A Missed Opportunity to Cultivate Positive Attitudes about Mental Health Recovery among Undergraduate Nursing Students – A Quasi-Experimental Controlled Study

Abstract

Introduction

Mental health recovery is a critical concept that needs to be thoroughly understood and supported by nurses. Undergraduate nurse educators have the opportunity to clarify misconceptions and cultivate positive recovery attitudes.

Aim

To assess the impact of an undergraduate nursing course on attitudes toward mental health recovery and the relationship between recovery attitudes and prejudice toward those who experience a mental illness.

Methods

A quasi-experimental pretest-posttest, nonequivalent-control group study was conducted using a sample of undergraduate nursing students in New York City (N = 126). The intervention group was assigned to an undergraduate mental health nursing course and the control group to a pediatric/maternal health nursing course. Attitudes toward mental health recovery and prejudice were measured at the beginning and end of the semester. Two-way mixed analyses of variance were used to determine the differences in students’ attitudes. Pearson product-moment correlation analyses were used to assess the relationship between prejudice toward people who experience a mental illness and attitudes toward recovery.

Results

The mental health nursing course had no measurable impact on students’ recovery attitudes. However, there was a moderate-to-strong inverse relationship between recovery attitudes and prejudice toward those who experience a general mental illness (r = −0.54), depression (r = −0.60), or schizophrenia (r = −0.43).

Conclusions

Curriculum reform is needed to optimize the impact of undergraduate education on students’ attitudes. Possible changes include a more holistic approach to mental health that does not over accentuate the biomedical model, the use of nontraditional clinical sites that provide students an opportunity to interact with those further along in their recovery, and the inclusion of those in recovery in curriculum development. As there was a moderate-to-strong inverse relationship between recovery attitudes and prejudice, educational interventions that positively impact one may also impact the other. Further research is needed to investigate if the relationship is causal.

People learn to say what professionals say; “I am a schizophrenic, a bi-polar, a borderline, etc.” Yet instead of weeping at such a capitulation of personhood, most professionals applaud these rote utterances as “insight.” Of course the great danger of reducing a person to an illness is that there is no one left to do the work of recovery. (Deegan, 2002, p. 6)

Perspectives on recovery

There are two predominant perspectives on mental health recovery: clinical recovery and personal recovery. The concept of clinical recovery was developed by mental health professionals and uses a strictly biomedical viewpoint. This perspective largely focuses on symptom reduction and psychopharmacological treatment (Davidson & Roe, 2007; Slade et al., 2008).

The concept of personal recovery was developed by those who have experienced mental health challenges themselves and focuses on the holism, uniqueness, and autonomy of the individual (Anthony, 1993; Slade et al., 2014). Dr. Patricia Deegan, who was quoted in the epigraph and who herself was diagnosed with schizophrenia as a teenager, is thought to be the first to put words to the concept of personal recovery (Stacey & Stickley, 2012). According to Deegan, personal recovery is a unique journey that is defined and directed by the individual (Deegan, 1988). It is person centered and rooted in empowerment and autonomy, optimism and possibility. Personal recovery is non-linear, can occur despite the presence of symptoms, and is “a way of living a satisfying, hopeful, and contributing life even with limitations caused by illness” (Anthony, 1993, p. 17).

Rates of recovery

Rates of personal recovery are currently difficult to determine as it is highly individualized and defined by those who experience it. Prominent researchers of personal recovery have stated that there is no quantitative measure that comprehensively represents personal recovery (Shanks et al., 2013). According to Andresen et al. (2010), there is little relationship between measures of clinical recovery and measures of personal recovery. Clinical recovery can occur without personal recovery and personal recovery can occur without clinical recovery (Slade et al., 2014). Clinical recovery focuses on the reduction of symptoms as an outcome while personal recovery focuses on the promotion of health as a process (van Weeghel et al., 2019). Clinical recovery is concerned with limitations and personal recovery is concerned with possibilities (Slade & Longden, 2015). Clinical recovery is an absence, personal recovery is a presence.

