exploring the interrelationships of cognition and …

EXPLORING THE INTERRELATIONSHIPS OF COGNITION AND SOCIAL

COMMUNICATION THROUGH DEVELOPMENT OF THE PROFILE OF

PRAGMATIC IMPAIRMENT IN COMMUNICATION IN INDIVIDUALS WITH

TRAUMATIC BRAIN INJURY

__________________

A Dissertation

Presented to

The Faculty of the Department

Of Psychology

University of Houston

__________________

In Partial Fulfillment

Of the Requirements for the Degree of

Doctor of Philosophy

__________________

By

Jace M. Waguspack

August, 2016

ii

EXPLORING THE INTERRELATIONSHIPS OF COGNITION AND SOCIAL

COMMUNICATION THROUGH DEVELOPMENT OF THE PROFILE OF

PRAGMATIC IMPAIRMENT IN COMMUNICATION IN INDIVIDUALS WITH

TRAUMATIC BRAIN INJURY

__________________

An Abstract of a Dissertation

Presented to

The Faculty of the Department

Of Psychology

University of Houston

__________________

In Partial Fulfillment

Of the Requirements for the Degree of

Doctor of Philosophy

__________________

By

Jace M. Waguspack

August, 2016

iii

Abstract

Deficits in social functioning are common following traumatic brain injury (TBI).

Previous research suggests that there are multiple, complex factors which underlie such deficits,

including cognition and social communication. Standardized measurement of social

communication following TBI is challenging, and often involves the use of structured rating

scales. The Profile of Pragmatic Impairment in Communication (PPIC) is one such scale that

shows promise, though it requires further development and empirical testing to improve its utility

in the TBI population. The current study is archival in nature. Data were obtained from two prior

study samples in projects investigating social communication in the community dwelling adult

TBI population: the social communication assessment measures study (SCA study, N = 121) and

a randomized clinical trial for social communication intervention (IPR study, N = 83). In order to

further develop the PPIC and examine the underlying cognitive abilities which impact social

pragmatics, the 84 behavioral items of the PPIC were reduced to a set of 20 items deemed to be

most characteristic of social communication difficulties following TBI. These 20 items were

analyzed using exploratory factor analysis. Following an iterative process, a two factor solution

accounting for 60.77% of the total variance was obtained, and it included 9 of the 20 originally

selected items. These factors were labeled Partner Sensitivity (5 items) and Conversational Flow

(4 items), and subscale scores were created by summing the item scores within each factor. The

cognitive underpinnings of social pragmatics as measured by the new PPIC subscales were

examined using hierarchical linear regression, using measures of attention, executive functioning,

and affect perception as predictor variables and the new PPIC subscale scores, AIPSS Overall

Sending score, and the TIRR Social Communication Rating Form (an experimental measure) as

outcome variables. After adjusting for demographic and injury-related variables, performance on

cognitive measures accounted for a unique 22% of the variance in PPIC Conversational Flow

scores and 17% of the variance in AIPSS Overall Sending scores, while performance on cognitive

measures did not account for a statistically significant amount of unique variance in PPIC Partner

iv

Sensitivity scores or TIRR Social Communication Rating Form scores. These results represent

important preliminary steps in the development of the PPIC into a more parsimonious and useful

tool and in developing a more sophisticated understanding of the relationship between cognition,

social communication, and social functioning in TBI.

v

ACKNOWLEDGMENTS

I would like to thank Dr. Hannay for her time, guidance, and encouragement throughout

my graduate school career. Her commitment to teaching and mentorship has played a crucial role

in my education and professional development, and I owe her my sincerest gratitude. I would also

like to thank Dr. Struchen for serving as my committee co-chair. Her willingness to take on the

additional responsibility of guiding a student through the dissertation process allowed me to

pursue an area of research that I am fascinated by and passionate about, and I am extremely

grateful for her time and help. Additionally, I would like to thank Drs. Massman, Pappadis, and

Steinberg for serving on my committee, and for being gracious with their time, expertise, and

support. Finally, I would like to thank my wife, Jessica, and my family. Their love and support

provided me with the strength and determination to finish this race. Thank you all.

vi

TABLE OF CONTENTS

Chapter 1: Background and Literature Review ................................................................................ 1

Overview of Traumatic Brain Injury ............................................................................................. 1

Injury Severity .............................................................................................................................. 2

Cognitive and Behavioral Changes Following TBI ........................................................................ 4

Social Functioning and Social Cognition in TBI ............................................................................ 6

Relationship between Social Cognition and other Cognitive Domains in TBI ............................. 8

Social Communication in TBI ....................................................................................................... 8

The Profile of Pragmatic Impairment in Communication .......................................................... 12

Present Problem ........................................................................................................................ 17

Hypotheses of the Current Study .............................................................................................. 18

Chapter 2: Methods ....................................................................................................................... 21

Participants & Procedures ......................................................................................................... 21

Measures.................................................................................................................................... 25

Statistical Analyses ..................................................................................................................... 30

Chapter 3: Results .......................................................................................................................... 33

Sample Characteristics ............................................................................................................... 33

Specific Aim 1: PPIC Development ............................................................................................. 33

Specific Aim 2: Prediction of Social Communication Difficulties ............................................... 40

Chapter 4: Discussion ..................................................................................................................... 46

Specific Aim 1: PPIC Development ............................................................................................. 46

Specific Aim 2: Prediction of Social Communication Difficulties ............................................... 48

Study Limitations & Future Directions ....................................................................................... 53

Conclusion .................................................................................................................................. 56

APPENDIX A Figures and Tables ..................................................................................................... 58

APPENDIX B Distribution Histograms, P-P Plots, and Scatterplots ................................................ 72

Partner Sensitivity Regression Residual Plots ............................................................................ 72

Conversational Flow Regression Residual Plots ......................................................................... 72

TIRR Social Communication Rating Form Regression Plots ....................................................... 73

AIPSS Regression Plots ............................................................................................................... 73

REFERENCES ................................................................................................................................... 74

vii

LIST OF TABLES

Table 1. Hypothesized Factor Structure for Selected PPIC Items……………………….51

Table 2. Predictor and Outcome Variables for Specific Aim 2………………………….52

Table 3. Comparison of Demographic Characteristics

and Key Measures of the SCA and IPR Participants……………...53

Table 4. Correlations Among PPIC Items………………………………………….……54

Table 5. Varimax Rotated Principal Axis Factoring Loadings and Communality

Estimates for PPIC (3 Factors).……………………………….....55

Table 6. Varimax Rotated Principal Axis Factoring Loadings and Communality

Estimates for PPIC (2 Factors)……………………………….....55

Table 7. Descriptive Statistics for Social Communication and Community

Integration Measures…………………………………………...56

Table 8. Descriptive Statistics for Predictor and Outcome Measures……………….....57

Table 9. Correlations Among Predictor and Dependent Variables………………….....58

Table 10. Prediction of PPIC Partner Sensitivity Scale Scores……………………......59

Table 11. Prediction of PPIC Conversational Flow Scale Scores……………...……...60

Table 12. Prediction of TIRR Social Communication Rating Form Scores………......61

viii

Table 13. Prediction of AIPSS Overall Sending Scores……………………...………62

Figure 1. PPIC Item Selection Process…………………………………………….....63

COGNITION AND SOCIAL COMMUNICATION IN TBI

1

Chapter 1: Background and Literature Review

Overview of Traumatic Brain Injury

Traumatic brain injury (TBI) is one of the leading causes of disability in the

United States today (Faul, Xu, Wald, & Coronado, 2010). In the year 2000, the estimated

total cost of TBI was $60 billion (Finklestein et al., 2006), and there are approximately

1.7 million reported TBI’s annually (Faul et al., 2010). TBI is defined as injury to the

brain due to an external mechanical force, and common causes include motor vehicle

collisions (MVCs), falls, and assaults (Faul et al., 2010).

Each TBI is different due to a variety of factors (e.g., magnitude and direction of

forces, composition of object impacted). In a closed traumatic brain injury, the brain is

damaged through an external mechanical force but the brain and meninges are not

penetrated by skull fragments or external objects (Lezak, Howieson, Bigler, & Tranel,

2012). Certain brain regions are especially susceptible to TBI. In particular, the frontal

and temporal lobes are often damaged due to the boney ridges that protrude from the base

of the skull and the brain’s tendency to scrape and tear against these during rapid

deceleration and frontal impact (Fork et al., 2005). Diffuse axonal injury (DAI) is also

common following closed TBI, especially when the injury is sustained at high velocities

(i.e. in motor vehicle collisions) (Levine et al., 2008). In such cases, DAI occurs from

rotational acceleration/deceleration forces which cause tearing and shearing of axons

which comprise the sub-cortical white matter (Sidaros et al., 2008). Not surprisingly,

many of the cognitive and behavioral impairments typically seen in closed TBI patients

are correlated with these pathologies.


2

Injury Severity

One heavily researched topic within traumatic brain injury involves the

classification, application, and impact of initial injury severity. While the methods used

to define injury severity vary widely in the research literature, the most commonly used

variables include Glasgow Coma Scale score (GCS, Teasdale & Jennett, 1974), length of

coma (LOC), duration of post-traumatic amnesia (PTA), pupillary response, and presence

and severity of intracranial abnormalities detected by CT scans (Sherer et al., 2008).

While some classification schemes differ, head injury severity is generally categorized as

mild, complicated mild, moderate, and severe (Van Baalen et al., 2003). Severe TBI is

thought to account for approximately 10% of documented TBIs, while moderate and

complicated mild injuries account for an additional 10%, and mild injuries account for

the remaining 80% of documented injuries (Bruns & Hauser, 2003). It is noted, however,

that estimating the prevalence of mild head injuries is difficult, as many of these

individuals never seek medical treatment (Langlois, Rutland-Brown, & Wald, 2006).

When determining injury severity using the GCS, researchers and clinicians

typically define severe TBI as a GCS score of 3-8, moderate TBI as 9-12, and

mild/complicated mild TBI as 13-15 (Rimel et al., 1982) although this subdivision is

somewhat artificial and can result in misclassification of patients in terms of their clinical

characteristics (Maas et al., 2012; Sherer et al., 2008). Currently, inconsistency exists

regarding which GCS score for a given patient defines their injury severity (American

Academy of Neurological Surgeons, 2000). The most commonly used GCS scores are the

ER admission GCS, the worst GCS during the 24 hours following injury, and the best

GCS during the 24 hours following injury (Sherer et al., 2008). Each of these methods


3

has limitations and can lead to over- or underestimations of injury severity (Lezak et al.,

2012; Sherer et al., 2008).

Duration of post-traumatic amnesia (PTA) is another injury severity indicator that

is commonly used. Most researchers define PTA duration as the length of time between

when a patient can consistently follow commands and when the patient shows consistent

orientation and reliable formation of new episodic memories (Sherer et al., 2008). Of

course, when PTA ends and more permanent memory loss begins is not always easy to

determine (Wilson et al., 1999).

PTA duration has been linked to functional outcome in the TBI population and

has utility as a reliable prognostic indicator (Walker et al., 2008). According to a

commonly used schema developed by Russell and Smith (1961), PTA duration of less

than 1 hour is indicative of mild TBI, 1-24 hours is considered to be a moderate TBI, 1-7

days represents a severe TBI, and PTA duration of greater than 7 days is considered a

very severe TBI. More recent research lends support to a different PTA classification

scheme known as the Mississippi PTA Intervals (Nakase-Richardson et al., 2009). Under

this classification scheme, PTA duration of 0-14 days is considered to be a moderate TBI,

15-28 days is considered to be a moderate severe injury, 29-70 days is considered to be a

severe injury, and PTA duration of greater than 70 days is considered to be extremely

severe (Nakase-Richardson et al., 2009). While research has shown that PTA duration is

significantly correlated with initial GCS score, disparity between these two severity

variables exists (Sherer et al., 2008). The GCS is useful in predicting morbidity and

mortality during the acute phase of TBI (Sherer et al., 2008), whereas PTA duration is

more useful as a severity indicator for later outcome (Walker et al., 2010).


4

Cognitive and Behavioral Changes Following TBI

There are several common cognitive and behavioral problems that many

individuals face after TBI, and not surprisingly these tend to correspond to the areas of

the brain discussed above. Deficits in executive function, memory, word finding,

attention, and processing speed are all common following TBI (Rios et al., 2004;

Spikman, Deelman, & van Zomeran, 2000; Spikman et al. 2012).

Deficits in attention and cognitive processing speed are some of the most

consistently documented impairments following TBI. As previously mentioned, many

TBIs result in DAI, particularly when the injury involves the rapid

acceleration/deceleration forces often present in motor-vehicle accidents. DAI has been

associated with deficits in attention and processing speed, likely due to the disruption of

connections between different brain regions (Bonnelle et al., 2011; Felmingham,

Baguley, & Green, 2004; Scheid et al., 2006). These deficits in attention and cognitive

processing speed are associated with poorer functional outcome (Ponsford, Draper, &

Schonberger, 2008; Spitz et al., 2012).

