De-Stigmatization for Individuals with Severe Mental Illness and Substance Use Disorder: A Multi-Method Approach to the Development of the Biondo REACH Training Program for Healthcare Students

doi:10.21203/rs.3.rs-6675567/v1

Download PDF

Research Article

De-Stigmatization for Individuals with Severe Mental Illness and Substance Use Disorder: A Multi-Method Approach to the Development of the Biondo REACH Training Program for Healthcare Students

https://doi.org/10.21203/rs.3.rs-6675567/v1

This work is licensed under a CC BY 4.0 License

You are reading this latest preprint version

Despite the development of de-stigmatization training programs, individuals with severe mental illness (SMI) and/or substance use disorder (SUD) continue to face profound levels of stigmatization from their healthcare providers (HCPs). Stigmatizing behaviors exhibited by HCPs exacerbate dehumanizing and devaluing experiences and inhibit people with SMI and SUD from seeking services. Moreover, recipients of stigmatization from HCPs experience poorer physical and mental health outcomes, self-esteem, and self-efficacy, and overall quality of life. Although some de-stigmatization trainings have shown to be useful in reducing stigmatizing beliefs, there is a need to address the primary concerns expressed both by healthcare students and individuals with SMI and/or SUD. We employed a multi-methods study to: (1) understand the lived experience of individuals with SMI and/or SUD and their interactions with HCP, (2) examine self-reported perceptions of healthcare students’ stigmatizing beliefs towards individuals with SMI and/or SUD, and (3) develop preliminary goals towards creating a collaborative training program co-taught with people with lived experience (PWLE) of SMI and/or SUD. We collected quantitative data from healthcare students at an urban university using the Attribution Questionnaire and lived experiential qualitative data from individuals with SMI and/or SUD through focus groups. Results showed that healthcare students primarily exhibit pitying and helping stigmatizing behaviors, while PWLE feel dehumanized, devalued, and excluded from their treatment. Our training program—Rehumanization, Empathy, Attunement, and Compassion in Healthcare (Biondo REACH)—will be developed and co-taught by PWLE, focusing on the identified gaps in healthcare services between PWLE and HCP.

stigmatization

dehumanization

severe mental illness

substance use disorder

healthcare

training program

Stigmatization occurs when populations and communities are labeled and divided into ingroups and outgroups, with those in designated outgroups subject to negative stereotypes, discrimination, and loss of status. The dynamics of ingroups and outgroups are often associated with elements of power and proximity to power; those in the outgroups often have less power and are systematically placed on the fringe and in the margins. Discrimination due to stigmatization can be individual, driven by interpersonal interactions and relationships, and structural, arising from institutional and systemic barriers (Link & Phelan, 2001). In healthcare settings, stigmatization can arise from negative attitudes and behaviors, lack of provider skills and training, and structural factors such as organizational culture, quality of care standards, and resource investment (Knaak et al., 2017). For patients with SMI and/or SUD, stigmatization affects their ability to seek and participate in medical care and influences treatment and health outcomes after care has been accessed (Corrigan et al., 2014).

One result of stigmatization in medical settings is diagnostic overshadowing, when people with mental illness are underdiagnosed with co-occurring physical or mental health conditions, resulting in delayed or inappropriate treatment and worse health outcomes (Jones et al., 2008). Diagnostic overshadowing may be due to misattribution of symptoms, lack of knowledge or training about mental illness presentations, provider bias, or a combination thereof (Jones et al., 2008). Patient experiences indicate diagnostic overshadowing may be due to clinician mistrust and frequent attribution of pain and physical symptoms to mental health conditions, focusing on mental over physical health (Cunningham et al., 2023b). Patients seeking care in an emergency department (ED) frequently cited diagnostic overshadowing as a barrier to care, with ED staff triaging patients as psychiatric regardless of their complaint (Clarke et al., 2007).

Stigmatizing views on mental illness, diagnostic overshadowing, and insufficient workup negatively impact medical care for people with mental illness across locations and practice settings (Carerra et al., 2023; Hallyburton & Allison-Jones, 2023; Riffel & Chen 2020). Structural flaws in the healthcare system, such as provider training, resource availability, and lack of service coordination, can also negatively impact care (Riffel & Chen, 2020). Many primary care physicians feel unprepared to manage mental illness. Stigmatizing views of mental illness are widespread and associated with a negative outlook on treatment adherence and likelihood of success (Vistorte, 2018). Lack of formal training on mental illness, institutional resources, and opportunities for care coordination frequently impact HCP ability to care for patients with SMI or SUD (Loeb et al., 2012). People with SMI who are also people of color and/or members of the lesbian, gay, bisexual, transgender, and queer community reported intersectional discrimination influenced by mental illness stigma as well as racist, homophobic, and transphobic beliefs, including microaggressions, microinsults, and difficulty finding knowledgeable HCP with whom they could also relate (Hempeler et al., 2024).

Additionally, stigmatization of SMI is associated with longer physical illness duration and reduced visits to medical facilities, and leads to delays in care, poorer health outcomes, and decreased patient empowerment and quality of life (Chuckwuma et al., 2024). Additionally, there is a significantly increased risk of premature death and excess mortality among people with mental illness (de Mooij et al., 2019; Harris & Barraclough, 1998; Kisely & Siskind, 2021; Walker et al., 2015). The risk of all-cause mortality is 2.2 times higher for patients with mental illness than those without, with 67% of deaths in this population attributable to natural causes (Walker et al., 2015). Individuals with a mental illness develop physical health conditions and die at younger ages than those without. Furthermore, mental illness is associated with having more hospitalizations, longer hospital stays, and higher healthcare costs for physical health conditions (Richmond-Rakerd et al., 2021).

People with SMI and/or SUD frequently use strategies to avoid or reduce discrimination, including not disclosing their mental health diagnosis, changing providers when they experienced discrimination, bringing a support person to appointments, and practicing self-advocacy (Cunningham et al., 2023a; Clarke et al., 2007). Positive perceptions and behaviors by health care providers, including empathy, provider advocacy, and avoiding clinical tools and materials with stigmatizing language, can also positively impact patient care (Riffel & Chen, 2020).

Study Design

Mixed methods research is an approach that combines both qualitative and quantitative research techniques within a single study to provide a more comprehensive understanding of a research problem. Integrating numerical data (quantitative data) with in-depth textual insights (qualitative data) allows for a more complete exploration of complex issues and enhances the richness of the findings. Creswell (2009) described mixed methods research as a “procedure for collecting, analyzing, and mixing quantitative and qualitative data at some stage of the research process within a single study in order to understand a research problem more completely” (p. 15). The primary benefit of mixed methods is its ability to draw on the strengths of both approaches, offering a more holistic perspective than either method alone. Integrating more than one type of data collection and analytic approach allows for understanding new patterns and novel questions while also allowing the researcher to capture diverse perspectives about the same issue. Ivankova and Creswell (2009) referenced the work of Green et al., (1989) and Tashakkori and Teddlie (1998) in noting, “collecting and analyzing quantitative and qualitative data within one study will produce a more comprehensive understanding of the research situation than collecting only one type of data or the other” (p. 145).

