private stigma (i.e., negative beliefs about mental illness that an individual holds; Eisenberg et al., 2009). In other words, public stigma can be conceptualized as the degree of stigma towards mental illness that one believes others hold at a societal level, while personal stigma can be conceptualized as the degree of stigma that one personally holds towards mental illness. Both levels relate to a variety of negative outcomes, such as psychological distress, treatment delay, premature treatment drop-out, more negative views toward seeking help for mental health issues, and reduced help-seeking behaviors (Barksdale & Molock, 2009; Clement et al., 2015; Eisenberg et al., 2009; Kulesza et al., 2015; Masuda et al., 2009, 2012; Masuda & Latzman, 2011). Individuals with mental illness might avoid seeking treatment due to fear of being labelled as mentally ill and facing discrimination and/or rejection from others (Kulesza et al., 2015). Such findings highlight the importance of identifying factors that might influence mental illness stigma in order to redress it.

Perceived prevalence of mental illness

While several studies have investigated the prevalence of mental illness stigma (e.g., Parcesepe & Cabassa 2013) and the prevalence of mental illness (e.g., Kessler et al., 2007), there has been minimal research on perceived prevalence of mental illness in light of these two factors. The existing research suggests that individuals underestimate the prevalence of mental illness. Turetsky and Sanderson (2018) found that college students underestimated the percentage of students on campus (1) who sought help from the college counseling center by 16–18%, (2) who felt so depressed that it was hard to function by 27–31%, (3) who seriously contemplated suicide by approximately 10%, and (4) who felt overwhelmed by all that they had to do in the past 12 months by approximately 18–22%. This discrepancy is problematic, especially since research that suggests that understanding mental illness as rare is associated with increased mental illness stigma (Feldman & Crandall, 2007). It is also worth noting that many of these discrepancies and perceived public stigma were significantly reduced after participants received brief interventions aimed at correcting perceived norms related to mental illness on campus, further suggesting that perceived norms have an impact on mental illness stigma.

The influence of perceived norms on stigma and attitudes toward help-seeking

Social influence theories suggest that when individuals learn a behavior or condition is more common than they previously believed, this can cause them to view this behavior as more acceptable as well (Deutsch & Gerard, 1955; Mulla et al., 2019; Rivis & Sheeran, 2003). There is extensive research indicating that perceived descriptive norms (i.e., beliefs about how others view a specific situation) relating to a behavior/condition influence individuals’ behavior and acceptance of that behavior/condition (Rivis & Sheeran, 2003) These effects were found across a variety of domains, including topics such as pro-environmental behaviors, intimate partner violence (IPV), and mental illness stigma (Göckeritz et al., 2010; Mulla et al., 2019; Norman et al., 2008).

While there are several potential hypotheses as to why descriptive norms impact behavior, they all relate to social comparison theory and social learning theory (Bandura & Walters, 1977; Festinger, 1954). These theories propose that individuals learn what opinions, beliefs, and behaviors are acceptable based on seeing/hearing the opinions, beliefs, and behaviors of others. More recent theoretical underpinnings that relate to these overarching theories include Modified Labeling Theory (MLT; Link et al., 1989) and the Theory of Planned Behavior (TPB; Ajzen, 1991). The MLT proposes that people become aware of stigma toward individuals with mental illness early in their lives as a part of cultural socialization (e.g., through media portrayals or messages from others), which leads to awareness of public stigma and the expectation that society might negatively evaluate individuals who have mental health issues and/or seek help for mental health issues (Kulesza et al., 2015; Link et al., 1989). The TPB can further explain how this might translate to reduced help-seeking behaviors. The TPB proposes that one’s behavior is influenced by intentions to engage in a behavior, attitudes toward the behavior, perceived social norms, and perceived control over a behavior (Ajzen, 1991). Thus, if individuals believe that there are negative social norms around mental illness and/or help-seeking, they would be less likely to seek help (Chandrasekara et al., 2016). Such perceived social norms can also impact individuals’ attitudes and intentions toward help-seeking behavior, further impacting this behavior (Chandrasekara et al., 2016). Thus, changing perceived norms around mental illness could impact individuals’ beliefs and behaviors by changing their perceptions of public stigma and/or their levels of personal stigma, although this hypothesis needs to be tested.

Overview of present study and hypotheses

Given the substantial negative impact of mental illness stigma (e.g., Clement et al., 2015) it is important to identify factors contributing to it. One possible factor is a perceived under-estimation of mental illness, which the theory of planned behavior predicts could negatively influence help-seeking behaviors. While past research has provided support for the notion that perceived prevalence impacts mental illness stigma (e.g., Turetsky & Sanderson, 2018), no studies could be identified that investigate this relationship directly. The present study aimed to address this gap in the literature first testing the hypothesis that the perceived prevalence of mental illness is lower than the actual prevalence of mental illness. The present study then tested the hypothesis that the perceived prevalence of both given-year and lifetime mental illness will relate to lower levels of stigma and more positive attitudes towards help-seeking. Lastly, since stigma and attitudes toward help-seeking are related to mental health treatment utilization (e.g., Elhai et al., 2008; Kulesza et al., 2015), it was also hypothesized that those who have not received services will report lower perceived prevalence rates of mental illness than those who received services in the past or are presently receiving services. For the sake of clarity, a summary of the present hypotheses is provided below:

Hypothesis 1

The perceived past-year and lifetime prevalence rates of mental illness will be lower than the actual prevalence rates.

