Acknowledging Stigma: Levels of Prejudice among Undergraduate Nursing Students toward People Living with a Mental Illness—A Quasi-Experimental Single-Group Study

Abstract

Introduction

The undergraduate mental health nursing course may be an optimal time to cultivate students’ positive attitudes toward people living with a mental illness.

Aim

To determine the impact of an undergraduate mental health nursing course on students’ attitudes toward people living with a mental illness, depression, and schizophrenia.

Method

A quasi-experimental single-group pretest posttest study was conducted using a sample of undergraduate nursing students in New York City (N = 44). Self-reported measures of prejudice toward those living with a mental illness were collected at the beginning of a mental health nursing course and again at its conclusion.

Results

A statistically significant decrease in prejudice scores was found concerning mental illness (p = .03, d = 0.23), depression (p = .01, d = 0.31), and schizophrenia (p = .013, d = 0.34). Subscale analysis revealed significant decreases in the fear/avoidance and unpredictability subscales. Yet no significant change was found in the subscales of authoritarianism and malevolence for any of the three conditions.

Discussion

A mental health course led to a modest decrease in prejudice. However, certain facets of prejudice remain unchanged.

Implications for Practice

Major curricular reform is needed to optimize the impact of undergraduate nursing education.

Introduction

I hope to God I never get any serious mental health issues again, because I couldn’t handle being treated like I’m nobody, and have no say in how I’m treated.—Eva, after an experience with healthcare workers (Thornicroft et al., 2007, p. 119)

Mental illness and stigma

The stigma attached to mental illness results in stereotypes, prejudice, and discrimination and has been described “as having worse consequences than the conditions themselves” (Thornicroft et al., 2016, p. 1123). Nurses have held the same stigmatizing attitudes as the general public, to the detriment of patient care (İnan et al., 2019). Furthermore, just like professional nurses, nursing students have also shown negative attitudes toward those living with a mental illness (Foster et al., 2019; Heim et al., 2019). Every student nurse will come across patients living with a mental illness, no matter the specialty or setting they eventually choose. Nurse educators have the unique and invaluable opportunity of helping to shape positive attitudes among nursing students toward people living with a mental illness (Palou et al., 2020). One of the greatest opportunities can be found during the undergraduate mental health nursing course where students are systematically exposed to knowledge about mental illness, perspectives of those living with mental illness, and experiences caring for those with mental illness (Henderson et al., 2007). As poignantly stated by Moxham et al. (2016), “Stigma is learned, and concomitantly can be unlearned” (p. 171).

People who experience mental illness not only deal with the illness itself, but also the stigma attached to mental illness (Petkari et al., 2018). Stigma can be thought of as a negative mark or brand that creates distinct out-groups that are looked down upon, devalued, and dehumanized as tarnished and defective (Goffman, 1963). Stigma has numerous healthcare ramifications. When individuals do seek help, they can experience the results of healthcare workers’ stigmatizing attitudes, including authoritarian and coercive treatments that are dehumanizing (Thornicroft et al., 2007). Stigma transforms a person into an illness (Yanos, 2018).

Theoretical framework

This study was guided by the Mental Illness Stigma Framework (MISF) developed by Fox et al. (2018). The MISF was created to synthesize a diverse body of stigma research and diverse theoretical frameworks, including those of Corrigan and Shapiro (2010) and Thornicroft et al. (2016). The MISF states that the stigma of mental illness is established by culture and results in a “socially devalued identity” (Fox et al., 2018, p. 351). At the individual level, the framework is divided into two categories with unique stigma mechanisms, namely the perspective of the stigmatizer and the perspective of the stigmatized. This study focuses on the perspective of the stigmatizer. The three mechanisms of stigma that derive from the perspective of the stigmatizer are stereotypes, prejudice, and discrimination. Stereotypes represent cognitive responses that the stigmatizer may have to the stigmatized; prejudice represents affective responses; and discrimination represents behavioral responses. Corresponding expressions and examples of these mechanisms are shown in Table 1.

Table 1. Mechanisms of stigma.

Mechanism	Expression	Example
Stereotypes	Beliefs	Spiders are dangerous
Prejudice	Attitudes	I don’t like spiders
Discrimination	Behaviors	I will avoid spiders

Stereotypes, prejudice, and discrimination can lead to various deleterious states for those with mental illness, and it is worth repeating that the stigma of mental illness can often be worse than the mental illness itself (Thornicroft et al., 2016). Those who are stigmatized may be excluded socially, feared, pitied, coerced, thought to be incompetent, and receive inequitable health care (Fox et al., 2018). This study focuses on the mechanism of prejudice. According to Kenny et al. (2018), prejudice is defined as a “negative outgroup attitude” and is an antecedent of discrimination that “drives discriminatory behavior” (p. 1). Stereotypes also give rise to prejudice; therefore, prejudice is a “central component” of stigma mechanisms and is “the avenue with the most potential to modify” (Kenny et al., 2018, p. 2).