Many TBI patients also experience memory impairments as well, which can affect

the acquisition as well as the retrieval of information (Dikmen, Machamer, and Temkin,

2009). These impairments have been associated with damage to the temporal lobes,

which are vulnerable during TBI (Lezak et al., 2012). Poor performance on measures of

memory has been associated with poor functional outcome, particularly regarding return


5

to productivity (Boake et al., 2001), whereas intact performance on memory measures is

associated with an increased likelihood of returning to work (Hanlon et al., 1999).

Language deficits in individuals with TBI may vary due to the locations and

severity of the injury. While aphasic syndromes are rare in TBI, these patients often

exhibit difficulties in word-finding and naming (Levin, 1991). Impaired verbal fluency is

also common (Ponsford, Draper, & Schonberger, 2008). It is important to note that these

language disturbances are distinct from communication skills, which requires the

individual to use language effectively for different purposes depending on the nature of a

conversational exchange (Prigatano, Roueche, & Fordyce, 1985). This distinction will be

discussed in greater detail elsewhere.

Executive dysfunction is one of the most common and debilitating cognitive

impairments frequently present following TBI (Spikman, Deelman, & Zomeren, 2000).

As mentioned previously, the pre-frontal cortex and white matter connections are

particularly vulnerable to TBI, and damage to these structures is associated with

executive dysfunction (Spikman et al., 2000). Rather than a discrete cognitive process,

executive functioning is an umbrella term that includes planning and organization,

problem solving, initiation of goal-directed activity, impulse control, working memory,

self-awareness, and emotion regulation (Lezak, 1982). Deficits in these abilities are

associated with a number of poor outcomes, including decreases in productive activity

and impairments in social functioning (Boake et al., 2001; Spikman et al., 2000; Struchen

et al., 2008).


6

Behavioral issues may include irritability, personality change, and disinhibition

(Spikman et al., 2012; Warriner, Rourke, Velikonja, & Metham, 2003). Not surprisingly,

these issues are thought to contribute to a variety of difficulties for an individual who has

sustained a TBI, including impaired social functioning.

Social Functioning and Social Cognition in TBI

Evidence suggests that individuals who have sustained traumatic brain injuries

experience an increased degree of social isolation and impaired social functioning

following injury (Hoofien et al., 2001; Marsh, Kersel, Havill, & Sleigh, 2002). This can

have an adverse impact on a person’s subjective experience of quality of life, their

productivity during and after recovery, and the amount of strain or burden placed upon

caregivers (Marsh et al., 2002). There are a number of factors thought to contribute to

and exacerbate social functioning impairments following TBI. Cognitive impairments

and behavioral changes following injury are thought to impact an individual’s ability to

function effectively in social situations negatively (Spikman et al., 2012). In addition to

the cognitive problems that have already been discussed, more recent research has begun

to examine the role of social cognition in effective social functioning. Social cognition

refers to “the mental operations that underlie social interactions, including perceiving,

interpreting, and generating responses to the intentions, dispositions, and behavior of

others” (Green et al., 2008 p. 1211). Recent research points to the existence of two

related social cognitive systems in the human brain (Frith & Frith, 2010). “Cold” social

cognition refers to the mentalizing abilities necessary for theory of mind (Adolphs, 2010;

McDonald, 2013). Theory of mind refers to the ability to infer the mental states of others

and then make predictions about their behavior (Bibby & McDonald, 2005). “Hot” social


7

cognition refers to the ability to understand the mood states of others and empathize with

them (Adolphs, 2010, McDonald, 2013;).

Not surprisingly, it has been discovered that an individual’s social cognitive

functioning has an impact on their ability to effectively function in social situations

(Couture, Penn, & Roberts, 2006; Struchen et al., 2008). In fact, there is research

indicating that social cognition has a greater impact on social functioning and social

communication than does “neuro-cognition” (i.e. memory, language, attention, executive

functioning, etc) in individuals with schizophrenia, (Penn, Spaulding, Reed, & Sullivan,

1996; Pinkham & Penn, 2006; Roncone et al., 2002), and this finding appears to be

supported in the TBI population as well (Struchen et al., 2008).

In recent years, social cognition (particularly facial emotion recognition and

theory of mind) has become a subject of interest among TBI researchers. Facial emotion

perception is the ability to accurately infer the mood state of others based on affective

facial cues (Bornhofen & McDonald, 2008). Studies have consistently documented

impaired performance on measures of emotion recognition (Henry et al., 2006; Ietswaart

et al., 2008; Spikman et al., 2012) and theory of mind (Henry et al., 2006; Muller et al.,

2010; Spikman et al., 2012) in patients with moderate and severe traumatic brain injury

relative to control subjects. Moreover, these deficits are enduring, and have been

observed in moderate and severe TBI patients both soon after injury and up to a year

post-injury (Ietswaart et al., 2008). Research indicates that a collection of brain

structures forms a social cognitive circuit, which is involved in various aspects of

processing social situations and cues; this circuit includes the amygdale, fusiform gyrus,

superior temporal sulcus, and prefrontal cortices (Pinkham et al., 2003). Given the


8

pervasiveness of frontal lesions and axonal injury in moderate and severe TBI, it is no

surprise that deficits in social cognitive abilities are also observed in these individuals.

Research has also directly examined severity of social cognitive deficits and presence of

pre-frontal lesions, and it was observed that impairments in facial emotion recognition in

particular were associated with pre-frontal lesions, though the authors do note that this

effect was somewhat accounted for by injury severity (Spikman et al., 2012).

Impairments in social cognition following TBI have been linked to worse social

(Bornhofen & McDonald, 2008; Struchen et al., 2008) and occupational (Struchen et al.,

2008) functioning.

Relationship between Social Cognition and other Cognitive Domains in TBI

A number of studies have focused on the relationship between social cognitive

deficits and other, more general cognitive deficits following TBI. The results of these

studies indicate that social cognition is distinct from other cognitive domains impacted by

TBI (McDonald 2013; Spikman et al., 2012). However, the two are related, and cognitive

deficits can have an impact on social cognitive processes. Specifically, performance on

measures of verbal and non-verbal memory, working memory, attention, and processing

speed predict facial affect recognition ability in patients with TBI (Yim et al., 2013).

Furthermore, impairments in executive functioning have been associated with theory of

mind deficits in patients with TBI (Dennis et al., 2009; Henry et al., 2006).

Social Communication in TBI

Related to the study of social cognition in TBI is the investigation of social

communication following TBI. Social communication abilities can be defined as “both

verbal and nonverbal skills that allow one to be able to understand others and what others


9

mean to communicate, as well as to express oneself to others in a manner that conveys

the intended meaning” (Struchen et al., 2011).

According to an information processing model advocated by Richard McFall

(1982), social communication can be divided into three distinct stages. The first is the

decoding stage, during which the conversational participant receives, perceives, and

interprets a message. Receiving involves the actual detection of the incoming information

via the appropriate sensory modality (i.e. hearing or sight). Perceiving entails

transforming the raw sensory data into information that can be stored in short term

memory for use by the individual. McFall notes that a breakdown in perceiving could be

the result of inattention or distractibility, two problems commonly experienced in

individuals with TBI. Interpretation requires the individual to judge and apply meaning to

the message received given the current context. Within the framework of McFall’s

model, social cognitive abilities such as emotion perception and theory of mind take

place primarily at the level of interpretation.

The second stage of McFall’s model is the decision stage. During this stage of

communication, the individual who has received a message must generate adequate

responses, test those responses against the demands of the conversational context and

environment, select the most appropriate response, and evaluate the risks and utility of

giving the selected response. McFall posits that deficits in this set of skills may result in

suboptimal social communication, which could range from impulsive behavior to overly

conservative or restricted behavior.


10

The final stage of McFall’s model is the encoding stage, which include the skills

of execution and self-monitoring. Execution involves an individual’s ability to effectively

translate his/her selected response into action to emit the intended message. Self-

monitoring refers to the individual’s ability to monitor any discrepancies between the

intent of the message and the actual impact of the message, and make behavioral

adjustments accordingly. Poor execution may manifest itself as unintentionally

ambiguous or confusing verbal or non-verbal behaviors that confound the intended

message, while poor self-monitoring may result in an individual not realizing that a

message was rude or inappropriate in the conversational context.

Effective use of these social communication skills is often impaired following

TBI, even in the absence of aphasia or other specific language disturbances (Soulberg &

Mateer, 1988; Struchen et al., 2011). Two specific areas within social communication

that have received attention are discourse analysis and social pragmatics. Discourse refers

to the syntactical and linguistic characteristics of sent messages during a conversation

(Coelho, 1999). Discourse types may include descriptive, narrative, procedural,

persuasive, expository, and conversational discourse (Coelho, 1999). These

characteristics can be quantified and examined in various ways through the process

known as discourse analysis. Common discourse analysis methods include

microlinguistic analyses (phonologic and/or lexical production, syntax), macrolinguistic

analyses (cohesion, story structure, and coherence), and miscellaneous analyses

(productivity, rating scales, response appropriateness/relevance, compensatory strategies,

analysis of topic, and content analysis) (Coelho, 1999). Numerous discourse deficits are

routinely observed following TBI. Specifically, impairments in discourse production,


11

cohesion, story structure, and coherence have been observed (Coelho, 1999). Some

researchers have suggested that these deficits, particularly in cohesion and story structure,

are related to executive dysfunction (Coelho, 1999; Coelho, Liles, & Duffy, 1995;

Ylvisaker & Szekeres, 1989).

In addition to discourse deficits, impairments in social pragmatics are common

following TBI. In the context of social communication and TBI, many researchers have

used the term to refer to the employment of communication skills which supersede basic

linguistic abilities (Perkins, Body, & Parker, 1995), or the use of basic linguistic abilities

and other communication behaviors in interpersonal interactions (Milton, Prutting, &

Binder, 1984). Impairments in these social communication abilities may lead to

inadequate contribution to conversation, difficulties in topic maintenance, or being

tangential, inappropriate, or over-talkative (Struchen et al., 2011). Not surprisingly,

researchers have demonstrated associations between executive functioning, social

communication abilities, and social functioning outcomes (Struchen et al., 2008). Studies

of social pragmatics in the TBI population generally attempt to quantify the use and

misuse of certain communication behaviors during interpersonal interactions using rating

scales for various communication behaviors or self-report measures of interpersonal

communication style and effectiveness (Body, Perkins, & McDonald, 1999).

One such self-report measure of interpersonal communication effectiveness is the

La Trobe Communication Questionnaire (LCQ; Douglas, O’Flaherty, & Snow, 2000).

The LCQ was originally developed to measure perceived communication difficulties in

adults following TBI. Thirty items were developed following Damico’s analysis of

discourse categories (Damico, 1985) and Grice’s theory of conversational maxims (Grice,


12

1975). A recent study by Struchen et al. (2008) further examined the LCQ using principal

components analysis. Results of these analyses yielded 4 factors comprised of 27 of the

30 LCQ items, which the researchers labeled Initiation/Conversational Flow,

Disinhibition/Impulsivity, Conversational Effectiveness, and Partner Sensitivity

(Struchen et al., 2008). LCQ scores have been found to be predictive of social integration

outcomes following TBI (Struchen et al., 2011).

In addition to self-report measures of communication effectiveness, measures of

researcher/clinician rated social communication have been created and utilized. The use

of these measures provides researchers and clinicians with a standardized tool that can be

used to more directly observe impairments in social pragmatics following TBI. One such

rating scale is the Profile of Pragmatic Impairment in Communication.

The Profile of Pragmatic Impairment in Communication

The Profile of Pragmatic Impairment in Communication (PPIC), formerly known

as the Profile of Functional Impairment in Communication (PFIC; Linscott, Knight, &

Godfrey, 1996) is a standardized rating form that was created to assess communication

difficulties during an unstructured discourse sample in individuals who had sustained a

traumatic brain injury. The measure consists of 84 individual behavioral items assessing

various aspects of social communication, and these items were grouped into 10 “feature

summary scales” (Linscott et al., 1996). These scales are logical content, general

participation, quantity, quality, internal relation, external relation, clarity of expression,

social style, subject matter, and aesthetics.


13

When initially designing the measure, the creators of the PPIC examined common

communication difficulties following TBI reported in the literature and formulated the 84

individual behavioral items to capture these impairments (Linscott et al., 1996). Then, the

behavioral items were organized into feature summary scales based on Grice’s model of

communication theory (Grice, 1975). Grice’s model posits that there are four maxims of

conversation that must be followed for successful communication. These maxims are

quantity, quality, relevance, and manner (Grice, 1975). A summary of Grice’s maxims is

provided by Body, Perkins, and McDonald (1999, p 83-84). The maxim of quantity states

that conversational participants say no more or no less than is needed to effectively

communicate their intended message. The maxim of quality states that conversational

participants should not say anything that they believe is false or for which they lack

supporting evidence. The maxim of relevance states that a conversational participant’s

comments should be relevant to the topic at hand. The maxim of manner states that

conversational participants should be concise and organized in their communication

without being obscure or ambiguous. The authors of the PPIC elaborated on Grice’s

model to include pragmatic aspects of communication not directly addressed in the

model, such as aesthetics (i.e. pauses, gestures, volume) and subject matter (i.e.

appropriateness of the topic for the conversation) (Linscott et al., 1996).