Hypothesis 2

A higher perceived prevalence rate will be associated with lower personal and public stigma and more positive attitudes towards help-seeking.

Hypothesis 3

Individuals who have not received psychological services will have lower perceived prevalence rates of mental illness than those who received services in the past or are presently receiving services.

Methods

Participants

A power analysis conducted using GPower V3.1.9 and correlation coefficients for perceived norms obtained from past literature suggested that a sample size of at least 348 would be necessary to detect meaningful effects (Mulla et al., 2019; Norman et al., 2008). The final sample included 638 participants from the U.S. through Amazon’s Mechanical Turk (mTurk) marketplace. Participants were between the ages of 18 and 73 (M = 37.34, Median = 35, SD = 12.05). They identified as primarily female (60.7%) or male (37.6%), with the remaining participants (1.7%) identifying as transgender, gender non-binary, or genderqueer. In terms of race and ethnicity, most participants were White/European American (69.3%), Black/African American (8.6%), Asian/Asian American (8.5%), or Hispanic/Latinx American (7.5%), with the remaining participants (6.1%) identifying as a different race/ethnicity (e.g., Multi-Racial/Multi-Ethnic, Native American/Native Alaskan, or South Asian/Indian American).

Participants reported living in the Southeast (28.7%), Midwest (24%), Northeast (19.3%), West (17.6%), or Southwest (10.3%) region of the United States. The average annual income for participants was approximately $42,000 (SD = ~$56,000), whereas the average household income was approximately $67,000 (SD = ~$104,000). Most participants reported that they were employed full-time (58.9%), whereas 21.2% indicated that they were employed part-time, and 19.7% reported that they were unemployed (0.2% declined to answer). Regarding level of education, 0.8% of the sample completed some high school or less, 9.7% obtained a high school diploma or GED, 8.8% completed some junior college credits, and 9.2% completed an associate degree. Additionally, 9.4% completed some credits at a 4-year college and 37.1% of participants reported completing a bachelor’s degree. In terms of graduate school, 2.7% completed some graduate school, 19.7% completed a master’s degree, and 2.5% completed a doctoral degree. Of the participants who reported currently attending school (18.7%), more attended school full-time (11.8%) than part-time (6.7%).

Lastly, participants were also asked about their utilization of mental health services. Half (50.0%) of the participants reported never using services, 33.1% reported previously using services, and 16.8% reported currently using services. One participant declined to answer this question.

Measures

Perceived prevalence of mental health disorders

To assess participants’ perceived prevalence of mental health disorders, participants were asked to “Please estimate the percentage of the general U.S. population that you believe meet criteria for a mental health disorder in a given year (from 0–100%),” and to, “Please estimate the percentage of the general U.S. population that you believe meet criteria for a mental health disorder at any point in their lives (from 0–100%).” Other studies have used similar approaches to study the perceived descriptive norms of other phenomena, such as IPV (Mulla et al., 2019; Neighbors et al., 2010).

Perceived public mental illness stigma

Perceived public stigma was assessed using the Devaluation-Discrimination measure (DD; Link, 1987). This scale asks participants to rate their agreement with 12 statements relating to normative beliefs about current/former mental patients (e.g., “Most people would willingly accept a former mental patient as a close friend”) on a six-point scale (ranging from “Strongly Disagree” to “Strongly Agree”). Item ratings are averaged, giving a score ranging from 1–6, with higher scores indicating greater perceived public mental illness stigma. The DD is one of the most widely used measures of perceived public stigma regarding mental illness (Wei et al., 2015). This scale demonstrates good internal consistency in the current sample (α = .87) and past samples (α = .88), as well as convergent validity with relevant constructs (e.g., social withdrawal for those with mental health disorders; Link et al., 1987; Link et al., 2001).

Personal mental illness stigma

To assess personal mental illness stigma, participants completed a modified version of the Discrimination-Devaluation Scale. This scale was modified by replacing “Most people…” with “I…”on each item to capture personal attitudes, rather than perceived public attitudes (e.g., “I believe that a former mental patient is just as trustworthy as the average person”). This scale (referred to as the Personal Stigma Scale or PSS) asks participants to rate their agreement on 12 statements relating to their own perceptions of individuals with mental illness. Ratings are made on a six-point scale (ranging from “Strongly Disagree” to “Strongly Agree”). The items on this scale are summed and averaged, giving a score ranging from 1–6 with higher scores indicating greater stigma. A similarly modified version of the PSS has been successfully used in other studies (e.g., De Freitas et al., 2018), demonstrated good internal consistency (α = .89), and was associated with relevant constructs (e.g., public stigma and help-seeking; Eisenberg et al., 2009). The present version of the scale was found to have high internal consistency as well (α = .92).

