Speech deficits in serious mental illness: A cognitive resource issue?

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Abstract

Speech deficits, notably those involved in psychomotor retardation, blunted affect, alogia and poverty of content of speech, are pronounced in a wide range of serious mental illnesses (e.g., schizophrenia, unipolar depression, bipolar disorders). The present project evaluated the degree to which these deficits manifest as a function of cognitive resource limitations. We examined natural speech from 52 patients meeting criteria for serious mental illnesses (i.e., severe functional deficits with a concomitant diagnosis of schizophrenia, unipolar and/or bipolar affective disorders) and 30 non-psychiatric controls using a range of objective, computer-based measures tapping speech production (“alogia”), variability (“blunted vocal affect”) and content (“poverty of content of speech”). Subjects produced natural speech during a baseline condition and while engaging in an experimentally-manipulated cognitively-effortful task. For correlational analysis, cognitive ability was measured using a standardized battery. Generally speaking, speech deficits did not differ as a function of SMI diagnosis. However, every speech production and content measure was significantly abnormal in SMI versus control groups. Speech variability measures generally did not differ between groups. For both patients and controls as a group, speech during the cognitively-effortful task was sparser and less rich in content. Relative to controls, patients were abnormal under cognitive load with respect only to average pause length. Correlations between the speech variables and cognitive ability were only significant for this same variable: average pause length. Results suggest that certain speech deficits, notably involving pause length, may manifest as a function of cognitive resource limitations. Implications for treatment, research and assessment are discussed.

Introduction

Serious mental illness (SMI) — defined in terms of serious functional impairments due to a diagnosable mental illness (e.g., schizophrenia, major depression, bipolar disorders), carries a profound burden of illness and disability. Mounting evidence suggests that there are often commonalities in individuals with SMI with respect to symptom presentation (e.g., Insel et al., 2010), functional impairments (e.g., Pini et al., 2001, Simonsen et al., 2011), neurobiology (e.g., Ng et al., 2008) and treatment response (e.g., Roth et al., 2004) related variables in ways that transcend traditional diagnostic boundaries (NIMH, 2013). In response, there have been repeated calls to understand the mechanisms underlying symptoms in mental illness beyond those involved with traditionally-defined diagnostic groups. In the present paper, we evaluate whether cognitive liabilities underlie speech deficits in individuals with SMI using highly sensitive objective measures and both experimental and correlational methods.

Deficits in speech communication, defined in terms of reduced production (e.g., alogia), variability (e.g., blunted affect) and content (e.g., poverty of content — speech that lacks meaning, irrespective of quantity of speech) are a staple of SMI (American Psychiatric Association [APA], 1994; Cohen et al., 2012b, Tremeau et al., 2005). These deficits are often chronic in course, medication resistant and related to poor prognosis (Kirkpatrick et al., 2001). Despite these symptoms reflecting important Research Domain Criteria (RDoC) as “Production of Non-facial Communication”, and hence, being potentially instrumental for understanding pathophysiological processes and improving diagnosis (Insel et al., 2010, Cohen et al., 2012b, National Institute of Mental Health, 2013), our understanding of their nature is poor. An unfortunate obstacle in understanding and measuring speech deficits is a reliance on interviewer-based rating scales (Horan et al., 2011, Kirkpatrick et al., 2011). Data from these scales are relatively insensitive to change given the limited range of response options and ambiguous operational definitions, produce ordinal data that are inappropriate for parametric statistics, often cover wide temporal swaths, and are imprecise for isolating specific behaviors (Alpert et al., 2002, Cohen et al., 2008, Cohen and Elvevaag, 2014). Moreover, these scales have limited resolution for understanding how expressive deficits modulate within individuals, how they differ across individuals, and how they are uniquely related to cognitive, functional, pathophysiological, genetic and other variables. Thus, it is little surprise that our mechanistic understanding of speech deficits is poor. Emerging computerized technologies have allowed for assessment of speech deficits with near perfect inter-rater reliability and greater sensitivity and specificity than clinical rating scales (Alpert et al., 2002, Cohen et al., 2008, Cohen et al., 2012b, Cohen and Hong, 2011).

There is reason to think that speech deficits may reflect a broader cognitive resource issue in patients with SMI. A substantial amount of research from a range of disciplines suggests that humans have a limited amount of cognitive resources at any given time, and allocating resources towards one task (e.g., remembering a phone number or name, operating a motor vehicle) limits the resources available for speech (e.g., Plass et al., 2010). To date, at least six studies conducted using experimental methods have found evidence that depletion of cognitive resources results in reduction of speech quantity (Barch and Berenbaum, 1994, Barch and Berenbaum, 1996, Yin et al., 2007, Cohen et al., 2012a, Cohen et al., 2014a, Tuček et al., 2012). Some of these studies have also documented changes in speech variability (Yin et al., 2007, Cohen et al., 2012a, Cohen et al., 2014a, Tuček et al., 2012) and speech content (Barch and Berenbaum, 1994, Barch and Berenbaum, 1996) as well.