Stigma in nursing and the nursing knowledge perspective

One of the core principles of nursing is humanization (Travelbee, 1969; Willis et al., 2008). Ultimately, stigma is the dehumanization of those with mental illness; therefore, stigma is the antithesis of optimal nursing practice and accurate nursing knowledge. Nurse educators must not only be aware of stigma but must also seek to abolish stigma in thoughts, attitudes, and actions. Nurses can challenge and eliminate stigma by providing humanizing care to every patient.

Undergraduate nursing education interventions

A literature review focused on quantitative studies was conducted to measure how undergraduate nursing educational interventions impacted the stigma of mental illness. A total of 37 studies were found from within the selected timeframe (2000–2022). The studies were conducted in 20 countries on five continents. Of these studies, nine focused on the classroom (24.3%), 18 focused on clinical interventions (48.6%), and 10 focused on a combination of the two (27%). Results were mixed in terms of reducing stigma. Both Chan and Cheng (2001) and Madianos et al. (2005) found significant reductions in stigma on the Opinions about Mental Illness scale after completion of a mental health nursing course. However, Tambag (2018) found that a mental health course had no significant impact on 57 fourth-year nursing students’ beliefs and attitudes toward mental illness.

Psychometric limitations of instruments

Altogether 25 different instruments were used in these studies, with the overwhelming majority being self-report instruments using Likert-type scales. Kenny et al. (2018) noted that many issues exist with the psychometrics of stigma-measuring instruments and that “2/3 of all published measures of stigma have not had any psychometric evaluations” (p. 2). Many of the instruments, including the ones most often used, contain double-barreled items that ask two questions at once, that have not been replicated by factor analysis, and that may promote response bias by having unbalanced scales with an unequal number of positive and negatively keyed items (Kenny et al., 2018).

Gaps in the literature and goals of the current study

Out of 37 quantitative studies reviewed, only four (10.8%) were conducted in the United States. Eleven studies (29.7%) were conducted in Australia, even though the United States has 13 times the population. The paucity of research on stigma in the United States is not just limited to undergraduate nursing education, but extends to professional nursing as well (de Jacq et al., 2016). This study aimed to remedy this lack of data. Furthermore, this study crossed a threshold and introduced valid, reliable, sensitive, and accessible instruments in stigma research by using the shortened disorder-specific versions of the Prejudice toward People with Mental Illness (PPMI) scale for the first time in the United States and for the first time in an undergraduate nursing population. The goal of this study was to explore the impact of an undergraduate mental health nursing course on prejudice toward people living with mental illness, depression, or schizophrenia.

Methods

Study design

This study used a single-group pretest-posttest quasi-experimental design.

Ethical considerations

The study was approved by the institutional review board at Teachers College, Columbia University, protocol number 21-233. Written consent was obtained from the nursing school where the study was conducted. Informed consent was obtained from each participant. Participants who completed both the pretest and posttest were given a $10 electronic gift card.

Participants and setting

The study used a convenience sample of nursing students in an accelerated bachelor of science in nursing (ABSN) program in New York City. The ABSN program is 15 months long, and students are required to hold a non-nursing bachelor’s degree prior to enrolling. The inclusion criteria were students’ ability to provide consent, voluntary participation, and enrollment in the mental health nursing course that is offered in the second term of the program. Exclusion criteria were not completing either the pretest and posttest.

Procedure

Students were emailed a week before the 2021 summer term to notify them of the study. On the first day of the course, after the syllabus was presented and before any course content was covered, the study purpose and methods were explained to the students. After informed consent was obtained students who wished to participate were invited to complete the pretest via a link sent through Zoom. Students then completed the course as they normally would. At the end of the course, after all content had been presented and clinical experiences completed, students were again sent a link via Zoom to complete the posttest. Students were also sent an email with the posttest link which would remain active for 2 wk after the conclusion of the course. Data were collected via Qualtrics (https://www.qualtrics.com).

Intervention

The intervention in this study was an undergraduate mental health course. Over 12 wk, the students completed 45 classroom hours and 30 clinical hours. The classroom component was co-taught by the researcher and a colleague. The classroom hours were completed over Zoom due to COVID-19 requirements, and the clinical hours were conducted in person on locked acute inpatient psychiatric units. The course objectives include the following:

Discuss ethical and legal practices in the care of the mentally ill client.