Personal attitudes toward help-seeking

Participants completed a modified version of the Attitudes Toward Seeking Professional Psychological Help Scale - Short Form (ATSPPH-SF; Elhai et al., 2008) to assess their personal attitudes toward mental health help-seeking. This 10-item scale asks participants to rate their agreement with statements related to help-seeking (e.g., “I would want to get psychological help if I were worried or upset for a long period of time”) on a four-point scale (0 to 3), with higher scores indicating more positive attitudes toward help-seeking. The minimum possible score is zero, and the maximum possible score is 30. The ATSPPH-SF is one of the most commonly used measures of attitudes toward health-seeking (Wei et al., 2015), has evidenced good internal consistency (α = 0.78), and was found to be associated with less treatment-related stigma, greater intentions to seek treatment in the future, recent use of mental health treatment, and intensity of recent treatment (Elhai et al., 2008). The wording of this scale was slightly changed in the present study (i.e., changing “psychologist” to “mental health professional” and “psychotherapy” to “mental health services”), due to the variety of professionals who now provide mental health services. The internal consistency of this modified scale remained high (α = 0.82).

Demographics

Participants completed demographics questions related to their age, gender identity, race/ethnicity, geographic region, education, income, work status, and use of mental health services.

Procedures

After receiving approval from the home university’s Institutional Review Board, N = 800 participants were recruited through mTurk. Data was collected between April and May of 2021, during the heart of the COVID-19 pandemic. The survey description was only displayed to potential mTurk participants who were in the United States and had been approved for at least 95% of their previous tasks on mTurk. After reading the study description and clicking on the survey link in mTurk, participants were redirected to a Qualtrics survey. Participants were then presented with an informed consent statement. If participants consented to participate, indicated by selecting the corresponding radio button and continuing the study, they completed the remaining survey questionnaires. The questionnaires were presented in a random order, except for the demographic questionnaire, which always appeared last. Three validity checks were embedded throughout the study (e.g., “The answer to this question is ‘Agree.’ Please select ‘Agree’ to indicate you are paying attention”). Participants took a median of 5 min and 50 s to complete the survey and were compensated $0.15, which is similar to the rate of compensation for other psychological research studies (e.g., Casler et al., 2013; Lace et al., 2020).

Results

Preliminary analyses

Analyses were completed using SPSS 27. After removing 105 participants with incomplete data and 57 participants who did not pass all three validity checks, a final sample of 638 participants remained. The means and standard deviations of the study variables are provided in Table 1.

Table 1.

Means and Standard Deviations of Main Study Variables

Variable Mean (SD)
Perceived Past-Year Prevalence of Mental Illness (%) 44.35 (24.40)
Perceived Lifetime Prevalence of Mental Illness (%) 54.87 (25.73)
Perceived Public Stigma 3.40 (0.83)
Personal Stigma 2.40 (1.01)
Attitudes Toward Help-Seeking 19.09 (5.91)
Open in a new tab

Established norms were not available for perceived prevalence rate. Perceived public stigma scores were lower than those reported in the initial validation sample of community respondents (3.40 in the present study vs. 4.03 to 4.33; Link 1987). However, these differences may be related to mental illness stigma generally declining over the past 30 years (e.g., APA, 2019; Pescosolido et al., 2021). Previous private stigma scores could not be identified for adult community population, although the present score of 2.40 was similar to those previously reported in college populations. Specifically, they were higher than those reported by Eisenberg et al., 2009 (2.01) and lower than those reported by De Freitas et al., 2018 (3.04 to 3.37). Attitudes Towards Help-Seeking scores (19.09) were similar to those reported in the original validation sample of college students and medical patients (16,63 to 23.49; Elhai et al., 2008).

Hypothesis 1

The first hypothesis, that participants would underestimate the perceived prevalence of mental illness, was proposed prior to the start of the COVID-19 pandemic. Due to the unavailability of lifetime prevalence rates during/after the pandemic, it could not be tested whether participants underestimated the lifetime prevalence of mental health disorders. There were also no given-year prevalence rates of mental illness during the pandemic that could be identified. However, there were point-prevalence estimates of mental illness during the pandemic (i.e., the mental illness prevalence rate as measured at a specific point in time). These estimates are likely lower than the past-year prevalence rates during the pandemic or lifetime prevalence rates after the pandemic, but they range from approximately 70–80% (Nochaiwong et al., 2021; Twenge & Joiner, 2020). To provide an estimate of given-year prevalence during the pandemic, Twenge and Joiner’s (2020) estimated prevalence rate of 70.4% was used. A one-sample t-test was then conducted to see whether this given-year prevalence rate was different from participants’ perceived prevalence rate. The results of this analysis suggest that participants’ estimated given-year prevalence of mental health disorders (M = 44.34, Median = 45, SD = 24.4) was lower than the prevalence rate reported in the literature t (637) = -26.97, p < .001. These findings support hypothesis 1.

Hypothesis 2

The second hypothesis of this study was that a higher perceived lifetime and given-year prevalence would be associated with lower personal and public stigma and more positive attitudes toward help-seeking. To test this hypothesis, Pearson’s correlations were calculated between the main study variables. These correlations are provided in Table 2 below.

Table 2.

Correlations of Main Study Variables

Variable 1 2 3 4 5
1. Perceived Given-Year Prevalence of Mental Illness (%) 1 - - - -
2. Perceived Lifetime Prevalence of Mental Illness (%) 0.80* 1 - - -
3. Perceived Public Stigma − 0.01 − 0.04 1 - -
4. Personal Stigma − 0.03 − 0.24* 0.27* 1 -
5. Attitudes Toward Help-Seeking 0.037 0.15* − 0.16* − 0.64* 1
Open in a new tab

Note. * p < .01

As seen in Table 2, perceived given-year prevalence rate was only correlated with perceived lifetime prevalence (r = .80). While perceived lifetime prevalence rate was also not associated with perceived public stigma, it was weakly but significantly correlated with personal stigma (r = − .24) and attitudes toward help-seeking (r = .16), as predicted. These findings suggest that estimating a higher lifetime prevalence of mental illness was associated with lower levels of private stigma and more positive attitudes toward help-seeking. Attitudes toward help-seeking were negatively correlated with personal stigma (r = − .64), such that those with more positive attitudes towards help-seeking had less personal stigma. Further, higher positive attitudes toward help-seeking were weakly associated with public stigma (r = − .16).