Conceptual framework

This study was guided by the CHIME-D framework created through systematic reviews by Leamy et al. (2011) and Stuart et al. (2017). The researchers revealed six characteristics of personal recovery (henceforth referred to as recovery unless stated otherwise) that form the acronym CHIME-D: connectedness, hope, identity, meaning in life, empowerment, and difficulties. Recovery requires connection, through the support of either loved ones, peer advocates, a community, or professional help. Hope inspires optimism and cultivates positivity, aspirations, possibility, and the motivation to change. In the recovery process, identity can be positively redefined in the face of an illness through a transformative process that overcomes challenges and stigma (Deegan, 2002). Meaning in life occurs through myriad ways as the individual develops a deeper understanding of past experiences as well as purpose for the future. Recovery requires empowerment, which focuses on an individual’s strengths, responsibility, and autonomy (Leamy et al., 2011). Finally, the characteristic of difficulties refers to the non-linear nature of recovery where challenges may occur that can include interpersonal struggles, financial instability, and the resurgence of psychiatric symptoms (Stuart et al., 2017). This framework was taught to students in the intervention group and also guided the instrument choice for measurement of recovery attitudes.

Nurses’ attitudes toward recovery

A thorough understanding and positive attitude toward mental health recovery is essential for nursing practice as it seeks to cultivate empowerment and hope in those for whom nurses care (Gyamfi et al., 2020). In a profession of advocacy, nurses can be advocates of hope. However, there is a paucity of research concerning the knowledge and attitudes of nurses toward personal recovery. In the quantitative literature that does exist, Cleary and Dowling (2009) found that mental health nurses’ attitudes about recovery were significantly more negative than that of other mental health professionals such as social workers and psychologists. In addition, the study findings revealed that the nurses surveyed had significantly less knowledge of the non-linearity of the recovery process. Non-linearity means that recovery does not always follow a straightforward trajectory and that “a person does not necessarily need to be free from illness and symptoms to be in recovery” (Bedregal et al., 2006, p. 101). A replication study conducted by Gaffey et al., (2016) revealed that the significant disparity between nurses and mental health professionals regarding knowledge of the non-linearity of the recovery process still existed and had widened in a span of 5 years.

Nursing students’ attitudes toward recovery

Foster et al. (2019) conducted one of the few experimental studies using a sample of undergraduate nursing students that included a quantitative instrument specifically concerning recovery: the Recovery Attitudes Questionnaire (RAQ-7). The pretest results showed a mean score of 4.0 out of 5, indicating more positive attitudes. The authors attributed this to the possibility of recovery concepts being covered theoretically in the mental health course conducted before the students’ clinical placement. Furthermore, they also found that student attitudes toward recovery were more positive after clinical placement as indicated by a statistically significant increase in total RAQ-7 scores from 4.0 to 4.1 (p < .01, d = 0.28). The study did not have a control group. Choi et al. (2016) conducted a study on the impact of a mental health clinical practicum on mental illness prejudice in undergraduate nursing students. They used the Social Stigma Scale of Mental Illness Patients (Kim & Seo, 2004), an instrument that includes an 8-item subscale concerning the impossibility of recovering from a mental illness. The clinical practicum included 3 wk of clinical placement on hospital-based psychiatric units and 1 week in a community mental health center. The students also completed two simulations, with standardized patients, focusing on therapeutic communication and two clinical group seminars focusing on personal knowledge and presenting clinical cases. Findings indicated that nursing student attitudes about recovery were significantly more pessimistic after completing the practicum (p = .013, d = 0.32). The authors did not use a control group in this analysis.

Qualitative research has shown that nursing students may not have a clear and thorough understanding of recovery concepts. Watson and Reimann (2021) found that nursing students had a partial understanding of recovery and often mistook the biomedical perspective of clinical recovery for personal recovery. Additionally, Chua et al. (2023) found that nursing students’ understanding of recovery was “predominantly reflective of the biomedical model” (p. 6).