The rater watches a videotaped 10-15 minute session of the participant having an

unstructured conversation with a research confederate and scores each behavioral item

within a feature summary scale on a 4-point Likert scale ranging from 0 (not at all) to 3

(nearly always or always). Using the ratings on the behavioral items within each feature

summary scale as a guide, the rater then ranks the participant’s overall proficiency in that


14

domain of communication on a 6-point Likert scale ranging from normal (0) to very

severely impaired (6). This overall proficiency rating is the feature summary scale score,

regardless of ratings of individual behavioral items within the scale.

In the original PPIC study, 20 participants were selected from a larger TBI sample

based on their perceived level of social communication proficiency. The researchers

selected 10 participants whom they subjectively rated as having the greatest social

communication impairments and 10 participants rated as having the least social

communication impairments. All participants had sustained a severe TBI as defined by a

period of PTA lasting between 24 hours and 10 weeks. The researchers then trained 8

raters to use the PPIC who were blinded to the original ratings of the participants’ social

skill proficiency. After rating each 15 minute conversation with the PFIC, the raters were

given a short survey designed to assess the face validity of the measure. Analysis of the

data revealed a significant effect of group (TBI patients previously rated as most vs least

impaired) and rater, though the researchers reported no group X rater interaction

(Linscott et al., 1996). The high-skill TBI group performed significantly better across

most PPIC summary scales than did the low-skill TBI group.

The reliability of the PPIC was examined by calculating intra-class correlation

coefficients within raters (0.43 to 0.64), between two raters (0.75-0.88), and across all

eight raters (0.86 to 0.94), and the authors concluded that the feature summary scales

demonstrated good inter-rater reliability. Statistical significance for these coefficients

was not reported in this study. In order to examine concurrent validity, the examined

associations between group membership and feature summary scale scores. All feature

summary scale scores were significantly correlated with group membership as were


15

logical content, general participation, and external relation scores (r > .94, p < 0.05)

(Linscott et al., 1996). Based on the results of surveys taken by the raters, the authors

concluded that the PPIC exhibited strong face validity, as it was rated as a good measure

of communication, practical, and comprehensive by the 8 raters.

Since its development, the PPIC has been used in a small number of TBI and

social communication studies. Godfrey et al. (2000) used the PPIC in a small pediatric

TBI population to examine the utility of the PPIC in characterizing social communication

impairments exhibited during a family problem solving discussion in a pediatric sample.

When comparing the performance of the TBI participants on the PPIC to performance of

11 matched orthopedic control participants, the TBI group performed significantly worse

on the quality, internal relation, clarity of expression, social style, subject matter, and

aesthetics feature summary scale scores (Godfrey et al., 2000). Furthermore, performance

was correlated with injury severity (determined using PTA duration) for all feature

summary scale scores except quantity. It is important to note, however, that the

conversational sample used to obtain PPIC scores in this study was based on a family

problem-solving discussion rather than an unstructured conversation. As the PPIC was

initially created and developed using unstructured conversational samples, the use of a

different conversational paradigm in this study may limit the generalizability of the

findings to other studies using the PPIC.

Dahlberg et al. (2006) conducted a study on social communication impairments in

TBI in which they utilized the PPIC as a clinician-rated estimate of participants’ social

communication ability, and compared this to the participants’ or their significant others’

estimate of the participants’ social communication ability. The researchers identified 7


16

behavioral items for which the TBI participants’ mean score was 1.5 or higher,

interpreted as being indicative of at least occasional difficulty in that area (Dahlberg et

al., 2006). These behavioral items were as follows: asks questions, perceives

misinterpretation of meaning, uses questions well, skilled at taking turns, integrates own

ideas with other’s ideas, contributes equally to the conversation, and helps direct the

conversation. When examining TBI participants’ performance on feature summary

scales, participant scores were mildly impaired on the social style, aesthetics, internal

relation, and external relation scales. Participant scores for the general participation

summary scale fell within the moderately impaired range (Dahlberg et al., 2006).

The PPIC has also been used as a primary outcome measure in several clinical

trials. Dahlberg et al. (2007) conducted a randomized clinical trial focused on

improvement of social communication skills following TBI. Participants in the treatment

group showed significant treatment effects on 7 of the 10 PPIC summary scales when

compared to the deferred treatment group. In a similar study, Braden et al. (2010) found

that PPIC summary scores showed a trend towards improvement over time following

treatment. The PPIC has also been used in other clinical trials aimed at remediation of

social communication skills (Struchen et al., in preparation), though in contrast to the

previously mentioned studies no significant improvement was observed in global PPIC

scores.

The PPIC’s creation was theory driven, based on the Grice models of

communication. Items were included to assess all possible communication difficulties

that may be encountered after TBI according to this model. There are no published

studies known to this author which involve a factor analysis of the PPIC items to


17

determine whether the theoretically derived structure of the measure (i.e. the 10 feature

summary scales) is empirically supported. And, many of the PPIC’s behavioral items

occur with low frequency in the broader TBI population and may or may not be

discriminative or helpful in terms of an evaluation that leads to useful recommendations

for rehabilitation. Despite these limitations, the PPIC has been adopted for use in several

clinical trials targeting remediation of social communication skills in TBI patients due to

the lack of other suitable published measures. The absence from the literature of other

tools for clinician-rated measurement of social pragmatic communication skills highlights

the need for further development of the PPIC.

Present Problem

Further development of the PPIC into a more manageable empirically based

instrument would provide researchers and clinicians with a structured, practical tool for

the assessment of important social communication difficulties after TBI. Also,

development of an outcome measure that is more parsimonious increases the number of

statistical analyses that can be performed with the limited sample sizes that are often

typical of TBI outcome research. A streamlined measure also may enable further

exploration of the relationships between cognition and social communication. Examining

the cognitive mechanisms that may underlie social communication difficulties further

informs an understanding of abilities that are important for successful conversational

interaction and may yield viable targets for intervention and development of possible

compensatory strategies in future research.

Development of the PPIC presents a number of methodological challenges. First,

in order to conduct a proper factor analysis of the PPIC items and investigate whether the


18

theoretical structure designed by the original researchers is empirically supported, an

extremely large sample would be needed (between 420 and 840 participants to maintain

the conventional guideline of 5-10 participants per variable). Furthermore, there is no

accepted “gold standard” measure known to the author at this time for the measurement

of social pragmatics in an unstructured conversational paradigm. The lack of similar

measures for comparison makes establishing the validity of the PPIC difficult. Given

these methodological challenges and the current sample of 204 participants, it was

decided that the author would select items most characteristic of social communication

problems following TBI. Review of the relevant literature, group discussion with experts

in measure development and TBI research, and the author’s own clinical and research

experience with TBI patients were used to guide the item selection process.

Hypotheses of the Current Study

Specific aim 1. The first aim of the current study was to examine the reliability,

validity, and factor structure of the twenty behavioral items from the PPIC that were

selected by the author as most characteristic of social communication problems after TBI

through exploratory factor analysis. An exploratory factor analysis of these twenty items

was conducted. Based on results of the exploratory factor analysis, other specific

hypotheses about the relationships between performance on cognitive measures and new

factor scores of the PPIC were created and then tested. Analyses designed to establish

preliminary evidence for criterion-related and construct validity of the revised PPIC were

also conducted.

Hypothesis 1a. The hypothesized factor structure for the revised PPIC is presented

in Table 1. It was predicted that the resulting factors would represent different aspects of


19

social communication as measured by the PPIC, but that they would be modestly

correlated with one another due to the expected relatedness of different aspects of social

communication.

Hypothesis 1b. In order to provide preliminary evidence of criterion-related

concurrent validity for the PPIC revisions, the newly developed factor structure was

compared to social functioning outcome measures, as previous research has provided

evidence of a relationship between social communication and social functioning

outcomes. It was predicted that the factor scores of the revised PPIC would be correlated

significantly with measures of social functioning and community integration.

Hypothesis 1c. In order to provide preliminary evidence of convergent construct

validity for the PPIC revisions, the newly developed factor scores for participants were

compared to established and experimental measures which involve demonstrating social

communication skills.It was hypothesized that the factor scores of the revised PPIC

would be related to these measures, with better performance on the PPIC correlating with

better performance on other measures of social communication.

Specific aim 2. The second aim of the current study was to examine the

relationship between performance on measures of attention/executive functioning and

affect perception and proficiency to social communication.Table 2 contains a summary of

predictor and outcome variables.

Hypotheses 2a-2c. Performance on measures of attention/executive functioning

and social cognition were expected to account for a significant amount of the variance in

performance on social communication measures, above that accounted for by


20

demographic and injury related variables. Specifically, poorer performance on measures

of attention/executive functioning and affect perception would be predictive of worse

social communication. Based on previous research (Struchen et al., 2008), it was

expected that modest to strong relationships between measures of affect perception and

executive functioning would be present. Conceptually, social communication requires an

individual to rapidly alternate between processing incoming messages and formulating

appropriate responses to these messages, which requires accurate perception and

interpretation of the affective and social cues being received as well as some proficiency

in set-switching and multi-tasking. It was therefore anticipated that performance on

measures of mental flexibility and affect perception would make a statistically significant

unique contribution to the explanation of the variance in social communication

performance.

Purpose of the Current Study

The purpose of the current study is to develop the PPIC into a more practical and

parsimonious measure of social communication proficiency for the TBI population.

Doing so not only assists in the investigation of social communication difficulties

following TBI, it facilitates exploration of the neuro- and social-cognitive processes that

underlie these social communication difficulties. The current study investigates the

contributions of select measures of attention, executive functioning, and affect perception

to social communication impairments following TBI.


21

Chapter 2: Methods

Participants & Procedures

Approval for this study was obtained from the Committee for the Protection of

Human Subjects (CPHS) of the Institutional Review Board (IRB) at the University of

Houston. Data for this archival study were collected originally for research grants and

studies at TIRR Memorial Hermann with the approval of and in compliance with

regulations mandated by the CPHS of the IRB at Baylor College of Medicine (BCM).

Permission for the use of these data was obtained from the appropriate investigator in a

letter that supplied the current protocol number(s) from the BCM IRB for the database(s)

storage. Data from 204 participants with TBI were included in the analyses for Specific

Aim 1. Persons with TBI were included from one of two studies: 121 participants who

had been recruited from participants of the local National Institute for Disability and

Rehabilitation Research TBI Model System (NIDRR-TBIMS) sample to participate in a

separate project designed to evaluate social communication assessment measures (SCA

study) and 83 were participants recruited from a randomized clinical trial of a social

communication intervention (IPR study). For Specific Aim 2, only participants from the

SCA study (N=121) were included as the cognitive measures were not administered for

participants in the IPR study.

Persons participating in the SCA study were drawn from the overall sample of

NIDRR-TBIMS participants at the local rehabilitation site in the Southern US. Criteria

for inclusion in the Model Systems study included: diagnosis of TBI resulting in

admission to the emergency department of a Model Systems hospital between 8-24 hours

post-injury; aged > 16 years; acute care and inpatient rehabilitation received within the


22

Model System facilities; residence in a designated catchment area; and provision of

informed consent by the person with injury or a family member.

Participants in the SCA study and/or their family member or legally authorized

representative signed a separate consent form to participate in a study to evaluate social

communication abilities. Additional inclusion criteria for that study restricted participants

to those aged 18 years or older and excluded those with severe communication deficits

(e.g., global aphasia), inability to communicate, prior central nervous system dysfunction

that might impact cognition (e.g., stroke, brain tumor), and severe psychiatric disorder

(e.g., schizophrenia, schizoaffective disorder). Persons with mild language impairments

such as anomia were not excluded from participation, nor were participants with

psychiatric disorders that did not include psychotic features (e.g., major depression,

generalized anxiety disorder, etc.).

For the SCA study participants a testing session was scheduled at the research

facility. During this session, they were administered a series of structured interviews,

self-report questionnaires, measures of executive functioning, and social communication

measures, including the measures used in the current study.

Participants for the IPR study were recruited from the following sources: 1)

individuals with TBI admitted to a comprehensive inpatient brain injury rehabilitation

program in a rehabilitation hospital, 2) individuals with TBI admitted to an inpatient

rehabilitation program within a county hospital setting, and 3) individuals who had

participated in previous research projects who had provided written assent to be contacted

for future research studies. Participants recruited for prior studies were also initially

recruited from consecutive admissions to either a Level 1 trauma center or to an inpatient


23

brain injury rehabilitation program. Given this method of recruitment, there was some

overlap of participants between the SCA study and the IPR study (N = 25 participated in

both studies). For purposes of the this study, if a participant had participated in both

former studies, only data obtained in the SCA study was included in analyses to avoid

oversampling of any given individual participant in proposed analyses.