To test whether stigma and/or perceived prevalence rates predict help-seeking attitudes, a multiple regression analysis was conducted. Age and gender were controlled for in this multiple regression due to research suggesting that these factors can also impact help-seeking and stigma (e.g., Mackenzie et al., 2006; Topkaya, 2014). Results from the multiple regression were statistically significant, F(4, 686) = 107.2, adjusted R2 = 0.38, p < .001, such that personal stigma significantly predicted attitudes towards help-seeking, β = 0.63, t = 18.99, p < .001, while perceived public stigma, perceived lifetime prevalence, and perceived given year prevalence rates were not significant predictors, p = .77, p = .66, and p = .51, respectively.

Hypothesis 3

The third hypothesis stated that participants who have not received psychological services would have lower perceived prevalence rates than those who have received or are receiving such services. Results suggest there were significant mean differences between those who had never, had previously, and were currently using mental health services on perceived prevalence of mental illness over both a given year, F(2,634) = 5.76, p = .003, and across their lifetime, F(2,634) = 16.42, p < .001. Tukey’s HSD test demonstrated that those who had never received mental health services estimated lower prevalence rates over a given year (M = 41.24) than those who had previously received treatment (M = 48.34, p = .003). Those who were currently receiving treatment also had a higher perceived given-year prevalence rate (M = 46.01), but there were no significant differences compared to the previous treatment group. Tukey’s HSD also revealed that those who had never received mental health services estimated lower prevalence rates over the lifetime (M = 49.22) than both those who had previously received treatment (M = 62.24, p < .001) and those who were currently in treatment (M = 59.21, p = .001). There were no significant differences between those currently in treatment and those who had previously been in treatment.

Discussion

The present study aimed to provide more clarity on the relationships between the perceived prevalence rate of mental illness, mental illness stigma, and attitudes towards help-seeking. The first hypothesis proposed that the prevalence rate of mental illness would be underestimated while the second hypothesis posited that higher perceived prevalence rates and lower stigma would be associated with greater help-seeking attitudes. The third hypothesis stated that those who had not sought treatment would have lower perceived prevalence estimates than those with a history of mental health treatment.

The present study’s results support the hypothesis that participants would under-estimate the overall prevalence of mental illness when using Twenge and Joiner’s (2020) point-estimate of 70.4%. It should be noted that while official prevalence rates during the COVID-19 pandemic are currently unavailable, estimates in the literature support the notion that the present participants underestimated the prevalence of mental illness. For instance, in addition to Twenge and Joiner’s (2020) prevalence rate of 70.4% for mental distress, other studies found point prevalence estimates of 80% for psychological distress, 56% for depression alone, and 30–40% prevalence for depression, anxiety, and posttraumatic stress symptoms (Ettman et al., 2020; Nochaiwong et al., 2021). Since these studies all report point-estimates, it is safe to assume that the year-long prevalence rates of mental illness during the COVID-19 pandemic and lifetime prevalence rates following the pandemic would be higher. Consequently, while the present findings suggest that the public may be more aware of mental health difficulties during the COVID-19 pandemic, they likely still underestimate the true prevalence rate of mental illness, which is consistent with Hypothesis 1. However, future research should test whether the present findings of individuals underestimating mental illness is reflective of overall beliefs or simply a result of the recent increase in mental health concerns given the disruption of the pandemic.

In discussing the findings related to hypothesis 1, it is also important to note that this study’s results demonstrate a high mean approximation of mental illness prevalence by the general population in the past year (44.35%) and across the lifetime (54.87%). One possible and initially unforeseen factor that might account for this higher-than-anticipated perceived prevalence rate was the COVID-19 pandemic, during which mental illness worsened for many individuals (Ettman et al., 2020). Although the perceived prevalence rates in the present study would be overestimates when compared to pre-pandemic prevalence rates (20.6% year; 47.4% lifetime; SAMHSA, 2020 and Kessler et al., 2007), they are likely underestimates during the COVID-19 pandemic. This suggests the high mean prevalence approximation may be a result of the increased discussion and normalization of mental health in the media during the pandemic. Another possible explanation for this finding may be the sample population’s high levels of education compared to the general population. According to the United States Census Bureau, in 2021 23.5% and 14.4% of Americans reported a bachelor’s degree and a professional degree respectively as their highest level of education. These statistics demonstrate notable difference from the present sample population, with nearly 40% having obtained a bachelor’s degree and 22.4% having completed a master’s or doctorate degree. It is possible that higher levels of education may be associated with greater awareness of mental health difficulties and therefore contributing to a higher mean estimate, although this hypothesis will need to be tested.