Gaps in the literature and goals of the current study

There is a great lack of research on the attitudes of undergraduate nursing students toward recovery (Gyamfi et al., 2020) and the interventions that can impact such attitudes. Although certain stigma instruments cover recovery concepts in individual items, few studies, or the instruments used, have focused wholly on recovery. Furthermore, Foster et al. (2019) concluded that there is scant research on the impact of traditional mental health clinical placements on nursing students’ attitudes toward recovery. Therefore, the current study’s purpose was to address the above-mentioned research gaps and assess the impact of an undergraduate mental health nursing course on nursing students’ attitudes toward the recovery of those living with a mental illness. It also explored the relationships between the stigma attached to mental illness and attitudes toward recovery.

Methods

Study design

This study used a quasi-experimental, nonequivalent control group, pretest-posttest design.

Ethical considerations

Approval was obtained from the Institutional Review Board of Teachers College, Columbia University, protocol number 21-371. The study site’s dean granted the necessary permission and the participants provided informed consent. All students were made aware that participation was voluntary, it would not impact their education or grade, and they could cease participation at any time. A $10 electronic gift card was given to those who completed both the pretest and the posttest.

Sample size

G*Power (Faul et al., 2007) was used to conduct a power analysis for two statistical tests: Pearson correlation analysis (two-tailed) and a two-way mixed analysis of variance (ANOVA). Both analyses used a power of 0.8, alpha level of 0.05, a small effect size of 0.15 for the two-way mixed ANOVA, and a medium effect size of 0.3 for the Pearson correlations. The largest of the two resultant samples sizes was 90.

Participants and setting

A convenience sample of nursing students from an undergraduate nursing program in New York City was recruited. This accelerated baccalaureate program lasts 15 months and requires students to already have a Bachelor’s degree in a non-nursing field. For this study, participation was sought from two student cohorts in fall 2021 and spring 2022. All 163 of the students were in the second term of the program, when they took a mental health nursing course or a pediatric/maternal health nursing course. Considering the class size and clinical site availability, students were assigned to one of the courses by alphabetical order using their last names. Those in the mental health nursing course were assigned to the intervention group and those in the pediatric/maternal health nursing course were assigned to the control group.

The inclusion criteria were students’ ability to provide consent, voluntary participation, and enrollment in the second term of the program. The exclusion criteria were students in the intervention group who were absent for 30% or more of the classroom lectures or who had clinical absences that were not made up. This was only applied to the intervention group as such students would not have sufficiently participated in the intervention as intended.

Procedure

Students were informed of the study via email 1 week before classes started. On the first day, over Zoom, the students were invited to participate after providing informed consent. The participants completed the pretest before being presented with any course content. They completed the posttest at the end of their respective courses. All data were collected using Qualtrics, a survey management software.

Interventions

Both 14-week courses had both classroom and clinical components. The intervention group received 45 h of classroom time and 30 h of clinical experience. The control group received 60 h of classroom time and 60 h of clinical experience as the course included both pediatric and maternity nursing. All classroom activities were held over Zoom because of the COVID-19 pandemic and all clinical activities were conducted in person through a large New York City hospital network. The control group was chosen because they were at the same point in the program as the intervention group.

The intervention group was taught all chapters of the required text which includes the concept of recovery (Videbeck, 2010). Both biomedical and psychosocial explanations for mental illness were taught, though there undoubtedly was a biomedical predominance due to its more reliable framework for testing (Chua et al., 2023). The CHIME-D framework was introduced as a foundational concept early in the course and highlighted throughout. The work of Dr. Patricia Deegan was used to explore the meaning of recovery (Deegan, 1988).