In the present study, the research team sought a comprehensive understanding of a complex issue, with particular interest in capturing diverse perspectives. Mixing more than one type of data allowed this team to better understand the complex topic of interest. The qualitative data in this study were captured through focus groups from people with lived experiences (PWLE) of SMI. We specifically wanted to understand their perspectives on stigma, treatment, and how they experience their HCP. Additionally, we collected quantitative data from HCP trainees to better understand how those trainees view and perceive individuals living with SMI and/or SUD. Teddlie and Tashakkori (2010) defined mixed methods research as research that involves collecting and analyzing both qualitative and quantitative data. In this present study, data were collected in parallel phases, and we were specifically interested in capturing multiple perspectives and views on the problem. The design and execution of the current study are also consistent with the definition provided by Creswell and Clark, first in 2007, refined in 2011, and further clarified in 2017. Cresswell and Clark (2017) highlighted that mixed methods research involves research methods, design, and an overarching philosophical orientation. Creswell and Clark (2017) note that the mixed methods researcher:

Collects and analyzes both qualitative and quantitative data rigorously in response to research questions and hypothesis; Integrates (or mixes or combines) the two forms of data and their results; organizes these procedures into specific research designs that provide the logic and procedures for conducting the study and; frames these procedures within the theory and philosophy. (p. 5)

The central premise of the current study’s approach was the recognition that combining different types of data and data collection approaches would enrich our understanding of the complex issue at hand.

While this study meets the aforementioned criteria of mixed-method research, it may also be characterized as multi-method research. As noted by Anguera et al (2018), some scholars make no distinction between mixed and multi-method research. For example, Stange et al. (2006) use the terms interchangeably when noting, “Mixed methods (also known as multimethod) research involves integrating quantitative and qualitative approaches to generating new knowledge” (p. 292).

In 2007, Johnson et al. conducted a content analysis and examined nineteen definitions of mixed-methods research. They engaged with several thought leaders in the field to arrive at key distinctions and characteristics of mixed methods research. The definitions that they arrived at were widely varied. This included different ideas on how the actual “mixing” occurred, when it occurred, why it occurred, and the overarching purpose of the research. Our study, which specifically seeks to integrate the findings at the conclusion of the study, is best characterized as a multi-method study, as it draws inferences using the data to arrive at a deeper understanding of a complex issue. In the present study, the inferences being drawn are specifically examined after data collection and are used to inform the development of an anti-stigma curriculum, informed by the expertise of those with lived experiences, to improve the knowledge and education of healthcare trainees.

Study Participants

Participants were recruited in two separate groups for this study to satisfy the research aims. We detail the recruitment strategies of each group below.

Arm 1: Quantitative

We recruited study participants for each arm of the study individually. The first arm of the study employed a quantitative design that surveyed 98 participants at an urban university. Inclusion criteria were that study participants were either second-year students enrolled in the medical program or first-year students enrolled in the physician assistant program. The year of study for respective participants was determined based on the comparability of healthcare knowledge and not having worked in a clinical rotation with patients. Fifty participants were enrolled in the medical program and 48 in the physician assistant program. Demographic data were collected and are outlined in Table 1. Participants were recruited through a flyer sent via email to student listservs.

Table 1
Participant Demographic Data for Quantitative Arm, N = 98
	Total (N = 98)	Physician Assistant Students (n = 48)	Medical Students (n = 50)
Age, Mean ± SD
Range, years	24.15 ± 2.32	22.88 ± 1.82	25.38 ± 2.09
Gender, n (%)
Male	25 (26)	3 (6)	22 (44)
Female	71 (72)	44 (92)	27 (54)
Non-binary	1 (1)	1 (2)	0 (0)
Prefer not to Disclose	1 (1)	0 (0)	1 (2)
Race, n (%)
American Indian or Alaska Native	0 (0)	0 (0)	0 (0)
Asian	25 (26)	15 (31)	10 (20)
Black or African American	8 (8)	0 (0)	8 (16)
Native Hawaiian or Pacific Islander	1 (1)	0 (0)	1 (2)
White	57 (58)	32 (67)	25 (50)
Biracial	3 (3)	0 (0)	3 (6)
A Race not Listed	1 (1)	0 (0)	1 (2)
Prefer not to Disclose	3 (3)	1 (2)	2 (4)
Ethnicity, n (%)
Not Hispanic, Latine, or Spanish	86 (88)	40 (83)	46 (92)
Mexican, Chicanx	0 (0)	0 (0)	0 (0)
Puerto Rican	0 (0)	0 (0)	0 (0)
Cuban	0 (0)	0 (0)	0 (0)
Bi-ethnic	1 (1)	1 (2)	0 (0)
Another Ethnicity not Listed	8 (8)	5 (10)	3 (6)
Prefer not to Disclose	3 (3)	2 (4)	1 (2)
Note. This table provides demographic characteristics for the MD and PA students who completed the Attribution Questionnaire.

Arm 2: Qualitative

Participants for the second arm of the study were recruited from an urban nonprofit organization that provides mental health services to individuals in the surrounding communities. Inclusion criteria for the qualitative arm of the study were: (1) adults over the age of 18 years, (2) having a self-reported diagnosis of a severe mental illness and/or substance use disorder, and (3) the ability to communicate in English. Forty participants were enrolled in the second arm of the study. Demographic data were collected and are outlined in Table 2. Participants were recruited through flyers hung in common areas of the facility.

The Institutional Review Board at [redacted] approved the study protocols, Protocol # iRISID-2023-2855 (Arm 1) and Protocol # iRISID-2023-2972 (Arm 2). Informed was obtained by all participants in both arms of the study.

Table 2
Participant Demographic Data for Quantitative Arm, N = 40
Age, Mean ± SD	52.35 ± 13.78
Range, years	23–83
Gender, n (%)
Male	16 (40)
Female	23 (57.5)
Transgender Female	1 (2.5)
Race, n (%)
American Indian or Alaska Native	1 (2.5)
Asian	0 (0)
Black or African American	28 (70)
Native Hawaiian or Pacific Islander	0 (0)
White	4 (10)
Biracial or Multiracial, Black & Puerto Rican	1 (2.5)
A race not listed here
Spanish	2 (5)
Latine	3 (12.5)
Prefer not to Disclose	1 (2.5)
Ethnicity, n (%)
Not of Hispanic, Latine, or Spanish Origin	28 (70)
Mexican	0 (0)
Puerto Rican	7 (17.5)
Cuban	1 (2.5)
Dominican	1 (2.5)
Prefer not to Disclose	3 (7.5)
Note. This table provides demographic characteristics for the individuals with lived experience of SMI and/or SUD who participated in the focus groups.