Inclusion and exclusion criteria for consenting and/or consented participants for

the previous IPR study are presented below. All participants had a traumatic brain injury,

as documented by medical records. Participants were recruited at the time of admission at

the respective rehabilitation sites, or through in-person conversations scheduled after

contacting potential participants by phone or letter. Given that one of the inclusion

criteria was participation in an inpatient rehabilitation program, persons with complicated

mild, moderate, and severe TBI were included in the study, and the majority of patients

sustained more severe injuries that would have warranted admission to an inpatient

rehabilitation program. There were no participants with uncomplicated mild injuries

included in this study. Screening evaluations to establish eligibility criteria for

randomization in the clinical trial were conducted no earlier than 9-months post injury.

Participants had to be > 18 years of age and live within a 100-mile radius of the

research center because of developmental issues impacting socialization and logistical

issues (e.g., transportation) for participants to attend study treatment sessions respectively

would have necessitated a separate methodology for younger individuals. Eligible

participants were also required to be residing in non-institutional settings, because such

settings allow for greater opportunities for social communication in various contexts.

Participants had to be fully oriented and no longer in a post-confusional state after injury,


24

so that they could participate fully in treatment sessions. Evaluation instruments and

treatment were available in the English language only; therefore, participants who were

not fluent in English were excluded from participation in the study. Individuals with other

central nervous system diagnoses or severe psychiatric disorders (e.g., schizophrenia)

were excluded from participation. Additionally, persons with severe expressive and/or

receptive aphasia were excluded from participation, as such severe language difficulties

would limit the individual’s ability to participate in treatment. Although some eligible

participants may have been receiving rehabilitation services at the time of recruitment for

that study (9-months post-injury), such individuals were not excluded from participation

in the clinical trial. However, to ensure that such individuals were equally represented in

both arms of the clinical trial, randomization was conducted within two strata: those

receiving current treatment and those receiving no treatment.

With the IPR study, participants underwent a screening evaluation for the clinical

trial designed to identify individuals who were experiencing difficulties with one or more

communication behaviors. Demographic and injury-related information was also

collected. All participants with TBI meeting screening eligibility criteria that consented to

participate in the treatment study completed a baseline evaluation following the screening

evaluation and prior to randomization to treatment condition. Participants were asked to

complete questionnaires, tests, and interviews, including the measures used in the current

study.

Item Selection Process. Decisions about which items to retain for exploratory

factor analysis were based on review of the relevant literature and consultation with


25

dissertation committee members who are experts in TBI research and measure

development. A summary of the item selection process can be found in Figure 1.

Measures

Demographic, pre-injury characteristics, & injury severity measures.

Participant information about demographics and injury severity was obtained from

patient interview and from the TBI Model Systems database. Data regarding age, sex,

race/ethnicity, years of education, injury severity, and time post-injury at assessment are

reported and were explored for use as covariates in planned analyses.

Neuropsychological measures. Neuropsychological measures of attention and

executive functioning were given to participants in the SCA study, including the Trail

Making Test, Controlled Oral Word Association, the Color-Word Interference subtests of

the Delis-Kaplan Executive Functioning Scale, and the Script Analysis Task. A brief

description of each of these measures follows.

The Trail Making Test (TMT; Army Individual Test Battery, 1944) was administered

as a test of visual attention and executive function. On the first trial (Trails A),

participants are presented with a page that has numbers on it and are instructed to draw a

line connecting the numbers, in sequence, while being timed. On the second trial (Trails

B), the examinee is given a sheet of paper that contains numbers and letters and asked to

draw a line alternating between numbers and letters in sequence while being timed. For

the current study, only the Trails B total time to completion was utilized, as this variable

is known to be sensitive to disruption in TBI patients (Spikman et al., 2000), and is also

predictive of social functioning (Struchen et al., 2008).


26

During the Controlled Oral Word Association (COWA; Multilingual Aphasia

Examination, 1994), participants are presented with a letter of the alphabet (specifically,

letters F, A, and S) and asked to generate as many words as they can during a 60 second

time period. Participants are instructed not to respond with the proper names of people or

places, and are also instructed to not use the same word repeatedly with different endings.

The total number of valid responses that participants gave across the three trials was

utilized for these analyses. Total number of valid responses on the COWA has been

demonstrated to be sensitive to the effects of TBI (Spikman et al., 2000) and may be

related to social communication.

The Color-Word Interference Test of the Delis-Kaplan Executive Functioning Scale

(CWIT; Delis-Kaplan Executive Function Scale (D-KEFS), 2001) was administered as a

test of complex attention and executive function. There are four subtests that comprise

this measure. The third subtest, Inhibition, was selected for use in this study. During this

subtest, the participant is presented with color words that are printed in a different color

ink (i.e. the word RED may be printed in BLUE ink). The participant must name the ink

color and not read the word for each item as quickly as possible. The current study used

the total time to completion for the Inhibition subtest, as this score has been linked to

social and occupational functioning following TBI (Struchen et al., 2008).

The Script Analysis Measure (Sirigu et al., 1995) is an experimental measure

designed to test the participant’s ability to organize and plan out the steps for a complex,

non-routine task without the benefit of externally imposed structure. The examinee is

asked to plan a leisure trip to Mexico and instructed to write down all actions that would

be necessary to complete this task, starting when they began planning the trip and ending


27

when they arrive in Mexico. Following the modified scoring procedure developed by

Struchen et al. (2007), scores derived from this measure include: total number of actions

generated, total time to complete the script generation, total number of errors, key

element errors, early closure errors, late closure errors, and mean importance rating for

key elements. For the current study, the mean key element importance rating score was

utilized, as this variable has been shown to be sensitive to disruption following TBI and is

predictive of social functioning outcomes (Struchen et al., 2007).

Emotion Perception Measures. The emotion perception measures utilized in the

SCA study included selected subtests from the Florida Affect Battery (FAB; Bowers et

al., 1991). For the proposed study, the Facial Affect Matching and Conflicting Emotional

Prosody subtests were selected. The Facial Affect Matching subtest requires the

participant to process the emotion being displayed during each item, and then select a

different face displaying the same emotional expression. The Conflicting Emotional

Prosody subtest requires the participant to correctly identify the emotional prosody of a

voice independent of the speaker’s content. The scores for each subtest are the number of

correct responses. Performance on these subtests has been demonstrated to be predictive

of social and occupational functioning in TBI patients (Struchen et al., 2008).

Social Communication Measures. Social communication measures included the

Profile of Pragmatic Impairment in Communication, the TIRR TBI Social

Communication Rating Form, and the Assessment of Interpersonal Problem Solving

Skills. Information on the basic structure and construction of the Profile of Pragmatic

Impairment in Communication (Linscott, Knight, & Godfrey, 1996) is discussed in detail

in chapter 1. For the current study, the PPIC was used to rate an unstructured


28

conversation between a research confederate and a participant. Research confederates

were provided with minimal instruction, and were told to converse with participants as

though they were meeting them for the first time (which they usually were) in a

community setting. Research confederates introduced the task to participants as a “getting

to know you” conversation, telling participants that they would find out information

about the participant, and that the participant should find out some information about

them. The 10-15 minute conversation that followed was video recorded and reviewed by

raters using the PPIC at a later date.

The TIRR Social Communication Rating Form was originally designed as an attempt

to simplify the measurement of communication difficulties in TBI patients during a

conversational discourse sample. It consists of 17 behavioral items, and it includes items

such as “Transitions between conversation topics made by the individual were smooth,”

and “Conversational topics were appropriate given the context.” A complete copy of the

measure can be found in Appendix C. Each item is rated by a trained researcher after

watching a video-taped unstructured conversation between a participant and research

confederate using a 5-point Likert scale ranging from 0 (not applicable, opportunity not

present) to 4 (Most of the time or always). Three of the items are reverse coded. The

researcher also rates the participants overall appropriateness of social communication

skills using the same 5-point Likert scale. The mean of the 17 behavioral items is then

calculated to create the Total Average Item Score, with higher scores indicating greater

social communication skill. This measure was initially created as a more parsimonious

and user-friendly alternative to the PPIC. However, it has not yet been empirically


29

validated, and was included in this study as a preliminary attempt to investigate its utility

as a measure of post-TBI communication impairments.

The Assessment of Interpersonal Problem Solving Skills (AIPSS; Donahoe et al.,

1990) is a measure which involves showing the participant a videotaped vignette of

actors involved in either neutral or problematic social situations. The participant must

determine whether or not the scene depicts a problematic social situation (Identification

Score, 0-1 points), and if so describe the problem involved (Description Score, 0-2

points). The participant is asked to describe how they would respond in the depicted

situation (Processing Score, 0-2 points). The participant is then asked to role-play the

delivery of a response as the primary character in the vignette (Sending Skills) The

participant’s performance is scored separately for the verbal content (Content Score, 0-2)

of their response (disregarding any non-verbal or para-verbal behaviors) and their non-

verbal or para-verbal behaviors (Performance Score, 0-2 points) . The participant also

receives an Overall Sending Score, which takes into account the overall effectiveness of

the content of their message and their non-verbal/para-verbal behaviors. A copy of these

scoring guidelines is included in Appendix C. The current study utilized the participant’s

Overall Sending Score, which involves rating linguistic and para-linguistic aspects of the

participant’s response based on whether it was likely to achieve the desired outcome and

the extent to which the response was appropriate to context and presented in a polished

manner. There are five possible scores that can be obtained for the Overall Sending

Score, ranging from 0 to 2 points. Higher scores are indicative of more appropriate and

effective responses. The AIPSS overall sending score was included to measure another

aspect of the participant’s expressive communication ability.


30

Statistical Analyses

Specific aim 1.

Hypothesis 1a. An exploratory factor analysis was conducted on the 20 selected

PPIC items using the principal axis factoring technique in SPSS(24). Prior to conducting

factor analysis, the suitability of the data for factor analysis was assessed. A correlation

matrix containing each of the 20 selected items from the PPIC was created and inspected.

The Kaiser-Meyer-Olkin value was also calculated in order to examine the level of

diffusion or compactness in the pattern of correlations between items. Following

guidelines established by Kaiser (1974), a KMO value below 0.5 indicates a high level of

diffusion in the pattern of correlations, and would result in a re-examination of items to

be included in the factor analysis. Following guidelines set by Hutcheson & Sofroniou

(1999), KMO values between 0.5 and 0.7 were considered mediocre, values between 0.7

and 0.8 were considered to be good, values between 0.8 and 0.9 were considered to be

excellent, and values greater than 0.9 were considered to be superb. The Bartlett’s Test of

Sphericity was also conducted in order to determine whether the correlation matrix was

significantly different from an identity matrix. If the Bartlett’s Test of Sphericity reaches

statistical significance, this would provide further support for the factorability of the

correlation matrix. There are theoretical grounds suggesting that the factors comprised of

the 20 items are significantly correlated, so oblique rotation using the promax method in

SPSS was utilized for this analysis. The decision of how many factors to retain was based

on the number of factors with eigenvalues greater than one and examination of the

resultant scree plot. The resultant factors were then examined for internal consistency by


31

calculating Cronbach’s α for each factor. Values of 0.7 or greater were considered to

show adequate internal consistency for each factor.

Hypothesis 1b. Bivariate correlation coefficients were calculated between each

factor of the revised PPIC and CHART-SF Occupation subscale scores and CHART-SF

Social Integration subscale scores.

Hypothesis 1c. Bivariate correlation coefficients were calculated between each

factor of the revised PPIC,the TIRR Social Communication Rating Form total average

score, and AIPSS Overall Sending scores.

Specific Aim 2.

Hypotheses 2a-2c. ANCOVA models using hierarchical linear regression analyses

were created and tested for each of the four social communication measures. Given the

exploratory nature of this study, the decision was made to utilize an alpha level of .05

without correcting for multiple comparisons. The forced entry method was utilized for

each step in the analyses, and the variables in each step were selected based on theoretical

importance and results of previous research investigating cognition, social

communication, and social functioning in TBI patients (Struchen et al., 2008). Prior to

running these analyses, several assumptions of multiple linear regression were assessed.

The assumptions of multivariate normality were tested using the K-S test on the

standardized residuals to test whether they deviated significantly from normality. The

assumption of homoscedasticity was checked by inspecting a plot of residuals against

predictor variables. The assumption of independent errors was tested using the Durbin-

Watson test to test for serial correlations between errors.


32

During each analysis, demographic variables (age and years of education) were

entered as the first group, followed by the injury-related variables (months post-injury

and ER GCS scores) as the second group, followed by the cognitive variables (TMT-B

time to completion, CWIT (Inhibition) time to completion, COWA total score, SAM

mean key element importance ratings, FAB Matching Facial Affect, and FAB Conflicting

Emotional Prosody) as the final group for predicting social communication performance.