Indirect contact with those who experience a mental health condition can include videos or vignettes of individuals sharing their mental health experiences and can be a viable method of learning about mental illness and decreasing negative attitudes (Corrigan et al., 2012; Lee & Seo, 2018). Therefore, videos of first-person narratives covering most of the disorders discussed in the course were shown to students in the intervention group as a teaching strategy. This was followed by group discussions and Socratic dialogue. The videos were always of a person who had been diagnosed with a specific disorder and was also on the path of recovery. Students were asked to reflect and share the characteristics of CHIME-D that they saw in these stories of recovery. These videos allowed those with experience of mental illness the right to speak for themselves, share their signs and symptoms in their own words, describe the treatments that did and did not work, and humanize their experience of mental illness. The videos embodied the CHIME-D framework and showed that the individuals needed connections with others, hope in times of difficulties, a positive reframing of their identities, a new meaning in their lives, empowerment, and the non-linearity of recovery.

Instruments

Consumer Optimism Scale

Salyers et al. (2007) developed the Consumer Optimism Scale to measure attitudes and expectations regarding mental health recovery. The scale consists of 16 items (4 of which are reverse-scored) measured on a 5-point Likert scale (1 = none, 5 = almost all). Higher scores indicate higher levels of optimism. Scores are item means with a range of 1.0 to 5.0. Respondents are asked how many of those with mental illness would “expect to have recovery-related outcomes” (Salyers, Brennan, et al., 2013, p. 4). Example items are as follows: “will remain in the mental health system for the rest of their lives,” “will be able to function very well in the community,” and “will find work that enables them to be economically self-sufficient.” An analysis of the Consumer Optimism Scale items revealed that every CHIME-D characteristic was represented within the instrument; therefore, it was chosen for this study. Salyers, Brennan, et al., (2013) refined the Consumer Optimism Scale in an instrument called the Provider Expectations for Recovery Scale which retained the excellent psychometric properties of its predecessor. However, the Consumer Optimism Scale numerically has more items, and therefore more items that map onto the CHIME-D framework. Therefore the Consumer Optimism Scale was chosen for the current study. The authors’ permission was obtained for the use of the instrument.

Reliability and Validity

The Consumer Optimism Scale has shown excellent test-retest reliability with an intraclass correlation coefficient score of 0.92 and Cronbach’s alpha of 0.91 (Salyers et al., 2007). The scale has also exhibited convergent validity with the provider version of the Recovery Self-Assessment instrument (Salyers et al., 2007). For the current study, the Cronbach’s alpha was 0.91 at pretest and 0.94 at posttest.

Prejudice toward People with Mental Illness, Shortened versions

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) are disorder-specific instruments created by Bizumic et al. (2022) and derived from the original Prejudice toward People with Mental Illness (PPMI) scale (Kenny et al. 2018). The PPMI contains 28 items, and each of the three derived instruments contains 16 items from the original PPMI, modified to cover either general mental illness, depression, or schizophrenia. All three derived instruments measure four facets of prejudice (fear/avoidance, unpredictability, authoritarianism, and malevolence) on a 9-point Likert scale using positively and negatively phrased items. Higher scores indicate higher levels of prejudice with item means from 1.0 to 9.0. The full instruments can be found in Bizumic et al. (2022). Permission to use each of the three shortened instruments was obtained from the author.

Reliability and Validity

The original PPMI has strong concurrent validity with the commonly used Community Attitudes Toward Mental Illness scale (r = 0.78), as shown by Kenny et al. (2018). Furthermore, these authors also provided evidence that the PPMI has a strong correlation to the established antecedents of prejudice, including social dominance orientation (r = 0.52), and a moderate correlation to right-wing authoritarianism (r = 0.39). The shortened versions maintain the qualities of the PPMI and correlate almost perfectly with the original version (PPMI-SV, r = 0.98; PPMI-SV, r = 0.98; PPMI-SV, r = 0.99; Bizumic et al., 2022).

In addition, the three instruments demonstrated good reliability in a previous study (Richards, 2023): PPMI-SV (α = 0.80 to 0.81), PPD-SV (α = 0.73 to 0.78), and PPS-SV (α = 0.83 to 0.85). In the current study, Cronbach’s alpha values showed good reliability: PPMI-SV (α = 0.85), PPD-SV (α = 0.85), and PPS-SV (α = 0.85).