Data Collection

Measures

We administered the Attribution Questionnaire (AQ-27) as the outcomes measure for the participants in the study's quantitative arm. A qualitative, semi-structured interview was delivered through focus groups for participants in the second arm of the study.

Arm 1: Attribution Questionnaire (AQ-27). The AQ-27 is a 27-item, 9-point Likert scale developed to examine self-perception of stigmatizing beliefs and behaviors towards individuals with SMI. The AQ-27 provides a brief vignette about a man diagnosed with schizophrenia, then makes 27 statements regarding participants’ beliefs about the vignette patient. Statements are inclusive of nine constructs of stigmatization: (1) Blame, (2) Anger, (3) Pity, (4) Help, (5) Dangerousness, (6) Fear, (7) Avoidance, (8) Segregation, and (9) Coercion. Each statement was accompanied by a 9-point Likert scale. Higher scores in each construct represent greater levels of stigmatizing beliefs. This scale demonstrates good internal consistency (α = .77 to .91) for all but one factor, which demonstrated fair internal consistency (α = .60). Additionally, the test-retest reliability for each of the nine subscales ranged from α = .55 to α = .87, with seven of the nine constructs above α = .75 (Brown, 2008; Corrigan et al., 2004).

Arm 2: Focus Groups. The research team developed a semi-structured interview guide that included 11 open-ended questions with probative questions as needed. Participants joined one of six focus groups based on the location of their program. Focus groups consisted of between five and nine participants and lasted approximately 90 minutes. All focus groups were conducted at one of three locations associated with the partner non-profit organization, and times were chosen around the participants’ schedules for ease of attendance.

Data Analysis

Attribution Questionnaire

Data were collected via Research Electronic Data Capture (REDCap) (Harris et al., 2009; Harris et al., 2019) hosted at [redacted] University and extracted into an Excel file. We used descriptive statistics to determine both the overall scores of the AQ-27 and the subcategories on which participants scored highest.

Focus Groups

Focus group data were transcribed verbatim and uploaded into NVivo 14 (Lumivero, 2023) software for organization and analysis. Three coders completed the coding process. We used thematic analysis with inductive coding to capture the thoughts and ideas of participants through key words, phrases, and statements (Braun & Clarke, 2006). Codes were organized first into categories, then aggregated into final themes.

The coding and categorization of data were completed by three coders in total, with two coders analyzing data from each focus group. The first author (JB) was the primary coder and began the coding process with immersion in the data through iterative review of the transcript data. Next, the primary coder noted any initial impression, thoughts, and potential biases through memoing. Then, initial coding was conducted to capture latent content in the focus group data. The first author has experience as a qualitative analyst and thus reviewed, organized, coded, and analyzed all the data. The second coders reviewed 100% of the coded data to add clarifications and suggest potentially under- or miscoded data. The two coders discussed and reached consensus in the few instances where the second coder noted coding discrepancies.

Following the first stage of coding, the three coders assembled to organize the codes into categories. These categories were further organized and aggregated into the final themes, which represented the voices and essence of each participant (Braun & Clarke, 2006).

Results from the AQ-27 determined that participants scored help (7.44 ± 1.56) and pity (6.91 ± 1.40) highest, followed by avoidance (4.82 ± 1.68). Quantitative results are further detailed elsewhere (Biondo et al., in progress). Quantitative results yielded the following themes: (1) Agency in treatment decisions, (2) Emotional and structural challenges to healthcare, (3) Influence of power dynamics in healthcare, (4) Interactions and experiences between patients and HCPs, (5) Need for trust and advocacy in healthcare, and (6) Dehumanization and disregard of patient insight. Qualitative results are further detailed elsewhere (author et al., in progress).

Training Program

Learning Theories

Regarding our third aim to identify data-driven foci for a de-stigmatization training program, we considered the learning theories that will be foundational in developing the training. We will use social (cultural) constructivist and experiential learning theories to ground the course development framework. Each theory contributes fundamentally to the conceptual framework and to a more holistic learning process when coupled. Finally, we will note the consideration of andragogy—learning geared specifically towards adult learners—as activism, particularly in relationship with experiential learning theory.

Social (Cultural) Constructivist Theory

First conceptualized by Vygotsky, socio-cultural constructivism emphasizes (1) the socio-historical component of learning (Mukhalatati & Taylor, 2019; Taylor & Hamdy, 2013), (2) learning through and with one’s community (Taylor & Hamdy, 2013), (3) acquisition of new knowledge as it builds upon and integrates with existing knowledge, and (4) knowledge construction informed by social and physical environmental contributions (Mukhalatati & Taylor, 2019). Similarly, social constructivism prioritizes collaboration, referring to learning as “social activity” (Amna Saleem et al., 2021, p. 406). Learning occurs through sharing language and culture amongst individuals with a common goal of increasing understanding and knowledge. Community plays the role of both supporting and challenging members to push the limits of collaboration in an attempt to co-create new knowledge. Through a social (cultural) constructivist framework, the teacher acts as a facilitator and scaffolds knowledge only when necessary, as the primary learning is done in collaboration with others. This theory fosters an active role in learning through the collaborative integration of many opinions with diverse perspectives. This activation in learning leads to curiosity, critical thinking, problem solving, and expertise amongst learners (Amna Saleem et al., 2021).

Experiential Learning Theory

Experiential learning theory (ELT) similarly emphasizes activation when learning, suggesting knowledge is acquired through interactions and experiences with others (Conner, 2022; Mukhlaltati & Taylor, 2019). Conceptualized by Kolb, ELT values practice as a primary form of gaining knowledge (Mukhalatati & Taylor, 2019). Conner (2022) suggested that ELT involves a cyclical way of learning, moving through “experiencing, reflecting, thinking, and acting” (p. 3). One noted limitation of ELT is that, typically, social context is not considered (Mukhalatati & Taylor, 2019); however, an integration of ELT with social (cultural) constructivist theory could satiate the activation, experience, and social context of learning, providing a holistic learning theory.

Healthcare Advocacy

Experiential learning theory has been used as an andragogical tool with student activists with promising results. As a teaching framework, ELT has increased service and critical consciousness amongst college students while encouraging them to learn within and amongst community (Conner, 2022). Healthcare professionals are advocates by nature, often working towards equitable, accessible, and justice-driven care for their patients and clients. Olantumbosun and Wilby (2022) outline two types of healthcare advocacy and two ways of engaging within the system. Healthcare advocacy is either agency or activism, facilitated either by shared or directed engagement. Agency occurs on an individual level through which a healthcare worker directly supports an individual and through system navigation. Activism brings attention to resources and change-making within systems. Shared experiences occur in partnership between the provider and patient, while directed experiences occur when the HCP works on behalf of the patient. Healthcare advocacy happens when collaborative efforts amongst stakeholders positively impact patients' wellness (Olatunbosun & Wilby, 2022).

