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American Journal of Speech-Language Pathology logoLink to American Journal of Speech-Language Pathology
. 2024 Aug 6;33(5):2378–2386. doi: 10.1044/2024_AJSLP-22-00125

Stuttering Impact and Patient Trust in Indian Health Care: A Cross-Sectional Study

Nathan V Mallipeddi a,✉, Sivan Aulov b, Hector R Perez c
PMCID: PMC11427744

Abstract

Purpose:

This study aims to determine the relationship between (a) stuttering impact and trust in the health care system and (b) stuttering impact and trust in physicians among persons who stutter in India.

Method:

This quantitative study utilized cross-sectional electronic surveys to assess the experiences of 118 adults who stutter in India. The surveys queried (a) stuttering impact, (b) trust in the health care system, and (c) trust in physicians.

Results:

Stuttering impact is strongly negatively associated with trust in the health care system (r = −.940, p ≤ .0001, R2 = .885) and strongly negatively associated with trust in physicians (r = −.941, p ≤ .0001, R2 = .885). Controlling for age, gender, and income does not affect these relationships.

Conclusions:

The strongly significant associations found in this study between stuttering impact and trust call attention to how interrelated stuttering experiences are with trust in health care. Speech-language pathologists around the globe may wish to discuss how stuttering might affect health care experiences with their clients who stutter to build rapport, to advocate for people who stutter, and to better support their health professional colleagues.

Stuttering, or stammering, as the disorder is frequently called in India, refers to the difficulties of the time patterning and fluency aspects of the speech (Mann, 1966). Much research is still needed to fully understand stuttering, which is a communication disability characterized by prolongations, blocks, and repetitions of speech sounds (Bayati & Ayatollahi, 2021; Polikowsky et al., 2022). Current literature describes stuttering as an episodic, variable, and chronic disorder that can profoundly affect a person's daily functioning (Blood et al., 2011). Consistent evidence concludes that stuttering impacts many aspects of one's life, including self-image, perception by others, peer and intimate relationships, and opportunities for employment (Büchel & Sommer, 2004). The impact of stuttering, a measure of the effect of stuttering on one's life and emotions, is highly correlated with negative self-perceptions (Nang et al., 2018), higher frequencies of depressive symptoms (Briley et al., 2021), increased levels of stress (Boyle & Fearon, 2018), and decreased self-acceptance (Nang et al., 2018; Yaruss & Quesal, 2004). Stuttering has been determined to exhibit considerate variability across time and situations (Tichenor & Yaruss, 2021) and may influence the development of trust in relationships (Nang et al., 2018).

Experiences in health care affect persons who stutter as well, as they face barriers to communicating effectively in health care settings. These barriers may affect their ability to engage in ideal patient–provider communication and affect their willingness to trust in their providers and in the health care system. Previous research has shown that persons who stutter report poor interactions with health care workers and staff members because of their stuttering (Perez et al., 2015). In fact, research has suggested that health workers have persistently poor attitudes of persons who stutter (Cooper & Cooper, 1996; Yairi & Carrico, 1992). Perhaps as a result, persons who stutter reveal common avoidance behaviors, such as avoiding appointments or relying on others to communicate with doctors on their behalf because of their difficulties with stuttering (Perez et al., 2015). Nonetheless, there is no quantitative data on patient–provider communication or satisfaction of health care among persons who stutter. There is a significant need for further research in health care experiences among persons who stutter.

Generally, persons with speech, language, and/or voice disabilities (collectively referred to as communication disabilities [CD]) represent 10% of the U.S. population (Morris et al., 2016). Due to persistent difficulties with communication, several studies have concluded their impairments may put their health at risk. Poor patient–provider communications among persons with CD can lead to low satisfaction with one's provider and low satisfaction with the health care system (Hoffman et al., 2005; Morris et al., 2013; Nordehn et al., 2006). In some instances, this can lead to poorer health outcomes, exacerbated by negative biases and discriminatory systems and policies (Morris et al., 2021; Stransky et al., 2018). These individuals' collective communication difficulties have been exacerbated by the COVID-19 pandemic due to face mask mandates that place patients with communication-based disabilities at even greater risk for communication breakdowns.

Trust is defined as “accepted vulnerability to another's possible but not expected ill will” (Baier, 1986). Within the health care system (defined here as the systems and processes around the delivery of health care, which includes interactions with nurses and doctors), trust is imperative to receiving high-quality health care because patients are vulnerable and dependent on physicians' expertise and on surmounting systemic barriers in the health care system. In fact, low trust in health care is a barrier to individuals seeking care, accepting and adhering to medical recommendations, building therapeutic patient–provider relationships, and maintaining continuity of care (Armstrong et al., 2006; Rowe & Calnan, 2006; Thom et al., 2004; Whetten et al., 2006). These barriers lead to ineffective and inefficient health care (Armstrong et al., 2006). Researchers have long understood that low trust in health care is an important contributor to disparities in health and health care (Halbert et al., 2006).