It was anticipated that performance on TMT-B and FAB Matching Facial Affect would

emerge as significant individual predictors of performance on social communication

measures. These abilities are theoretically important for the social communication

process, and prior research has shown that both are sensitive to disruption after TBI

(Spikman et al., 2012; Struchen et al., 2008).

The degree of R2 change during each step of the regression was examined for

significance, and any variables that emerged as significant individual predictors were also

examined. The regression model was assessed for signs of collinearity by examining

variance inflation factors (VIFs), tolerances, and condition indexes. VIFs of 4 or greater

and tolerances of less than 0.2 were considered to be an indication of higher order

collinearity. Condition index values were also examined. Any value of 30 or greater was

considered to be indicative of possible multicollinearity. Furthermore, if two or more

variables related to a higher confidence index have high portions of variance explained,

concern was raised for multicollinearity among those variables.


33

Chapter 3: Results

Sample Characteristics

Demographic and injury-related characteristics of the two samples (SCA

participants and IPR participants) are presented in Table 3. The majority of sample

participants were men, as is often the case in TBI research studies (Langlois et al., 2006).

Comparisons of demographic characteristics between the two study samples were made

using independent t-tests and chi-square tests. There were significant differences in the

proportions of ethnicities represented in each sample (specifically for white, black, and

Hispanic/Latino participants) [χ2 (2) = 15.82; p < .01]. The IPR study sample contained a

greater proportion of black and Hispanic/Latino participants compared to the SCA study

sample. This was likely due to the inclusion of a county-funded inpatient rehabilitation

facility with a more ethnically diverse patient population as a recruitment site for the IPR

study. There were also statistically significant differences in the number of months post-

injury between SCA and IPR participants [t (208) = 5.00, p < .01], with fewer months

since the injury for the IPR group. This difference in time since injury was the result of

inherent differences in study design and recruitment procedures between the SCA and

IPR studies. The two study samples were comparable with respect to gender proportions

and proportions of closed vs. penetrating injuries, as well as in mean age, mean years of

education, and mean ER GCS scores. Based on ER-GCS scores, the majority of

participants (71.5%) sustained a severe TBI, and the vast majority of participants (94.5%)

sustained a non-penetrating (i.e., closed) TBI.

Specific Aim 1: PPIC Development


34

The 20 selected items from the PPIC were assessed for normality assumptions.

All of the item distributions were noted to be significantly non-normal based on

significance of the K-S statistic (p < .01) and examination of skewness, kurtosis, and

histograms. Most items were mildly to severely positively skewed. These items were

transformed to reduce skewness by taking the log of the raw scores. Following

transformation all PPIC item distributions remained significantly non-normal, so factor

analysis was conducted using the original item raw scores.

Data were missing for items 13 (3 cases), 14 (1 case) and 8 (59 cases). Many of

the missing values for item 8 (‘Perceived other’s misinterpretation of meaning’) resulted

from raters marking ‘not applicable’ for this item. Such ratings indicate that there was no

opportunity present for evaluating the participant’s perception of misunderstanding, most

likely because such misunderstandings are less likely to occur during such a short

conversational sample. Given the large amount of missing data for item 8, it was

excluded from all further analyses. The vast majority of data for items 13 and 14 were

present, and these items were therefore not excluded from further analyses.

The suitability of data for factor analysis was assessed. The Kaiser-Meyer-Olkin

value was .86, exceeding the recommended minimum value of .60 (Tabachnick & Fidell,

2001). The Bartlett’s Test of Sphericity was significant (p < .001), supporting the

factorability of the correlation matrix. The correlation matrix for the remaining 19 PPIC

items can be found in Table 4. Visual inspection of the initial correlation matrix was

notable for multiple high correlations (r > .80), and the determinant of the correlation

matrix was substantially lower than the conventional cut-off value of .00001 (Field,

2009). These findings were indicative of multicollinearity within the correlation matrix.


35

Following an iterative process, the variables considered most likely to be contributing to

multicollinearity were systematically eliminated from the analysis. Through this

procedure, it was determined that items 4 (Contributes spontaneously to the

conversation), 12 (Elaborates spontaneously), and 14 (Integrates own ideas with other’s

ideas) were overly redundant with other items, and these were excluded from further

analyses. Upon examination of the anti-image matrix, item 7 (provides excessive detail)

was noted to have an unacceptably low individual KMO value (< .5), and it was excluded

from further analyses.

The remaining 15 items were subjected to principal axis factoring using

orthogonal varimax rotation. Comparison of results utilizing the transformed and raw

scores revealed very similar factor structures. Therefore, only the analysis of the raw

scores is reported in order to facilitate interpretation. The Kaiser-Guttman criterion of

eigenvalue greater than 1.00 was initially used to determine how many factors to extract.

Using this criteria and examination of the scree plot, two, three, and four-factor solutions

were obtained. Item 20 was found to have no loadings of .3 or greater on any factor, and

it was excluded from further analyses. The four-factor solution produced a poorly defined

loading matrix. Furthermore, examination of the scree plot indicated that two or three-

factor solutions were a better fit for the data. When the extraction of three factors was

specified, a relatively clean loading matrix was produced. However, items 11 and 17

were found to have no loadings of .3 or greater on any of the three factors and were

discarded from the analysis. Principal axis factoring with varimax rotation specifying the

extraction of 3 factors was conducted on the remaining 12 items, producing a clean factor

structure after rotation (Table 5). It was noted, however, that communalities for all three


36

items within the third factor were relatively low compared to communalities of items in

the first two factors.

Reliability analysis was conducted for the items within each factor. The corrected

item-total correlations were all positive and ranged from .22 to .86. The coefficient alphas

for the first, second, and third factors were .93, .73, and .42, respectively, while the

coefficient alpha for all 12 items was .75. The coefficient alpha for the third factor was

below the recommended cutoff of .70 for social sciences research (Kline, 1999). Given

the relatively low communalities for items within the third factor, as well as the poor

reliability of this factor, the three items which comprised it (items 3, 16, and 18) were

excluded from further analysis. The factor analysis was repeated specifying only two

factors, producing a clean factor structure after rotation (Table 6). Reliability analysis for

items within the two remaining factors was repeated. The corrected item-total

correlations were all positive and ranged from .12 to .83. The coefficient alpha was .93

for the first factor (Partner Sensitivity), .73 for the second factor (Conversational Flow),

and .83 for all 9 items.

Factor scores of the participants were calculated for each of the identified factors

by the Regression method. Subscale scores were then created by summing the items

within each factor and, as statistically expected, correlations between factor scores and

the associated subscale scores were high (.99 for Partner Sensitivity and .96 for

Conversational Flow). Subscale scores were used in all further analyses for ease of

interpretation and generalizability. There was a trend toward statistical significance in the

correlation between Partner Sensitivity Scale and Conversational Flow Scale scores (rs =

.10, p = .07).


37

Descriptive statistics for the Partner Sensitivity and Conversational Flow scales

can be found in Tables 7 and 8. Examination of the distribution of Partner Sensitivity

Scale scores revealed a bi-modal distribution in the overall sample, with the majority of

participants showing either minor difficulties or severe difficulties in partner sensitivity

behaviors. In contrast, Conversational Flow scores were severely positively skewed, as

the majority of participants showed little or no impairment in these behaviors.

Furthermore, no participant in this sample obtained the most severe (highest) score for

the Conversational Flow Scale, as the highest observed score was 10/12.

Differences in subscale performance among different demographic groups were

tested using independent samples t-tests and one-way ANOVA. There were no significant

differences between men and women for PPIC Partner Sensitivity scores [t (204) = -0.60,

p = .55] or PPIC Conversational Flow scores [t (208)= 0.66, p = .51]. Comparisons of

PPIC scores between participants of different ethnicities were conducted. Due to the

small number of participants who identified themselves as East Asian/Pacific Islander,

Central Asian, Native American, or other, these participants were combined into one

group designated as “Other.” There was no statistically significant effect of

race/ethnicity on PPIC Partner Sensitivity scores [F (3,202) = 1.75, p = .16] or PPIC

Conversational Flow scores [F (3,206) = 1.21, p = .31].

Criterion-related concurrent validity. Descriptive statistics for the PPIC subscale

scores and other measures of community integration and social communication are

presented in Table 7. Correlations between PPIC subscale scores and CHART-SF

Occupation and Social Integration subscale scores were examined in order to provide

preliminary evidence of criterion-related concurrent validity for the newly created PPIC


38

subscales. Higher CHART-SF scores are indicative of better functioning, while lower

PPIC scores are indicative of better social communication abilities. It is important to note

that there were statistically significant differences in CHART-SF Occupation scores [t

(207) = 2.88, p < .01] and PPIC Partner Sensitivity scores [t (182.14) = -15.88, p < .01]

between the SCA and IPR participants, with SCA participants performing better on both

measures. There was a trend toward statistically significant better scores on the CHART-

SF Social Integration Scale for participants in the SCA sample compared to IPR

participants [t (188.65) = 1.87, p = .06].Conversational Flow Scale scores were not

statistically significantly different between the two samples [t (208) = -1.35, p = .18].

Due to the non-normal distribution of each of these variables, correlations were

calculated using a non-parametric statistic (Spearman’s rho).

Interpretations of the effect sizes of correlations were based upon guidelines set

by Cohen (1992), in which coefficients of .10 represent a small effect size, coefficients of

.30 represent a moderate effect size, and coefficients of .50 and higher represent a large

effect size. As described in the methods section, lower PPIC scores represent better

performance, while higher CHART-SF and AIPSS scores are indicative of better

performance. A small negative correlation was found between CHART-SF Occupational

scores and scores on the Partner Sensitivity Scale (rs=-.20, p < .01), indicating that lower

(better) partner sensitivity scores are associated with higher (better) Occupational Scores.

A moderate negative correlation was found between Occupational scores and the

Conversational Flow Scale (rs = -.36, p < .01), indicating that lower (better)

conversational flow scores are associated with better occupational scores. A moderate

negative relationship between CHART-SF Social Integration scores and Conversational


39

Flow scores was found (rs = -.39, p < .01), indicating that better (lower) conversational

flow scores were associated with better (higher) social integration scores. There was no

significant correlation found between CHART-SF Social Integration and Partner

Sensitivity scores (rs = -.07, p = .16), or between PPIC subscale scores (rs = .10, p = .07).

A moderate positive correlation was found between CHART-SF subscale scores (rs = .45,

p < .01).

Convergent Construct Validity. Correlations between PPIC subscale scores,

TIRR Social Communication Rating Form scores, and AIPSS Overall Sending scores

were examined in order to provide preliminary evidence of convergent construct validity

for the newly created PPIC subscales. Higher TIRR Social Communication Rating Form

and AIPSS scores are indicative of better expressive communication, while lower PPIC

scores are indicative of better social communication ability.

There was a strong negative correlation between TIRR Social Communication

Rating Form scores and scores on the Partner Sensitivity Scale (rs = -.84, p < .01). There

was a moderate negative correlations between TIRR Social Communication Rating Form

scores and PPIC Conversational Flow Scale scores (rs = -.41, p < .01). There was a

moderate positive correlation between TIRR Social Communication Rating Form scores

and AIPSS Overall Sending scores (rs = .38, p < .01). Moderate negative correlations

were found between AIPSS Sending scores and scores on the Partner Sensitivity Scale (rs

= -.33, p < .01) and the Conversational Flow Scale (rs = -.43, p < .01), indicating that

lower (better) performance on PPIC subscales are associated with higher (better) AIPSS

Sending Scores.


40

Specific Aim 2: Prediction of Social Communication Difficulties

All subsequent analyses were conducted using only data from participants in the

SCA study, as participants in the IPR study were not administered the cognitive measures

utilized in these analyses. Of note, the distribution of PPIC Conversational Flow scores

for SCA participants was similar to the distribution observed in the combined sample.

However, compared to the combined sample, the distribution of PPIC Partner Sensitivity

scores showed a less pronounced bi-modal distribution, with the majority of participants

scoring well on Partner Sensitivity items and a smaller group performing in the impaired

range. Based on examination of centered leverage values and Mahalanobis distances, two

cases were determined to be multivariate outliers and were excluded from all further

analyses. Descriptive data regarding performance on predictor and outcome measures are

presented in Table 8.

All variables were evaluated for assumptions associated with multivariate tests.