The hypothesis that higher perceived prevalence rates would be associated with lower mental illness stigma and higher positive attitudes towards help-seeking (Hypothesis 2) was also supported, in part. Year and lifetime perceived prevalence were highly correlated (r = .80), suggesting conceptual overlap. That said, the given-year prevalence rates were unrelated to any other variable in the study. Lifetime prevalence rates were weakly to moderately correlated with lower personal stigma, but were not associated with public stigma, providing some support for the initial hypothesis that as people understand mental illness as more common and less otherized, negative stereotyping of mental illness may begin to wane. While it is unclear why personal and public stigma are operating differently to influence attitudes and behavior, it could be that perceived personal prevalence and personal stigma are more conceptually related to each other since they both reflect the beliefs of the individual. Relatedly, perhaps perceived public stigma would be more related to estimates of the public’s perceived prevalence rate (i.e., the perceived prevalence rate of mental illness that one would estimate for society in general). However, this and other potential explanations for observed differences between personal and public stigma should be further explored in future studies. The weak but positive correlations between positive attitudes toward help-seeking and perceived lifetime prevalence rates provide some support for the notion that given a certain universality of mental health difficulties, seeking help is respected and encouraged. These findings are consistent with past studies suggesting relationships between stigma and help-seeking behaviors (e.g., Kulesza et al., 2015) and between perceived descriptive norms and acceptability of a behavior (e.g., Mulla et al., 2019). However, experimental studies are necessary before any causation can be concluded.

Lifetime prevalence rates were unrelated to public stigma, which was unexpected. It is possible that positive notions of people seeking help for mental illness are resilient to negative cultural narratives, but—consistent with Eisenberg et al.’s 2009 findings— internalized stigma regarding mental illness does impede seeking help. Because given-year prevalence rates were unrelated to expected variables, the findings might reflect the aberrant year the data were collected (2021). Replication post-pandemic is needed to further understand these relationships.

Additionally, a multiple regression analysis found that when controlling for age and gender, personal stigma significantly predicted attitudes towards help-seeking whereas perceived lifetime prevalence rate and given-year prevalence rate did not. These findings are consistent with past research emphasizing the importance of personal stigma in terms of help-seeking (e.g., Clement et al., 2015). Findings that personal stigma was correlated with perceived lifetime prevalence suggest that perceived prevalence rates could impact help-seeking attitudes indirectly (e.g., via personal stigma), but further studies that implement temporal and causal designs are needed to test such a hypothesis. The present results support Hypothesis 3, which proposed that those who have received mental health services would have higher perceived prevalence rates than those who have never received treatments. Indeed, those who never sought mental health treatment perceived both the given-year and lifetime prevalence rates as lower than those who are currently in treatment or have sought treatment in the past. This suggests that those who do not seek mental health services may not see mental illness as a significant or common problem, perhaps because they do not experience it. Another explanation could be that they do not seek treatment because they are deterred from seeking help or are not aware of opportunities for help. This line of thought, along with the findings of Hypothesis 2, are consistent with the TPB (Ajzen, 1991) in that choosing not to seek treatment may result from stigmatizing attitudes of mental illness and perceptions that mental illness is not common. However, given the various possible causal relationships between these variables, such that perceived prevalence could impact help-seeking attitudes, which in turn could impact usage, etc., future studies are needed to identify the temporal, and possibly bidirectional, relationships between help-seeking attitudes, usage of psychological services, and perceived prevalence of mental illness.

Implications

This study implies that most adults in the United States underestimate the prevalence of mental illness, a lower perceived prevalence rate is associated with increased personal stigma, and perceived prevalence rate might relate to mental health service utilization. Given that previous studies have found that education about true prevalence rates can change individuals’ attitudes and behaviors (e.g., Mulla et al., 2019), the present study supports the notion that educating individuals on the true prevalence rate of mental illness could be a way to influence stigma and help-seeking attitudes in relation to mental illness. However, future experimental studies are needed to test this hypothesis. Furthermore, such a hypothesis may be difficult to test until broader-scale estimates of the true prevalence of mental illness following the COVID-19 pandemic are available. Should these findings garner additional support, a translational approach to the data may be warranted. Specifically, direct productive public health endeavors could provide updated and accurate data on prevalence, along with the resources to address the growing need for mental health services that may rise as the public grows in awareness. By reducing stigma and increasing treatment participation, individual and communal hardships due to mental illness may be further alleviated to promote healthier outcomes at home, at work, and in communities.

Limitations and future directions

It is important to consider the results and implications of the present investigation in the context of the present study’s limitations. One such limitation is that the present study was conducted during the COVID-19 pandemic. While it seems unlikely that this pandemic would affect the present findings in a significant way other than raising the overall actual and perceived prevalence rate, it remains to be seen whether the present results will hold after this pandemic is over. An additional limitation to the present study is that participants may define mental illness in different ways. Future studies that aim to replicate and extend the present findings would likely benefit from asking participants for their definitions of mental illness to provide more information on definitions of mental illness might impact perceived prevalence. It could also prove beneficial to provide participants with a specific definition of mental illness, although such a definition could impact perceived prevalence rates. A final limitation is that a large portion of participants have received mental health services (approximately 50%) and identified as female (approximately 60%), which may limit the generalizability of this study. It will therefore be important for future research to replicate the current study while using a more representative sample and/or controlling for use of mental health services and gender.

