AJSLP

Supplement

Reading Comprehension in Parkinson’s Disease Laura L. Murraya and Stefanie Rutledgea

Purpose: Although individuals with Parkinson’s disease (PD) self-report reading problems and experience difficulties in cognitive–linguistic functions that support discourse-level reading, prior research has primarily focused on sentencelevel processing and auditory comprehension. Accordingly, the authors investigated the presence and nature of reading comprehension in PD, hypothesizing that (a) individuals with PD would display impaired accuracy and/or speed on reading comprehension tests and (b) reading performances would be correlated with cognitive test results. Method: Eleven adults with PD and 9 age- and educationmatched control participants completed tests that evaluated reading comprehension; general language and cognitive abilities; and aspects of attention, memory, and executive functioning. Result: The PD group obtained significantly lower scores on several, but not all, reading comprehension, language, and

cognitive measures. Memory, language, and disease severity were significantly correlated with reading comprehension for the PD group. Conclusion: Individuals in the early stages of PD without dementia or broad cognitive deficits can display reading comprehension difficulties, particularly for high- versus basic-level reading tasks. These reading difficulties are most closely related to memory, high-level language, and PD symptom severity status. The findings warrant additional research to delineate further the types and nature of reading comprehension impairments experienced by individuals with PD.

P

Larsen, Tysnes, & Alves, 2009; Altmann & Troche, 2011; Murray, 2008; Roberts-South & Orange, in press; Troster, 2011). Within the language literature, however, there has been nominal investigation of reading abilities beyond the isolated word or sentence level, even though several lines of evidence suggest this language modality may be vulnerable in PD. First, in addition to difficulties with certain aspects of expressive language such as verbal fluency (e.g., Hough, 2004), morphosyntax use (e.g., Longworth, Keenan, Barker, Marslen-Wilson, & Tyler, 2005), language formulation (e.g., Huber & Darling, 2011), and spoken discourse informativeness (e.g., Murray, 2000), individuals with PD have been shown to have difficulties with a variety of comprehension tasks. In numerous studies, individuals with PD who do not present with dementia have demonstrated difficulty with sentence-level comprehension, particularly in terms of syntactic processing (Bodis-Wollner & Jo, 2006; Colman, Koerts, Stowe, Leenders, & Bastiaanse, 2011; Friederici, Kotz, Werheid, Hein, & von Cramon, 2003; Grossman et al., 1991, 1992, 2000, 2003; Grossman, Lee, Morris, Stern, & Hurtig, 2002; Hochstadt, 2009; Hochstadt, Nakano, Lieberman, & Friedman, 2006; Song, Kim, Jeong, Song, & Lee, 2008; Zanini et al., 2004). For example, Geyer and Grossman

arkinson’s disease (PD) is one of the most common neurodegenerative diseases, afflicting just over 1% of adults by age 65 years (Boland & Stacy, 2012; Shulman, De Jager, & Feany, 2011; Wright Willis, Evanoff, Lian, Criswel, & Racette, 2010). Because its prevalence and incidence increases with age, and because the elderly represent one of the fastest growing segments of the population, understanding the breadth and nature of PD symptoms to foster early diagnosis and treatment remains an important research focus. PD typically presents with a variety of motoric symptoms (e.g., rigidity, bradykinesia), the physical manifestations of a loss of dopaminergic neurons in the substantia nigra, which modulate output to the cerebral cortex through the basal ganglia. In addition to these well-established motor symptoms, a growing literature has confirmed that the neurological consequences of PD also cause cognitive and linguistic changes (Aarsland, BrLnnick,

a

Indiana University, Bloomington

Correspondence to Laura L. Murray: [email protected] Editor: Swathi Kiran Associate Editor: Leonard LaPointe Received August 5, 2013 Revision received October 22, 2013 Accepted October 24, 2013 DOI: 10.1044/2014_AJSLP-13-0087

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Key Words: reading, neurologic disorders, cognition, Parkinson’s disease

Disclosure: The authors have declared that no competing interests existed at the time of publication.

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(1994) found that their participants with PD displayed similar listening comprehension performances as control participants on probes of simple transitive sentences but were significantly impaired in their comprehension of lexical-causative verbs; 40% of the patients with PD, however, performed as well as control participants across all sentence types, implying that this comprehension deficit was not universal. More recently, Colman and colleagues (2011) had adults with and without PD listen to sentences and determine whether a picture shown on a computer screen matched the given sentence; sentence stimuli were varied in terms of syntactic complexity and length. Across the stimulus manipulations, the two groups showed the same response pattern (e.g., greater difficulty with long passives vs. short passives). The PD group, however, always performed less accurately than the control group, leading Colman et al. to conclude that PD, even in the early stage of the disease, can cause broad but mild sentence processing difficulties. There has also been investigation, albeit more limited, of other aspects of comprehension in PD. For instance, Murray and Stout (1999) used the Discourse Comprehension Test (DCT; Brookshire & Nicholas, 1993) to assess listening comprehension in individuals with PD or Huntington’s disease (HD). The PD and HD groups and their age-matched control groups showed similar response patterns, performing more accurately on questions related to stated information and main ideas than implied information and details (Murray & Stout, 1999). The PD group, however, responded significantly less accurately than the control group on questions targeting implied main ideas and implied details. In a related study, Berg, Bjornram, Hartelius, Laakso, and Johnels (2003) found that individuals with PD and normal cognitive status (as quantified by a dementia screening test) were impaired on the Making Inferences and Sentence Analysis subtests of a Swedish, high-level language test. On the remaining subtests, there was no significant difference between individuals with or without PD, although the PD group consistently scored lower on all subtests. Other PD studies have similarly documented deficits in comprehension skills such as inferencing, humor and figurative language interpretation, and identification of speech acts or intentions (Anderson, Simpson, Channon, Samuel, & Brown, 2013; Bhat, Iyengar, & Chengappa, 2001; Holtgraves & McNamara, 2010; McKinlay, Dalrymple-Alford, Grace & Roger, 2009; Monetta, Grindrod, & Pell, 2009; Monetta & Pell, 2007; Tremblay, Monchi, Hudon, Macoir, & Monetta, 2012). Except for the Murray and Stout (1999) and Monetta et al. (2009) investigations, however, the high-level language comprehension tasks used in these studies involved stimuli that were limited to single sentences or a couple of utterances. Collectively, current evidence demonstrates that difficulties with comprehension at the sentence level are common in PD (e.g., Bhat et al., 2001; Colman et al., 2011). Problems at a discourse level are possible as well (Murray & Stout, 1999; Monetta et al., 2009) but have not yet received as much empirical investigation. Furthermore, with few exceptions, these comprehension deficits have been investigated through listening rather than reading tasks (Colman