Demographic Questionnaire

A demographic questionnaire was included at the end of the pretest survey concerning age, gender, ethnicity, and if participants had a family member or friend who had experience with mental health issues.

Data analysis

IBM SPSS Statistics (Version 26) was used to analyze the quantitative data. Using the general linear model approach, a two-way mixed ANOVA was used to assess the differences in the Consumer Optimism Scale scores between the groups over time. Pearson product-moment correlation analyses were used to assess relationships among the Consumer Optimism Scale, PPMI-SV, PPD-SV, and PPS-SV for the total sample at pretest.

Results

There were 137 (84%) out of 164 students who completed both the pretest and posttest. Eleven students in the intervention group were excluded from the main data analysis as they did not attend 30% or more of the classroom lectures. As a result, 72 students in the intervention group (74.2%) and 54 students in the control group (81.8%) were included in the analysis.

Demographic characteristics

The students’ age range was 20 to 45 years. Most students identified as female and the participants were multicultural with seven different ethnicities reported. Demographic characteristics are summarized in Table 1.

Table 1. Demographic Characteristics.

	Control Group		Intervention Group		Total Sample
Baseline characteristic	n	%	n	%	n	%
Gender^a
Female	45	83.3	65	90.3	110	87.3
Male	8	14.8	7	9.7	15	11.9
Prefer not to say^b	1	1.9	0	0	1	0.8
Age in years^c
20–29	43	79.6	58	80.6	101	80.2
30–39	10	18.6	10	14	20	15.9
≥40	1	1.9	3	4.2	4	3.2
Prefer not to say^b	0	0	1	1.4	1	0.8
Ethnicity^d
African American  or Black	9	16.7	5	6.9	14	11.1
Asian, Asian American,  or East Asian	7	13	14	19.4	21	16.7
Hispanic or Latino	6	11.1	6	8.3	12	9.5
Jewish	0	0	3	4.2	3	2.4
Middle Eastern	1	1.9	0	0	1	0.8
White	19	35.2	26	36.1	45	35.7
More than one	2	3.7	2	2.8	4	3.2
Prefer not to say^b	10	18.5	16	22.2	26	20.6
A family member has experienced a mental health issue^e
Yes	34	63	40	55.6	74	58.7
No	19	35.2	29	40.3	48	38.1
Prefer not to say^b	1	1.9	3	4.2	4	3.2
A friend has experienced a mental health issue ^f
Yes	35	64.8	46	63.9	81	64.3
No	18	33.3	22	30.6	40	31.7
Prefer not to say^b	4	5.6	4	5.6	5	4

Note: N = 126.

^a Gender did not differ by group, χ2(1) = 0.834, p = .361.

^b Where students preferred not to disclose certain demographic characteristics, the absence was treated as missing data for the analysis.

^c Age did not differ by group, t(123) = 0.648, p = .681, 95% CI [–1.17, 2.31].

^d Ethnicity did not differ by group, χ2(3) = 3.374, p = .338. The following responses for reported ethnicity had the fewest responses and were collapsed into one shared group: Jewish, Middle Eastern, More than one, Hispanic or Latino. There were no statistically significant differences in reported ethnicity between the groups.

^e No difference was found between groups, χ2(1) = 0.480, p = .489. ^fNo difference was found between groups, χ2(1) = 0.035, p = .852.

Attitudes toward recovery

A two-way mixed ANOVA was used to assess differences in the Consumer Optimism scores between the groups over time (Table 2). Following procedure, the control and intervention groups data were analyzed separately and there were no outliers in the Consumer Optimism data at pretest or posttest. Data were found to be normally distributed, as assessed by Shapiro-Wilk (p > .05). Levene’s test of homogeneity (p > .05) and Box’s test of equality of covariance matrices (p > .001) confirmed the homogeneity of variances and covariances.