We believe that integrating social (cultural) constructivism and experiential learning theory will inspire advocacy amongst healthcare student participants in our training program. A collaborative teaching experience between an educator and PWLE will provide social cultural insights, while facilitators and participants come together from diverse backgrounds to collaboratively co-create knowledge. This novel partnership between healthcare students and PWLE coming together for knowledge creation through experiential learning can deepen the desire for advocacy in the form of agency and activism and in both shared and directed ways.

Content Foci

Based on the qualitative and quantitative research findings, we identified three primary foci for the de-escalation training program: (1) empathy, (2) interpersonal skills, and (3) collaborative rehumanization. Results from our quantitative findings suggest that students stigmatize patients through pity and a desire to help, which creates devaluation and diminishes agency, respectively. Although healthcare students may believe their actions to be helpful, participants from the qualitative arm of the study indicate that this behavior is received as demeaning. Qualitative participants with lived experience of having SMI and/or SUD noted that they wished their HCPs showed more empathy and humanity towards them.

Participants with lived experience also expressed the need for healthier interpersonal relationships between those seeking and those providing services. Thus, the second focus of the program will be developing healthy and authentic interpersonal relationships. Combining the two aforementioned foci leads us to our final area of rehumanization. Participants with lived experience expressed their feelings of dehumanization due to their HCP. We aim to collectively unpack this concept and work towards a collaborative rehumanization process, fostering agency and self-efficacy amongst individuals with SMI and/or SUD seeking healthcare services and offering HCPs the opportunity to authentically relate with those seeking healthcare services.

Stigma, Bias, and Patient Behaviors in Health Care

Stigma and bias within healthcare has the potential to significantly alter patients' experience and access to healthcare. Stigma is a complex social process that involves labeling, stereotyping, and marginalizing individuals or groups based on perceived differences, often leading to discrimination, status loss, and social exclusion (Link & Phelan, 2001).

The work of Corrigan et al. (Corrigan & Watson, 2002; Corrigan et al., 2014) has significantly advanced our understanding of stigma and its detrimental effects on individuals with mental illness, particularly concerning help-seeking behaviors. Corrigan and Watson (2002) noted three interconnected components of stigma: stereotypes, prejudice, and discrimination. These authors emphasized that stereotypes are the culturally ingrained beliefs that someone may have of another person. As it relates to mental illness, these could be related to perceptions of the individual with SMI as being dangerous or incompetent (Corrigan & Watson, 2002).

Prejudice is related to internalized agreement with those negative stereotypes and can result in emotional responses like fear or disgust. Discrimination, in this particular model, relates to the behavioral responses that emerge from prejudice. In the context of SMI, discrimination may manifest as avoidance or distancing. Stigma has both public and personal elements that relate to both how society thinks about and reacts towards someone with mental illness and how one views oneself. When patients internalize the social beliefs about themselves or their mental illness, this can result in decreased self-efficacy and feelings of hopelessness (Corrigan & Watson, 2002; Corrigan et al., 2014).

Understanding Empathy, Sympathy, and Pity in Health Care

The emotions and perceptions HCPs hold towards their patients can shape the quality of care they deliver and how patients experience and interpret that care. Although emotions like empathy and sympathy are often viewed positively, pity is a more nuanced and potentially less beneficial response (Sinclair et al., 2016). Providers who feel empathy towards their patients may find that this enhances the patient-provider relationship. Providers who, even unintentionally, emote sympathy or pity may conversely find that this hinders their relationships with patients.

Understanding the distinctions between empathy, sympathy, and pity is important, as this can profoundly shape a patient’s experience. Empathy broadly refers to the capacity to understand another person’s circumstances and their emotional state. It involves both affective and cognitive dimensions. Affective empathy involves sharing or mirroring another's emotions, while cognitive empathy pertains to understanding another's perspective or mental state. This multifaceted construct is crucial for effective social interactions and moral reasoning (Cuff et al., 2016). Genuine empathy that involves both cognitive and affective components can improve the quality of all relationships, including those between patients and providers (Moudatsou et al., 2020; Nembhard et al., 2023)

Sympathy differs slightly from empathy (Nembhard et al., 2023; Clark et al., 2019). Sympathy involves recognizing and having care for another’s experience. While sympathy involves concern, it does not necessarily involve a shared emotional experience like empathy. Sympathy may lead to a superficial acknowledgement of someone else’s experience, without a deeper relational engagement. It can result in a somewhat detached perspective from the provider and a missed opportunity for connection. Sympathy alone, without a deeper emotional connection like what might be present in empathy, may interfere with authentic relationship building between providers and patients (Svenaeus, 2015).

Unlike empathy and sympathy, pity is a less helpful emotion in the context of patient-provider relationships. Pity involves feeling sorry for someone else; an element of detachment and disconnection between the two individuals often accompanies feelings of pity (Breyer, 2020). Patients may experience providers as condescending or judgmental when providers view them with pity. In healthcare settings, patients generally view pity as something they do not want their providers to feel towards them (Darabos et al., 2022). Providers who feel pity towards patients may unintentionally engage in paternalistic or patronizing behaviors towards patients, which can compromise patient autonomy and dignity (Gerdes, 2011; Sinclair et al., 2017).

Compassion, Interpersonal Skills, and Rehumanization Skill Development

Our research findings revealed that participants reported a lack of compassion from HCPs regarding their unique needs and circumstances. When confronted with dismissive, devaluing, and unkind behavior, participants felt dehumanized and unheard by their HCP. These negative experiences also impacted the perceived quality of care, prompting some patients to seek new healthcare options. The experiences described by study participants highlight the need for compassion, enhanced interpersonal skills, and rehumanization strategies when providing healthcare for people with SMI and/or SUD. Rehumanization is defined as the process that attempts to restore the sense of humanity that has been diminished through dehumanization (Jenkins et al., 2023). Participants expressed a strong desire for individualized care, which they felt required a deeper connection with the HCP. These deeper connections could be one way to facilitate the rehumanization process by establishing additional social connections for those with SMI and/or SUD (Jenkins et al., 2023). Behaviors that some may perceive as a lack of communication, temporary negative mood, or poor customer service may be perceived as discrimination by individuals with a mental health condition. Such perceptions can lead to feelings of devaluation and disrespect, which can negatively impact healthcare quality for patients (Hamilton et al., 2016). The experiences documented in this study and previous research emphasize the need for incorporating interpersonal skills, empathy cultivation, and strategies for rehumanization into education and training for HCPs.