et al., 2011; Geyer & Grossman, 1994; Grossman et al., 2000, 2002; Hochstadt et al., 2006; Tremblay et al., 2012), even though many individuals with PD self-report difficulties with reading (Davidsdottir, Cronin-Golomb, & Lee, 2005; Hunt, Sadun, & Bass, 1995; Pagonabarraga & Kulisevsky, 2012; Seichepine et al., 2011). Consequently, whether individuals with PD experience difficulties with written material, particularly at the discourse level, remains unresolved. Beyond this comprehension literature, a second line of evidence suggests that PD may compromise reading abilities. In PD, cognitive functions such as visuospatial perception, working and verbal memory, and executive processes such as inhibition are frequently compromised (Litvan et al., 2012; Pagonabarraga & Kulisevsky, 2012; Troster, 2011). In healthy and other patient populations, however, these cognitive functions have been associated with discourse comprehension, reading skills, or both (Borella, Caretti, & Pelegrina, 2010; Brannan & Williams, 1988; Coelho, 2005; Hudon et al., 2006; Karasinski & Ellis Weismer, 2010; Monetta et al., 2009; Tompkins, 2012; Troster, 2011; Yuill, Oakhill, & Parkin, 1989). For instance, Caretti, Borella, Cornoldi, and de Beni (2008) performed a meta-analysis of studies investigating the relationship between working memory and reading comprehension in healthy children and young adults. Participants in each reviewed study were divided into good and poor comprehension groups. Statistical analysis revealed that effect sizes were relatively large for comparisons between the good and poor comprehension groups, regardless of age, on verbal complex span, executive function, and verbal working memory measures, suggesting that these memory and executive skills play a role in reading comprehension across the life span. In addition, older adults with mild cognitive impairment (MCI) have been shown to have difficulty with memory for written information. Hudon and colleagues (2006) asked adults with MCI, Alzheimer’s disease (AD), or no disorder to read and remember a short story. The adults with MCI performed significantly more poorly than the control participants on immediate and delayed recall of main ideas and detail information, and both the MCI and control groups outperformed the AD group. Thus, more subtle cognitive deficits such as those experienced by individuals with MCI and, as discussed below, observed in many individuals with PD (e.g., Litvan et al., 2012), including those in the earliest stages of the disease, have the potential to negatively affect their retention of reading material. The reported prevalence, severity, and types of cognitive impairments in PD have varied in prior investigations (Kudlicka, Clare, & Hindle, 2011; Litvan et al., 2012; Pagonabarraga & Kulisevsky, 2012; Tremblay, Achim, Macoir, & Monetta, 2013; Troster, 2011). As an example, within the recent influx of studies providing evidence of the coexistence of MCI and PD (Aarsland et al. 2009, 2010; Anderson et al., 2013; Litvan et al., 2012; Monchi, Degroot, Mejia-Constain, & Bruneau, 2012; Song et al., 2008), MCI prevalence rates have varied from 15% to 62%, and the breadth of MCI subtypes has been observed (e.g., single vs. multiple domain; amnestic vs. nonamnestic; Troster, 2011).