Distributions for all variables were assessed for normality by significance of the K-S

statistic, visual inspection of histograms and P-P plots, and assessment of skewness and

kurtosis values. According to significance of the K-S statistic, distributions for all

variables except the TIRR Social Communication Rating Form scores were significantly

non-normal (p < .05).Normality of skewness and kurtosis values for each variable was

assessed using guidelines described by Kim (2013), in which skewness and kurtosis

values are divided by their standard errors to obtain a Z score. The absolute value for the

Z scores is compared to the recommended cutoff of greater than 3.29 for a sample size

between 50 and 300. Using these guidelines, skewness values for all measures except the

COWA, TIRR Social Communication Rating Form, and AIPSS were non-normal (p <


41

.05). Kutosis values for TMT-B, CWIT, SAM, Matching Facial Affect, and PPIC

Conversational Flow scores were non-normal (p < .05). Given the contradictory evidence

regarding the normality of COWA and AIPSS scores, histograms and P-P plots for these

variables were examined. Visual inspection of these histograms and P-P plots was

suggestive of slight departures from normality for the distributions of COWA and AIPSS

scores. Variable transformations were attempted to reduce skewness for both predictor

variables and outcome variables using square root, logarithmic, and inverse

transformations. These transformations were only successful in producing normal

distributions for a minority of the predictor variables and none of the outcome variables

at the cost of complicating interpretation of results. Therefore, variable transformations

were not utilized in the final analyses.

Histograms, P-P plots, and scatterplots of standardized residuals for each

regression model are presented in Appendix B. The assumptions of linearity and no

multicollinearity were met for all regression analyses. Other assumptions of linear

regression, including normality and homoscedasticity of residuals, were not met for

models predicting Partner Sensitivity scores, Conversational Flow scores, or TIRR Social

Communication Rating Form scores. However, these assumptions were met for the

regression model predicting AIPSS overall sending scores.

Descriptive Correlations. Descriptive correlations between predictor and outcome

variables are presented in Table 9. Statistically significant small to moderate correlations

were found between measures of affect perception and executive functioning, with better

performance on affect perception measures associated with better performance on

executive functioning measures. There was also a large correlation between the two


42

affect perception variables, and moderate to large correlations between three of the four

executive functioning variables. Performance on the fourth measure of executive

functioning, the Script Analysis Measure, did not reach statistical significance with either

the other executive functioning measures or the affect perception measures. All social

communication outcome measures showed small to moderate correlations with years of

education. PPIC Partner Sensitivity scores were significantly associated with the COWA,

the CWIT, and the affect perception measures. PPIC Conversational Flow scores were

significantly associated time to completion on TMT B and the CWIT, as well as the

affect perception measures. TIRR Social Communication Rating Form scores were

significantly correlated with performance on the COWA, the CWIT, and Matching Facial

Affect. AIPSS Overall Sending scores were significantly correlated with performance on

TMT B, the COWA, the CWIT, and the affect perception measures.

Prediction of PPIC Partner Sensitivity Scale scores. Hierarchical multiple

regression analyses were conducted to determine whether the addition of injury-related

variables and then of cognitive variables improved the prediction of PPIC scale scores

over and above demographic variables alone. Results for the model predicting Partner

Sensitivity are presented in Table 10.In the first step, demographic variables accounted

for a significant amount of variance in PPIC Partner Sensitivity scores (R2 = .09, F (2,

98) = 4.86, p < .05). In the second step, injury-related variables did not explain a

significant additional amount of variance in the variance of Partner Sensitivity scores

after controlling the variance accounted for by demographic variables, though the overall

model remained statistically significant (R2 = .12, R

2 change = .03, F(4,96) = 3.39, p =

.01). In the final step, cognitive variables did not explain a significant additional amount


43

of variance in the variance of Partner Sensitivity scores after controlling the variance

explained by both demographic and injury-related variables (R2 = .17, R

2 change = .05,

F(10, 90) = 1.90, p = .06). Examination of individual independent variables revealed that

years of education (β = -.23; t = -2.07, p < .05) was found to be a unique predictor of

Partner Sensitivity scores.

Prediction of PPIC Conversational Flow Scale scores. Results for the model

predicting Conversational Flow scores are presented in Table 11. In the first step,

demographic variables accounted for a significant amount of variance in Conversational

Flow scores (R2 = .10, F (2, 98) = 5.31, p = .01). In the second step, injury-related

variables did not explain a significant additional variance in the variance of

Conversational Flow scores after controlling the variance accounted for by demographic

variables, though the overall model remained statistically significant (R2 = .12, R

2 change

= .02, F(4,96) = 3.33, p = .01). In the final step, cognitive variables accounted for a

significant additional amount of variance in the variance of Conversational Flow scores

after controlling the variance explained by both demographic and injury-related variables

(R2 = .34, R

2 change = .22, F(10, 90) = 4.66, p < .001). Examination of individual

independent variables revealed that CWIT time to completion (β = .36; t = 3.48, p < .01)

and SAM Mean Key Element Importance ratings (β = -.20; t = -2.19, p < .05) were found

to be a unique predictor of Conversational Flow scores.

Prediction of TIRR Social Communication Rating Form scores. Hierarchical

multiple regression analyses were conducted to determine whether the addition of injury-

related variables and then of cognitive variables improved the prediction of TIRR Social


44

Communication Rating Form scores over and above demographic variables alone.

Results are presented in Table 12.

In the first step, demographic variables accounted for a significant amount of

variance in TIRR Social Communication Rating Form scores (R2 = .17, F (2, 42) = 4.15,

p < .05). In the second step, injury-related variables did not explain a significant

additional variance in the variance of TIRR Social Communication Rating Form scores

after controlling the variance accounted for by demographic variables, though the overall

model showed a trend toward significance (R2 = .18, R

2 change = .01, F(4,40) = 2.13, p =

.10). In the final step, cognitive variables did not explain a significant additional amount

of variance in the variance of TIRR Social Communication Rating Form scores after

controlling the variance explained by both demographic and injury-related variables,

though the overall model again showed a trend toward significance (R2 = .37, R

2 change

= .20, F(10, 34) = 2.02, p = .06). Examination of individual independent variables

revealed that years of education (β = .38; t = 2.59, p < .05) was found to be a unique

predictor of TIRR Social Communication Rating Form scores.

Prediction of AIPSS Overall Sending scores. Hierarchical multiple regression

analyses were conducted to determine whether the addition of injury-related variables

and then of cognitive variables improved the prediction of AIPSS Overall Sending scores

over and above demographic variables alone. Results are presented in Table 13.

In the first step, demographic variables accounted for a significant amount of

variance in AIPSS scores (R2 = .12, F (2, 93) = 6.04, p < .01). In the second step, injury-

related variables did not explain a significant additional variance in the variance of


45

AIPSS scores after controlling the variance accounted for by demographic variables,

though the overall model was statistically significant (R2

= .14, R2 change = .03, F(4,91)

= 3.70, p < .01). In the final step, cognitive variables accounted for a significant

additional amount of variance in the variance of AIPSS scores after controlling the

variance explained by both demographic and injury-related variables (R2 = .31, R

2 change

= .17, F(10, 85) = 3.82, p < .01). Examination of individual independent variables

revealed that Script Analysis Measure scores (β = .27; t = 2.78, p < .01) were found to be

unique predictors of AIPSS sending scores, and that years of education showed a trend

toward significance (β = .20; t = 1.88, p = .06).


46

Chapter 4: Discussion

Specific Aim 1: PPIC Development

It was predicted that a factor analysis of the 20 PPIC items selected by research as

characteristic of social communication difficulties following TBI would yield a four-

factor solution similar to the factor structure of the LCQ, a self report measure of social

communication difficulties. This hypothesis was not supported by results of the current

study, as 11 of the original 20 items were systematically discarded from analyses due to

issues with missing data, multicollinearity, inadequate factor loadings, and inadequate

reliability. It is surprising that several of the items that were excluded due to inadequate

factor loadings and reliability contained conceptually associated content that was thought

to be related to disinhibition and impulsivity, one of the more common behavioral

disturbances found among the TBI population (Body et al., 1999; McDonald & Pearce,

1998). However, results of the current study indicate that these behaviors, or researcher’s

ratings of these behaviors, were not consistently and strongly correlated with one another

in this sample. Given the findings of previous research indicating that a subset of

individuals with TBI experience disruptions in social communication related to apparent

disinhibition and impulsivity (Hartley & Jensen, 1992), and taking into account the well-

documented heterogeneity of cognitive, behavioral, and social communication deficits

within the TBI population (Body et al., 1999), further investigation of these behavioral

items using a different sample is recommended.

The two factor solution that was eventually obtained accounted for 60.77% of the

total variance. This solution had a clean factor structure, characterized by relatively high

factor loadings, no significant double-loadings, and all items loading significantly on


47

factors. Internal consistency for the two factors ranged from acceptable (α = .73) to

excellent (α = .93).

The items making up the first factor appear to consist of behaviors that would

facilitate dyadic interaction within a conversation. The phrasing of the items and

operational definition of the behaviors being rated is suggestive of a set of conversational

skills meant to enhance two-way communication within a conversation. These items are

also reflective of one’s awareness of and sensitivity to one’s conversational partner. In

contrast, items comprising the second factor appear to consist of behaviors that would

interfere with conversational interaction. The phrasing of these items and the

corresponding behaviors are suggestive of a set of expressive communication deficits

which degrade interactivity and interrupt the normal flow of a conversation.

The first of the two factors was labeled Partner Sensitivity, and it accounted for

40.99% of the total variance. The second factor was labeled Conversational Flow, and it

accounted for 19.78% of the total variance. Examination of the items comprising these

factors made conceptual sense, as the items within each factor appeared to pertain to

related aspects of social communication. These constructs also made sense from a clinical

perspective, identifying clusters of social communication difficulties which have been

documented in the TBI population (Linscott et al., 1996; Body et al., 1999; Hartley &

Jensen, 1992; Marsh & Knight, 1991; Chapman et al., 1992). Subscale scores were

created by summing item raw scores within each factor, and these subscale scores were

used in all further analyses.


48

In order to provide preliminary evidence for the validity of the newly created

PPIC subscale scores, correlations between PPIC subscale scores and other measures of

community integration and social communication were examined. It was hypothesized

that PPIC subscale scores would be significantly correlated with CHART-SF Occupation

and Social Integration scores, as well as with AIPSS Overall Sending scores.

Conversational Flow Scale scores showed moderate correlations with CHART-SF scores

and AIPSS sending scores, with better Conversational Flow scores being associated with

better community integration and expressive communication. Partner Sensitivity Scale

scores were modestly correlated with CHART-SF Occupational scores and moderately

correlated with AIPSS sending scores, with better Partner Sensitivity scores being

associated with better occupational/productivity outcomes and better expressive

communication ability. However, there was no statistically significant correlation

between CHART-SF Social Integration scores and Partner Sensitivity scores.

These results provide preliminary evidence for criterion-related concurrent

validity and convergent construct validity for PPIC subscale scores, though evidence for

the criterion-related concurrent validity of Partner Sensitivity scores is somewhat

equivocal. Given the relationship between the subscale scores and measures of

community integration, the behaviors that comprise these factors may represent viable

targets for intervention and remediation in TBI patients with social communication

difficulties pending further investigation and validation.

Specific Aim 2: Prediction of Social Communication Difficulties

It was hypothesized that performance on measures of neurocognition

(specifically, attention and executive functioning) and social cognition (specifically,


49

affect recognition) would significantly add to the prediction of social communication

ability as measured by PPIC subscales after accounting for the effects of demographic

and injury-related variables. Results of the current study partially support this hypothesis,

as performance on cognitive measures was related to certain aspects of social

communication. Specifically, performance on cognitive measures explained a significant

amount of variance in PPIC Conversational Flow scores and AIPSS Overall Sending

scores, both of which involve expressive social communication skills. For Conversational

Flow scores, CWIT time to completion and SAM mean key element importance scores

emerged as significant individual predictors. Better performance on these measures was

predictive of better Conversational Flow scores. The CWIT requires an individual to

process information quickly, selectively attend to certain aspects of a stimulus, and

inhibit an over-learned verbal response. The SAM requires an individual to organize and

formulate a plan for a complex task, and the score used in the current study (mean key

element importance scores) require the individual to make judgments about the

importance of each step in a complex behavioral sequence. Examination of the items that

comprise the PPIC Conversational Flow Scale (‘the flow of utterances is disrupted and

broken,’ ‘has a long response latency,’ ‘provides insufficient detail,’ and ‘has difficulty

naming objects’) provides the basis for a conceptual link between the complex

information processing speed, attention, and judgment skills required for these cognitive

tasks and the ability to express oneself without disruption during a conversation. This

idea has previously been discussed in the literature (Body et al., 1999; Hartley & Jensen,

1991; Marsh & Knight, 1991a), but findings are inconsistent and the relationship between


50

measures of information processing speed, attention, and executive functioning and

conversational flow require further investigation.

