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. 2016 May 4;12(4):844–850. doi: 10.1177/1557988316645152

A Validation of the Group-Based Medical Mistrust Scale in Formerly Incarcerated Black and Latino Men

Pamela Valera 1,✉, Javier F Boyas 2, Camila Bernal 1, Victoria Briones Chiongbian 3, Yvonne Chang 1, Rachel C Shelton 1
PMCID: PMC6131472  PMID: 27192716

Abstract

While there is a growing body of literature on medical mistrust and its relevance to public health, research on formerly incarcerated Black and Latino men and their perception of mistrust toward medical providers and medical institutions remains scant. Very little is known about whether formerly incarcerated Black and Latino men mistrust medical and clinical providers given their previous experiences with the criminal justice system. It is important to determine whether medical mistrust play a key role in the health and health behaviors of released Black and Latino men. The purpose of this study is to validate and assess the psychometric properties of the Group-Based Medical Mistrust Scale for use among formerly incarcerated Black and Latino men in New York City. The findings of the exploratory and confirmatory factor analyses state that a two-factor structure fit the data best. Two dimensions emerged as important subscales: discrimination and suspicion. The current findings suggest the two-factor Group-Based Medical Mistrust Scale is a valid and reliable assessment tool to discern medical mistrust levels among formerly incarcerated Black and Latino men.

Keywords: medical mistrust, formerly incarcerated men, Black, Latino, psychometrics, discrimination

Introduction

It is widely believed that the concept of health should be considered within a cultural context, given that cultural, social, and family influences are central forces that shapes attitudes and beliefs (Andrulis & Brach, 2007; Boyas, 2013; Institute of Medicine, 2004). Culture provides a milieu through which worldviews are explored and may influence how people perceive their health and health problems, especially how they seek out health care services, and how they react to recommendations to modify certain lifestyle behaviors, follow through with health care interventions, or adhere to medical treatment (Andrulis & Brach, 2007; Bynum, Davis, Green, & Katz, 2012; Institute of Medicine, 2004). Having said that, it is not a stretch to suggest that culture may also affect medical mistrust. Medical mistrust is defined as the inclination to distrust medical systems and health care personnel that are believed to represent the dominant culture (Bynum et al., 2012; Thompson, Valdimarsdottir, Winkel, Jandorf, & Redd, 2004). Extensive research has explored the relationship between race and ethnicity and trust (or lack thereof) of the health care system among Blacks and Latinos living in the United States (Boulware, Cooper, Ratner, LaVeist, & Powe, 2003; Boyas & Valera, 2011).

Previous research has demonstrated that Blacks who are familiar with the Tuskegee Syphilis Study are more reluctant to participate in medical research and distrust medical researchers and clinicians altogether (Boulware et al., 2003). Another study comparing trust professed for medical personnel among Latinos and non-Hispanic Whites revealed that Latinos were significantly less likely to trust doctors and physicians and they were also more likely to distrust other medical personnel of a different race or ethnicity, compared with non-Hispanic Whites (Boyas & Valera, 2011).

While there is a growing body of literature on medical mistrust in racial and ethnic minorities in the United States (Boulware et al., 2003; Boyas & Valera, 2011; Bynum et al., 2012; Shelton et al., 2010; Thompson et al., 2004), research on formerly incarcerated Black and Latino men and their perception of mistrust toward medical providers remains scant. This is a significant problem given that roughly 700,000 offenders are released into the community annually (Cuellar & Cheema, 2012). Many of these individuals suffer from health burdens experienced before incarceration, which may become exacerbated during imprisonment (Binswanger, Krueger, & Steiner, 2009). Compared with the general adult population, former inmates disproportionately suffer from a high incidence of chronic health conditions, such as diabetes mellitus, hypertension, asthma, and human immunodeficiency virus (Binswanger et al., 2009; Wilper et al., 2009). Once imprisoned, only a fraction of those needing services receive them, leaving many inmates without proper health care (Dumont, Allen, Brockmann, Alexander, & Rich, 2013; Kulkarni, Baldwin, Lightstone, Gelberg, & Diamant, 2010; Wilper et al., 2009). One study reported that as much as 68.4% of inmates with persistent medical conditions had not received an examination since entering jail (Wilper et al., 2009). A lack of medical attention on released inmates may contribute to increase emotional distress and psychiatric symptoms and may place formerly incarcerated individuals at risk for poor health (Binswanger et al., 2011; Schnittker, 2007). Because overall data on health care utilization for formerly incarcerated population are limited, Wang et al.’s (2008) study on former jail inmates reported that this population lacked access to health care services. Another study reported that recently released inmates faced multiple challenges during community reintegration such as continuing medical care (that was initiated during incarceration), suicidality, and exacerbated psychological distress (Binswanger et al., 2011). However, the concept of medical mistrust was not explored in either of those studies. If the health status and health care needs of formerly incarcerated Black and Latino men are to be understood, the experience of incarceration and its effects on whether to trust health care providers have to be considered.