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Regardless, it is agreed that PD can cause cognitive deficits, which become less circumscribed and more transparent as the disease advances (Aarsland et al., 2009; Pagonabarraga & Kulisevsky, 2012; Troster, 2011; Williams-Gray, Foltynie, Brayne, Robbins, & Barker, 2007). Cognitive skills that have been consistently reported to decline, even in those in the earliest stages of PD or without broad cognitive deterioration or dementia, include inhibition and cognitive set switching (Colman et al., 2009, 2011; Hochstadt, 2009; Kensinger, Shearer, Locascio, Growden, & Corkin, 2003; Marí-Beffa, Hayes, Machado, & Hindle, 2005; Monetta et al., 2009; Pollux & Robertson, 2002; Uc et al., 2005, 2006); working memory (Botha & Carr, 2012; Grossman et al., 1992; Hochstadt et al., 2006; Kensinger et al., 2003; Monetta & Pell, 2007; Monetta et al., 2009); verbal learning and recall (Bohlhalter, Abela, Weniger, & Weder, 2009; Murray & Stout, 1999; Song et al., 2008; Uc et al., 2006); attention, particularly visual attention (Colman et al., 2009, 2011; Filoteo, Williams, Rilling, & Roberts, 1997; Grossman et al., 2002; Murray & Stout, 1999; Rodriguez-Ferreiro, Cuetos, Herrera, Menéndez, & Ribacoba, 2010; Uc et al., 2005, 2006); visuospatial perception and construction (Botha & Carr, 2012; Crucian & Oken, 2003; Davidsdottir et al., 2005; Hunt et al., 1995; Seichepine et al., 2011; Uc et al., 2005, 2006); and processing speed (Grossman et al., 2002, 2003; Lee, Wild, Hollnagel, & Grafman, 1999; McKinlay et al., 2009; Uc et al., 2005, 2006). A potent association has been identified between these cognitive impairments and certain language and communication difficulties in PD (Altmann & Troche, 2011; Anderson et al., 2013; Colman et al., 2009, 2011; Grossman et al., 2002, 2003; Hochstadt, 2009; Hochstadt et al., 2006; Huber & Darling, 2011; Longworth et al., 2005; McKinlay et al., 2009; Monetta et al., 2009; Murray, 2000; Roberts-South & Orange, in press; Tremblay et al., 2012). Most studies in this line of research have examined the nature of sentence comprehension deficits in PD (e.g., Grossman et al., 2002, 2003; Colman et al., 2011). For example Hochstadt and colleagues (2006) found that both working memory and set-shifting were correlated with sentence listening comprehension in their participants with PD. Monetta and Pell (2007) examined the association between language comprehension and working memory in PD by administering a metaphorical sentence judgment reading task (i.e., whether each sentence made sense) and a verbal span task, respectively. They found that nine of 17 participants with PD had a working memory impairment (i.e., scores significantly lower than control participants): Whereas compared to control participants, all participants with PD were noted to have a slower response time and make more errors on the metaphorical sentence task, only those in the PD group with a working memory deficit had statistically significantly worse sentence task response times and error rates than control participants. In one of the few studies to examine discourselevel comprehension, Murray and Stout (1999) reported a strong relationship between the listening DCT performances of their participants with PD and general cognitive status and attention test results; neither immediate nor delayed verbal

recall scores, however, correlated with DCT performances. These identified associations between cognitive deficits and language symptoms warrant exploring correlations between cognitive status and reading abilities in individuals with PD, particularly given the applied implications of determining the functional nature of reading deficits if present (i.e., selecting treatment protocols or compensatory strategies that target cognitive functions, linguistic processes, or both). Among those individuals with PD who self-report reading difficulties, many attribute their reading problems to concentration issues (Davidsdottir et al., 2005), further suggesting a possibly influential relationship between cognitive status and reading in PD. To summarize, the current literature suggests that reading comprehension difficulties at the discourse level are likely in PD, given that deficits in reading and auditory comprehension at the sentence level (e.g., Grossman et al, 1991), auditory comprehension at the discourse level (e.g., Murray & Stout, 1999), and cognitive skills such as visuospatial perception, visual attention, and working memory (e.g., Uc et al., 2005), which support reading (e.g., Caretti et al, 2008), have been documented. Further, prior PD researchers have identified a potent relationship between the integrity of certain cognitive and language processing abilities (e.g., McKinlay et al., 2009). Given that there has been negligible exploration of either reading at the discourse level or the nature of these possible reading difficulties in individuals with PD, the current study was designed to examine the following hypotheses: 1.

Participants with PD who do not present with dementia will perform more poorly in terms of accuracy and speed than age- and education-matched, healthy adults on reading comprehension tests.

2.

Performance on reading comprehension tests will be correlated with performance on cognitive measures for both PD and control groups.

Method Participants Eleven participants with a diagnosis of PD and nine healthy adults, age- and education-matched to the PD group, participated (see Table 1), with no significant difference between the participant groups in terms of age, t(18) = 0.195, p > .8, or education, t(18) = 0.00, p = 1. All participants had no history of traumatic brain injury, stroke, alcohol or substance abuse; a preexisting reading, language, or memory impairment; or psychiatric illness or clinical depression within the previous 6 months, and were right-handed, native speakers of English. As in Murray (2000), visual acuity was considered adequate if subjects were able to read aloud newsprint, and hearing acuity was considered adequate if subjects scored better than 80% on the Speech Discrimination subtest of the Arizona Battery of Communication Disorders in Dementia (Bayles & Tomoeda, 1991); all participants met these criteria. Participants with PD signed

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Table 1. Participant characteristics.

Agea

Education (years)b

1 4 5 7 9 10 11 12 13 15 16

66 63 64 73 75 67 72 74 76 61 61

14 18 12 18 16 16 12 16 18 18 18

2 3 6 8 14 17 18 19 20

66 60 65 64 68 67 75 74 72

12 16 14 18 14 20 18 14 18

Participant

UPDRS scorec

Gender

PD medication

male male female male male male male male male male female

C-L C-L, selegiline C-L C-L C-L, bromocriptine C-L C-L, selegiline C-L C-L rasagiline C-L

PD group 19 14 22 18 19 15 20 17 19 12 22 Control group female male female female female male male male male

Note. UPDRS = Unified Parkinson’s Disease Rating Scale, modified for patient self-report. PD = Parkinson’s disease; C-L = carbidopa-levodopa. a MPD group = 67.9; Mcontrol group = 68.4. bMPD group = 16.0; Mcontrol group = 16.0. cUPDRS maximum score = 68, with higher scores indicating greater symptom severity.

HIPAA medical release forms to allow the researchers to confirm a diagnosis of PD from the participants’ medical records. This study was approved by the Indiana University Institutional Review Board, with all participants giving informed consent prior to participating in the study.

