Are Moral and Socio-conventional Knowledge Impaired in Severe Traumatic Brain Injury?

Are Moral and Socio-conventional Knowledge Impaired in Severe Traumatic Brain Injury? Abstract Objective The aim of this study was to investigate explicit moral and socio-conventional knowledge in Traumatic Brain Injury (TBI) patients. Method A group of 28 TBI patients was tested on a new set of moral and socio-conventional items. Responses of TBI patients were compared with those of 28 matched controls. Participants had to report how hard would be to perform specific moral or socio-conventional transgressions, using a 10-point Likert scale. We analyzed our data through mixed-effects models, to jointly assess by-participants and by-items variance. The factors considered were Type of Item (Moral vs. Socio-conventional) and Group (TBI vs. Controls). Results Results revealed a significant interaction between Type of Item and Group (χ2[1] = 25.5, p < .001). Simple-effects analyses showed that TBI, as Controls, were able to differentiate moral and socio-conventional transgressions (χ2[1] = 72.3, p < .001), as they deemed the former as more difficult to enact. TBI patients, however, evaluated moral transgressions as easier to fulfill (χ2[1] = 12.2, p = .001). Conclusions TBI patients can clearly differentiate moral and socio-conventional transgressions, suggesting that the explicit knowledge of these two dimensions is spared. TBI patients, however, considered moral transgressions as easier to fulfill with respect to Controls. This finding may suggest a tendency in TBI patients to underestimate the weight of moral transgressions. Neuropsychology, Traumatic brain injury, Social cognition, Morality Introduction Traumatic brain injury (TBI) constitutes a major health and socioeconomic problem that affects all societies throughout the world (Maas, Stocchetti, & Bullock, 2008). For diagnostic and research purposes there is a need to categorize patients along the spectrum of severity (mild, moderate, severe). Moderate-to-severe TBI patients commonly have ongoing physical, cognitive, and psychosocial sequelae. Psychosocial aspects refer to the emotional and behavioral components of the individual’s social functioning, such as the lack of initiative, impulsivity, irritability, socially inappropriate behavior, self-centeredness, and changes in affect (Ponsford, Olver, & Curran, 1995). The presence of emotional and behavioral problems following severe TBI has been associated with poor social adjustment, such as an inability to resume pre-injury activities and relationships (Tate & Broe, 1999). The long-term psychosocial functioning can remain impaired up to 17 years after the injury (Wood & Rutterford, 2006). The recent interest of social neuroscience for the impaired social perceptiveness in TBI patients is beginning to foster a better understanding of social and moral cognition in these patients. Social cognition refers to the ability to recognize and interpret interpersonal cues that enable us to understand and predict the other’s behavior. For severe TBI patients, the most common deficits in terms of social cognition entail the perception of emotions, empathy, and theory of mind (McDonald, 2013). Some empirical studies suggest that explicit social knowledge may be spared in severe TBI patients (Beer, John, Scabini, & Knight, 2006; Milne & Grafman, 2001; McDonald, Saad, & James, 2011; Turkstra, Dixon, & Baker, 2004), whereas others have found evidence of impaired social judgment, thus questioning this claim (Dimitrov, Grafman, & Hollnagel, 1996). With respect to implicit social knowledge, the issue is even more strongly debated (McDonald et al., 2011; Milne & Grafman, 2001). Moral cognition, instead, refers to the ability to follow ethical and accepted rules and norms (Blair & Cipolotti, 2000). A common way to test moral reasoning is through moral dilemmas involving a conflicting choice between two undesirable alternatives. In these dilemmas, both alternatives yield negative consequences, and none of them clearly emerge as the right choice in moral terms (e.g., choosing between killing one person and letting many people die). Moral cognition in relation to TBI