Discuss mental health disparities and the impact of social policies and healthcare policy on vulnerable populations.

Demonstrate behavior that reflects core professional values and ethical principles in the care of the mentally ill patient.

Classroom experience

Classroom experiences have been demonstrated to impact the stigma of mental illness to varying degrees with varying instruments (Duman et al., 2017; Emrich et al., 2003; Itzhaki et al., 2017). Due to the COVID-19 pandemic, the classroom portion of the course was held over Zoom and lasted 4 h each week. Teaching strategies included a combination of lecture, group discussions, small group work, exploring research articles, and autobiographical videos of people with first-hand experience of a mental health condition. All chapters of the required text were covered in the classroom (Videbeck, 2010).

Clinical experience

Clinical experiences have also been demonstrated to impact the stigma of mental illness to varying degrees (Chadwick & Porter, 2014; de Assunção Gil et al., 2016; Romem et al., 2008). This study’s clinical experiences allowed students to apply the concepts they learned in the classroom in a patient care area, with a strong focus on therapeutic patient interactions. Students had the opportunity to attend and participate in patient group activities such as music therapy, art therapy, goal groups, and medication information sessions. Students were encouraged to see the perspective of the patient and establish a therapeutic relationship through empathy.

Instruments

Prejudice toward people with mental illness, shortened versions

Three instruments were used to measure prejudice toward those living with general mental illness, depression, or schizophrenia. The Prejudice toward People with Mental Illness, Shortened Version (PPMI-SV), Prejudice toward People with Depression, Shortened Version (PPD-SV), and Prejudice toward People with Schizophrenia, Shortened Version (PPS-SV) were created by Bizumic et al. (2022). The three instruments are derived from the original PPMI (Kenny et al., 2018). The author granted permission to use the instruments. The PPMI measures prejudice, one of the three main mechanisms of stigma, the other two being stereotypes and discrimination. The PPMI has 28 items and uses a 9-point Likert scale. The PPMI is a balanced instrument that protects against response bias by using both positively and negatively phrased items (Table 2).

Table 2. Example instrument items concerning prejudice.

Instrument	Example Item
PPMI	I would find it hard to talk to someone who has a mental illness.
PPMI-SV	I would find it hard to talk to someone who has a mental illness.
PPD-SV	I would find it hard to talk to someone who has depression.
PPS-SV	I would find it hard to talk to someone who has schizophrenia.

Note: Prejudice toward People with Mental Illness (PPMI), Prejudice toward People with Mental Illness, Shortened Version (PPMI-SV), Prejudice toward People with Depression, Shortened Version (PPD-SV), and Prejudice toward People with Schizophrenia, Shortened Version (PPS-SV).

The PPMI covers four dimensions of prejudice with four distinct subscales: fear/avoidance (belief that those impacted by mental illness are dangerous and social distance is required; eight items), unpredictability (belief that the behavior of those impacted by mental illness is unreliable and not trustworthy; six items), authoritarianism (belief that it is acceptable to control, coerce, and force those impacted by mental illness into treatment and take away their rights; six items), and malevolence (belief that those impacted by mental illness are inferior and do not deserve sympathy or aid; eight items).

The PPMI-SV, PPD-SV, and PPS-SV retain all the previously stated qualities of the original PPMI, except that they each have 16 items instead of 28—four items for each facet of prejudice measured by the original PPMI. All subscale scores were item means with a range from 1.0 to 9.0 with higher scores indicating a higher level of prejudice. The full instruments and detailed scoring instructions can be found in Bizumic et al. (2022).

Reliability and validity

The three instruments demonstrated good reliability in the current study: PPMI-SV (pretest α = .82, posttest α = .81), PPD-SV (pretest α = .73, posttest α = .79), PPS-SV (pretest α = .85, posttest α = .83). Regarding validity, Bizumic et al. (2022) reported that the PPMI-SV, PPD-SV, and PPS-SV demonstrate convergent validity through correlations with known antecedents of prejudice, including generalized prejudice, social dominance orientation, and ethnocentrism. Additionally, item-level confirmatory factor analysis showed that “all items loaded significantly on their corresponding factors” (Bizumic et al., 2022, p. 4). Furthermore, as shown by Kenny et al. (2018) the PPMI has concurrent validity with the widely used Community Attitudes Toward Mental Illness scale (r = .78).