Procedure Participants completed the test battery described below, with the order of tests randomized across participants to reduce the impact of fatigue and minimize order effects. Testing lasted approximately 3–4 hr and took place in one or two sessions, depending on each participant’s preference. Participants were given as many breaks as they requested during each testing session. As in prior studies (e.g., Monetta et al., 2009), participants with PD were asked to schedule testing sessions to coincide with their PD medication peaks. Participants with PD completed the modified version of the Unified Parkinson’s Disease Rating Scale (UPDRS; Louis, Lynch, Marder, & Fahn, 1996). This version consists of the first 17 items from the original UPDRS, modified for patient self-report. The modified UPDRS was chosen to provide information on the particpants’ perceptions of the impact of PD on their cognition, emotional status, activities of daily living, and motor symptoms. Individuals with PD have been shown to reliably self-report their symptoms using the UPDRS section on activities of daily living (MartínezMartín et al., 2003) and, when using the modified UPDRS, have high levels of agreement with both caregiver and neurologist assessments (Louis et al., 1996).

Several measures were included in the test battery to evaluate cognitive abilities. First, the Dementia Rating Scales—2 (DRS; Mattis, 2001) was administered to each subject to determine the extent of any overall cognitive deficits. The DRS has been used in several prior studies of language and cognition in patients with PD (e.g., Murray, 2000; Murray & Stout, 1999; Piatt, Fields, Paolo, Koller, & Troster, 1999) and has been found to correlate with receptive language skills (Murray, 2000). The Map Search subtest of the Test of Everyday Attention (TEA; Robertson, Ward, Ridgeway, & Nimmo-Smith, 1994) was administered to assess visual scanning and selective attention. Previous researchers has documented that individuals with PD frequently have difficulties with visual search and visual attention (e.g., Uc et al., 2005). Likewise, because visual attention deficits have been demonstrated to negatively affect reading in acquired and developmental language disorders (e.g., Borella et al., 2010; Coelho, 2005; Mayer & Murray, 2002), it was anticipated that visual attention may similarly influence reading in other patient populations. The Judgment of Line Orientation Test (JLOT; Benton, Hamsher, Varney, & Spreen, 1983) was used to evaluate visuospatial perception. Individuals with PD have been shown to score lower and have a different pattern of errors than control participants on this measure (e.g., Finton, Lucas, Graff-Radford, & Uitti, 1998; Montse, Pere, Carme, Francesc, & Eduardo, 2001). Of note, children with reading comprehension disorders also perform more poorly on the JLOT than their peers with normal reading skills (Lindgren, de Renzi, & Richman, 1985).

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All participants completed a sentence reading span task to assess verbal working memory (Daneman & Carpenter, 1983). The task consisted of five sets of two, three, four, or five sentences and three sets of six sentences, which were displayed one sentence at a time; each sentence was printed in 20-point Times New Roman on a sheet of 8.5 in. × 11 in. white paper. Participants were instructed to begin reading aloud each sentence as soon as the sentence was displayed. Once the participant had finished reading one sentence, the next sentence in that set was immediately displayed, and the participant began reading the new sentence. When all sentences in a set had been read aloud, the participant was asked to recall the final word of each sentence in the set. Testing began with sets of two sentences and increased in the number of sentences per set until the participant failed to correctly name the final words in three out of five sets of sentences at a given level. The highest level at which the participant correctly named the final words in at least three of five sets of sentences was that participant’s sentence span. Previous studies have demonstrated that individuals with PD (e.g., Hochstadt et al., 2006; Kensinger et al., 2003) as well as typically developing children with poor reading comprehension (e.g., Borella et al., 2010) have impaired performance on sentence span tasks. The flanker task was administered via a laptop computer to assess inhibitory skills (Costa, Hernandez, & Sebastián-Gallés, 2008; Luk, Anderson, Craik, Grady, & Bialystok, 2010). To introduce the task, participants were presented with a white fixation dot for 500 ms, followed by a right- (>) or left-facing arrow ( .40. Analysis of the flanker task data revealed no significant group differences for overall average reaction time, t(18) = 1.48, p > .1, or average reaction time in the congruent condition, t(18) = 1.13, p > .2. Average reaction time in the incongruent condition, however, approached significance, t(18) = 1.89, p = .075, with PD participants reacting more slowly than control participants. No significant group differences were found for flanker task accuracy. Correlational analyses indicated that for the participants with PD there was a significant association ( p < .05) between DRS Memory and both DCT, r = .799, and GORT total scores, r = .629 (see Table 4). Several significant correlations were also identified when the DCT questions were

Table 2. Reading and language test results. PD patients Variable TOAL Opposites Derivations Analogies Similarities Spoken total (max. = 111) Written total (max. = 70) DCT Details, implied Details, stated Main ideas, implied Main ideas, stated Average time reading Average time on question(s) Total correct (max. = 120) GORT Maximum reading level Average time reading Average time on questions Total correct (max. = 50)

Controls

M (SD)

Range

M (SD)

Range

23.4 (3.3) 35.7 (9.0) 16.7 (2.4) 21.2 (6.3) 75.8 (13.2) 39.4 (9.5)

16–28 35–50 11–20 19–32 47–94 21–50

26.8 (2.9) 45.1 (4.5) 19.6 (2.3) 27.2 (4.4) 91.4 (8.9) 49.4 (5.3)