Existing Collaborative Trainings and Future Direction

Historically, there have been collaborative trainings between educators and PWLE in an effort to decrease stigmatization (Amsalem et al., 2020; Atienza-Carbonell et al., 2022; Grandon et al., 2021; Martinez-Martinez et al., 2024; Potts et al., 2022; Switaj et al., 2019). Significant variance exists among these trainings regarding training recipients, training protocol and duration, and outcome measures. Such variability makes it difficult to know how to best set up a de-stigmatization training program. Moreover, training programs must be implemented consistently to ensure the knowledge reaches recipients promptly and systematically. Extant collaborative training programs vary in length of training, from a single training delivery lasting between one and a half to three hours (Amsalem et al., 2020; Atienza-Carbonell et al., 2022; Martinez-Mertinez et al., 2024; Switaj et al, 2019), to a 2-part 1.5-hour training at the start and end of a psychiatric rotation (Potts et al., 2022), to a 6-session training lasting 2.5 hours per session (Grandon et al., 2021). Populations participating in the trainings include HCPs (Grandon et al., 2021), medical students (Amsalem et al., 2020; Atienza-Carbonell et al., 2022), medical students specifically in their psychiatric rotation (Potts et al., 2022), vocational-technical students (Martinez-Martinez et al., 2024), and a mix of psychiatric staff, students, employment office workers, teaching and administrative staff, and volunteers (Switaj et al., 2019). Outcome measures of each study also varied and included a wide range of quantitative measurements, including scales examining stigmatization reduction (Grandon et al., 2021; Heim et al, 2019; Martinez-Martinez et al., 2024; Potts et al., 2022; Switaj et al., 2019), social distance (Grandon et al., 2021), community attitudes towards individuals with mental illness (Amsalem et al., 2020; Atienza-Carbonell et al., 2022; Potts et al., 2022), mental health knowledge, empathy, and intergroup anxiety (Potts et al., 2022).

The inconsistencies amongst each extant training make it difficult to assess the effectiveness of a de-stigmatization training program. Our training, the Biondo Rehumanization, Empathy, Attunement, and Compassion in Healthcare (Biondo REACH) program is directly informed by both the population who would be receiving the training—healthcare students—and those with lived experience of an SMI and healthcare service-seeking. Moreover, PWLE will co-facilitate the training program in multiple ways. Not only will they provide anecdotal teaching, but they will also co-lead experiential learning practices. Based on our preliminary results, our training program will focus on empathy development and attunement between healthcare students and PWLE. Ultimately, we aim to develop a compassionate program that collaboratively works towards a rehumanization process for individuals with SMI and/or SUD.

Communication Disconnect Between Healthcare Providers and Recipients of Care

Although healthcare students, and thus future practitioners, may feel that their behaviors are helpful, recipients of healthcare services report the behaviors as being demeaning, creating hierarchical relationships and feelings of disconnect, diminishment, and dehumanization. Ineffective communication decreases the quality of care people receive while increasing care costs and negative health outcomes (Ratna, 2019). Miscommunication between HCPs and recipients is well documented (Clochesy et al., 2015; Kaufman et al., 2012; Ratna, 2019); however, our data highlights that not enough is being done to increase effective communication, particularly with individuals diagnosed with SMI seeking healthcare services. Moreover, HCPs have expressed resistance to treating people with SMI, describing them as “undesirable” patients (Kaufman et al., 2012, p. 176).

Due to this bias—unconscious or otherwise—HCPs make assumptions about individuals with SMI, under-inform them about their treatment, talk down to them, doubt self-reported symptoms, and adopt an overall demeanor of disrespect. This, in turn, disrupts the ability for patients with SMI to trust or respect their HCP (Kaufman et al., 2012). Each of the aforementioned behaviors was reported by PWLE in our focus groups. Furthermore, some research highlights the implementation of patient self-management, providing agency to the patient regarding their healthcare needs (Clochesy et al., 2015; Ratna, 2019). In contrast, our qualitative data show that patients with SMI and/or SUD feel excluded from their care plans.

Many research studies on communication between healthcare workers and patients found that HCPs are putting the onus on the patients to not only ensure healthy communication but also build rapport between the two (Clochesy et al., 2015; Ratna, 2019). Clochesy and colleagues (2015) also noted that patients are responsible for noting and interpreting providers' non-verbal behaviors. The concept of reception and interpretation of non-verbal cues was echoed by Ratna (2019). However, neither party has been taught to understand and respond to non-verbal cues. Our proposed training, the Biondo REACH program, incorporates the tenets of dance/movement therapy as embodied learning to prioritize the body as a resource for learning while incorporating non-verbal cues as a means of communication.

In tandem with non-verbal communication prioritization, it is imperative that healthcare workers attend to specific cultural needs of individuals with SMI and/or SUD (Kaufman et al., 2012; Ratna, 2019). This is inclusive of those who are racially and ethnically minoritized and have experienced the culture of SMI and SUD (author, In Print).

This study employed a multi-methods design in which a quantitative data strand was collected from MD and PA students using the AQ-27 and a qualitative data strand via semi-structured interviews with PWLE of SMI and/or SUD. Collecting both strands of data simultaneously allowed us to understand the phenomenon of stigmatization in healthcare from a holistic perspective. Given the miscommunication between the providers and recipients of healthcare, de-stigmatization training programs are necessary to develop and foster supportive relationships between HCPs and PWLE of SMI and/or SUD seeking healthcare services. Our data indicate that a training program inclusive of skill development in empathy, interpersonal relationships, and communication will benefit both populations. Moreover, extant research shows that training programs co-facilitated by PWLE are most effective. With that, we recommend developing, piloting, and evaluating our collaboratively taught Biondo REACH program. Benefits of a successful and widely implemented de-stigmatization training program, such as Biondo REACH, can improve patient-provider relationships, increase service-seeking by PWLE of SMI and/or SUD, improve and provide consistent training opportunities for healthcare students, and, ultimately, decrease stigmatization amongst individuals with SMI and/or SUD seeking healthcare services.

Acknowledgements

The authors would like to acknowledge Dr. Lara Carson Weinstein for her supervision and guidance on this research project.

Competing Interests

The authors declare no potential conflict of interest with respect to research, authorship, or publication of this article.

Human Ethics and Consent To Participate Declarations

All procedures performed in this study involving human participants were in accordance with the ethical standards of the institution at which it was conducted and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. We received ethical approval from the institutional review board at Thomas Jefferson University (iRISID-2023-2855; iRISID-2023-2973). Informed consent was obtained from all participants involved in the study. Data were collected anonymously. All data were stored on an encrypted, password-protected computer accessible only to the research team.