Moreover, very little is known as to whether formerly incarcerated Black and Latino men mistrust medical and clinical providers given their previous experiences with the criminal justice system. Therefore, it is important to determine to what extent medical mistrust play a key role in the health and health behaviors of newly released Black and Latino men. This issue cannot be fully explored because there are no available assessment tools designed to measure medical mistrust among Black and Latino men with criminal justice backgrounds. The only scale that is socially and culturally relevant that has dimensions of discrimination, suspicion, and support that would be appropriate for use is the Group-Based Medical Mistrust Scale (GBMMS). The GBMMS has been validated in Black and Latina women (Thompson et al., 2004), in urban Black men (Shelton et al., 2010), and in Black and White men diagnosed with prostate cancer (Halbert, Armstrong, Gandy, & Shaker, 2006), demonstrating strong validity and reliability (α = .87-.88). None of those studies included men who have criminal justice backgrounds. The purpose of this current study was to: (1) explore the psychometric properties of the GBMMS for use with formerly incarcerated Black and Latino men; and (2) identify the appropriate factor structure.

Method

Study Design and Sample

The current study employed a cross-sectional research design and used a purposive sample consisting of newly released (defined as released within 3 years or less) Black and Latino men ages 35 and older in the New York City area. The parent study was designed to examine cancer health disparities among a diverse sample of men released from prison or jail and under community supervision (Valera et al., 2014, 2015). Eligible participants had to self-identify as either Black or Latino; be at least 35 years and older; reside in the Bronx; be under parole or probation; never been diagnosed with cancer; and be able to provide informed consent. The research study was approved by the first author’s academic institution’s institutional review board. Data for the use of the study was collected from February 2012 through October 2012. Recruitment and data collection procedures have been reported elsewhere (Valera et al., 2014, 2015).

Measures

Sociodemographic Variables

Demographic information was examined using a 23-item questionnaire fill-in-the-blank and fixed-choice questions. The sociodemographic variables included: age, race/ethnicity, educational level, military status, employment status, income, among others. Incarceration was assessed by asking participants what type of correctional facility they were released from, such as jail or prison.

Group-Based Medical Mistrust Scale

The GBMMS is a 12-item scale developed by Thompson et al. (2004) thatmeasures medical mistrust in racial and ethnic groups. Each item comprises a 5-point Likert-type scale (1 = strongly disagree to5 = strongly agree). In earlier studies, three subscales of GBMMS emerged: (1) perceived lack of support from doctors and other health care providers; (2) perceived discrimination and group-based disparities in health care settings; and (3) perceived suspicion of the medical field including physicians and other health care providers. In this present study, the wording of the scale was modified specifically to “people with criminal justice backgrounds” instead of the original wording “people of my ethnic group” and “Black people” (see Table 2). Cronbach’s alphas of the GBMMS reported in two earlier studies were high: .87 (Shelton et al., 2010) and .83 (Thompson et al., 2004).

Table 2.

Fit Indices and Their Threshold Values.