20–30 35–50 15–23 19–32 70–101 40–56

26.5 (3.6) 28.0 (5.8) 21.2 (2.5) 22.5 (1.7) 79.4 (34.5) 92.4 (24.0) 98.2 (11.5)

23–31 16–35 15–24 20–24 50–152 68–147 74–113

28.0 (3.3) 30.7 (2.7) 21.9 (1.1) 23.1 (0.8) 89.8 (23.0) 77.4 (13.9) 104.0 (6.8)

21–33 27–34 21–24 22–24 51–122 53–94 91–113

10.7 (1.7) 76.7 (23.1) 81.6 (25.6) 35.4 (5.0)

9–14 53–112 52–138 27–44

13.4 (0.9) 82.1 (16.5) 80.1 (16.9) 41.0 (2.6)

12–14 54–103 54–104 36–44

Note. TOAL = Test of Adolescent and Adult Language; DCT = Discourse Comprehension Test; GORT = Gray Oral Reading Test.

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Table 3. Cognitive test results. PD patients Variable DRS Attention Initiation/Perseveration Construction Conceptualization Memory Total (max = 144) JLOT Flanker task Average RT (ms) Average RT, congruent Average RT, incongruent Total accuracy (%) Accuracy, congruent (%) Accuracy, incongruent (%) Sentence span TEA Total, 1st min Total, 2nd min Total (max. = 80)

Controls

M (SD)

Range

M (SD)

Range

36.1 (0.8) 36.4 (1.8) 6 (0) 37 (1.1) 23.6 (1.4) 139.1 (2.5) 23.8 (3.9)

35–37 31–37 6–6 35–39 20–25 133–142 16–28

36.3 (0.7) 36.6 (0.7) 6 (0) 37.9 (1.1) 24.7 (0.7) 141.4 (1.2) 25.0 (1.7)

35–37 35–37 6–6 36–39 23–25 139–143 23–28

722.5 (165.2) 677.5 (155.9) 756.3 (160.2) 97.0 (3.3) 98.9 (2.4) 95.0 (6.1) 1.9 (0.5)

485.0–1011.0 476.6–953.7 494.6–956.1 91–100 94–400 81–100 1–3

630.7 (87.3) 606.8 (75.8) 644.6 (96.2) 99.3 (1.3) 100.0 (0) 98.7 (2.7) 2.6 (0.5)

521.7–724.9 520.3–724.9 523.3–785.0 97–100 100–100 94–100 2–3

24.9 (11.9) 24.8 (6.0) 49.7 (15.4)

10–46 15–35 26–74

29.8 (5.5) 28.7 (3.7) 58.6 (7.0)

18–35 24–36 42–66

Note. DRS = Dementia Rating Scale; JLOT = Judgment of Line Orientation Test; RT = reaction time; TEA = Test of Everyday Attention, Map Search subtest.

Table 4. Correlations between reading comprehension and language and cognitive test scores for the PD group. Cognitive or language measure DRS Attention Initiation / Perseveration Construction Concepts Memory Total TOAL Opposites Derivations Analogies Similarities Sentence Combining Spoken scale Written scale JLOT Sentence span Flanker task Average RT RT, congruent RT, incongruent Accuracy Accuracy, congruent Accuracy, incongruent TEA UPDRS

DCT total

DCT implied details

DCT stated details

DCT implied main ideas

DCT stated main ideas

GORT total

GORT max. reading level

–.264 –.376 .00 .270 .799* –.191

.117 –.397 .00 .551 .341 –.217

–.227 –.305 .00 –.016 .873* –.146

–.343 –.229 .00 .109 .822* –.073

–.749* –.306 .00 .539 .460 –.214

.421 .077 .00 –.489 .629* .194

.378 .378 .00 –.218 .370 .486

.421 .220 .597 .124 .235 .362 .186 –.194 .164

.260 .108 .456 .005 –.237 .220 –.101 .181 .176

.495 .259 .543 .104 .379 .397 .235 –.284 .127

.485 .276 .561 .206 .409 .409 .328 –.371 .307

–.129 –.042 .364 .168 .154 .005 .180 –.179 –.159

.737* .479 .620* .074 .258 .621* .162 .145 .565

.526 .710* .583 –.014 .094 .719* .032 .174 .412

.336 .298 .361 .099 .039 .161 –.399 –.142

.180 .131 .242 .087 .017 .165 –.416 –.212

.324 .290 .328 .146 .094 .198 –.307 –.189

.284 .285 .291 .051 .010 .091 –.340 –.023

.358 .315 .368 –.091 –.106 –.078 –.250 .177

.180 .194 .155 .458 .418 .496 .183 –.684*

–.012 .037 –.094 .205 .165 .247 .186 –.886*

*p < .05.

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analyzed by type. DRS Memory scores were correlated with performance on questions targeting stated details, r =.873, and implied main ideas, r =.822; DRS Attention scores were negatively correlated with performance on questions targeting stated main ideas, r = –.749. Higher GORT total scores were also significantly associated with better performance of several TOAL subtests: Opposites, r = .737; Derivations, r = .710; Analogies, r = .620; and the Spoken Language scale; r = .621. Similarly, the PD participants’ GORT maximum reading level was significantly correlated with their TOAL Spoken Language scale, r = .719. Additionally, UPDRS self-ratings were significantly negatively correlated with both the GORT total score, r = –.684, and GORT maximum reading level, r = –.886. No other correlations between the reading and cognitive–linguistic test performances of the PD group approached significance. In contrast, most of the significant correlations identified in the PD data were not observed when analyzing the control group’s data (see Table 5). Instead, for the control participants, the DCT total score significantly correlated ( p < .05) with the TOAL Spoken Language, r = .809, and Written Language scales, r = .777, as well as the TOAL Opposites, r = .738, and Derivations subtests, r = .847. Likewise as DCT total scores increase, so too did TEA total scores, r = .809. Several significant correlations were identified when analyzing DCT questions by type, with most of these correlations between DCT question types and TOAL subtests or scales. The exception was a significant negative association between stated main ideas and DRS attention

scores, r = –.754, like that observed for the PD group. On the GORT, the control group’s total score significantly correlated with the TOAL Written Language scale, r = .698, as well as the Similarities subtest, r = .721. Finally, a higher GORT maximum reading level was associated with better performance on the Concepts subtest of the DRS, r = .732, and the Derivations subtest of the TOAL, r = .776.