Trust in health care is an important problem within the general population in India and may be a uniquely important problem among persons who stutter. Indians generally express low trust of the Indian health care system, with 63% of Indians believing that hospitals do not act in their best interests (Kane & Calnan, 2017). Although Indians report low trust in health care institutions, they also report consistently high trust in individual providers (Kane & Calnan, 2017), fueled by high satisfaction with patient–provider communication. By contrast, persons who stutter in India may have significant difficulty in maintaining patient–provider communication because of the impact of stuttering. They also face persistent barriers to engagement with providers. Negative beliefs of persons who stutter are common in India, and people who stutter face unique barriers that limit their engagement with medical providers, including low social status, limited access to stuttering support networks, and reduced availability of speech therapists (Nandhini et al., 2018; Subramanian & Prabhu, 2005). The barriers and stigma faced by persons who stutter may lead to low trust in both health care and in providers, which threatens to endanger the health and wellness of persons who stutter and to exacerbate health disparities in India (Kane et al., 2015).

Because persons who stutter have wide variability in how stuttering impacts their daily lives, we sought to explore how stuttering impact (the speaker's perceptions about stuttering, reactions to stuttering, and limitations in daily communication activities) and trust in health care are related. Specifically, in a group of persons who stutter in India, we explored associations between (a) stuttering impact and trust in the health care system and (b) stuttering impact and trust in physicians. Our hypothesis is that increased stuttering impact is associated with (a) lower trust in the health care system and (b) lower trust in physicians.

Method

We conducted a cross-sectional quantitative study utilizing electronic surveys to assess the relationship between (a) stuttering impact and trust in the health care system and (b) stuttering impact and trust in physicians. Stuttering impact was ascertained using the Overall Assessment of the Speaker's Experience With Stuttering–Adults (OASES-A), a validated survey of the effect of stuttering on one's life and emotions (Yaruss & Quesal, 2006). Trust in the health care system was ascertained using the Health Care System Distrust (HCSD) Scale (Shea et al., 2008). Trust in physicians was measured by the Trust in Physicians Scale (TPS; Anderson & Dedrick, 1990). All surveys relied completely on self-report and were administered, and no objective measure of stuttering was undertaken. Ethics approval for this research was obtained by the Albert Einstein College of Medicine Institutional Review Board and The Indian Stammering Association (TISA). The study qualified for a waiver of informed consent.

Participants

Because persons who stutter in India are a distinct population that can be difficult to identify, we recruited a convenience sample of adults who stutter through social media postings and the Telegram and WhatsApp groups of TISA. TISA is the leading association for persons who stutter in India with 1,050 members, all of whom received messages about the survey. Members participate in weekly or biweekly support group meetings, but membership is free. All TISA materials, including flyers, online advertising, and the Telegram and WhatsApp groups are primarily available in English. In order to be eligible for the study, participants had to self-identify as a person who stutters, be able to recall stuttering in medical experiences, be at least 18 years old, and speak English. We collected data electronically through Qualtrics.

Data Collection

Data collection was conducted anonymously and in English from January 2021 to April 2021. After providing consent, participants completed the four following electronic questionnaires:

Sociodemographic questionnaire. We asked participants to report their age, gender, patient–provider relationship duration (“Have you ever interacted with a physician? If yes, how long have you interacted with this physician?” with five responses varying from “0–6 months” to “more than 5 years”), Indian geographic region (identified as north/central/south), comorbid conditions (listed by participants and later dichotomized as ≥ 1 comorbid condition vs. 0), socioeconomic status (as measured by total self-reported annual household income), and a self-evaluation of health status (“Would you say in general your health is—?” with five responses ranging from “excellent” to “poor”). All sociodemographic questions, including geographic region and socioeconomic status, are asked to better understand the sample recruited, as India is highly variable geographically, economically, and with regard to health status.