Table 2. Two–way mixed ANOVA for attitudes toward recovery.

	Control (n = 54)		Intervention (n = 72)			ANOVA
Variable	M	SD	M	SD	Effect	F ratio	df	p	η^2
Consumer Optimism Scale
Interaction					G x T	1.65	1,124	.201	.013
Pretest	3.43	0.53	3.36	0.47
Posttest	3.5	0.55	3.34	0.57
Difference	0.07		−0.02
Time					T	0.49	1,124	.483	.004
Group					G	1.75	1,124	.188	.014

Note: N = 126. G = Group (Control/Intervention); T = Time of testing (Pretest/Posttest); ANOVA = analysis of variance.

There was no statistically significant interaction between group and time in the Consumer Optimism scores, F(1, 124) = 1.65, p = .201, partial η² = .013. The main effect of time did not show a statistically significant difference in scores from pretest to posttest, F(1, 124) = 0.49, p = .483, partial η²= .004. The main effect of group showed that there was no statistically significant difference in the scores between groups, F(1, 124) = 1.75, p = .188, partial η²= .014.

An intention-to-treat analysis using all the same aforementioned statistical tests included the 11 students in the intervention group who were removed for meeting exclusion criteria for being absent for 30% or more of the classroom lectures. The analysis revealed no appreciable differences in any statistical conclusions.

Relationship between recovery attitudes and stigma

Pearson product-moment correlations were used to assess the relationship between the Consumer Optimism Scale, PPMI-SV, PPD-SV, and PPS-SV of the total sample at pretest (Table 3). Outliers were found in the Consumer Optimism Scale as the total sample was analyzed and not the control and intervention groups separately. Outliers were also found in the PPS-SV data but not in the PPMI-SV or PPD-SV data. However, no extreme outliers were found. The Pearson correlations run with and without the inclusion of outliers revealed no appreciable differences. All data were found to be normally distributed as assessed by Shapiro-Wilk (p > .05), except for the PPS-SV. However, upon visual inspection of the Q-Q plot and histogram, the data appeared approximately normally distributed. A visual inspection of the scatterplots was used to verify that there were linear relationships among all variables.

Table 3. Correlations among consumer optimism and prejudice variables.

Variable	M	SD	1	2	3	4
1. Consumer Optimism Scale	3.39	0.49	—
2. PPMI-SV	3.86	0.97	−0.54*	—
3. PPD-SV	3.56	0.96	−0.60*	0.87*	—
4. PPS-SV	4.34	0.99	−0.43*	0.79*	0.71*	—

Note: N = 126. 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).

* p < .001, two-tailed.

There was a statistically significant, strong negative correlation between attitudes toward recovery and prejudice toward people experiencing a general mental illness, r(124) = −0.54, p < .001, with the Consumer Optimism levels explaining 29% of the variation in the PPMI-SV scores. There was a statistically significant, strong negative correlation between attitudes toward recovery and prejudice toward people experiencing depression, r(124) = −0.60, p < .001, with the Consumer Optimism levels explaining 36% of the variation in the PPD-SV scores. There was a statistically significant, moderate negative correlation between attitudes toward recovery and prejudice toward people experiencing schizophrenia, r(124) = −0.43, p < .001, with the Consumer Optimism levels explaining 18% of the variation in the PPS-SV scores.

Moreover, there was a statistically significant, strong positive correlation among prejudice toward people experiencing a general mental illness, depression, or schizophrenia, r(124) = 0.71 − 0.87, p < .001.

Discussion

This study is one of the very few to provide new quantitative evidence on the attitudes of nursing students toward mental health recovery and the impact of undergraduate nursing education on those attitudes. The findings show that the intervention of an undergraduate mental health nursing course had no measurable impact on attitudes toward mental health recovery.