Demographic questionnaire

The survey concluded with a short demographic questionnaire. This questionnaire sought to provide participants autonomy and inclusivity. Therefore, wherever possible, participants were encouraged to report demographic characteristics with a fill-in-the-blank option. Also, every item had the option to not disclose demographic data. The questionnaire asked participants about age, gender, ethnicity, and if they had a family member or friend who has experience with mental health issues.

Data analysis

Quantitative data were analyzed with IBM SPSS Statistics (Version 26). Descriptive statistics were used to summarize the baseline demographic characteristics of the sample, including reported age, gender, ethnicity, and if the student had a family member or friend who has experienced mental health issues. Prior to analyses, pertinent items were reverse-scored and item means for each of the three instruments along with the four subscales were calculated.

Item analyses showed that two items that were part of scales had negative item-total correlations, namely item 8, a reverse-scored item, on the PPMI-SV (-0.09) and item 15 on the PPD-SV (-0.006). All others had positive item-total correlations. Additionally, item 15 on the PPMI-SV diminished the Cronbach’s alpha of the malevolence subscale to .49. Each subscale on the three instruments has only four items. Fewer than 10 items on a given scale commonly leads to lower Cronbach’s alphas (Pallant, 2020). Subsequent statistical tests were run with and without these items and other than increasing subscale alpha scores, statistical conclusions did not meaningfully change and the three items were removed from the analysis. Thereafter, all Cronbach’s alphas showed moderate to high reliability (Hinton et al., 2014; Appendix, Table A1).

Paired-samples t tests were used to determine if there were statistically significant mean differences between pretest and posttest scores on the PPMI-SV, PPD-SV, and PPS-SV, as well as the subscales in each instrument. Where nonnormality and outliers existed, the Wilcoxon signed-rank test, which is a non-parametric equivalent of the paired-samples t test, was used as a sensitivity analysis. A sensitivity analysis is a post-hoc analysis that alters statistical assumptions to explore if statistical conclusions are in alignment or disagreement with each other (Thabane et al., 2013).

Results

In total, 44 students out of the 56 students in the course completed the pretest and posttest, which represented a 79% response rate.

Demographic characteristics

The students’ ages ranged from 21 to 41 (M = 27.3, SD = 5.49). In terms of gender, 39 (88.6%) students identified as female, and five (11.4%) identified as male. Other genders were not reported by any student. The sample was multicultural with five different ethnicities reported. A majority of the students reported having a family member who has experienced a mental health issue (54.5%) and a friend who has experienced a mental health issue (52.3%).

The results are summarized in Table 3.

Table 3. Demographic characteristics.

Characteristic	n	%
Age in years
20–29	36	81.8
30–39	5	11.4
≥40	3	6.8
Gender
Female	39	88.6
Male	5	11.4
Ethnicity
African American or Black	4	9.1
Asian, Asian American, orEast Asian	8	18.2
Hispanic or Latino	10	22.7
White	18	40.9
More than one	1	2.3
Prefer not to say	3	6.8
A family member has experienced a mental health issue
Yes	24	54.5
No	18	40.9
Prefer not to say	2	4.5
A friend has experienced a mental health issue
Yes	23	52.3
No	20	45.5
Prefer not to say	1	2.3

Note: N = 44.

Paired-samples t tests for prejudice toward people living with a mental illness, depression, or schizophrenia

There was a statistically significant reduction in prejudice toward people living with a mental illness, depression, or schizophrenia after completion of the undergraduate mental health nursing course (Table 4). In the PPMI-SV, prejudicial attitudes toward people diagnosed with general mental illness decreased significantly from pretest (M = 4.07, SD = 1.03) to posttest (M = 3.84, SD = 0.98), t(43) = 2.25, p = .03, d = 0.23, 95% CI [0.02, 0.43]. In the PPD-SV, prejudicial attitudes toward people diagnosed with depression decreased significantly from pretest (M = 3.73, SD = 0.79) to posttest (M = 3.48, SD = 0.82), t(43) = 2.68, p = .01, d = 0.31, 95% CI [0.43, 2.68]. In the PPS-SV, prejudicial attitudes toward schizophrenia decreased with a statistically significant reduction in scores from pretest (M = 4.54, SD = 0.98) to posttest (M = 4.21, SD = 0.94), t(43) = 2.59, p = .013, d = 0.34, 95% CI [0.07, 0.57].

Table 4. Paired-samples t tests with effect sizes for prejudice toward people living with a mental illness, depression, or schizophrenia.