OASES-A. Stuttering impact was measured using the OASES-A. The OASES-A is a self-report measure of the effect of stuttering on one's life; there is no observation or objective measure within the OASES-A. We chose to use validated self-report measures to detect stuttering impact, rather than objective measures of stuttering severity, for this project because self-reported measures better incorporate the internal challenges with stuttering (Yaruss & Quesal, 2006). The self-reported OASES-A provides a comprehensive assessment of stuttering from the speaker's perspective (Yaruss & Quesal, 2006). It is validated within the United States, and although it is translated into at least 10 languages, we are unaware of specific validation studies within India. The OASES-A provides impact scores to measure the degree of life impact a speaker experiences due to stuttering (Yaruss & Quesal, 2006). The OASES-A consists of 100 items on a 5-point Likert-type scale and typically takes approximately 20 min or less. Responses are totaled into impact scores, calculated using simple arithmetic by researchers, and higher scores indicate a greater degree of stuttering impact. OASES-A is composed of the following domains: (a) General Information, which includes 20 items related to the speaker's perception of how natural and fluent their speech is and their overall knowledge of stuttering; (b) Reactions to Stuttering, which includes 30 items that check the affective, behavioral, and cognitive reactions of an individual; (c) Communications in Everyday Situations, which includes 25 items that evaluate the degree of communication difficulties in everyday social, work, and domestic situations; and (d) Quality of Life, which includes 25 items regarding the individual's satisfaction with communicative abilities, personal and professional relationships, and other general judgments about their well-being. Impact scores can be reported for the entire test (total impact score), as well as for each of the four sections individually. In the primary and secondary analyses, our independent variable, called Stuttering Impact here, was the OASES-A total impact score. We also report the impact scores for the individual domains.

HCSD Scale. HCSD measures the trust of patients in the health care system (Shea et al., 2008). HCSD consists of nine questions and uses a 5-point Likert-type scale from strongly disagree (1) to strongly agree (5). Sample items include, “The health care system covers up its mistakes,” and “The health care system puts making money above patients' needs.” HCSD is composed of the following domains: (a) Values, measuring the participant's perception that the health care system wants to do what is needed for the participant, and (b) Competence, measuring the participant's perception that the health care system is able to do what is needed for the participant. The HCSD total score is the summed score of Values and Competence domains and ranges from 9 to 45. In this study for ease of interpretation, we inverted HCSD scores so that higher HCSD scores represented greater levels of trust. In the primary analysis, our dependent variable was the inverted HCSD total score.

TPS. TPS assesses an individual's trust in their physician (Anderson & Dedrick, 1990). The measure uses a 5-point Likert-type scale ranging from strongly disagree (1) to strongly agree (5). Sample items include, “My doctor is usually considerate of my needs and puts them first,” and “If my doctor tells me something is so, then it must be true.” TPS is composed of the following domains: (a) Dependability of the Physician, measuring the ability of a physician to look out for the patient's best interests; (b) Confidence in the Physician's Knowledge and Skills, measuring a patient's confidence in a physician's ability to develop treatments; and (c) Confidentiality and Reliability of Information between physician and patient, measuring the patient's belief in a physician's commitment to the privacy of the physician–patient relationship. Scores of each domain are summed to create the TPS total score, which ranges from 11 to 55. Higher scores reflect greater levels of trust. In our secondary analysis, our dependent variable was the TPS total score.

Data Analysis

For analyses, we only included participants with complete surveys (Jamshidian & Mata, 2007). Descriptive information pertaining to patient demographics was calculated as means with standard deviations for continuous variables (or medians with interquartile ranges for variables that are not normally distributed) and proportions for categorical variables (see Table 1). The 25th, 50th, and 75th percentiles were also calculated for continuous demographic variables. For the bivariate analyses, Pearson's correlation tests were conducted to assess the associations between OASES-A impact scores and both HCSD and TPS total scores. Additionally, we conducted additional bivariate analyses between each of the subscales of the OASES-A (General Information, Reactions to Stuttering, Communications in Everyday Situations, and Quality of Life) and both HCSD and TPS total scores. The significance threshold for these analyses was two-sided and set at –.05.

Table 1.

Characteristics of survey participants (N = 118).

Characteristic n (%) Characteristic n (%)
Gender Other conditions
 Male 83 (70)  No 111 (94)
 Female 33 (28)  Skin disease 1 (1)
 Other 2 (2)  Diabetes 2 (2)
Age (years)  ADHD 2 (2)
 18–24 40 (34)  Mental health 2 (1)
 25–33 38 (32)  Other 3 (1)
 34–60 40 (34) Annual household income
Geographic region  0–200,000 41 (35)
 North 43 (37)  200,001–1,000,000 41 (35)
 South 32 (27)  1,000,001–50,000,000 36 (30)
 Central 43 (36) General perception of health
Interactions with physician  Excellent 5 (21)
 0–6 months 20 (17)  Very good 42 (36)
 6 months–1 year 6 (5)  Good 26 (22)
 1–2 years 19 (16)  Fair 17 (14)
 2–5 years 32 (27)  Poor 8 (7)
 More than 5 years 41 (35)
Stuttering impacta, mean (SD) 2.9 (1.4)
Trust in health careb, mean (SD) 27.8 (12.5)
Trust in physicianc, mean (SD) 35.7 (14.8)
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Note. Annual household income is measured in rupees. ADHD = attention-deficit/hyperactivity disorder.

a

Overall Assessment of the Speaker's Experience With Stuttering–Adults total impact score, where higher values represent greater impact of stuttering.

b

Inverted Health Care System Distrust total score, where higher values represent greater trust in health care.

c

Trust in physician scale, where higher values represent greater trust in physician.