has been scarcely investigated. In fact, to the best of our knowledge, there has been no empirical study providing clear evidence of spared explicit moral knowledge in severe TBI adult patients. If anything, a recent preliminary study has shown that adolescents with moderate-severe TBI display poorer moral reasoning abilities compared to healthy controls (Beauchamp, Dooley, & Anderson, 2013). Given the scarce and conflicting evidence regarding social and moral reasoning in TBI, and the potential key-role of these faculties in the understanding of the psychosocial sequelae associated to TBI, the aim of this study was to directly assess moral and social knowledge in TBI patients, in order to shed light on the potential differences with respect to a group of matched controls. The relationship between explicit moral and social knowledge is usually investigated with the moral/conventional paradigm introduced by Turiel (1983). This author proposed a set of features that sharply distinguish moral from conventional transgressions. According to Turiel, people distinguish conventional (precisely, socio-conventional) from moral transgressions. Specifically, normally developing individuals recognize that some transgressions appear to be matters of social conventions because they are contingent, local, and their wrongness is justified by referring to social order. Moral transgressions, by contrast, are perceived to be universally wrong (independent of convention), more punishable, and their wrongness is justified by referring on harm, injustice, and rights violations. Under this perspective, moral norms tend to be treated as universally applicable, whereas the validity of social conventions is more context-dependent. Indeed, moral norms are considered as characterized by a normative force that operates independently of extant structures of authority or social order. The ability to draw this distinction is deemed as a critical sign of moral knowledge, intended as the faculty to evaluate activities under a specific moral perspective and to make judgments about those activities using distinct moral features. In fact, the ability to distinguish moral from social-conventional transgressions has often been considered as a critical point to support the claim that morality constitutes a distinct cognitive domain (Dwyer, 1999; Hauser, 2006; Mikhail, 2011). Morality is characterized as a universal code of conduct that individuals consider as most important. In committing to this normative aspect of morality, people recognize that there are situations in everyday life that requires a moral response, and that some moral responses are more appropriate than others. People are able to provide justification of their conduct in light of such moral norms, and are able to make moral evaluations of one’s own and others’ actions and behaviors. Furthermore, people are committed to regard some behaviors as immoral, including some behaviors that people themselves are tempted to perform (Dwyer, 1999). Despite the space of moral and social transgression is wide, people have shown that they are able to determine which sorts of transgressions are moral and which are conventional (Huebner, Lee, & Hauser, 2010). For these reasons, it is conceivable that moral cognition, that underlies this ability, could represent a specific cognitive dimension (Hauser, 2006; Mikhail, 2011; Turiel, 1979). Research on the moral-conventional distinction has relied almost exclusively on scenarios designed for young children, even where participants are adults or incarcerated psychopaths (Blair, 1995; Blair & Cipolotti, 2000). Furthermore, to the best of our knowledge, there are no studies that have investigated this distinction on a sizeable sample of TBI patients. For these reasons, using a new and more suitable set of moral/socio-conventional items, the present study investigated the features defining this distinction in order to evaluate more precisely patients’ social and moral cognition, and in order to better clarify whether explicit moral and social knowledge were spared in severe TBI chronic patients. Method Participants Twenty-eight outpatients (21 males, 7 females) with a mean age of 