Index Threshold Reference
Normed fit index >.95 35
Tucker–Lewis index >.95 35
Comparative fit index >.95 35
Root mean square error of approximation <.06 36
Standardized root mean square residual <.08 35
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Statistical Analysis

Univariate statistics were used to describe all study variables. Several bivariate statistics were employed: Pearson’s r, one-way ANOVA, and independent t test. Pearson’s r was used to calculate correlations between the various subscales of the GBMMS. The main analyses used exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) to replicate and validate the GBMMS for use with formerly incarcerated men. For the EFA, principal components analysis was used to extract the factors; a nonorthogonal Oblimin procedure was used to rotate the factors. The CFA was conducted on the measurement model proposed by Shelton et al. (2010). The construct validity of the GBMMS scores were calculated by determining the mean of the participants’ responses across the individual items. Model fit was assessed via the chi-square and several fit indices: comparative fit index (a goodness-of-fit index), the root mean square error of approximation, and the standardized root mean square residual (both badness-of-fit indices; Kline, 2011). The internal consistency reliability was assessed using Cronbach’s alpha. All data analyses were calculated using SPSS (version 22).

Results

Descriptive Statistics

Descriptive characteristics of the parent study have been reported elsewhere (Valera et al., 2014, 2015). Approximately half of the participants were Black (49%); the rest of the sample consisted of Latinos (46.3%) and participants of other racial and ethnic groups (4.6%). In addition, men who reported their race or ethnicity as “other” were excluded from the data analysis. In terms of last incarceration, approximately 43% reported being in jail or prison less than a year, 12% reported being incarcerated for less than 2 years, 23% of the men were in custody for less than 5 years, and 22% were incarcerated for more than 5 years. The majority of the men reported one or more chronic medical conditions such as being positive for hepatitis C, mental health problems, asthma, arthritis, and chronic pain.

The mean mistrust scores ranged from one to five; the mean mistrust score was 2.36 (SD = 0.99). The mistrust scores were similar to previous studies (Shelton et al., 2010; Thompson et al., 2004).

Reliability

The internal consistency of the entire GBMMS scale was high (α = .79), indicating strong internal consistency. The alpha for the Suspicion subscale was .70; the alpha for the Discrimination subscale was .77. The third subscale, Lack of Support, did not have reliability data because it was measured as a single item.

Exploratory Factor Analysis

It was appropriate to conduct an EFA as the Kaiser-Meyer-Olkin measure of sampling adequacy was close to one (i.e., .85) and Bartlett’s test of sphericity was significant, χ2(66) = 853.08, p < .001. As reported in Table 1, the findings varied from that of Shelton et al. (2010). First, Shelton et al. (2010) extracted three factors. Although three factors were extracted in the current study (correlations between factors are reported in Table 1), items only loaded onto two factors (total variance explained by the two factors was 47.07%). The loadings of Items 2 (“Doctors have the best interests of people with criminal justice backgrounds in mind”) and 9 (“Doctors and health care workers do not take the medical complaints of people with criminal backgrounds seriously”) were below the acceptable criterion of .40 (Tabachnick & Fidell, 2007); thus, there were no items that loaded onto the third factor (Lack of Support).

Table 1.

Exploratory Factor Analysis Pattern Matrix for the Mistrust Scale Original 11 items.