Our primary analysis used multivariate linear regression to ascertain the relationship between stuttering impact, measured by the OASES-A total impact score, and trust in the health care system, measured by the inverted HCSD total score. Although OASES-A total impact score can be interpreted categorically, we elected for this study to use the score as a continuous variable. Our secondary analysis used multivariate linear regression to ascertain the relationship between stuttering impact, measured by the OASES-A total impact score, and trust in physicians, measured by the TPS total score. Additional exploratory analyses used multivariate linear regression to ascertain the relationship between each of the subscales of the OASES-A (General Information, Reactions to Stuttering, Communications in Everyday Situations, and Quality of Life) and both HCSD and TPS total scores. All regression models controlled for age, gender, and annual household income. Each model was subjected to regression diagnostic tests. Both models failed tests for heteroscedasticity using the Breusch–Pagan/Cook–Weisberg post-estimation tests, so we report regression results using robust standard errors. Additionally, we used the D'Agostino K2 tests in each model to check normality of residuals. We used SPSS v26.0 and STATA v14.2 for all analyses.

Results

Sociodemographics and Data Summary

One hundred eighty-six adults who stutter chose to participate. One hundred eighteen participants completed the entire study and thus were included in this analysis (see Table 1 for participant characteristics). The median age of the participants was 27.5 years. Of all participants, 83 were male (70.3%), 33 were female (28.0%), and two identified as neither male nor female (1.7%). A plurality of participants reported interacting with a physician for longer than 5 years (34.7%). The sample was geographically diverse, with 43 (36.4%), 32 (27.1%), and 43 (36.4%) individuals selecting North, South, and Central India, respectively. Most participants (94.1%) reported not having any other medical conditions or disabilities. The median annual household income of the participants was 500,000 rupees, which is approximately equivalent to $6,750 in the United States and represents the middle-income bracket in India. Twenty-five (21.2%) participants described their health as excellent, 42 (35.6%) respondents reported their health as very good, 26 (22.0%) people described their health as good, 17 (14.4%) individuals reported their health as fair, and eight (6.8%) people described their health as poor. Finally, 106 participants (89.8%) reported receiving speech therapy at some point in their lives.

Participants tended to have variable stuttering impact, trust in health care, and trust in physician. Mean stuttering impact was 2.9 of 5 (range: 1.3–4.7), mean trust in health care was 27.8 of 45 (range: 10–45), and mean trust in physician was 35.8 of 55 (range: 14–55).

Greater Stuttering Impact Is Strongly Negatively Associated With Trust in the Health Care System and With Trust in Physicians

We found a strong negative association between stuttering impact, measured by the OASES-A total impact score, and trust in the health care system, measured by the inverted HCSD total score (r = −.940, p < .0001; see Figure 1). We also found a strong negative association between stuttering impact, measured by the OASES-A total impact score, and the level of trust in physicians, measured by TPS total score (r = −.941, p < .0001; see Figure 2). In bivariate analyses of subscales of the OASES-A with HCSD and TPS, each domain showed a strongly negative association with trust in health care and trust in physician (see Table 2).

Figure 1.

A scatterplot depicts the correlation between the trust in health care, HCSD total score on the y axis, and the stuttering impact, OASES-A total impact score, on the x axis. The regression line runs between (1.3, 41) and (4.7, 14).

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Stuttering impact and trust in health care. HCSD = Health Care System Distrust; OASES-A = Overall Assessment of the Speaker's Experience With Stuttering–Adults.

Figure 2.

A scatterplot depicts the correlation between the trust in physician, TPS total score, on the y axis, and the Stuttering impact, OASES-A total score, on the x axis. The regression line runs between (1.3, 52) and (4.7, 19).

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Stuttering impact and trust in physician. TPS = Trust in Physicians Scale; OASES-A = Overall Assessment of the Speaker's Experience With Stuttering–Adults.

Table 2.

Regression analyses incorporating Overall Assessment of the Speaker's Experience With Stuttering–Adults Scales and the Health Care System Distrust or Trust in Physicians Scale (N = 118).

Independent variable Dependent variable r a R 2 p value
OASES-A total impact score HCSD −.940 .884 < .0001
TPS −.941 .887 < .0001
General Information HCSD −.927 .862 < .0001
TPS −.948 .902 < .0001
Reactions to Stuttering HCSD −.918 .844 < .0001
TPS −.899 .810 < .0001
Communications in Everyday Situations HCSD −.931 .868 < .0001
TPS −.934 .875 < .0001
Quality of Life HCSD −.928 .862 < .0001
TPS −.936 .877 < .0001
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Note. All results were statistically significant. Regression analyses, including R2 and p values, were obtained from adjusted regression models. Control variables included age, gender, and household income. Variables and values in bold pertain to our primary analysis. OASES = Overall Assessment of the Speaker's Experience With Stuttering–Adults; HCSD = Health Care System Distrust; TPS = Trust in Physicians Scale.

a

Pearson's correlation coefficients were obtained in bivariate analyses.