Variable	Pretest		Posttest		t(43)	p	Cohen’s d
	M	SD	M	SD
PPMI-SV	4.07	1.03	3.84	0.98	2.25	.03	0.23
PPD-SV	3.73	0.79	3.48	0.82	2.68	.01	0.31
PPS-SV	4.54	0.98	4.21	0.94	2.59	.013	0.34

Note: N = 44. PPMI-SV = Prejudice toward People with Mental Illness, Shortened Version, PPD-SV = Prejudice toward People with Depression, Shortened Version, PPS-SV = Prejudice toward People with Schizophrenia, Shortened Version.

Subscales

Fear/avoidance

The fear/avoidance subscales on the PPMI-SV and PPS-SV showed a statistically significant reduction in prejudice scores. In the PPMI-SV, attitudes of fear/avoidance toward people diagnosed with general mental illness decreased significantly from pretest (M = 4.62, SD = 1.57) to posttest (M = 3.92, SD = 1.50), t(43) = 4.45, p < .001, d = 0.46, 95% CI [0.38, 1.02]. In the PPD-SV, attitudes of fear/avoidance toward people diagnosed with depression did not significantly change from pretest (M = 4.20, SD = 1.28) to posttest (M = 3.98, SD = 1.14), t(43) = 1.32, p = .193, d = 0.18, 95% CI [-0.12, 0.57]. In the PPS-SV, attitudes of fear/avoidance toward people diagnosed with schizophrenia decreased significantly from pretest (M = 5.35, SD = 1.69) to posttest (M = 4.44, SD = 1.68), t(43) = 3.67, p = .001, d = 0.54, 95% CI [0.41, 1.41].

Unpredictability

The unpredictability subscales on the PPMI-SV and PPD-SV showed a statistically significant reduction in prejudice scores. In the PPMI-SV, attitudes regarding the unpredictability of those diagnosed with general mental illness decreased significantly from pretest (M = 5.66, SD = 1.24) to posttest (M = 5.17, SD = 1.37), t(43) = 2.51, p < .016, d = 0.38, 95% CI [0.1, 0.87]. Likewise, in the PPD-SV, attitudes regarding the unpredictability of those diagnosed with depression decreased significantly from pretest (M = 4.98, SD = 1.01) to posttest (M = 4.43, SD = 1.20), t(43) = 3.51, p = .001, d = 0.5, 95% CI [0.24, 0.88]. In the PPS-SV, attitudes regarding the unpredictability of those diagnosed with schizophrenia did not significantly change from pretest (M = 6.22, SD = 0.99) to posttest (M = 5.84, SD = 1.13), t(43) = 1.92, p = .062, d = 0.36, 95% CI [-0.02, 0.78].

Authoritarianism and malevolence

No statistically significant differences were found on any of the authoritarianism or malevolence subscales. Many of the mean scores increased by a nonsignificant degree. The authoritarianism subscale of the PPMI-SV showed the greatest increase in prejudicial scores from pretest (M = 3.65, SD = 1.62) to posttest (M = 4.01, SD = 1.65) with a p value that approached statistical significance, t(43) = −1.99, p = .053, d = 0.22, 95% CI [-0.72, 0.005].

The Wilcoxon signed-rank test was used as a sensitivity analysis and was always in alignment with the significance values of the t tests, except for one test concerning the PPD-SV malevolence subscale. One extreme outlier in this subscale was defined as a boxplot value that exceeded three box lengths from the 25th or 75th percentile (Hinton et al., 2014). Here, the Wilcoxon signed-rank test resulted in a statistically significant reduction in prejudice scores, where the paired-samples t tests did not. The participant’s mean pretest score of 2.33 was similar to that of the sample’s mean pretest score of 2.24. However, the participant’s posttest score was 5.67, indicating increased prejudicial attitudes, while the sample’s posttest score was 1.99. The items in the subscale were: “We, as a society, should be spending much more money on helping people with depression” (reverse-scored), “People who develop depression are genetically inferior to other people”, and “People who develop depression are not failures in life” (reverse-scored). The participant was not an outlier in any other PPD-SV subscale. This discrepancy speaks to the impact that outliers may have on data. However, there was no justification to remove the outlier as it presented as a legitimate response. The subscale results are summarized in Table 5.

Table 5. Paired-samples t tests with effect sizes for prejudice subscales.