Item M (SD) Mdn Factor 1: Suspicion Factor 2: Discrimination Factor 3: Lack of Support
4. People who have a criminal background should be suspicious of information from doctors and health care workers. 2.06 (1.52) 1 .89
3. People who have a criminal background should not confide in doctors and health care workers because it will be used against them. 1.85 (1.41) 1 .62
5. People who have a criminal background cannot trust doctors and health care workers. 1.73 (1.29) 1 .58
1. Doctors and health care workers sometimes hide information from patients who have a criminal history. 2.56 (1.64) 2 .46
10. People with criminal backgrounds are treated the same as people of other groups by doctors and health care workers. 2.92 (1.74) 3 −.79
11. In most hospitals, people with criminal backgrounds receive the same kind of care. 2.70 (1.69) 2 −.72
8. People of with criminal backgrounds receive the same medical care from doctors and health care workers as people from other groups. 2.77 (1.69) 2 −.67
12. I have personally been treated poorly or unfairly by doctors or health care workers. 2.13 (1.68) 1 −.46
2. Doctors have the best interests of people who have a criminal history. 3.49 (1.55) 4 .28
Correlation between subscales:
 Suspicion (α = .70) —
 Discrimination (α = .77) −.56 —
 Lack of support −.06 −.04 —
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Second, the items that loaded onto the current study’s first factor of Suspicion (i.e., Items 1 [“Doctors and health care workers sometimes hide information from people with criminal justice backgrounds”], 3 [“People with criminal justice backgrounds should not confide in doctors and health care workers because it will be used against them"], 4 [“People with criminal justice backgrounds should be suspicious of information from doctors and health care workers”], and 5 [“People with criminal justice backgrounds cannot trust doctors and health care workers”]) were not exactly the same as the items that loaded onto Shelton et al.’s (2010) factor of Suspicion (i.e., Items 3 [“Black people should not confide in doctors and health care workers because it will be used against them”], 4 [“Black people should be suspicious of information from doctors and health care workers”], 5 [“Black people cannot trust doctors and health care workers”], 6 [“Black people should be suspicious of modern medicine”], and 7 [“Doctors and health care workers treat Black people like guinea pigs”]).

The items that loaded onto the current study’s second factor of Discrimination (i.e., Items 8 [“People with criminal justice backgrounds receive the same medical care from doctors and health care workers as people from other groups], 10 [“People with criminal justice backgrounds are treated the same as people of other groups by doctors and health care workers”], 11 [“In most hospitals, people with criminal justice backgrounds receive the same kind of care”], and 12 [“I have personally been treated poorly or unfairly by doctors or health care workers because of my criminal justice background”]) were similar to the items that loaded onto Shelton et al.’s (2010) factor of Discrimination (i.e., Items 8 [“Black people receive the same medical care from doctors and health care workers as people from other groups”], 10 [“Black people are treated the same as people of other groups by doctors and health care workers”], and 11 [“In most hospitals, people of different ethnic groups receive the same kind of care”]).

Confirmatory Factor Analysis

The covariance matrix yielded by the Shelton et al. (2010) model was not positive definite (i.e., variances need to be positive, not negative). The correlation between Suspicion and Lack of Support was very high, r = .97, p < .001, indicating redundancy between the constructs. The model was modified by removing items with standardized factor loadings below .50 (Hair et al., 2010). This resulted in the deletion of the following items: Items 1 (“Doctors and health care workers sometimes hide information from people with criminal justice backgrounds”), 2 (“Doctors have the best interests of people with criminal justice backgrounds in mind”), and 6 (“People with criminal justice backgrounds should be suspicious of modern medicine”). Since the Lack of Support construct only had one remaining item, it was deleted from the model.

The final model, depicted in Figure 1, fit the data well as all the fit indices met (see Table 3) their thresholds. Results of the CFA measurement model, model fit, and fit indices are specified in Table 2. The normed fit index, Tucker–Lewis index, and comparative fit index were all above the cutoff of .95, while the root mean square error of approximation achieved the level of .05. This final model consisted of two latent constructs, Suspicion and Discrimination. Four items loaded on highly to the Suspicion construct: Items 3 (“People with criminal justice backgrounds should not confide in doctors and health care workers because it will be used against them”), 4 (“People with criminal justice backgrounds should be suspicious of information from doctors and health care workers”), 5 (“People who have a criminal background cannot trust doctors and health care workers”), and 7 (“Doctors and health care workers treat people of with criminal backgrounds like “guinea pigs”) (α = .71). Three items loaded on highly to the Discrimination construct: Items 8 (“People of with criminal backgrounds receive the same medical care from doctors and health care workers as people from other groups”), 10 (“People with criminal backgrounds are treated the same as people of other groups by doctors and health care workers”), and 11 (“In most hospitals, people with criminal backgrounds receive the same kind of care”) (α = .78).

Figure 1.

Figure 1.

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Final measurement model for mistrust.

Table 3.

Fit Indices for the Final Measurement Model.