When Controlling for Age, Gender, and Annual Household Income, Greater Stuttering Impact Is Strongly Negatively Associated With Trust in the Health Care System and With Trust in Physicians

Incorporation of age, gender, and annual household income as predictor variables revealed that controlling for the three variables did not significantly impact the relationships between the OASES-A total impact score and either the inverted HCSD total score (B = −8.38, CI [−7.82, −8.94], p < .0001, R2 = .884) or the TPS total score (B = −9.94, CI [−9.30, −10.59], p < .0001, R2 = .887). In both models, the D'Agostino K2 test rejected the null hypothesis that residuals were normally distributed: HCSD, χ2(2) = 31.182, p < .0001; TPS, χ2(2) = 64.090, p < .0001. When residuals are not normally distributed, caution must be taken in interpreting statistical significance if p values for the models themselves are marginal, which was not the case in our primary and secondary analyses. In exploratory analyses, each OASES-A subscale was strongly negatively associated with trust in health care and trust in physician after adjusting for age, gender, and annual household income (see Table 2).

Discussion

This project is one of the few to examine stuttering impact and trust in the health care system and in physicians, and the only to examine trust in a sample of Indian persons who stutter. This study is also the first, to our knowledge, to quantitatively examine health care experiences among persons who stutter in any country. In our sample, we believe that there is a signal of strong and robust relationships between stuttering impact and trust, and the results of this study expose a new area where stuttering might affect health care system interactions.

Trust is the foundation of effective health care relationships—it has been defined as the confidence and sense of comfort that originates from the belief that patients can rely on an individual to perform competently, responsibly, and in a manner considerate of patients' interests (Barber, 1983). Trust in itself can influence health outcomes through several pathways. First, it can influence patient behaviors in the office; patients who do not trust their physicians may be less willing to discuss sensitive topics in their presence. Second, it can influence contact with the health system; patients who do not trust the system may avoid the health care system altogether. Since most measures of physician trust rely exclusively on patients' impressions after one-on-one interactions, measures of trust of the health care system are also important because marginalized populations, such as persons who stutter, have a tendency to avoid care altogether (Anderson & Dedrick, 1990; Perez et al., 2015). Therefore, a specific strength of this study is obtaining trust measurements at both the patient–provider level and at the systems level. While systemic access barriers to health care are also a major issue in India, this research focuses instead on patient perceptions in lieu of systemic barriers. This study also fits well within the broader context of disparities facing persons with speech, language, and voice disabilities when seeking supportive care, while opening a novel avenue for exploration into the experiences of persons who stutter.

The unique relationship that we observed in this study may be at least partially explained by persistently negative biases of stuttering associated with cultural norms in India. India has a long history with stuttering and retains historical myths and stigma about the disorder, which may influence personal experiences in health care settings. Even today, mothers of persons who stutter may recommend digesting holy basil, Glycyrrhiza glabra, black pepper, and ginger to produce “clear and fluent speech” (Rout et al., 2014). Harmful myths about stuttering in India are prevalent. These include the belief that fluency can be achieved for persons who stutter by reading aloud to a mirror, by wearing a seashell as a ring, or by placing a betel nut under the tongue (Rout et al., 2014). Also, training for professionals in dealing with persons who stutter is woefully inadequate. A sociological study showed that 51.7% of teachers indicated that children should continue repeating words until they are fluent (Pachigar et al., 2011). Children who stutter do not fare much better outside the classrooms. Speech therapy is highly expensive, so few children have access to skilled speech practitioners who may positively influence the client's conception of health care professionals. Alternatives, such as critical social support networks, are not well established in India (Pachigar et al., 2011; Rout et al., 2014). The relationship between stuttering and trust is especially important in health care because of the need for trust in sensitive patient–physician relationships, especially during counseling and around treatment.

Although this study focused on the relationship between stuttering impact and trust in Indian health care and physicians, negative attitudes about persons who stutter are common around the globe, and it is possible these might influence trust in health care and trust in physicians across the world. Speech-language pathologists around the globe may wish to discuss how stuttering might influence health care experiences to motivate better health care system interactions among their clients who stutter. For example, one area of potential emphasis may be to develop strategies to self-advocate in a physician's office, such as by asking for more time, coming prepared with questions, or through self-disclosure to the physician. These simple strategies can improve patient–provider communication and increase trust. Although these strategies may not improve systemic health care access barriers, starting with patient-directed strategies, such as by reducing stuttering impact in individuals, may be hugely beneficial for many patients.