Discussion Individuals with PD, even those in the early stages of the disease who do not present with dementia, can experience language comprehension difficulties, particularly when faced with processing more complex or high-level language stimuli (Grossman et al., 2002; Hochstadt et al., 2006; Murray & Stout, 1999). Such difficulties appear to be closely linked to the cognitive status of the individual with PD. Prior PD research, however, has primarily focused on auditory comprehension, included only sentence-level stimuli, or both (e.g., Colman et al., 2011; Tremblay et al., 2012), even though individuals with PD voice concern over their reading ability (Davidsdottir et al., 2005). Accordingly, the current study examined the integrity and nature of reading comprehension skills at the discourse level in individuals with PD. The present results did not fully support the hypothesis that participants with PD would demonstrate reduced accuracy and speed on reading comprehension tasks compared to the control group: No significant group differences were

Table 5. Correlations between reading comprehension and language and cognitive test scores for the control group. Cognitive or language measure DRS Attention Initiation / Perseveration Construction Concepts Memory Total TOAL Opposites Derivations Analogies Similarities Sentence Combining Spoken scale Written scale JLOT Sentence span Flanker task Average RT RT, congruent RT, incongruent Accuracy Accuracy, congruent Accuracy, incongruent TEA

DCT total

DCT implied details

DCT stated details

DCT implied main ideas

DCT stated main ideas

GORT total

GORT max. reading level

–.131 –.102 .00 .422 .446 .480

–.107 .00 .00 .429 .480 .579

–.134 –.152 .00 .299 .334 .280

.056 .254 .00 –.013 .112 .235

–.754* .318 .00 .320 .302 .201

.555 –.540 .00 .047 –.139 –.040

–.067 –.434 .00 .732* .067 .369

.292 .424 .727* .322 .047 .492 .286 .646 .135

.514 .579 .256 .721* .223 .520 .698* –.113 .558

.638 .776* .171 .394 .651 .636 .643 –.082 .478

.027 –.126 .084 –.282 .00 –.282 .781*

.317 .506 .179 .222 .00 .222 .202

.00 .036 .080 .607 .00 .607 .498

.738* .847* .581 .588 .605 .809* .777* .289 .211

.777* .807* .443 .546 .686* .766* .783* .174 .143

.534 .678* .528 .420 .442 .645 .560 .273 .060

.396 .387 .398 .168 .00 .168 .809*

.476 .446 .486 .171 .00 .171 .791*

.353 .358 .381 .143 .00 .143 .634

.322 .479 .235 .524 .595 .403 .720* .548 .350 .050 .045 –.003 .209 .00 .209 .497

*p < .05.

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found for speed on either reading test or for accuracy on the DCT. Nevertheless, on the GORT, participants with PD performed less accurately and had a lower maximum reading level than the control group. Failure to identify significant group differences on the DCT contradicted the findings of Murray and Stout (1999), whose participants with PD displayed impaired performance on DCT questions pertaining to implied information. Such contrasting findings are likely the product of both procedural and participant differences. That is, whereas Murray and Stout used the original DCT questions and had participants listen to the stories, the current study utilized questions developed by Fossett and colleagues (2004) and had participants read the stories. Furthermore, compared to the current participants with PD, those in the Murray and Stout (1999) study appeared to have more cognitive issues: (a) They demonstrated visual attention deficits (i.e., significantly poorer TEA scores compared to their control group, a result not observed in the present study); (b) two participants scored within the mild-dementia range on the DRS (vs. none in the current study); and (c) their average DRS score of 132.8 was lower than that of the current PD participants (i.e., 139.1). This pattern of DCT results across studies (i.e., impaired performance only in the presence of more marked cognitive deficits) is consistent with prior research indicating a cognitive basis to language comprehension deficits in PD (e.g., Colman et al., 2011; Grossman et al., 2002, 2003; Hochstadt, 2009; Monetta & Pell, 2007; McKinlay et al., 2009). That reading comprehension impairments in the participants with PD were identified with the GORT but not the DCT may reflect, at least in part, that the DCT stories are less linguistically demanding than those on the GORT. Whereas the DCT stories have a Flesch-Kincaid reading level of 4.4 to 6.0, GORT reading levels vary from 3.7 to 18.8. Thus, the more basic reading skills assessed by the DCT may remain intact longer in PD than the higher-level reading skills tested by the GORT. Previous PD investigations have similarly documented deficits in discourse-level comprehension (Monetta et al., 2009; Murray & Stout, 1999) and other higher-level language skills (Anderson et al., 2013; Berg et al., 2003; Holtgraves & McNamara, 2010; McKinlay et al., 2009), but good performance on more basic comprehension tasks (Anderson et al., 2013; Geyer & Grossman, 1994; Grossman et al., 1992; Monetta et al., 2009), including those found on aphasia tests (Murray & Stout, 1999; Song et al., 2008). Further, the current participants with PD scored significantly lower on the TOAL than the control participants, and some TOAL scores were correlated with GORT performances. In contrast, none of the TOAL and DCT scores were significantly related. Items on the TOAL are presented in order of increasing difficulty, such that lower scores indicate mastery of more basic (i.e., those expected of an elementary school student) but not more advanced language skills (i.e., those expected of a senior high school student). These findings again support the conclusion that the participants with PD were impaired on higher-level language skills, including higher-level reading comprehension, whereas more basic language skills remained intact.