Funding

This research was funded by the Jefferson Smart and Healthy Cities Fellowship.

Amna Saleem, H., & Farah Deeba. (2021). Social constructivism: A new paradigm in teaching and learning environment. PERENNIAL JOURNAL OF HISTORY, 2(2), 403–421. https://doi.org/10.52700/pjh.v2i2.86
Amsalem, D., Gothelf, D., Dorman, A., Goren, Y., Tene, O., Shelef, A., Horowitz, I., Dunsky, L. L., Rogev, E., Klein, E. H., Mekori-Domachevsky, E., Fischel, T., Levkovitz, Y., Martin, A., & Gross, R. (2020). Reducing stigma toward psychiatry among medical students: A multicenter controlled trial. The Primary Care Companion for CNS Disorders, 22(2). https://doi.org/10.4088/PCC.19m02527
Anguera, M. T., Blanco-Villaseñor, A., Losada, J. L., Sánchez-Algarra, P., & Onwuegbuzie, A. J. (2018). Revisiting the difference between mixed methods and multimethods: Is it all in the name? Quality & Quantity, 52(6), 1–14. https://doi.org/10.1007/s11135-018-0700-2
Atienza-Carbonell, B., Hernández-Évole, H., & Balanzá-Martínez, V. (2022). A patient as educator intervention: Reducing stigmatizing attitudes toward mental illness among medical students. Frontiers in Public Health, 10, 1020929. https://doi.org/10.3389/fpubh.2022.1020929
Babicki, M., Kotowicz, K., & Mastalerz-Migas, A. (2021). The Assessment of Attitudes of Medical Doctors towards Psychiatric Patients-A Cross-Sectional Online Survey in Poland. International Journal of Environmental Research and Public Health, 18(12). https://doi.org/10.3390/ijerph18126419
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
Breyer, T. (2020). Empathy, sympathy, and compassion. The Routhledge handbook of phenomenology of emotion (pp. 429–440). Routledge.
Brown, S. A. (2008). Factors and measurement of mental illness stigma: a psychometric examination of the Attribution Questionnaire. Psychiatric Rehabilitation Journal, 32(2), 89–94. https://doi.org/10.2975/32.2.2008.89.94
Chukwuma, O. V., Ezeani, E. I., Fatoye, E. O., Benjamin, J., Okobi, O. E., Nwume, C. G., & Egberuare, E. N. (2024). A systematic review of the effect of stigmatization on psychiatric illness outcomes. Cureus, 16(6), e62642. https://doi.org/10.7759/cureus.62642
Clark, M. A., Robertson, M. M., & Young, S. (2019). I feel your pain: A critical review of organizational research on empathy. Journal of Organizational Behavior, 40(2), 166–192. https://doi.org/10.1002/job.2348
Clarke, D. E., Dusome, D., & Hughes, L. (2007). Emergency department from the mental health client’s perspective. International Journal of Mental Health Nursing, 16(2), 126–131. https://doi.org/10.1111/j.1447-0349.2007.00455.x
Clochesy, J. M., Dolansky, M. A., HickmanJr., R. L., & Gittner, L. S. (2015). Enhancing communication between patients and healthcare providers: SPAR3. Journal of Health and Human Services Administration.
Conner, J. O. (2022). Applying experiential learning theory to student activism. Journal of Further and Higher Education, 46(9), 1229–1242. https://doi.org/10.1080/0309877X.2022.2061843
Corrigan, P. W., Druss, B. G., & Perlick, D. A. (2014). The impact of mental illness stigma on seeking and participating in mental health care. Psychological Science in the Public Interest, 15(2), 37–70. https://doi.org/10.1177/1529100614531398
Corrigan, P. W., & Watson, A. C. (2002). Understanding the impact of stigma on people with mental illness. World Psychiatry: Official Journal of the World Psychiatric Association (WPA), 1(1), 16–20.
Corrigan, P. W., Watson, A. C., Warpinski, A. C., & Gracia, G. (2004). Stigmatizing attitudes about mental illness and allocation of resources to mental health services. Community Mental Health Journal, 40(4), 297–307. https://doi.org/10.1023/b:comh.0000035226.19939.76
Creswell, J. W. (2009). Research desigh: Qualitative, quantitative, and mixed methods approaches (3rd ed.). Sage.
Creswell, J. W., & Plano Clark, V. L. (2007). Designing and conducting mixed methods research. Sage.
Creswell, J. W., & Plano Clark, V. L. (2011). Designing and conducting mixed methods research (2nd ed.). Sage.
Creswell, J. W., & Plano Clark, V. L. (2017). Designing and conducting mixed methods research (3rd ed.). Sage.
Cuff, B. M. P., Brown, S. J., Taylor, L., & Howat, D. J. (2016). Empathy: A review of the concept. Emotion Review, 8(2), 144–153. https://doi.org/10.1177/1754073914558466
Cunningham, R., Imlach, F., Every-Palmer, S., Haitana, T., & Peterson, D. (2023). Dealing with discrimination in physical health care services: strategies of people with mental health and substance use conditions. Journal of Patient Experience, 10, 23743735231211776. https://doi.org/10.1177/23743735231211778
Cunningham, R., Imlach, F., Haitana, T., Every-Palmer, S., Lacey, C., Lockett, H., & Peterson, D. (2023). It’s not in my head: a qualitative analysis of experiences of discrimination in people with mental health and substance use conditions seeking physical healthcare. Frontiers in Psychiatry, 14, 1285431. https://doi.org/10.3389/fpsyt.2023.1285431
Darabos, K., Berger, A. J., & Ford, J. S. (2022). Empathy without sympathy: An analysis of support-related preferences among young adult cancer survivors. Journal of Psychosocial Oncology, 40(4), 457–472. https://doi.org/10.1080/07347332.2021.1914271
de Mooij, L. D., Kikkert, M., Theunissen, J., Beekman, A. T. F., de Haan, L., Duurkoop, P. W. R. A., Van, H. L., & Dekker, J. J. M. (2019). Dying too soon: excess mortality in severe mental illness. Frontiers in Psychiatry, 10, 855. https://doi.org/10.3389/fpsyt.2019.00855
Gerdes, K. E. (2011). Empathy, Sympathy, and Pity: 21st-Century Definitions and Implications for Practice and Research. Journal of Social Service Research, 37(3), 230–241. https://doi.org/10.1080/01488376.2011.564027
Grandón, P., Saldivia, S., Cova, F., Bustos, C., Vaccari, P., Ramírez-Vielma, R., Vielma-Aguilera, A., Zambrano, C., Ortiz, C., & Knaak, S. (2021). Effectiveness of an intervention to reduce stigma towards people with a severe mental disorder diagnosis in primary health care personnel: Programme Igual-Mente. Psychiatry Research, 305, 114259. https://doi.org/10.1016/j.psychres.2021.114259
Greene, J. C., Caracelli, V. J., & Graham, W. F. (1989). Toward a conceptual framework for mixed-method evaluation designs. Educational Evaluation and Policy Analysis, 11(3), 255–274.
Gupta, S., Kumar, A., Kathiresan, P., Pakhre, A., Pal, A., & Singh, V. (2024). Mental health stigma and its relationship with mental health professionals - A narrative review and practice implications. Indian Journal of Psychiatry, 66(4), 336–346. https://doi.org/10.4103/indianjpsychiatry.indianjpsychiatry_412_23
Hallyburton, A., & Allison-Jones, L. (2023). Mental health bias in physical care: An integrative review of the literature. Journal of Psychiatric and Mental Health Nursing, 30(4), 649–662. https://doi.org/10.1111/jpm.12911
Hamilton, S., Pinfold, V., Cotney, J., Couperthwaite, L., Matthews, J., Barret, K., Warren, S., Corker, E., Rose, D., Thornicroft, G., & Henderson, C. (2016). Qualitative analysis of mental health service users’ reported experiences of discrimination. Acta Psychiatrica Scandinavica, 134(Suppl 446), 14–22. https://doi.org/10.1111/acps.12611
Harris, E. C., & Barraclough, B. (1998). Excess mortality of mental disorder. The British Journal of Psychiatry, 173, 11–53. https://doi.org/10.1192/bjp.173.1.11
Harris, P. A., Taylor, R., Minor, B. L., Elliott, V., Fernandez, M., O’Neal, L., McLeod, L., Delacqua, G., Delacqua, F., Kirby, J., Duda, S. N., & REDCap Consortium. (2019). The REDCap consortium: Building an international community of software platform partners. Journal of Biomedical Informatics, 95, 103208. https://doi.org/10.1016/j.jbi.2019.103208
Harris, P. A., Taylor, R., Thielke, R., Payne, J., Gonzalez, N., & Conde, J. G. (2009). Research electronic data capture (REDCap): A metadata-driven methodology and workflow process for providing translational research informatics support. Journal of Biomedical Informatics, 42(2), 377–381. https://doi.org/10.1016/j.jbi.2008.08.010
Heim, E., Henderson, C., Kohrt, B. A., Koschorke, M., Milenova, M., & Thornicroft, G. (2019). Reducing mental health-related stigma among medical and nursing students in low- and middle-income countries: a systematic review. Epidemiology and Psychiatric Sciences, 29, e28. https://doi.org/10.1017/S2045796019000167