We found stuttering impact in this group tended to be consistent, if not slightly higher, compared with measures of stuttering severity in other studies across the world. Our mean stuttering impact was 2.9. Conversely, Bleek et al. (2012) administered the OASES-A to 112 persons in Germany to assess the relationships between personality and characteristics of people who stutter. They found mean stuttering impact of 2.47. Likewise, Freud et al. (2017) examined the association between stuttering impact and demographic characteristics. In 91 Israeli participants who stuttered, mean stuttering impact was 2.47. These results may indicate that our group felt more impacted by stuttering than other groups surveyed across the world, but further research is needed on how this might affect trust across the world.

Our results indicate that trust within health care system interactions may be an important point of discussion between speech therapists when considering stressors that reduce well-being among persons who stutter. Because poor patient–provider communication can reduce trust and reduce well-being, discussing it openly may be hugely beneficial to clients. Considering factors such as trust, rapport, and camaraderie and opening up effective lines of communication between patients and speech-language pathologists could be a path to the delivery of more effective support for persons who stutter.

Limitations

There are various limitations worth considering when interpreting information presented in this study. Although our sample of participants was diverse among various metrics, including income and geographical location, it was still limited because the number of survey participants (N = 118) only constituted 11.2% of TISA membership (N = 1,050). Because persons who stutter in India can be difficult to identify, we recruited a convenience sample of adult members of TISA. Therefore, these data may be reflective of persons who choose to join a national stuttering group, which may exclude those most highly marginalized in society or those less impacted by stuttering. Another limitation is the lack of a control group in our study. However, stuttering impact can be highly variable among persons who stutter, as we saw in this study. Moreover, because our question was how stuttering impact is associated with trust, a control group that does not stutter is not necessary. Future research can utilize innovative recruitment strategies and/or control groups to be more inclusive of Indians who stutter and of the Indian population. Other further research can also determine how stuttering impact is related to trust in health care and in physicians around the world.

Conclusions

These findings raise concerns about the health care received by a highly marginalized group of persons who stutter. Trust in the health care system and in one's provider is paramount to good health care system interactions and outcomes. Indians who stutter may face stigma that might influence trust, and future studies are warranted in varying contexts and countries to explore these important findings. We strongly believe that this work has implications for how we work with persons who stutter. Speech-language pathologists may wish to talk about how stuttering might influence health care experiences to motivate better health care system interactions among their clients who stutter. Considering how stuttering is related to trust, rapport, and camaraderie could be a path to the delivery of more effective therapy for persons who stutter.

Data Availability Statement

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

Acknowledgments

This work was supported by the Fulbright-Nehru Student Research Grant awarded to Nathan V. Mallipeddi and the National Institute on Drug Abuse (Grant K23DA044327) awarded to Hector R. Perez. The authors have no acknowledgments to report at this time.

Funding Statement

This work was supported by the Fulbright-Nehru Student Research Grant awarded to Nathan V. Mallipeddi and the National Institute on Drug Abuse (Grant K23DA044327) awarded to Hector R. Perez.