This finding is not consistent with that of Foster et al. (2019), whose mixed-method study showed that student attitudes toward recovery were quantitatively and qualitatively more positive after a mental health nursing clinical experience. The authors used the RAQ-7, which was developed to measure beliefs that those living with a mental health condition can recover. The students had already completed the classroom portion of the course before their study began. However, the authors did not include a control group and there was no significant change in one of the RAQ-7 subscales: “Recovery is difficult and differs among people.” This subscale includes three items concerning the nonlinearity of recovery, its individual and personal nature, and the negative impact stigma can have on the recovery journey. Unlike the Consumer Optimism Scale, the RAQ-7 does not cover all of the CHIME-D characteristics and heavily focuses on hope and difficulties. Most notably, there is a lack of items that cover the characteristics of connectedness and meaning. Moreover, identity and empowerment are also not covered. Additionally, the RAQ-7 contains no reverse-coded items.

In this study, students in the intervention group only had clinical rotations in hospital-based acute psychiatric units. These clinical sites may offer very limited recovery perspectives as patients are experiencing the height of their symptomatology and are just beginning the recovery process. These hospital-based units were all locked units where patient autonomy, and therefore to some degree empowerment, is more limited than in a home or community setting. This lack of exposure to recovery experiences in the community settings may have resulted in a lack of increased optimism in students’ attitudes toward recovery.

The intervention group was introduced to the CHIME-D model and it was highlighted throughout the course, and first person narratives of those in recovery were used for a majority of the mental health disorders; the intervention still had no effect on students’ attitudes toward recovery. There are numerous possible reasons why the intervention had no effect. Stacey and Stickley (2012) posited that recovery is a challenging concept for students to accept because, among other reasons, recovery may occur without the help of healthcare professionals such as registered nurses, the profession they are pursuing. The recovery concepts may also come into direct conflict with students’ past experiences with people experiencing mental health issues and their ­preconceived ideas about the possibilities of recovery (Stacey & Stickley, 2012). Additionally, students often expect nursing education to be in complete alignment with the medical model and can be critical of educational content that includes holism, social determinants of health, and therapeutic communication skills that are the cornerstone of a recovery-oriented practice (Stacey & Stickley, 2012, p. 536).

It is possible that the lack of change in student attitudes toward mental health recovery was due to an unbalanced curricular epistemology that favors empirics and the subsequent biomedical model. This imbalance may have resulted in students misunderstanding mental health recovery in past research (Chua et al., 2023;; Watson and Reimann, 2021). In light of this, it may be necessary to revise the curriculum. Chua et al. (2023) suggested that nursing curricula need not remove the biomedical model but include a more “holistic approach” (p. 1). A balanced way of knowing and presenting knowledge would align with Carper’s vision of nursing epistemology (Carper, 1978). The prevailing biomedical model of mental illness hinders the cultivation of positive attitudes toward recovery as it disallows perspectives that differ from clinical recovery (Chua et al., 2023, p. 2). Carper’s four ways of knowing in nursing are empirics, the science of nursing; esthetics, the art of nursing; personal knowing, the self-awareness of nursing; and ethics, the morality of nursing. All ways of knowing should be valued to ensure a more holistic nursing curriculum. In a systematic literature review, Hawsawi et al. (2021) found that critiquing the biomedical perspective of recovery increased healthcare providers’ knowledge and positive attitudes toward mental health recovery.

The moderate to strong negative correlations found between attitudes toward recovery and prejudice toward people living with mental health conditions in undergraduate nursing students may be the first of its kind demonstrated in the literature. These findings suggest that educational interventions that target prejudice reduction may have a positive impact on recovery attitudes. Conversely, interventions that seek to increase optimistic recovery attitudes may reduce prejudice toward people living with mental health conditions. It is possible that the attitude that people with mental health conditions cannot recover is in itself prejudicial, hence the moderate to strong negative relationship.