Hempeler, C., Schneider-Reuter, L., Windel, A. S., Carlet, J., Philipsen, L., Juckel, G., Gather, J., Yeboah, A., & Faissner, M. (2024). Intersectional discrimination in mental health care: A systematic review with qualitative evidence synthesis. Psychiatric Services, 75(11), 1125–1143. https://doi.org/10.1176/appi.ps.20230252
Ivankova, N. V., & Creswell, J. W. (2009). Mixed methods. Qualitative research in applied liguistics: A practical introduction (pp. 135–161). Palgrave Macmillan.
Ivanova, M. (2022). The stigmatization of schizophrenia. University of Ottawa Journal of Medicine, 11(2). https://doi.org/10.18192/uojm.v11i2.6078
Jenkins, T. A., Robison, M., & Joiner, T. E. (2023). Dehumanization and mental health: clinical implications and future directions. Current Opinion in Behavioral Sciences, 50, 101257. https://doi.org/10.1016/j.cobeha.2023.101257
Jones, S., Howard, L., & Thornicroft, G. (2008). Diagnostic overshadowing: worse physical health care for people with mental illness. Acta Psychiatrica Scandinavica, 118(3), 169–171. https://doi.org/10.1111/j.1600-0447.2008.01211.x
Kaufman, E. A., McDonell, M. G., Cristofalo, M. A., & Ries, R. K. (2012). Exploring barriers to primary care for patients with severe mental illness: frontline patient and provider accounts. Issues in Mental Health Nursing, 33(3), 172–180. https://doi.org/10.3109/01612840.2011.638415
Kisely, S., & Siskind, D. (2021). Excess mortality from cancer in people with mental illness-Out of sight and out of mind. Acta Psychiatrica Scandinavica, 144(4), 315–317. https://doi.org/10.1111/acps.13363
Knaak, S., Mantler, E., & Szeto, A. (2017). Mental illness-related stigma in healthcare: Barriers to access and care and evidence-based solutions. Healthcare Management Forum / Canadian College of Health Service Executives = Forum Gestion Des Soins de Sante / College Canadien Des Directeurs de Services de Sante, 30(2), 111–116. https://doi.org/10.1177/0840470416679413
Kohn, L., Christiaens, W., Detraux, J., De Lepeleire, J., De Hert, M., Gillain, B., Delaunoit, B., Savoye, I., Mistiaen, P., & Jespers, V. (2021). Barriers to somatic health care for persons with severe mental illness in belgium: A qualitative study of patients’ and healthcare professionals’ perspectives. Frontiers in Psychiatry, 12, 798530. https://doi.org/10.3389/fpsyt.2021.798530
Link, B. G., & Phelan, J. C. (2001). Conceptualizing stigma. Annual Review of Sociology, 27(1), 363–385. https://doi.org/10.1146/annurev.soc.27.1.363
Loeb, D. F., Bayliss, E. A., Binswanger, I. A., Candrian, C., & deGruy, F. V. (2012). Primary care physician perceptions on caring for complex patients with medical and mental illness. Journal of General Internal Medicine, 27(8), 945–952. https://doi.org/10.1007/s11606-012-2005-9
Lumivero (2023). NVivo Qualitative Data Analysis. Computer software.
Martínez-Martínez, C., Sánchez-Martínez, V., Aguilar-Gascón, L., María Ortega-Galán, Á., & Ramos-Pichardo, D., J (2024). Involving Persons With Lived Experience to Improve Vocational Students’ Stigmatizing Attitudes Toward Mental Disorders: A Quasi-Experimental Study. Journal of the American Psychiatric Nurses Association, 30(1), 160–168. https://doi.org/10.1177/10783903221090528
Moudatsou, M., Stavropoulou, A., Philalithis, A., & Koukouli, S. (2020). The role of empathy in health and social care professionals. Healthcare (Basel), 8(1). https://doi.org/10.3390/healthcare8010026
Mukhalalati, B. A., & Taylor, A. (2019). Adult learning theories in context: A quick guide for healthcare professional educators. Journal of Medical Education and Curricular Development, 6, 2382120519840332. https://doi.org/10.1177/2382120519840332
Nembhard, I. M., David, G., Ezzeddine, I., Betts, D., & Radin, J. (2023). A systematic review of research on empathy in health care. Health Services Research, 58(2), 250–263. https://doi.org/10.1111/1475-6773.14016
Olatunbosun, C., & Wilby, K. J. (2022). Advocacy as a professional responsibility. Canadian Pharmacists Journal: CPJ = Revue Des Pharmaciens Du Canada : RPC, 155(6), 298–301. https://doi.org/10.1177/17151635221125782
Oud, M. J. T., & Meyboom-de Jong, B. (2009). Somatic diseases in patients with schizophrenia in general practice: their prevalence and health care. BMC Family Practice, 10, 32. https://doi.org/10.1186/1471-2296-10-32
Potts, L. C., Bakolis, I., Deb, T., Lempp, H., Vince, T., Benbow, Y., Waugh, W., Kim, S., Raza, S., Henderson, C., & INDIGO READ Study Group. (2022). Anti-stigma training and positive changes in mental illness stigma outcomes in medical students in ten countries: a mediation analysis on pathways via empathy development and anxiety reduction. Social Psychiatry and Psychiatric Epidemiology, 57(9), 1861–1873. https://doi.org/10.1007/s00127-022-02284
Ratna, H. (2019). The Importance of Effective Communication in Healthcare Practice. Harvard Public Health Review, 23, 1–6.
Richmond-Rakerd, L. S., D’Souza, S., Milne, B. J., Caspi, A., & Moffitt, T. E. (2021). Longitudinal associations of mental disorders with physical diseases and mortality among 2.3 million new zealand citizens. JAMA Network Open, 4(1), e2033448. https://doi.org/10.1001/jamanetworkopen.2020.33448
Riffel, T., & Chen, S. P. (2020). Stigma in Healthcare? Exploring the Knowledge, Attitudes, and Behavioural Responses of Healthcare Professionals and Students toward Individuals with Mental Illnesses. The Psychiatric Quarterly, 91(4), 1103–1119. https://doi.org/10.1007/s11126-020-09809-3
Sinclair, S., Beamer, K., Hack, T. F., McClement, S., Bouchal, R., Chochinov, S., H. M., & Hagen, N. A. (2017). Sympathy, empathy, and compassion: A grounded theory study of palliative care patients’ understandings, experiences, and preferences. Palliative Medicine, 31(5), 437–447. https://doi.org/10.1177/0269216316663499
Sølvhøj, I. N., Kusier, A. O., Pedersen, P. V., & Nielsen, M. B. D. (2021). Somatic health care professionals’ stigmatization of patients with mental disorder: a scoping review. Bmc Psychiatry, 21(1), 443. https://doi.org/10.1186/s12888-021-03415-8
Stange, K. C., Crabtree, B. F., & Miller, W. L. (2006). Publishing multimethod research. Annals of Family Medicine, 4(4), 292–294. https://doi.org/10.1370/afm.615
Svenaeus, F. (2015). The relationship between empathy and sympathy in good health care. Medicine Health Care and Philosophy, 18(2), 267–277. https://doi.org/10.1007/s11019-014-9601-x
Swildens, W., Termorshuizen, F., de Ridder, A., Smeets, H., & Engelhard, I. M. (2016). Somatic Care with a Psychotic Disorder. Lower Somatic Health Care Utilization of Patients with a Psychotic Disorder Compared to Other Patient Groups and to Controls Without a Psychiatric Diagnosis. Administration and Policy in Mental Health, 43(5), 650–662. https://doi.org/10.1007/s10488-015-0679-0
Świtaj, P., Grygiel, P., Krzyżanowska-Zbucka, J., Sonik, J., Chrostek, A., Jahołkowski, P., Wciórka, J., & Anczewska, M. (2019). The evaluation of the impact of anti-stigma training led by experts by experience on participants’ attitudes towards persons with mental illness. Psychiatria Polska, 53(6), 1219–1236. https://doi.org/10.12740/PP/109818
Tashakkori, A., & Teddlie, C. (1998). Mixed methodology: Combining qualitative and quantitative approaches (Applied social research methods series, 46). Sage.
Taylor, D. C. M., & Hamdy, H. (2013). Adult learning theories: implications for learning and teaching in medical education: AMEE Guide 83. Medical Teacher, 35(11), e1561–e1572. https://doi.org/10.3109/0142159X.2013.828153
Teddlie, C., & Tashakkori, A. (2010). Overview of contemporary issues in mixed methods research. In Sage Handbook of mixed methods in social and behavioral research (pp. 1–44).
Thornicroft, G., Rose, D., & Kassam, A. (2007). Discrimination in health care against people with mental illness. International Review of Psychiatry, 19(2), 113–122. https://doi.org/10.1080/09540260701278937
Vistorte, A. O. R., Ribeiro, W. S., Jaen, D., Jorge, M. R., Evans-Lacko, S., & de Mari, J. J (2018). Stigmatizing attitudes of primary care professionals towards people with mental disorders: A systematic review. International Journal of Psychiatry in Medicine, 53(4), 317–338. https://doi.org/10.1177/0091217418778620
Walker, E. R., McGee, R. E., & Druss, B. G. (2015). Mortality in mental disorders and global disease burden implications: a systematic review and meta-analysis. JAMA Psychiatry, 72(4), 334–341. https://doi.org/10.1001/jamapsychiatry.2014.2502