Variable	Pretest		Posttest		t(43)	p	Cohen’s d
	M	SD	M	SD
Fear/Avoidance
PPMI-SV	4.62	1.57	3.92	1.50	4.45	<.001	0.46
PPD-SV	4.20	1.28	3.98	1.14	1.32	.193	0.18
PPS-SV	5.35	1.69	4.44	1.68	3.67	.001	0.54
Unpredictability
PPMI-SV	5.66	1.24	5.17	1.37	2.52	.016	0.38
PPD-SV	4.98	1.01	4.43	1.20	3.51	.001	0.5
PPS-SV	6.22	0.99	5.84	1.13	1.92	.062	0.36
Authoritarianism
PPMI-SV	3.65	1.62	4.01	1.65	−1.99	.053	0.22
PPD-SV	3.10	1.19	3.16	1.14	−0.36	.722	0.05
PPS-SV	4.14	1.58	4.17	1.49	−0.21	.836	0.02
Malevolence
PPMI-SV	2.30	1.02	2.17	1.20	0.75	.460	0.17
PPD-SV	2.24	1.04	1.99	1.09	1.72	.093	0.23
PPS-SV	2.43	1.02	2.41	1.20	0.12	.908	0.02

Note: N = 44. PPMI-SV = Prejudice toward People with Mental Illness, Shortened Version, PPD-SV = Prejudice toward People with Depression, Shortened Version, PPS-SV = Prejudice toward People with Schizophrenia, Shortened Version.

Discussion

The research findings show that an undergraduate mental health nursing course is impactful in decreasing prejudicial attitudes toward those who experience mental illness. The overall scores of each of the three scales significantly moved in a less prejudicial direction with effect sizes between small and medium. The highest initial mean prejudice scores were found regarding schizophrenia, followed by general mental illness, and then depression, while posttest means followed the same pattern. This indicates that attitudes toward schizophrenia might have the greatest possibility for change. These findings are consistent with similar studies that measured the impact of an undergraduate mental health nursing course (Duman et al., 2017; Itzhaki et al., 2017; O’Ferrall‐González et al., 2020).

Though the overall scores showed a significant and meaningful impact, the subscales showed far more mixed results. A majority of the fear/avoidance and unpredictability subscales showed significantly lower prejudice scores across all instruments at posttest. These findings are consistent with those of previous research showing that a mental health clinical rotation significantly decreased measures of fear (Romem et al., 2008) and of desired social distance akin to fear/avoidance (Foster et al., 2019; İnan et al., 2019; Markström et al., 2009).

Conversely, all the authoritarianism and malevolence subscales showed no significant differences on the paired-samples t tests. It should be noted that the pretest means for authoritarianism and malevolence were lower than those of fear/avoidance and unpredictability, which suggests the possibility of floor effects that would make it difficult to show posttest changes. However, this study’s posttest authoritarian and malevolence subscale means can be compared to the results of a study by Bizumic et al. (2022) that had a sample of 299 mental health professionals (MHP) and 427 members of the general population (GP) who completed the same three shortened instruments. An ANOVA (Appendix, Table A2) showed that MHP authoritarian subscale scores were significantly lower than this study’s posttest scores for all three mental health conditions (p < .001). The MHP malevolence subscale scores were significantly lower for the condition of general mental illness (p < .05) and schizophrenia (p < .001). Additionally, the GP authoritarian scores were significantly lower than the nursing students in this study for the condition of general mental illness (p < .01) and depression (p < .001) with no significant difference found for schizophrenia. The GP malevolence subscale scores were not significantly different from the nursing students for the condition of general mental illness and schizophrenia. This shows that there is still room for prejudice scores to decrease despite authoritarian and malevolence scores currently being lower than that of the fear/avoidance and unpredictability subscales. Thus, floor effects were not present in the current study.

Nonetheless, no significant difference was found on any of the three malevolence subscales. Examples of malevolence subscale items that showed no significant change, and yet the mean prejudice score increased, include: “People who become mentally ill are not failures in life,” (reverse scored) and “People with schizophrenia do not deserve our sympathy.” This finding is in alignment with a study by Kenny and Bizumic (2016), in which the original 28-item PPMI was used to measure the impact of acceptance and commitment training or education about stigma and mental health. The results showed that malevolence scores increased to a statistically significant level after the interventions, while fear/avoidance, unpredictability, and authoritarianism decreased to a statistically significant level. The authors concluded that it is possible that a diminished inclination to help may result from addressing the stereotype that vast differences exist between those diagnosed with a mental illness and the general population.

No significant difference was found on any of the three authoritarian subscales. Examples of authoritarian subscale items that showed no significant change, and yet the mean prejudice score increased, include: “People who are mentally ill should be forced to have treatment,” “Those who have depression should not be allowed to have children,” and the reverse-scored item “Society does not have a right to limit the freedom of people with schizophrenia.”