Index Values
Chi-square 19.77
Degrees of freedom 13
Probability level .10
Normed chi-square 1.52
Normed fit index .96
Tucker–Lewis index .98
Comparative fit index .99
Root mean square error of approximation .05
Lower bound 90% confidence interval .00
Upper bound 90% confidence interval .08
P-close .53
Standardized root mean square residual .05
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Discussion

The aim of this present study was to examine the validity of the GBMMS in a sample of formerly incarcerated Black and Latino men. While Shelton et al. (2010) previously validated the GBMMS among a sample of urban Black men, participants had no reported history of criminal justice involvement, and attitudes of mistrust specific to criminal justice populations could not be determined. Shelton et al. (2010) identified a three-factor structure capturing Suspicion, Discrimination, and Lack of support. The current exploratory factor analysis identified that items loaded onto the Suspicion and Discrimination factors were highly similar to those in Shelton et al.’s (2010) model. However, confirmatory factor analysis results indicated that a two-factor model measuring Suspicion and Discrimination better fit the data due to the high redundancy between the Suspicion and Lack of Support constructs.

Limitations

Limitations of the current study should be acknowledged. First, the cross-sectional research design limits the ability to make any causal inferences. Second, the nonprobability sample limits the generalizability of the results. In addition, no variables were included that related to the participant’s use of a regular provider or other provider-related measures that would have further supported the construct validity of the measure. Third, the study sample was derived from one geographic location. Related, the data relied on self-report measures of discrimination that captured a single dimension. This scale did not measure multiple aspects of discrimination, such as intensity, frequency, or duration.

Future research should examine what impact interacting with medical personnel in prison had on levels of trust. Since the present study only included perceived medical mistrust scores of formerly incarcerated men, much needed studies on mistrust of medical providers among those with criminal justice histories should consider including baseline mistrust scores prior to incarceration, during incarceration, and follow up while they are in reentry.

In addition, the sample includes Latinos who are culturally diverse and vary in terms of immigration status and the number of years lived in the United States, and because this study relies heavily on the argument that culture shapes attitudes about health, acculturation, and racial diversity may be factors to consider in future research. Additional studies on medical mistrust with formerly incarcerated men may want to consider whether levels of mistrust among Latinos is shaped by predisposing factors, such as age, education level, and having insurance coverage; enabling factors, such as whether the respondent has someone they consider their personal doctor, whether their doctor speaks the same language, and perceived barriers to health care; and need factors, such as self-rated health and the number of chronic conditions.

Conclusion

Despite these limitations, this study demonstrated that GBMMS is a reliable and appropriate measure for measuring medical mistrust in formerly incarcerated men. In general, study participants had a moderate, but not heightened levels of mistrust toward their health care providers. This is an important finding and may be attributed to several factors. First, encounters with the health care system could have largely been during incarceration, because inmates, many of whom are uninsured when they enter prison, often do not obtain care pre- and postincarceration (Estelle v. Gamble, 1976; Rold, 2008). Second, this population in general may have limited interactions with health care providers altogether. That being said, the GBMMS assessment tool could be used to measure change in mistrust levels pre- and postincarceration.

Taken together, the current findings demonstrate that the GBMMS can be a reliable tool to discern trust levels among formerly incarcerated Black and Latino men (Boulware et al., 2003; Boyas & Valera, 2011; Shelton et al., 2010; Thompson et al., 2004). Health care providers who interface with criminal justice populations should recognize this as a strength in which a positive relationship can be developed, because former inmates may be more likely to adhere to recommended preventive services and consider provider input in the decision-making process about medical treatment. Eliminating medical mistrust as a barrier may be an important first step toward eliminating health disparities experienced by formerly incarcerated Black and Latino men (Kraetschmer, Sharpe, Urowitz, & Deber, 2004; O’Malley, Sheppard, Schwartz, & Mandelblatt, 2004; Pascoe & Richman, 2009).

Acknowledgments

The authors thank the study team members: Molly Kratz, Christopher McLaughlin, Shae Cali, Stephanie Cook, and Mario Rodriguez.

Footnotes

Declaration of Conflicting Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Cancer Institute to Dr. Pamela Valera (K01CA154861).

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