Additional future research could investigate whether mental illness status might change the present findings, given that individuals with or without mental illness experience the stigma of mental health differently. It could also be beneficial for future studies to test whether perceived prevalence relates to distress in individuals with mental illness, given that mental illness stigma is often associated with distress in those with mental illnesses (e.g., Masuda et al., 2009). Given the impact that cultural factors such as age, gender, and race/ethnicity can have on mental illness stigma (e.g., Bradbury 2020, Crowe & Kim, 2020; Conner et al., 2009), it will also be important for future studies to investigate how the present results may be influenced by participants’ unique cultural backgrounds. A final avenue for future research would be to test whether educating individuals about the true prevalence of mental illness and/or using other strategies aimed at reducing prejudice (e.g., perspective taking and stereotype replacement; Devine et al., 2012) could prove beneficial in reducing mental illness stigma and consequently increasing help-seeking behaviors. Similar approaches have been found effective for reducing racial prejudice (e.g., Devine et al., 2012). These potential studies could build on the present findings to better understand factors contributing to mental illness stigma, how to reduce such stigma, and ways to promote help-seeking behaviors.

Conclusion

Overall, the present study suggests that many individuals in the United States might underestimate the prevalence of mental illness and that lower perceived prevalence rates might be associated with increased personal stigma and mental health utilization. Future researchers should build upon these findings by seeing whether these findings hold after the COVID-19 pandemic, differ in those with and without mental health disorders, and whether providing psychoeducation about the true prevalence of mental illness might impact stigma or help-seeking behaviors.

Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Declarations

Disclosure of potential conflicts of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Ethics approval

All procedures performed in the study were approved by the Saint Louis University Institutional Review Board and were in accordance with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all participants prior to them completing the study.