For AIPSS Overall Sending scores, only the SAM mean key element importance

score emerged as a significant individual predictor. Better SAM scores were predictive of

better AIPSS Overall Sending scores. AIPSS Overall Sending scores are obtained by

asking the participant to role-play how they would respond in a situation in which there is

a social problem (i.e., if someone were to cut in front of them in a line). For the Overall

Sending score, the participant’s verbal response, as well as their para-verbal behaviors

(i.e., facial expressions, tone of voice, body language), are considered when rating the

quality of their response and the likelihood of achieving a satisfactory resolution to the

social problem. Similar to conversational flow skills, judgment and organization of one’s

thoughts are involved in formulating and expressing a verbal response within a social

context (McFall, 1982; Body et al., 1999; McDonald & Pearce, 1998). Furthermore, prior

studies have linked executive functioning deficits in participants with TBI to sub-optimal

request strategies in hypothetical social situations, which would support the involvement

of planning, judgment, and problem solving in an expressive communication task such as

the Sending portion of the AIPSS. Unlike expressive language skills in an unstructured

conversation, however, the individual completing the AIPSS is being asked to role-play

their response in a given social situation rather than to respond “in the moment” as part of

a dynamic conversation. This may allow participants more time to process and formulate

a response, which may explain why a measure of selective attention and information

processing speed (such as the CWIT) is not a significant individual predictor of AIPSS


51

Overall Sending scores, while a measure involvement planning and judgment (such as the

SAM) is.

In contrast, performance on cognitive measures was not found to be predictive of

other aspects of social communication, such as the sensitivity of an individual to a

conversational partner. Cognitive variables, as a group, did not explain a significant

amount of variance in PPIC Partner Sensitivity Scale scores above that already accounted

for by demographic variables (age and education). There were similar findings for TIRR

Social Communication Rating Form scores. This is not surprising given the strong

correlation between TIRR Social Communication Rating Form scores and PPIC Partner

Sensitivity scores (rs = -.84, p < .01), which suggests that these two variables are actually

measuring very similar constructs. An unexpected finding was that only education

emerged as a significant individual predictor of PPIC Partner Sensitivity scores and TIRR

Social Communication Rating Form scores. More years of education were predictive of

better scores on both measures. It is possible that a relationship exists between education

and partner sensitivity behaviors, though it is impossible to determine causality based on

the current study results. One possible explanation is that individuals with higher levels

of education had better premorbid partner sensitivity skills, and that these individuals are

less vulnerable to social communication deficits following TBI. This “cognitive reserve

hypothesis” has been demonstrated with cognitive test performance in the TBI population

(Kesler, Adams, Blasey, & Bigler, 2003). It may also be that the significance of

education as a predictor of Partner Sensitivity scores and TIRR Social Communication

Rating Form scores is acting as a proxy for other variables that have not been accounted


52

for in this study. Further investigation of the relationship between education and social

communication skills is needed.

As mentioned previously, these results support previous work which has explored

different communication deficit subtypes, or “profiles,” in TBI patients. One such profile

is characterized by failure to engage one’s conversational partner (Marsh & Knight,

1991b; Linscott et al., 1996). Descriptions of these individuals have much in common

with poor performance on items from the Partner Sensitivity Scale. Previous work has

generally not found significant relationships between traditional measures of cognitive

ability and this category of social skill deficit (Marsh & Knight, 1991b). This suggests

that traditional measures of cognition and social cognition do not adequately measure the

cognitive processes which underlie this aspect of social communication. One such social

cognitive process that may show a greater relationship to conversational partner

sensitivity behaviors is theory of mind. As discussed in the introduction section, theory of

mind requires an individual to maintain an awareness of another person’s potential

thought process in order to predict that person’s intentions. Given that research has found

that both theory of mind and partner sensitivity are affected in many individuals with TBI

(Muller et al., 2010; Spikman et al., 2012), the link between these abilities bears further

investigation. The complexity of social communication behaviors such as partner

sensitivity and the consistent failure to find a link between traditional cognitive measures

and these behaviors may also point to the effects of moderator variables as a bridge

between cognitive abilities and social communication. The external structure provided by

the examiner and the testing environment for most traditional neuropsychological

measures may mask underlying difficulties in the application of higher order cognitive


53

processes that individuals with TBI may have in a less structured environment. Further

investigation of non-traditional measures of attention, executive functioning, and social

cognition (such as the Script Analysis Measure) and their relationships to traditional

cognitive measures and social communication may serve as a useful step towards

understanding social communication in the TBI population.

Study Limitations & Future Directions

There are a number of methodological and statistical limitations present in the

current study which may confound the interpretation and generalizability of these results.

The factor analysis of the PPIC and subsequent explorations of the relationships between

social communication, cognition, and demographic and injury-related characteristics was

conducted on a sample comprised solely of TBI patients. The absence of a control group

limits interpretation of these findings given the lack of available normative data regarding

the range of social communication ability in the general population. While it may be the

case that members of the general population are unlikely to display difficulties associated

with conversational flow behaviors (as was the case even within this TBI sample), it is

conceivable that there is a wider range of partner sensitivity behaviors within the normal

population. A related limitation regarding the measurement of social communication in

general, and the PPIC in particular, is that these tools often do not account for cross-

cultural social and conversational norms. Not only are there differences in typical or

acceptable conversational behavior across cultures, but individuals who identify

themselves as being members of a particular cultural/ethnic group may vary on their level

of acculturation within that group (Sue & Sue, 2015). These factors can complicate the

rating and interpretation of social communication behaviors for individuals who hold


54

different cultural norms from the researcher or clinician using these tools. While no

statistically significant differences for Partner Sensitivity scores and Conversational

Flow scores were found between different ethnic groups in this study, the continued

investigation and consideration of cultural norms in the measurement of social

communication remains warranted.

Another limitation inherent to the measurement of social communication

behaviors with observational measures such as the PPIC is that conversational samples

are generally not recorded in vivo, but are arranged as “simulated interactions [in which]

an attempt is made to parallel real-life situations, and the subject and confederate are

given minimal instructions” (Marsh, 1999). Furthermore, participants are generally aware

that the conversation is being recorded and/or observed. In this regard, it is difficult to

know what ramifications observer effects may have on a participant’s social

communication behavior. It is also possible that social communication difficulties

following TBI may not manifest themselves in a single brief conversational interaction

except in more severe cases. The amount of missing data for the PPIC item ‘perceives

other’s misinterpretation of meaning’ due to ratings of ‘not applicable’ provides a prime

example. Except in the most obvious cases, this behavior is difficult to observe in a brief,

unstructured conversational sample unless it is explicitly elicited by the researcher.

However, difficulties in this area could have significant social consequences for

individuals with TBI. The use of self- and other-report measures such as the LCQ to rate

typically occurring social communication difficulties by the person with TBI and a

significant other may offer a useful comparison against those which are observed using

an observational measure like the PPIC. Another approach may involve observation of


55

patient social interactions with clinicians and other patients within an inpatient

rehabilitation facility. This approach may circumvent the difficulties associated with

simulated conversational paradigms, while also providing valuable information to

clinicians and researchers about social communication proficiency in these TBI patients.

Other limitations of the current study include the marginal adequacy of the ratio

of predictor variables to sample size. While a sample size of 100 for 10 predictor

variables is conventionally considered to be an adequate ratio (10 to 1) by many

researchers, others argue that a ratio of 15 participants for each predictor is more

appropriate (Field, 2009). The use of an inadequate sample size in regression can result in

inadequate statistical power in some cases, therefore increasing the risk of making a type

II error. Similarly, while measures of sampling adequacy indicated a sufficient sample

size for factor analysis in the current study, many researchers advocate for a minimum

sample size of 300 in factor analytic studies (Tabachnick & Fidell, 2001). The ideal

solution in both cases would be to obtain a larger sample of TBI patients. However, given

practical limitations associated with obtaining large sample sizes for studies involving

TBI patients in the community, an alternative approach to the regression analyses may

involve including fewer predictor variables in the regression model. Examining

relationships between predictor variables and outcome variables prior to creating and

testing the regression models in an effort to select the most appropriate predictor

variables may result in a more parsimonious statistical model that simultaneously

preserves statistical power. Finally, the violation of several statistical assumptions

(normality of distributions, homoscedasticity of residuals) may have reduced the

statistical power of these analyses, obscuring potentially significant findings of the


56

overall models or the unique contributions of individual predictor variables. Violation of

these statistical assumptions also limits the generalizability of these findings to the wider

TBI population.

Despite these limitations, the results of the current study represent an important

exploratory step in the investigation of social communication deficits and cognition in

TBI. Further research is needed to test the validity and generalizability of the two new

PPIC subscale scores, perhaps by using confirmatory factor analysis methods on a

different sample of TBI patients. Furthermore, while it may be difficult or even

impractical to develop a comprehensive set of norms for PPIC items and subscales

(particularly given the previously mentioned differences in cultural conversational

norms), future studies should include a non-TBI control group in order to test differences

between PPIC subscale scores in TBI vs. non-TBI individuals. As mentioned previously,

comparisons between self- and other-report measures of social communication (i.e., the

LCQ) and observational measures such as the PPIC may facilitate a more complete

understanding of social communication following TBI.

Conclusion

Despite several decades of research, the social communication difficulties

exhibited by individuals with TBI and the relationship between cognition, social

communication, and social functioning within this population are still poorly understood.

These constructs represent a complex interplay between various factors at multiple levels,

and the study of these relationships is further complicated by the difficulties in measuring

such complex and multifaceted behaviors in a standardized yet ecologically valid manner.

These issues highlight the need for development of accurate, reliable, and practical


57

measures that can be utilized by both researchers and clinicians for the identification of

social communication difficulties in the TBI population. The development of such tools

facilitates greater understanding of the connection between neurocognition, social

cognition, and social communication, and may provide clinicians with viable treatment

targets for remediation of social difficulties following traumatic brain injury.


58

APPENDICES

APPENDIX A Figures and Tables

Table 1

Hypothesized Factor Structure for Selected PPIC Items Initiation/Conversational Flow: Conversational Effectiveness:

The flow of utterances is disrupted and broken (dysfluency) Elaborates spontaneously

Has difficulty naming objects (anomic) Integrates own ideas with other’s ideas

Contributes spontaneously to the conversation Repeats information

Has a long response latency Partner Sensitivity:

There is good continuity between ideas Contributes equally to the conversation

Provides insufficient detail Helps direct the conversation

Disinhibition/Impulsivity: Perceives other’s misinterpretation of meaning

Talks about self too much (egocentric) Asks questions

Inappropriate (sexual, religious, political) content Gives appropriate types of listener responses

Provides excessive detail Is skilled at taking turns

Interrupts

Is overly intimate


59

Table 2

Predictor and Outcome Variables for Specific Aim 2

Predictors

Outcome Measures

Demographic Variables

Age

Years of Education

Injury-Related Variables

Duration of time since injury (months)

Injury Severity (Emergency Room GCS Score)

Attention/Executive Functioning Measures:

Controlled Oral Word Association

Trail Making Test

DKEFS Color-Word Interference Test (Inhibition)

Script Analysis Task

Affect Perception Measures:

Florida Affect Battery (Matching Facial Affect, Conflicting Emotional Prosody)

Social Communication Measures:

Profile of Pragmatic Impairment in Communication Subscale Scores

TIRR TBI Social Communication Rating Form

Assessment of Interpersonal Problem Solving Skills-Sending Score


60

Table 3

Comparison of demographic characteristics and key measures of the SCA and IPR participants

Total (N = 210) SCA Study (n = 116) IPR Study (n = 94) P

Race/Ethnicity, n (%)

White 135 (64.30) 88 (75.90) 47 (50.00)

< .01 Black 36 (17.10) 12 (10.30) 24 (25.50)

Hispanic/Latino 31 (14.80) 12 (10.30) 19 (20.20)

Other 8 (3.80) 4 (3.50) 4 (4.30)

Age mean (SD) [min-max]

36.70 (12.90) [18-75]

37.03 (11.83) [18 – 75]

36.30 (14.16) [18 – 71]

.69

Gender, n (%)

Male 146 (69.50) 79 (68.10) 67 (71.30) .62

Education in Years

mean (SD) [min-max] 13.14 (2.29) [6-20] 13.28 (2.39) [6-20] 12.96 (2.15) [8-19] .31

Months Post Injury

mean (SD) [min-max]

60.94 (49.73)

[10.00 – 289.80]

75.59 (46.75)

[12.60 – 289.80]

42.88 (47.52)

[10.00 – 219.70]

<.01

ER GCS Scores mean (SD) [min-max]

7.10 (4.12) [3-15]

6.68 (3.81) [3 – 15]

7.78 (4.53) [3-15]

.10

Initial Injury Severity Classification by

ER GCS Score, n (%)

Severe: 3-8 123 (71.50) 80 (68.90) 43 (66.20)

.29 Moderate: 9-12 17 (8.20) 11 (9.40) 6 (6.30)

Mild: 13-15 32 (15.30) 16 (13.80) 16 (17.00)

Injury Type, n (%)

Closed TBI 190 (94.50) 102 (93.60) 88 (95.70) .52

Penetrating TBI 11 (5.50) 7 (6.40) 4 (4.30)

ER GCS = Glasgow Coma Scale score upon admission to the emergency room


61

Table 4

Correlations among PPIC items

Item 1 2 3 4 5 6 7 9 10 11 12 13 14 15 16 17 18 19

1 -

2 .42** -

3 .02 -.01 -

4 -.01 .15* .15* -

5 -.02 .17** .06 .75** -

6 -.02 .11 .25** .83** .77** -

7 .01 .08 -.09 -.01 -.08 .01 -

9 .40** .18** .09 .01 .18* -.03 -.25** -

10 .02 .23** .03 .82** .84** .76** .01 .02 -

11 .18** .01 .06 -.10 -.20** -.16** .16* .12* -.01 -

12 .03 .19** .10 .94** .76** .80** -.02 -.01 .85** -.12* -

13 -.01 .12 .23** .82** .79** .78** -.03 .05 .77** -.05 .79** -

14 .03 .24** .22** .81** .84** .82** -.06 .05 .81** -.14* .80** .83** -

15 .00 .07 .27** .82** .54** .66** -.00 -.03 .67** .01 .81** .72** .61** -

16 .00 -.18* .17** -.16* -.18** -.08 .05 .05 -.17** .20** -.15* -.13* -.15* -.11 -

17 -.08 -.10 -.05 -.06 -.10 -.10 .07 -.11 -.09 -.02 -.04 -.06 -.10 -.02 .29** -

18 .08 -.15* .20** -.23** -.35** -.13* .46** -.06 -.32** .28** -.28** -.21** -.29** -.14* .35** .20** -

19 .64** .31** .09 .02 .08 -.03 -.10 .44** .10 .08 .04 .05 .04 .07 -.02 -.05 .01 -

20 -.09 -.04 -.03 -.09 -.04 -.06 .21** -.06 -.13* -.06 -.12* -.08 -.08 -.10 .03 .14* .12* -.13*

N 210 210 210 210 210 210 210 210 210 210 210 206 209 210 210 210 210 210

Note. PPIC = Profile of Pragmatic Impairment in Communication.