According to Anthony (1993), a pioneer in the development of the concept of recovery, nursing needs to consider not where we are as a profession but where we want to be. Though challenging, it is neither unrealistic nor romantic to expect nurses and nurse educators to wholeheartedly adopt the ideals of recovery in mental health nursing and nursing education. It is not an indication of false hope but of a reality in dire need of change. As opposed to the biomedical reductionist ideals, nursing should adopt the ideas of personal recovery focusing on encouraging connection, hope, identity, meaning, and empowerment. Through advocacy, partnership, and unconditional positive regard, nurses put patients, who are people, not the illness, at the center of treatment. That is, they provide person-centered care, not illness-centered care.

Limitations

This quasi-experimental study’s results would have been strengthened with randomization. Generalization of the findings may be limited because of the use of a convenience sample. The instruments used in this study were all self-report measures covering socially sensitive topics and may have been impacted by a response bias due to the social desirability of participants (Van de Mortel, 2008). It is possible that participants may have altered responses to present themselves as individuals with high levels of optimism toward recovery and low levels of prejudice toward people with mental health conditions.

Implications and future research

Unfortunately, the current study found no positive impact on the students’ attitudes toward recovery of those diagnosed with a mental illness. The traditional clinical groups in the hospital-based acute psychiatric units exposed the students to individuals in the most acute stages of symptomatology, not those further along in the recovery process. Therefore, nontraditional clinical sites need to be integrated into the course as there is evidence that they decrease the desire for social distance from those impacted by a mental illness (Moxham et al., 2016).

There also may be a way of addressing this shortcoming by way of collaboration with other courses within a nursing program. For example, there is a community nursing course in the ABSN program used for the current study that includes both classroom and clinical experiences. Partnering with this course may provide a unique opportunity to revisit the concepts of recovery and apply them in the community nursing context. Additionally, the community nursing clinical experiences may provide the chance to highlight and support recovery outside of the acute inpatient psychiatric units.

As well intentioned and rigorous as the classroom interventions were designed to be, they undoubtedly were not enough to transform well entrenched attitudes. The indirect contact by way of videos of individuals sharing their recovery journey seemingly had no measurable impact on the recovery attitudes of the students. Revisions that holistically integrate the concepts of recovery further into the curriculum need to be made. No matter the intervention that is chosen for future research, the inclusion of a control group is of the utmost importance to strengthen study design and examine the possible threats of maturation and testing. Additionally, an instrument created with the CHIME-D framework in mind currently does not exist and would be invaluable.

This study also demonstrated that a moderate to strong negative relationship exists between prejudice toward people experiencing a mental illness and attitudes toward recovery. Consequently, educational interventions that aim to decrease prejudice may increase positive attitudes toward recovery, and vice versa. Further research should explore this possible causative relationship in depth.

Conclusions

This study’s findings showed that an undergraduate nursing course had no measurable impact on student attitudes toward mental health recovery. It also demonstrated a moderate to strong negative relationship between prejudice toward people who experience a mental illness and attitudes toward recovery. Since it is a critical component of mental health, professional nurses require a deeper understanding of and a positive attitude toward recovery (Cleary et al., 2013). As students have reported that most of their understanding of mental health recovery comes from their undergraduate education, that is the best time to make a positive impact (Chua et al., 2023).

Just as challenging setbacks are part of the recovery process, failing to make an impact on attitudes about recovery is also perhaps a necessary step back and a humble realization. The path of recovery is not always linear, and neither are the educational interventions that seek to cultivate more positive attitudes toward recovery.

Nursing is a process of humanization (Willis et al., 2008) and not the “capitulation of personhood” (Deegan, 2002, p.6). It is not a profession of devaluation, reducible stigmatization, and pessimism. It is about advocacy, not abandonment. Therefore, those in the nursing profession and undergraduate nursing education must seek to understand, engage with, and support the work of recovery, to be an unrelenting advocate of hope. As Anthony (1993) states, “Recovery is a deeply human experience, facilitated by the deeply human responses of others. Recovery can be facilitated by any one person. Recovery can be everybody’s business” (p. 18).

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.