Footnotes

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  1. Ajzen I. The theory of planned behavior. Organizational Behavior and Human Decision Processes. 1991;50(2):179–211. doi: 10.1016/0749-5978(91)90020-T. [DOI] [Google Scholar]
  2. American Psychological Association (2019). Survey: Americans Becoming More Open About Mental Health. Retrieved from: https://www.apa.org/news/press/releases/apa-mental-health-report.pdf
  3. Bandura A, Walters RH. Social learning theory. Prentice Hall: Englewood cliffs; 1977. [Google Scholar]
  4. Barksdale CL, Molock SD. Perceived norms and mental health help-seeking among african american college students. The Journal of Behavioral Health Services & Research. 2009;36(3):285–299. doi: 10.1007/s11414-008-9138-y. [DOI] [PubMed] [Google Scholar]
  5. Bradbury A. Mental health stigma: the impact of age and gender on attitudes. Community Mental Health Journal. 2020;56(5):933–938. doi: 10.1007/s10597-020-00559-x. [DOI] [PubMed] [Google Scholar]
  6. Casler K, Bickel L, Hackett E. Separate but equal? A comparison of participants and data gathered via Amazon’s MTurk, social media, and face-to-face behavioral testing. Computers in Human Behavior. 2013;29(6):2156–2160. doi: 10.1016/j.chb.2013.05.009. [DOI] [Google Scholar]
  7. Chandrasekara WS. Help-seeking attitudes and willingness to seek psychological help: application of the theory of planned behavior. International Journal of Management Accounting and Economics. 2016;3(4):233–245. [Google Scholar]
  8. Clarke M, Whitty P, Browne S, McTigue O, Kamali M, Gervin M, Kinsella A, Waddington JL, Larkin C, O’Callaghan E. Untreated illness and outcome of psychosis. The British Journal of Psychiatry. 2006;189:235–240. doi: 10.1192/bjp.bp.105.014068. [DOI] [PubMed] [Google Scholar]
  9. Clement S, Schauman O, Graham T, Maggioni F, Evans-Lacko S, Bezborodovs N, Morgan C, Rüsch N, Brown JS, Thornicroft G. What is the impact of mental health-related stigma on help-seeking? A systematic review of quantitative and qualitative studies. Psychological Medicine. 2015;45(1):11–27. doi: 10.1017/S0033291714000129. [DOI] [PubMed] [Google Scholar]
  10. Conner KO, Koeske G, Brown C. Racial differences in attitudes toward professional mental health treatment: the mediating effect of stigma. Journal of Gerontological Social Work. 2009;52(7):695–712. doi: 10.1080/01634370902914372. [DOI] [PubMed] [Google Scholar]
  11. Corrigan PW, Watson AC. Understanding the impact of stigma on people with mental illness. World Psychiatry. 2002;1(1):16. [PMC free article] [PubMed] [Google Scholar]
  12. Crowe A, Kim T. Ethnicity, life satisfaction, stress, familiarity, and stigma toward mental health treatment. Journal of Counseling & Development. 2020;98(1):83–93. doi: 10.1002/jcad.12302. [DOI] [Google Scholar]
  13. DeFreitas SC, Crone T, DeLeon M, Ajayi A. Perceived and personal mental health stigma in latino and african american college students. Frontiers in Public Health. 2018;6:49. doi: 10.3389/fpubh.2018.00049. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Deutsch M, Gerard HB. A study of normative and informational social influences upon individual judgment. The Journal of Abnormal and Social Psychology. 1955;51:629–636. doi: 10.1037/h0046408. [DOI] [PubMed] [Google Scholar]
  15. Devine PG, Forscher PS, Austin AJ, Cox WT. Long-term reduction in implicit race bias: a prejudice habit-breaking intervention. Journal of Experimental Social Psychology. 2012;48(6):1267–1278. doi: 10.1016/j.jesp.2012.06.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Eisenberg D, Downs MF, Golberstein E, Zivin K. Stigma and help-seeking for mental health among college students. Medical Care Research and Review. 2009;66(5):522–541. doi: 10.1177/1077558709335173. [DOI] [PubMed] [Google Scholar]
  17. Elhai JD, Schweinle W, Anderson SM. Reliability and validity of the attitudes toward seeking professional psychological help scale-short form. Psychiatry Research. 2008;159(3):320–329. doi: 10.1016/j.psychres.2007.04.020. [DOI] [PubMed] [Google Scholar]
  18. Ettman, C. K., Abdalla, S. M., Cohen, G. H., Sampson, L., Vivier, P. M., & Galea, S. (2020). Prevalence of depression symptoms in US adults before and during the COVID-19 pandemic. JAMA Network Open, 3(9), 10.1001/jamanetworkopen.2020.19686 [DOI] [PMC free article] [PubMed]
  19. Feldman DB, Crandall CS. Dimensions of mental illness stigma: what about mental illness causes social rejection? Journal of Social and Clinical Psychology. 2007;26(2):137–154. doi: 10.1521/jscp.2007.26.2.137. [DOI] [Google Scholar]
  20. Festinger L. A theory of social comparison processes. Human relations. 1954;7(2):117–140. doi: 10.1177/001872675400700202. [DOI] [Google Scholar]
  21. Göckeritz S, Schultz PW, Rendón T, Cialdini RB, Goldstein NJ, Griskevicius V. Descriptive normative beliefs and conservation behavior: the moderating roles of personal involvement and injunctive normative beliefs. European Journal of Social Psychology. 2010;40(3):514–523. [Google Scholar]
  22. Gulati G, Kelly BD. Physician suicide and the COVID-19 pandemic. Occupational Medicine. 2020;70(7):514–514. doi: 10.1093/occmed/kqaa104. [DOI] [Google Scholar]
  23. Hunt, G., Greene, R., & Whiting, G. (2016). On pins & needles: Caregivers of adults with mental illness. National Alliance for Caregiving. Retrieved from: https://www.caregiving.org/wpcontent/uploads/2020/05/NAC_Mental_Illness_Study_2016_FINAL_WEB.pdf
  24. Kessler RC, Andrews G, Colpe LJ, Hiripi E, Mroczek DK, Normand SLT, Walters EE, Zaslavsky AM. Short screening scales to monitor population prevalences and trends in non‐specific psychological distress. Psychological Medicine. 2002;32:959–976. doi: 10.1017/s0033291702006074. [DOI] [PubMed] [Google Scholar]
  25. Kessler RC, Angermeyer M, Anthony JC, Graaf DE, Demyttenaere R, Gasquet K, Girolamo IDE, Gluzman G, Gureje S, Haro O, Kawakami JM, Karam N, Levinson A, Medina Mora D, Oakley Browne ME, Posada-Villa MA, Stein J, Adley Tsang DJ, Aguilar-Gaxiola CH, Alonso S, Ustün J. Lifetime prevalence and age-of-onset distributions of mental disorders in the World Health Organization’s World Mental Health Survey Initiative. World Psychiatry. 2007;6(3):168–176. [PMC free article] [PubMed] [Google Scholar]
  26. Kisely S, Scott A, Denney J, Simon G. Duration of untreated symptoms in common mental disorders: association with outcomes: international study. The British Journal of Psychiatry. 2006;189(1):79–80. doi: 10.1192/bjp.bp.105.019869. [DOI] [PubMed] [Google Scholar]