* p < .05, **p < .01


62

Table 5

Varimax rotated principal axis factoring loadings and communality estimates for PPIC

Item # Questionnaire item Factor I Factor II Factor III h2**

Factor I

13 Gives appropriate types of listener responses 0.91* 0.83

6 Contributes equally to the conversation 0.89 0.79

10 There is good continuity between ideas 0.87 0.84

5 Is skilled at taking turns 0.84 0.79

15 Helps direct the conversation 0.76 0.58

Factor II

1 The flow of utterances is disrupted and broken 0.83 0.69

19 Has a long response latency 0.79 0.62

9 Provides insufficient detail 0.51 0.26

2 Has difficulty naming objects (anomic) 0.45 0.25

Factor III

18 Talks about self too much (egocentric) 0.62 0.42

3 Asks questions 0.45 0.27

16 Is overly intimate 0.45 0.21

Percentage Variance (54.62%) 31.48 14.91 8.24

Note. *Boldface indicates significant primary loadings (≥.40) of items on each factor; **h2= communalities


63

Table 6

Varimax rotated principal axis factoring loadings and communality estimates for PPIC

Item # Questionnaire item Factor I Factor II h2**

Partner Sensitivity

10 There is good continuity between ideas 0.90* 0.82

13 Gives appropriate types of listener responses 0.90 0.81

6 Contributes equally to the conversation 0.87 0.76

5 Is skilled at taking turns 0.87 0.76

15 Helps direct the conversation 0.73 0.53

Conversational Flow

1 The flow of utterances is disrupted and broken 0.83 0.69

19 Has a long response latency 0.79 0.62

9 Provides insufficient detail 0.51 0.26

2 Has difficulty naming objects (anomic) 0.44 0.21

Percentage Variance (60.77%) 40.99 19.78

Note. *Boldface indicates significant primary loadings (≥.40) of items on each factor; **h2= communalities


64

Table 7

Descriptive statistics for social communication and community integration measures

Variable (range of possible scores)

N Mean (SD)

Median (IQR)

[min-max]

CHART-SF-Occupation Scale (0-100)

209 72.15 (33.06) 93 (44.5-100)

[0-100]

CHART-SF-Social Integration Scale (0-100)

210 86.16 (22.16) 100 (74.0-100)

[0-100]

PPIC Partner Sensitivity Scale (0-15)

206 7.91 (5.63)

9 (2-13)

[0-15]

PPIC Conversational Flow Scale (0-12)

210 1.43 (1.88)

1 (0-2)

[0-10]

TIRR Social Communication Rating Form Avg. Total Score (1-4)

49 3.20 (0.64)

3.35 (2.69-3.82)

[2-4]

Assessment of Interpersonal Problem Solving Skills- Overall Sending Scores % Correct (0-100)

107 62.07 (20.36) 66.7 (50-77.8)

[0-100]

Note. CHART-SF = Craig Handicap Assessment and Reporting Technique-Short Form PPIC = Profile of Pragmatic Impairment in Communication


65

Table 8

Descriptive statistics for predictor and outcome measures for Specific Aim 2

Variable (range of possible scores)

N Mean (SD) [min-max] Skewness [Std. Error]

Kurtosis [Std. Error]

Trail Making Test Time to Completion Part B 109 92.63 (56.05) [32-346] 2.50 [0.23] 7.04 [0.46] Controlled Oral Word Association Total Words Generated 114 27.01 (12.57) [0-52] -0.55 [0.23] -.48 [0.45] Color-Word Interference Test Trial 3 (Inhibition) Time to Completion (0-180)

111 64.07 (20.98) [34-136] 1.48 [0.23] 2.37 [0.46]

Script Analysis Measure Mean Key Element Importance (0-5) 114 4.17 (1.12) [0-5] -2.55 [0.23] 6.78 [0.45] Matching Facial Affect Correct Responses (0-20)

114 16.70 (3.18) [3-20] -1.35 [0.23] 2.39 [0.45]

Conflicting Emotional Prosody Correct Responses (0-36)

114 28.52 (7.09) [11-36] -0.98 [0.23] -.21 [0.45]

PPIC Partner Sensitivity Scale (0-15) 111 4.17 (4.66) [0-15] 1.08 [0.23] -.22 [0.46] PPIC Conversational Flow Scale (0-12) 114 1.21 (1.92) [0-9] 2.20 [0.23] 5.27 [0.45] TIRR Social Communication Rating Form Average Total Score (1-4)

48 3.20 (0.65) [2-4] -0.46 [0.34] -1.17 [0.67]

AIPSS Overall Sending Scores % Correct (0-100) 107 62.27 (20.37) [0-100] -0.69 [0.24] .14 [0.47] Note. PPIC = Profile of Pragmatic Impairment in Communication

TIRR = Texas Institute of Rehabilitation and Research AIPSS = Assessment of Interpersonal Problem Solving Skills


66

Table 9

Correlations among Predictor and Dependent Variables

Variable 1 2 3 4 5 6 7 8 9 10 11 12 13 14

1. Age -

2. Education .21* -

3. Months post-

injury .08 .06 -

4. ER GCS .23** .11 -.02 -

5. TMT B .32** -.21* .03 -.03 -

6. COWA -.03 .16* .06 -.08 -.32** -

7. CWIT .28** -.19* .22* -.04 .55** -.33** -

8. SAM -.17* -.06 .12 .04 -.04 .15 -.03 -

9. MFA -.25** .28** -.09 .01 -.42** .27** -.43** .06 -

10. CEP -.21* .35** -.02 -.07 -.62** .22** -.36** .08 .56** -

11. PPIC Partner -.04 -.36** -.01 .11 .11 -.20* .34** -.13 -.31** -.25** -

12. PPIC

Conversational Flow .13 -.16* .03 -.03 .28** -.14 .32** -.00 -.30** -.26** .28** -

13. TIRR SCRF .28* .37** .15 .11 -.14 .37** -.32* .17 .28* .14 -.84** -.41** -

14. AIPSS .01 .34** .01 .01 -.22* .17* -.21* .12 .36** .36** -.33** -.42** .38** -

N 114 114 114 105 109 114 111 114 114 114 111 114 48 105

Note. *p < .05, **p < .01; ER GCS = Emergency Room Glasgow Coma Scale score; TMT B = Trail Making Test Form B; COWA =

Controlled Oral Word Fluency Test; CWIT = Delis-Kaplan Executive Functioning Scales Color-Word Interference Test; SAM =

Script Analysis Measure; MFA = Florida Affect Battery Matching Facial Affect; CEP = Florida Affect Battery Conflicting Emotional

Prosody; PPIC = Profile of Pragmatic Impairment in Communication; TIRR SCRF = Texas Institute of Research and Rehabilitation

Social Communication Rating Form; AIPSS = Assessment of Interpersonal Problem Solving Skills


67

Table 10

Prediction of PPIC Partner Sensitivity Scale scores Variable β t sr2 R R2 ΔR2

Step 1 .30 .09 .09*

Age .09 .87 .01

Education -.31 -3.12** .09

Step 2 .35 .12 .03

Age .03 .26 .00

Education -.33 -3.26** .10

Months post-injury -.02 -.16 .00

ER GCS .19 1.90 .03

Step 3 .42 .17 .05

Age -.08 -.64 .00

Education -.23 -2.07* .04

Months post-injury -.03 -.25 .00

ER GCS .21 2.01* .04

TMT-B Time -.03 -.21 .00

COWA Total Score .00 .04 .00

CWIT Inhibition Time .07 .57 .00

SAM Mean Key Element Importance -.10 -.93 .01

Facial Affect Matching -.13 -1.05 .01

Conflicting Emotional Prosody -.08 -.57 .00

Note. *p < .05, **p < .01; ER GCS = Emergency Room Glasgow Coma Scale score; TMT-

B = Trail Making Test Form B; COWA = Controlled Oral Word Association Test; CWIT =

Delis-Kaplan Executive Functioning Scales Color Word Interference Test; SAM = Script

Analysis Measure


68

Table 11

Prediction of PPIC Conversational Flow Scale scores Variable β t sr2 R R2 ΔR2

Step 1 .31 .10 .10*

Age .24 2.39* .05

Education -.28 -2.79** .07

Step 2 .35 .12 .02

Age .25 2.38* .05

Education -.28 -2.81** .07

Months post-injury .14 1.50 .02

ER GCS -.05 -.53 .00

Step 3 .58 .34 .22**

Age .04 .35 .00

Education -.11 -1.13 .01

Months post-injury .08 .83 .01

ER GCS .01 .14 .00

TMT-B Time -.01 -.12 .00

COWA Total Score .04 .39 .00

CWIT Inhibition Time .36 3.48** .09

SAM Mean Key Element Importance -.20 -2.19* .04

Facial Affect Matching -.15 -1.33 .01





Analysis Measure


69

Table 12

Prediction of TIRR Social Communication Rating Form scores Variable β t sr2 R R2 ΔR2

Step 1 .41 .17 .17*

Age .08 .52 .01

Education .38 2.59* .13

Step 2 .42 .18 .01

Age .09 .54 .01

Education .38 2.53* .13


ER GCS -.04 -.28 .00

Step 3 .61 .37 .20

Age .21 1.28 .03

Education .22 1.39 .04


ER GCS -.07 -.44 .04

TMT-B Time -.14 -.77 .01

COWA Total Score .23 1.47 .04

CWIT Inhibition Time -.21 -1.26 .03

SAM Mean Key Element Importance .15 1.04 .02

Facial Affect Matching .07 .40 .00





Analysis Measure


70

Table 13

Prediction of AIPSS Overall Sending scores. Variable β t sr2 R R2 ΔR2

Step 1 .34 .12 .12**

Age -.12 -1.14 .01

Education .35 3.47** .11

Step 2 .37 .14 .03

Age -.10 -.89 .01

Education .36 3.56** .12

Months post-injury -.15 -1.58 .02

ER GCS -.04 -.42 .00

Step 3 .56 .31 .17**

Age .09 .83 .01

Education .20 1.88 .03

Months post-injury -.15 -1.56 .02

ER GCS -.09 -.86 .01

TMT-B Time -.05 -.44 .00

COWA Total Score -.08 -.78 .00

CWIT Inhibition Time -.09 -.78 .00

SAM Mean Key Element Importance .27 2.78** .06

Facial Affect Matching .15 1.24 .01

Conflicting Emotional Prosody .15 1.18 .01




Analysis Measure


71

Initial item pool:

84 items

Reduced item set:

24 items

Literature review,

clinical & research

experience to inform

initial item selection

Items for use in

exploratory factor

analysis:

20 items

Group discussion with

committee members

to eliminate

redundant items

Use of LCQ factors to

inform factor analysis

hypotheses

Figure 1. Initial item selection process for the Profile of

Pragmatic Impairment in Communication.


72

APPENDIX B Distribution Histograms, P-P Plots, and Scatterplots

Partner Sensitivity Regression Residual

Plots

Conversational Flow Regression Residual

Plots


73

TIRR Social Communication Rating Form

Regression Plots

AIPSS Regression Plots


74

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