References

  1. Anderson, L. A., & Dedrick, R. F. (1990). Development of the trust in physician scale: A measure to assess interpersonal trust in patient–physician relationships. Psychological Reports, 67(Suppl. 3), 1091–1100. 10.2466/pr0.1990.67.3f.1091 [DOI] [PubMed] [Google Scholar]
  2. Armstrong, K., Rose, A., Peters, N., Long, J. A., McMurphy, S., & Shea, J. A. (2006). Distrust of the health care system and self-reported health in the United States. Journal of General Internal Medicine, 21(4), 292–297. 10.1111/j.1525-1497.2006.00396.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Baier, A. (1986). Trust and antitrust. Ethics, 96(2), 231–260. 10.1086/292745 [DOI] [Google Scholar]
  4. Barber, B. (1983). The logic and limits of trust. Rutgers University Press. [Google Scholar]
  5. Bayati, B., & Ayatollahi, H. (2021). Speech therapists' perspectives about using tele-speech therapy: A qualitative study. Disability and Rehabilitation: Assistive Technology, 18(5), 621–626. 10.1080/17483107.2021.1900933 [DOI] [PubMed] [Google Scholar]
  6. Bleek, B., Reuter, M., Yaruss, J. S., Cook, S., Faber, J., & Montag, C. (2012). Relationships between personality characteristics of people who stutter and the impact of stuttering on everyday life. Journal of Fluency Disorders, 37(4), 325–333. 10.1016/j.jfludis.2012.07.003 [DOI] [PubMed] [Google Scholar]
  7. Blood, G. W., Blood, I. M., Dorward, S., Boyle, M. P., & Tramontana, G. M. (2011). Coping strategies and adolescents: Learning to take care of self and stuttering during treatment. Perspectives on Fluency and Fluency Disorders, 21(3), 68–77. 10.1044/ffd21.3.68 [DOI] [Google Scholar]
  8. Boyle, M. P., & Fearon, A. N. (2018). Self-stigma and its associations with stress, physical health, and health care satisfaction in adults who stutter. Journal of Fluency Disorders, 56, 112–121. 10.1016/j.jfludis.2017.10.002 [DOI] [PubMed] [Google Scholar]
  9. Briley, P. M., Ellis, C., Jr, & Jacobs, M. M. (2021). The impact of stuttering—Hiding in plain sight. JAMA Neurology, 78(6), 646–647. 10.1001/jamaneurol.2021.0633 [DOI] [PubMed] [Google Scholar]
  10. Büchel, C., & Sommer, M. (2004). What causes stuttering? PLOS BIOLOGY, 2(2), Article e46. 10.1371/journal.pbio.0020046 [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Cooper, E. B., & Cooper, C. S. (1996). Clinician attitudes towards stuttering: Two decades of change. Journal of Fluency Disorders, 21(2), 119–135. 10.1016/0094-730x(96)00018-6 [DOI] [Google Scholar]
  12. Freud, D., Kichin-Brin, M., Ezrati-Vinacour, R., Roziner, I., & Amir, O. (2017). The relationship between the experience of stuttering and demographic characteristics of adults who stutter. Journal of Fluency Disorders, 52, 53–63. 10.1016/j.jfludis.2017.03.008 [DOI] [PubMed] [Google Scholar]
  13. Halbert, C. H., Armstrong, K., Gandy, O. H., & Shaker, L. (2006). Racial differences in trust in health care providers. Archives of Internal Medicine, 166(8), 896–901. 10.1001/archinte.166.8.896 [DOI] [PubMed] [Google Scholar]
  14. Hoffman, J. M., Yorkston, K. M., Shumway-Cook, A., Ciol, M. A., Dudgeon, B. J., & Chan, L. (2005). Effect of communication disability on satisfaction with health care: A survey of Medicare beneficiaries. American Journal of Speech-Language Pathology, 14(3), 221–228. 10.1044/1058-0360(2005/022) [DOI] [PubMed] [Google Scholar]
  15. Jamshidian, M., & Mata, M. (2007). Advances in analysis of mean and covariance structure when data are incomplete. In Lee S. Y. (Ed.), Handbook of latent variable and related models (1st ed., pp. 21–42). Elsevier. 10.1016/B978-044452044-9/50005-7 [DOI] [Google Scholar]
  16. Kane, S., & Calnan, M. (2017). Erosion of trust in the medical profession in India: Time for doctors to act. International Journal of Health Policy and Management, 6(1), 5–8. 10.15171/ijhpm.2016.143 [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Kane, S., Calnan, M., & Radkar, A. (2015). Trust and trust relations from the providers' perspective: The case of the healthcare system in India. Indian Journal of Medical Ethics, 12(3), 157–168. 10.20529/IJME.2015.045 [DOI] [PubMed] [Google Scholar]
  18. Mann, M. B. (1966). Observation on stuttering in India. Indian Journal of Otolaryngology, 18(2), 44–50. 10.1007/bf03048242 [DOI] [Google Scholar]
  19. Morris, M. A., Dudgeon, B. J., & Yorkston, K. (2013). A qualitative study of adult AAC users' experiences communicating with medical providers. Disability and Rehabilitation: Assistive Technology, 8(6), 472–481. 10.3109/17483107.2012.746398 [DOI] [PubMed] [Google Scholar]
  20. Morris, M. A., Meier, S. K., Griffin, J. M., Branda, M. E., & Phelan, S. M. (2016). Prevalence and etiologies of adult communication disabilities in the United States: Results from the 2012 National Health Interview Survey. Disability and Health Journal, 9(1), 140–144. 10.1016/j.dhjo.2015.07.004 [DOI] [PubMed] [Google Scholar]