  27. Kulesza M, Pedersen ER, Corrigan PW, Marshall GN. Help-seeking stigma and mental health treatment seeking among young adult veterans. Military Behavioral Health. 2015;3(4):230–239. doi: 10.1080/21635781.2015.1055866. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Lace JW, Evans LN, Merz ZC, Handal PJ. Five-factor model personality traits and self-classified religiousness and spirituality. Journal of Religion and Health. 2020;59:1344–1369. doi: 10.1007/s10943-019-00847-1. [DOI] [PubMed] [Google Scholar]
  29. Link BG. Understanding labeling effects in the area of mental disorders: an assessment of the effects of expectations of rejection. American Sociological Review. 1987;52(1):96–112. doi: 10.2307/2095395. [DOI] [Google Scholar]
  30. Link, B. G., Cullen, F. T., Struening, E., Shrout, P. E., & Dohrenwend, B. P. (1989). A modified labeling theory approach to mental disorders: an empirical assessment. American Sociological Review, 400–423. 10.2307/2095613
  31. Link BG, Struening EL, Neese-Todd S, Asmussen S, Phelan JC. Stigma as a barrier to recovery: the consequences of stigma for the self-esteem of people with mental illnesses. Psychiatric Services. 2001;52(12):1621–1626. doi: 10.1176/appi.ps.52.12.1621. [DOI] [PubMed] [Google Scholar]
  32. Mackenzie CS, Gekoski WL, Knox VJ. Age, gender, and the underutilization of mental health services: the influence of help-seeking attitudes. Aging and mental health. 2006;10(6):574–582. doi: 10.1080/13607860600641200. [DOI] [PubMed] [Google Scholar]
  33. Magaard, J. L., Seeralan, T., Schulz, H., & Brütt, A. L. (2017). Factors associated with help-seeking behaviour among individuals with major depression: a systematic review. PloS one, 12(5), 10.1371/journal.pone.0176730 [DOI] [PMC free article] [PubMed]
  34. Masuda A, Price M, Anderson PL, Schmertz SK, Calamaras MR. The role of psychological flexibility in mental illness stigma and psychological distress for the stigmatizer. Journal of Social and Clinical Psychology. 2009;28(10):1244–1262. doi: 10.1521/jscp.2009.28.10.1244. [DOI] [Google Scholar]
  35. Masuda A, Latzman RD. Examining associations among factor-analytically derived components of mental illness stigma, distress, and psychological flexibility. Personality and Individual Differences. 2011;51(4):435–438. doi: 10.1016/j.paid.2011.04.008. [DOI] [Google Scholar]
  36. Masuda A, Anderson PL, Edmonds J. Help-seeking attitudes, mental health stigma, and self-concealment among african american college students. Journal of Black Studies. 2012;43(7):773–786. doi: 10.1177/0021934712445806. [DOI] [Google Scholar]
  37. Mulla MM, Witte TH, Richardson K, Hart W, Kassing FL, Coffey CA, Hackman CL, Sherwood IM. The causal influence of perceived social norms on intimate partner violence perpetration: converging cross-sectional, longitudinal, and experimental support for a social disinhibition model. Personality and Social Psychology Bulletin. 2019;45(4):652–668. doi: 10.1177/0146167218794641. [DOI] [PubMed] [Google Scholar]
  38. Neighbors C, Walker DD, Mbilinyi LF, O’Rourke A, Edleson JL, Zegree J, Roffman RA. Normative misperceptions of abuse among perpetrators of intimate partner violence. Violence Against Women. 2010;16(4):370–386. doi: 10.1177/1077801210363608. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Nochaiwong S, Ruengorn C, Thavorn K, Hutton B, Awiphan R, Phosuya C, Ruanta Y, Wongpakaran N, Wongpakaran T. Global prevalence of mental health issues among the general population during the coronavirus disease-2019 pandemic: a systematic review and meta-analysis. Scientific Reports. 2021;11(1):1–18. doi: 10.1038/s41598-021-89700-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Norman RM, Sorrentino RM, Windell D, Manchanda R. The role of perceived norms in the stigmatization of mental illness. Social Psychiatry and Psychiatric Epidemiology. 2008;43(11):851–859. doi: 10.1007/s00127-008-0375-4. [DOI] [PubMed] [Google Scholar]
  41. Parcesepe AM, Cabassa LJ. Public stigma of mental illness in the United States: a systematic literature review. Administration and Policy in Mental Health and Mental Health Services Research. 2013;40(5):384–399. doi: 10.1007/s10488-012-0430-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Pescosolido, B. A., Halpern-Manners, A., Luo, L., & Perry, B. (2021). Trends in public stigma of mental illness in the US, 1996–2018. JAMA Network Open, 4(12), 10.1001/jamanetworkopen.2021.40202 [DOI] [PMC free article] [PubMed]
  43. Rivis A, Sheeran P. Descriptive norms as an additional predictor in the theory of planned behaviour: a meta-analysis. Current Psychology. 2003;22(3):218–233. doi: 10.1007/s12144-003-1018-2. [DOI] [Google Scholar]
  44. Substance Abuse and Mental Health Services Administration (2019). NSDUH Detailed Tables. Retrieved from https://www.samhsa.gov/data/report/2018-nsduh-detailed-tables
  45. Substance Abuse and Mental Health Services Administration (2020). Key substance use and mental health indicators in the United States: Results from the 2019 National Survey on Drug Use and Health (HHS Publication No. PEP20-07-01-001). Rockville, MD: Center for Behavioral Health Statistics and Quality, Substance Abuse and Mental Health Services Administration. Retrieved from https://www.samhsa.gov/data/sites/default/files/reports/rpt29393/2019NSDUHFFRPDFWHTML/2019NSDUHFFR1PDFW090120.pdf
  46. Topkaya N. Gender, self-stigma, and public stigma in predicting attitudes toward psychological help-seeking. Educational Sciences: Theory and Practice. 2014;14(2):480–487. [Google Scholar]
  47. Turetsky KM, Sanderson CA. Comparing educational interventions: correcting misperceived norms improves college students’ mental health attitudes. Journal of Applied Social Psychology. 2018;48(1):46–55. doi: 10.1111/jasp.12489. [DOI] [Google Scholar]
  48. Twenge JM, Joiner TE. Mental distress among U.S. adults during the COVID-19 pandemic. Journal of Clinical Psychology. 2020;76(12):2170–2182. doi: 10.1002/jclp.23064. [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. U.S. Census Bureau (2022, February 24). United States Census Bureau. Retrieved July 1, 2022, from https://www.census.gov/newsroom/press-releases/2022/educational-attainment.html
  50. Wei Y, McGrath PJ, Hayden J, Kutcher S. Mental health literacy measures evaluating knowledge, attitudes and help-seeking: a scoping review. Bmc Psychiatry. 2015;15(1):1–20. doi: 10.1186/s12888-015-0681-9. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

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

Data Availability Statement

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Articles from Current Psychology (New Brunswick, N.j.) are provided here courtesy of Nature Publishing Group

RESOURCES