These findings echo the results of Bingham and O’Brien (2018), who measured the impact of a mental health clinical rotation on stigmatizing attitudes using the Corrigan (2012) Attribution Questionnaire. Their findings showed a significant positive change in stereotypes of fear and avoidance, while coercion, akin to authoritarianism, showed a nonsignificant negative change. The authors reported that acute inpatient clinical settings “could reinforce negative stereotypes” (p. 5), which may explain the nonsignificant negative change in coercion in their study, as well as the nonsignificant negative change in authoritarianism in the current study. Similarly, Stuhlmiller and Tolchard (2019) conducted an experimental study where both groups received the same didactic classroom experience but had different clinical environments. The students who had a clinical rotation in a recovery-oriented community setting significantly reduced self-reported authoritarianism while a clinical rotation in an acute inpatient hospital setting did not (Stuhlmiller & Tolchard, 2019). Furthermore, Moxham et al. (2016) found that traditional mental health clinical environments, such as hospital-based psychiatric units, had no impact on measures of desire to socially distance from those diagnosed with a mental illness when compared to a recovery-oriented clinical environment.

There is no national body in the United States that oversees rates of involuntary treatment, involuntary admission, and the use of seclusion and restraint. However, a recent study used available data from 25 states to reveal that from 2011 to 2018 the mean rate of involuntary commitment “increased by three times the mean state population increase” (Lee & Cohen, 2021, p. 61). New York was not among the states that the researchers had data for. Anecdotally, the principal investigator of the current study has led previous clinical groups on the same units used in the present study. During the morning handoff it was not uncommon to note that the majority of the patients on the unit were there involuntarily.

It is possible that the students in the current study had authoritative attitudes reinforced as the clinical experiences occurred in authoritative environments where patients’ rights do get taken away. These are also environments where nurses, whom students may understandably emulate, at times engage in authoritative involuntary treatment that includes forced medication, seclusion, and restraint.

Limitations

The limitations of the study include the lack of a control group and lack of randomization. Furthermore, self-report instruments were used and response bias is a possibility. Generalizability may be limited as the study was conducted in one nursing school in New York City. Replication studies are needed to corroborate findings. Despite these limitations, the results show that some facets of prejudice were more susceptible to positive change than others.

Implications and future research

Undergraduate education is one of the most important opportunities to influence nurses’ attitudes toward people experiencing a mental illness. Therefore, the nonsignificant differences on the authoritarianism and malevolence subscales are high cause for concern. As previously stated, professional nurses share some of the general public’s stigmatizing attitudes, to the detriment of patient care (İnan et al., 2019). This undergraduate mental health nursing course was successful in changing some facets of prejudice more so than others. But if these prejudicial attitudes are not addressed at the pre-licensure level, it is unlikely that they will ever be addressed.

Further research is needed on the current impact of undergraduate mental health courses and subsequently augmentations to the course that potentiate destigmatization including further exploration and coverage of nursing knowledge and theory, humanism, and concepts of recovery, as well as highlighting the holistic biopsychosocial model rather than the one-dimensional biomedical model. Previous research has shown that increased classroom and clinical hours have led to greater reductions in stigmatizing attitudes (Happell, 2009; Happell et al., 2008). Thus, future research including multiple nursing schools with varying classroom and clinical hours, as well as unique course characteristics, could reveal more specific qualities of the undergraduate nursing course that may diminish stigma further. One such characteristic is coproduced curricula between those who have experienced a mental health condition and nursing educators, which have resulted in meaningful reductions of stereotypes and of desire for social distance in undergraduate nursing students at the international level (Happell et al., 2019). This innovative collaboration may impact other avenues of stigma as well. Additionally, clinical sites, beyond the traditional acute inpatient care settings, that include patients further along the journey of recovery, may be beneficial (Moxham et al., 2016).

The shortened versions of the PPMI have proven to be valuable instruments in detecting the degree of prejudicial attitudes as well as specific facets of prejudice. Future development and differentiation of these instruments should be applied to different mental health disorders such as bipolar disorder, eating disorders, and substance use disorder. This may lead to specific interventions to address and diminish prejudicial attitudes. Replication studies are highly encouraged as this study occurred in the summer of 2021 in the second year of the COVID-19 pandemic. Didactic activities were held through Zoom, not in person as they normally would be. Thus, replication studies that include in-person classroom experiences are needed to validate or refute the current findings. Such studies would benefit from a stronger study design that utilizes a control group and randomization. Also, a qualitative arm to future studies may elucidate malevolent attitudes.