In addition, the GORT appears more sensitive than the DCT to these higher-level reading difficulties. Consistent with our second hypothesis, significant associations were identified between the reading comprehension and cognitive test performances of the participants with PD. Primarily memory scores, however, correlated with reading comprehension even though the test battery evaluated a variety of cognitive functions that in healthy and other patient populations have been shown to support reading, high-level language processing, or both (Borella et al., 2010; Coelho, 2005; Hudon et al., 2006; Tompkins et al., 2002). Even within the memory measures, only those skills probed by the DRS Memory subscale (i.e., orientation, delayed recall of verbal information, and verbal and visual recognition memory; Mattis, 2001) correlated with accuracy on the GORT and DCT. In contrast, working memory, probed by the sentence span task, was not correlated with either reading comprehension measure for either participant group. This result was surprising given that (a) participants with PD scored lower than control participants on both the DRS and sentence span memory measures; (b) a relationship between working memory and other language comprehension tasks has been previously identified in the PD literature (Grossman et al., 1992; Hochstadt, 2009; Hochstadt et al., 2006; McKinlay et al., 2009; Monetta & Pell, 2007); and (c) reading span tasks such as that used in the current study have been shown to evoke use of a similar set of processes as reading comprehension tasks (Engle, Tuholski, Laughlin, & Conway, 1999). It is possible that the method used to score our working memory span task confounded identifying a significant relation with our reading measures. Friedman and Miyake (2005) determined that traditional span scores (e.g., highest set size completed, the measure used in the current study) generated smaller correlations with reading comprehension measures, had lower reliability, and were less normally distributed than continuous span scores (e.g., tallying the number of words recalled). Indeed, in most prior PD studies in which an association between working memory and language comprehension was identified, the span task used yielded a continuous span score (Monetta & Pell, 2007; Monetta et al., 2009) or a much larger sample of participants with PD was included (Hochstadt et al. 2006; McKinlay et al., 2009). Similar to the current findings, Colman et al. (2011) found no relation between a traditional working memory span score and the sentence comprehension performances of their participants with PD. Therefore, to examine the relation between working memory and reading comprehension in the future, researchers might select span measures that allow calculating a continuous span score or consider other working memory measures such as n-back tasks, which generate continuous data (for a review of working memory tests, see Wright & Fergadiotis, 2012). In addition to the DRS Memory score, reading comprehension was correlated with overall PD symptom severity. That is, performance on the GORT was negatively impacted in participants who rated their PD symptoms as more severe on the modified UPDRS. This link between language abilities and PD symptom or disease severity has

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been previously documented in both comprehension (Holtgraves & McNamara, 2010; Monetta et al., 2009) and production studies (Colman et al., 2009). The poorer GORT performance among those with more severe PD symptoms may reflect the influence of increasing memory difficulties, which as previously mentioned also correlated with reading comprehension; additionally or alternately, it may reflect the influence of progressive difficulties with additional cognitive factors (e.g., set-shifting) or PD symptoms (e.g., apathy; oculomotor deficits) not directly evaluated in our current test battery but that have the potential to influence reading or language skills more broadly (Colman et al., 2009; Hunt et al., 1995; Pluck & Brown, 2002). The significant relationship between reading comprehension and symptom severity ratings also likely reflects the progressive deterioration of the neurobiological systems (e.g., basal ganglia and neostriatum pathology) that sustain cognitive–linguistic functioning (Grossman et al., 2003; Holtgraves & McNamara, 2010; Monetta & Pell, 2007). An unexpected finding was a negative correlation between the DRS Attention score and accurate responses to DCT questions pertaining to explicitly stated main ideas. This association was observed for both the PD and the control groups: Individuals who achieved a higher rather than lower DRS Attention score were more likely to make errors when responding to these types of DCT questions. Conversely, the literature has established that questions regarding explicitly stated main ideas are the easiest to answer for both patient and healthy adult populations (Brookshire & Nicholas, 1998; Fossett et al., 2004; Murray & Stout, 1999). Indeed, current participants in the PD and control groups had little difficulty with these types of questions compared to those involving implied information or details, obtaining group mean accuracies of 94% and 96%, respectively. Similarly, participants in the PD and control groups made few errors (range of 0–1 and 0–2 errors, respectively) on the DRS Attention items. Thus, it appears most likely that this negative correlation is spurious, rather than suggestive of a paradoxical role of attention when responding to these types of DCT questions. Other investigators have identified significant correlations between language comprehension and attention or executive functioning not only in individuals with PD (Grossman et al., 1992, 2002; Hochstadt, 2009; Hochstadt et al., 2006; Holtgraves & McNamara, 2010; Monetta et al., 2009; Murray & Stout, 1999; Tremblay et al., 2012; Zanini et al., 2004) but also in other populations (Borella et al., 2010; Cutting, Materek, Cole, Levine, & Mahone, 2009). In contrast, such associations were observed in neither the current nor some prior PD studies (Colman et al., 2011; Grossman et al., 1992; Monetta et al., 2009; Tremblay et al., 2012). One likely explanation for these mixed findings relates to the array of language comprehension, attention, and executive function measures used across PD studies to date (Kudlicka et al., 2011). For example, inhibition has been frequently assessed using the Stroop task (Colman et al., 2011; Grossman et al., 2002; Holtgraves & McNamara,