  21. Morris, M. A., Wong, A. A., Dorsey Holliman, B., Liesinger, J., & Griffin, J. M. (2021). Perspectives of patients with diverse disabilities regarding healthcare accommodations to promote healthcare equity: A qualitative study. Journal of General Internal Medicine, 36(8), 2370–2377. 10.1007/s11606-020-06582-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Nandhini, D. G., Thalamuthu, A., Valarmathi, S., Karthikeyen, N., & Srikumari Srisailapathy, C. (2018). Genetic epidemiology of stuttering among school children in the state of Tamil Nadu, India. Journal of Fluency Disorders, 58, 11–21. 10.1016/j.jfludis.2018.10.001 [DOI] [PubMed] [Google Scholar]
  23. Nang, C., Hersh, D., Milton, K., & Lau, S. R. (2018). The impact of stuttering on development of self-identity, relationships, and quality of life in women who stutter. American Journal of Speech-Language Pathology, 27(3S), 1244–1258. 10.1044/2018_AJSLP-ODC11-17-0201 [DOI] [PubMed] [Google Scholar]
  24. Nordehn, G., Meredith, A., & Bye, L. (2006). A preliminary investigation of barriers to achieving patient-centered communication with patients who have stroke-related communication disorders. Topics in Stroke Rehabilitation, 13(1), 68–77. 10.1310/5K2W-P6CD-EFDF-8HG4 [DOI] [PubMed] [Google Scholar]
  25. Pachigar, V., Stansfield, J., & Goldbart, J. (2011). Beliefs and attitudes of primary school teachers in Mumbai, India towards children who stutter. International Journal of Disability, Development and Education, 58(3), 287–302. 10.1080/1034912X.2011.598664 [DOI] [Google Scholar]
  26. Perez, H. R., Doig-Acuña, C., & Starrels, J. L. (2015). “Not unless it's a life or death thing”: A qualitative study of the health care experiences of adults who stutter. Journal of General Internal Medicine, 30(11), 1639–1644. 10.1007/s11606-015-3302-x [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Polikowsky, H. G., Shaw, D. M., Petty, L. E., Chen, H. H., Pruett, D. G., Linklater, J. P., Viljoen, K. Z., Beilby, J. M., Highland, H. M., Levitt, B., Avery, C. L., Harris, K. M., Jones, R. M., Below, J. E., & Kraft, S. J. (2022). Population-based genetic effects for developmental stuttering. Human Genetics and Genomics Advances, 3(1), Article 100073. 10.1016/j.xhgg.2021.100073 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Rout, N., Kumar, S., & Kumar, N. (2014). A survey on conceptions of stuttering. Rehabilitation Process and Outcome, 3, RPO.S12755. 10.4137/rpo.s12755 [DOI] [Google Scholar]
  29. Rowe, R., & Calnan, M. (2006). Trust relations in health care—The new agenda. European Journal of Public Health, 16(1), 4–6. 10.1093/eurpub/ckl004 [DOI] [PubMed] [Google Scholar]
  30. Shea, J. A., Micco, E., Dean, L. T., McMurphy, S., Schwartz, J. S., & Armstrong, K. (2008). Development of a revised health care system distrust scale. Journal of General Internal Medicine, 23(6), 727–732. 10.1007/s11606-008-0575-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Stransky, M. L., Jensen, K. M., & Morris, M. A. (2018). Adults with communication disabilities experience poorer health and healthcare outcomes compared to persons without communication disabilities. Journal of General Internal Medicine, 33(12), 2147–2155. 10.1007/s11606-018-4625-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Subramanian, U., & Prabhu, B. (2005). Stuttering research and treatment around the world: India. The ASHA Leader, 10(14), 7–8. 10.1044/leader.wb4.10142005.7 [DOI] [Google Scholar]
  33. Thom, D. H., Hall, M. A., & Pawlson, L. G. (2004). Measuring patients' trust in physicians when assessing quality of care. Health Affairs, 23(4), 124–132. 10.1377/hlthaff.23.4.124 [DOI] [PubMed] [Google Scholar]
  34. Tichenor, S. E., & Yaruss, J. S. (2021). Variability of stuttering: Behavior and impact. American Journal of Speech-Language Pathology, 30(1), 75–88. 10.1044/2020_ajslp-20-00112 [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Whetten, K., Leserman, J., Whetten, R., Ostermann, J., Thielman, N., Swartz, M., & Stangl, D. (2006). Exploring lack of trust in care providers and the government as a barrier to health service use. American Journal of Public Health, 96(4), 716–721. 10.2105/ajph.2005.063255 [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Yairi, E., & Carrico, D. M. (1992). Early childhood stuttering: Pediatricians' attitudes and practices. American Journal of Speech-Language Pathology, 1(3), 54–62. 10.1044/1058-0360.0103.54 [DOI] [Google Scholar]
  37. Yaruss, J. S., & Quesal, R. W. (2004). Stuttering and the International Classification of Functioning, Disability, and Health: An update. Journal of Communication Disorders, 37(1), 35–52. 10.1016/S0021-9924(03)00052-2 [DOI] [PubMed] [Google Scholar]
  38. Yaruss, J. S., & Quesal, R. W. (2006). Overall Assessment of the Speaker's Experience of Stuttering (OASES): Documenting multiple outcomes in stuttering treatment. Journal of Fluency Disorders, 31(2), 90–115. 10.1016/j.jfludis.2006.02.002 [DOI] [PubMed] [Google Scholar]

Associated Data

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

Data Availability Statement

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

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