Conclusion

This study provides evidence that stigma is not immutable and is amenable to change in a more humanizing direction with less prejudice. It also shows that much more progress must be made, specifically regarding authoritarian and malevolent prejudices toward those experiencing a mental illness. The historian Howard Zinn once said, “You can’t be neutral on a moving train” (Zinn, 2018). If progress is to be made, an honest and critical look at undergraduate mental health nursing education is necessary. Eva, quoted in the epigraph to this article, felt devalued, having her very selfhood stripped away after coming into contact with healthcare workers. Her words beckon to, motivate, and confront nurse educators to truly challenge stigma. Her words are worth reiterating until similar experiences are no longer repeated.

“I hope to God I never get any serious mental health issues again, because I couldn’t handle being treated like I’m nobody, and have no say in how I’m treated.”—Eva (Thornicroft et al., 2007, p. 119)

Acknowledgements

The authors would like to thank Dr. Michele L. Roberts, and Dr. Ann Marie P. Mauro for scholarly guidance in the preparation of this manuscript.

Disclosure statement

The authors report no competing interests to declare. The authors confirm that all authors meet ICMJE criteria for authorship credit (www.icmje.org).

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.

Appendix

Table A1. Cronbach’s alpha reliability coefficients for prejudice instruments.

	Pretest	Posttest
PPMI-SV	.82	.81
Fear/Avoidance	.71	.84
Unpredictability	.64	.76
Authoritarianism	.78	.76
Malevolence	.53	.72
PPD-SV	.73	.79
Fear/Avoidance	.67	.51
Unpredictability	.64	.74
Authoritarianism	.52	.59
Malevolence	.54	.80
PPS-SV	.85	.83
Fear/Avoidance	.83	.85
Unpredictability	.70	.75
Authoritarianism	.76	.74
Malevolence	.66	.72

Note: N = 44. PPMI-SV = Prejudice toward People with Mental Illness, Shortened Version, PPD-SV = Prejudice toward People with Depression, Shortened Version, PPS-SV = Prejudice toward People with Schizophrenia, Shortened Version.

Table A2. Comparison of mean prejudice scores from the general population, mental health professionals, and the Intervention group at posttest.

Variable	GP	MHP	IG	GP and MHP Δ	IG and MHP Δ	IG and GP Δ	F ratio (2, 767)	η^2
	M (SD)	M (SD)	M (SD)
Fear/Avoidance
PPMI-SV	3.48 (1.62)	2.87 (1.11)	3.92 (1.5)	0.61***	1.05***	0.44	20.67	.05
PPD-SV	3.11 (1.46)	3.01 (1.16)	3.98 (1.14)	0.1	0.97***	0.87***	10.17	.03
PPS-SV	4.12 (1.91)	2.81 (1.29)	4.44 (1.68)	1.31***	1.63***	0.32	58.71	.13
Unpredictability
PPMI-SV	4.64 (1.52)	3.94 (1.33)	5.17 (1.37)	0.7***	1.23***	0.53*	27.45	.07
PPD-SV	3.86 (1.51)	3.39 (1.38)	4.43 (1.2)	0.47***	1.04***	0.57*	15.10	.04
PPS-SV	5.84 (1.43)	4.83 (1.40)	5.84 (1.13)	1.01***	1.01***	0	47.38	.11
Authoritarianism
PPMI-SV	3.26 (1.62)	2.93 (1.30)	4.01 (1.65)	0.33**	1.08***	0.75**	11.41	.03
PPD-SV	2.45 (1.32)	2.37 (1.18)	3.16 (1.14)	0.08	0.79***	0.71***	7.60	.02
PPS-SV	3.77 (1.77)	3.14 (1.34)	4.17 (1.49)	0.63***	1.03***	0.4	17.14	.04
Malevolence
PPMI-SV	2.29 (1.15)	1.8 (.86)	2.17 (1.2)	0.49***	0.37*	0.12	19.27	.05
PPD-SV	2.36 (1.18)	1.92 (.94)	1.99 (1.09)	0.44***	0.07	0.37*	15.01	.04
PPS-SV	2.11 (1.09)	1.82 (.92)	2.41 (1.2)	0.29***	0.59***	0.3	10.33	.03

Note: GP = general population; N = 427. MHP = mental health professionals; N = 299. IG = intervention group; N = 72. Δ = difference. PPMI-SV = Prejudice toward People with Mental Illness, Shortened Version, PPD-SV = Prejudice toward People with Depression, Shortened Version, PPS-SV = Prejudice toward People with Schizophrenia, Shortened Version.

*p < .05. **p < .01. ***p < .001.