2010; Tremblay et al., 2012). We selected a go-no-go task (i.e., flanker task) with nominal speech-language response demands, which in turn, may have moderated the relationship between reading comprehension and inhibition for both our PD and control groups. Even when both the Stroop and similar language comprehension tasks have been utilized, however, both positive (e.g., Grossman et al., 2002) and null (e.g., Colman et al., 2011) correlations have been reported. Thus in addition to considering the types of tasks used, discrepant correlational outcomes might also be attributed to variation in participant characteristics. Across studies, PD samples have differed in terms of their cognitive profiles (e.g., Murray and Stout, 1999, who included individuals with mild dementia, vs. Tremblay et al., 2012, whose PD sample had subtle, isolated cognitive deficits) as well as other factors known to influence cognitive functioning such as being on (e.g., Monetta et al., 2009) versus off medications (e.g., Tremblay et al., 2012) or presenting with or without depression (e.g., Tremblay et al., 2012). Although, as in the current investigation, comprehension performance was more likely to be correlated with cognitive ability that was versus was not significantly impaired (Colman et al., 2011; Grossman et al., 1992; Tremblay et al. 2012), further research using more systematic and standardized assessment procedures is clearly needed to reconcile these contrasting correlational findings and confirm specific cognitive–linguistic relationships in PD. The current study has extended the cognitive–linguistic profile previously ascribed to PD by identifying discourselevel reading comprehension deficits. Of note, such reading impairments were documented in participants who were in the relatively early stages of PD and did not present with dementia or broad cognitive deficits. In fact, several of the participants continued to work, at least part time. In addition, the assessment took place under conditions that would maximize rather than compromise reading and other cognitive–linguistic abilities. For instance, participants scheduled testing to coincide with their PD medication peaks. Recent research suggests that in the early stages of PD, dopaminergic medications, like those our participants were taking, positively affect cognitive functioning (Crucian & Oken, 2003; Pagonabarraga & Kulisevsky, 2012). Furthermore, distractions were minimized during testing, and, although reading tasks were timed, task instructions did not place time constraints on the participants. Nevertheless, reading comprehension deficits were still evident. Indeed several current participants with PD made comments to the researchers similar to “I don’t read much anymore; it’s too hard now.” Comparable sentiments have been noted for some time in the PD literature (Davidsdottir et al., 2005; Hunt et al., 1995; Seichepine et al., 2011). Several limitations in the present investigation must be acknowledged. First, the small sample size of the participant groups limits confidence in the reliability of our statistical findings (Button et al., 2013). For instance, failure to identify previously identified relationships between language comprehension and attention or executive functioning may have been due to low statistical power, rather than or in addition

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to methodological differences between the current and prior studies. Second, several participant characteristics were not recorded and/or could not be controlled such as (a) medication regimes (e.g., different amounts and timing of medication), which could differentially affect specific linguistic and cognitive functions (Crucian & Oken, 2003; Pagonabarraga & Kulisevsky, 2012; Uc et al., 2005) and (b) presence and/or onset characteristics of symptoms (e.g., visual hallucinations, initial tremor versus nontremor symptoms, side of motor symptom onset), which have been shown to influence the types and severity of cognitive deficits in PD (Botha & Carr, 2012; Pagonabarraga & Kulisevsky, 2012; Seichepine et al., 2011; Tremblay et al., 2013). Documenting and controlling these participant variables in future studies would assist in determining which individuals with PD are at greatest risk of developing reading difficulties. In addition, only individuals in the early stages of PD with no dementia were included in this study. Whether greater severity of PD would exacerbate the reading difficulties observed in this participant sample should be determined by including individuals in the later stages of the disease or, ideally, through longitudinal research. Finally, our test battery itself was relatively broad, assessing a variety of cognitive and linguistic functions. Nevertheless, it lacked the depth to identify precisely which components of the domains tested were most affected in PD and might underlie reading comprehension difficulties. For example, within the domain of attention, only visual selective attention was tested, leaving open the possibility that other attention functions and modalities may have been impaired and contributed to reading comprehension problems. Given the role reading plays in many daily activities, including those for pleasure, self-care, or work-related purposes, identifying and treating reading comprehension deficits have the potential to positively impact the quality of life of individuals with PD. Of note, whereas many participants in the current study had received speech therapy for their motor speech symptoms, none had been referred for or received services to identify or manage cognitive– linguistic symptoms. The current findings suggest that the GORT may be more sensitive than the DCT to reading comprehension difficulties in the early stages of PD and that these reading difficulties are most closely related to memory, high-level language, and PD symptom severity status. Additional research, however, is needed to determine the reliability of this diagnostic recommendation and to delineate further the types and nature of reading comprehension impairments in PD so as to guide management of this cognitive–linguistic symptom.

Acknowledgments This study was funded in part by the 2011 ASHA Students Preparing for Academic and Research Careers (SPARC) Award, awarded to the second author. We thank the members of the Fort Wayne, IN, Parkinson’s Support Group and research assistant Sarah McNeil.

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S258 American Journal of Speech-Language Pathology • Vol. 23 • S246–S258 • May 2014

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