No competing interests reported.

Download PDF

Reviews received at journal
06 Jan, 2026
Reviewers agreed at journal
01 Dec, 2025
Reviewers agreed at journal
24 Nov, 2025
Reviews received at journal
08 Oct, 2025
Reviewers agreed at journal
18 Sep, 2025
Reviewers invited by journal
16 Sep, 2025
Editor assigned by journal
17 May, 2025
Submission checks completed at journal
17 May, 2025
First submitted to journal
15 May, 2025

You are reading this latest preprint version

De-Stigmatization for Individuals with Severe Mental Illness and Substance Use Disorder: A Multi-Method Approach to the Development of the Biondo REACH Training Program for Healthcare Students

Status:

Version 1

Abstract

Background

Methods

Study Design

Study Participants

Arm 1: Quantitative

Arm 2: Qualitative

Data Collection

Measures

Data Analysis

Attribution Questionnaire

Focus Groups

Results

Training Program

Learning Theories

Social (Cultural) Constructivist Theory

Experiential Learning Theory

Healthcare Advocacy

Content Foci

Discussion

Stigma, Bias, and Patient Behaviors in Health Care

Understanding Empathy, Sympathy, and Pity in Health Care

Compassion, Interpersonal Skills, and Rehumanization Skill Development

Existing Collaborative Trainings and Future Direction

Communication Disconnect Between Healthcare Providers and Recipients of Care

Conclusions

Declarations

References

Additional Declarations

Status:

Version 1