There is good reason to suspect that cognitive resource limitations may reflect a mechanism by which speech deficits manifest. First, patients with SMI show a broad range of cognitive deficits and these deficits are, in at least some studies, similar across diagnostic categories (Simonsen et al., 2011, Cohen et al., 2012b). Second, poorer cognitive ability has been associated with negative symptoms in schizophrenia (e.g., Cohen et al., 2007), severity of melancholia in depression (e.g., Austin et al., 1999), and with poorer social functioning in bipolar disorder (Burdick et al., 2010) using interview-based rating scales. Third, correlational studies have demonstrated a link between cognitive deficits (e.g., processing speed) and abnormal speech production and speech variability in patients with SMI (e.g., Gur et al., 2006, Cohen et al., 2013). Finally, several experimental studies have demonstrated that increased cognitive load in patients with schizophrenia was associated with decreased speech production and poverty of content (Barch and Berenbaum, 1996, Melinder and Barch, 2003).

There are critical limitations in our understanding of the link between cognition and speech deficits in SMI. Of note, experimental studies examining patients (i.e., Barch and Berenbaum, 1996, Melinder and Barch, 2003) failed to include control groups, so it is unclear whether speech is actually abnormal relative to the population. Moreover, prior studies employing objective or computerized analysis of speech tended to focus solely on speech production at the expense of speech variability and speech content. Furthermore, prior studies have employed limited indices of speech production (e.g., word counts) and variability (e.g., mean volume, variability of F0). This is a critical point highlighted in a recent meta-analysis of objective measures of speech deficits in schizophrenia (Cohen et al., 2014b) — that there has been little consistency in which speech variables are reported across studies (e.g., eight different variables of speech production reported across 13 studies), and considerable disparity in magnitude of deficit across these variables (range of ds =  0.20 to − 2.56). In the present study, we addressed these limitations and conducted the most sophisticated study to date clarifying the cognitive underpinnings of speech deficits in SMI. We employed both correlational and experimental approaches, and a broad set of sophisticated and diverse computer-based measures of natural speech indicated in a recent psychometric investigation from our group (Cohen et al., 2014c).

Section snippets

Participants

Participants were recruited from outpatient community mental health clinics and group homes based on meeting federal criteria for having an SMI defined in terms of adults (i.e., age 18 or older) who currently, or in the past year, meet criteria for a diagnosable mental, behavioral, or emotional disorder that results in functional impairment which substantially interferes with one or more major life activities (i.e., per the ADAMHA Reorganization Act). Participants included 52 patients with

Zero-order correlations

Zero-order correlations (see Table 2) suggested that the variables were relatively independent of each other. The only variables approaching redundancy (i.e., r > 0.85) were between the word count and pause length variables for controls (r =  0.83) and the pause number and pause length variables for the patients (r =  0.80).

Demographic and descriptive variables

Education and GAF scores were significantly different between the patient and control groups (ps < .05), but there were no other significant differences (see Table 1). Patients

Discussion

There are five notable findings from this study. First, patients with SMI were deficient in nearly every aspect of speech production and content measured in this study. Second, consistent with prior studies (Barch and Berenbaum, 1994, Barch and Berenbaum, 1996, Yin et al., 2007, Cohen et al., 2012a, Cohen et al., 2014a, Tuček et al., 2012) depletion of cognitive resources resulted in people (both with and without SMI) producing less speech, and speech that was less semantically and lexically

Role of funding source

Funding for this study was provided by a Louisiana Board of Regents and National Institute of Mental Health (R03 MH092622) grant to the primary author. The funding agencies had no further role in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the paper for publication.

Contributors

Alex S Cohen was the primary investigator for this project and designed the study and wrote the bulk of the manuscript. Jessica McGovern, Thomas Dinzeo and Michael Covington helped manage the literature searches and the analyses and provided conceptual material to the planning and presentation of this project. All authors contributed to and have approved the final manuscript.

Conflicts of interest

There are no conflicts of interest to report.

Acknowledgments

The authors wish to acknowledge the subjects for their participation, lab members for their help in processing and collecting data and MMO Behavioral Health Systems for their assistance in subject outreach.

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