36.29 years (SD = 11.92) and a mean education of 10.39 years (SD = 2.73) were recruited from the TBI database of Physical Medicine and Rehabilitation Unit of Papa Giovanni XXIII Hospital of Bergamo. The distribution of age for TBI patients is represented in Fig. 1. Fig. 1. View largeDownload slide Age distribution in the sample of TBI patients (controls were matched). Fig. 1. View largeDownload slide Age distribution in the sample of TBI patients (controls were matched). Inclusion criteria were: presence of severe traumatic brain injury, defined by GCS < 8 or evidence of posttraumatic amnesia > 7 days (Stein, 1996); chronic phase of patients’ recovery (i.e., at least 1 year postinjury); fluency in Italian; age from 18 to 70 years. Exclusion criteria were: presence of pre-accident history of developmental, neurological, or psychiatric disorders; positive history of alcohol or drug dependency; persistent postinjury language deficits or neglect. Twenty-eight control participants (21 males, 7 females) with a mean age of 36.50 years (SD = 11.52) and a mean education of 10.71 years (SD = 2.59) were recruited among friends and family members of the staff at the Physical Medicine and Rehabilitation Unit. The exclusion criteria were: positive history of developmental, neurological, or psychiatric disorders. The TBI and the control group did not differ in age (t = –.07, df = 54, p = .95) and years of education (t = –.45, df = 54, p = .65). TBI and control participants were enrolled in a larger four-sessions study, of which the present research represents a part. Testing occurred, on average, 7.04 years (SD = 6.90) after the injury. The TBI group had a mean length of Post-Traumatic Amnesia (PTA) of 90.75 days (SD = 43.39). The group was characterized by heterogeneity of traumatic injuries in terms of pathophysiology (contusions, hemorrhages, hematomas, diffuse axonal injury, etc.), and location of brain lesions, documented by CT or MRI scans. Demographic and clinical details are provided in Table 1. Table 1. Demographic and clinical features of participants with traumatic brain injuries Subject No. Age (years) Education (years) Gender Length of PTA (days) GCS Time postinjury (years) Cause of TBI Brain damage reported on acute phase neuroimaging 1 27 8 M 29 N/A 10 MVA SDH L T-P lobe 2 22 11 M 81 5 4 MVA Contusions Bilat F + R T lobes, R BG, L Thalamus, L Corpus Callosum, DAI 3 41 13 M 56 8 1 Fall SAH, L SDH, Contusion R T lobe 4 32 8 M 147 3 17 MVA Diffuse Edema, EDH L and R, Contusion R F lobe 5 21 8 M 51 5 3 MVA Ped SAH, R SDH, Contusions R T + Bilat F lobes 6 51 8 M 98 4 3 MVA SAH, ICH, Contusions R F Lobe, Corpus Callosum, DAI 7 59 13 M 95 7 5 MVA SAH, Contusions Bilat F + L T + R P lobes 8 30 11 M 83 5 14 MVA Diffuse Edema, SAH, Contusion R F lobe 9 31 11 M 84 4 15 MVA Diffuse Edema, EDH L P-O lobe, Contusions Bilat F-T-P lobes + L Cerebellum, R BG 10 63 8 M 53 6 4 SRHI SAH Bilat, Contusions Bilat F lobes, SDH R P, DAI 11 24 8 M 178 7 6 MVA L SDH, Contusions Bilat F + R O lobes 12 42 13 M 17 7 2 Fall SAH, SDH L T lobe, Contusions Bilat F + R T lobes 13 32 13 M 71 5 14 MVA R Hemispheric Edema, Contusions F-T lobes, R BG 14 49 8 M 172 3 9 MVA Extensive Contusions Bilat F-T lobes 15 31 8 M 142 4 7 MVA EDH L F-T lobe, Contusions Bilat F + L T lobes 16 36 13 M 126 3 10 MVA Diffuse Edema, SAH, Contusions Bilat F + L T lobes, L Thalamus, DAI 17 56 8 M 35 N/A 33 MVA SAH, Contusions Bilat F lobes 18 42 13 M 134 5 1 MVA SAH, Contusions Bilat F lobes, L thalamus, Corpus Callosum, DAI 19 26 8 F 34 5 2 MVA SAH, ICH, Contusions Bilat T-P lobes 20 29 18 F 112 N/A 1 MVA EDH Bilat, Contusions Bilat F + R P + Bilat O lobes 21 37 8 M 118 6 8 MVA SDH Bilat F lobes, Contusions R F lobes, Corpus Callosum, R thalamus, DAI 22 24 8 M 89 N/A 1 MVA Contusions Bilat F-T + Bilat F-P lobes, Corpus Callosum, DAI 23 38 13 F 131 3 1 MVA SAH, L SDH, Contusions L F-T lobes 24 29 11 M 87 7 7 MVA SAH, Contusions Bilat F lobes, L internal capsule, DAI 25 27 13 F 98 3 7 MVA SAH, Contusions Bilat F lobes 26 43 8 F 30 N/A 5 MVA Ped SAH, Contusions L F-P lobes, Corpus Callosum 27 22 13 F 113 4 1 MVA Ped L EDH, R BG, Contusions Bilat F-T lobes, Corpus Callosum, DAI 28 52 8 F 77 N/A 6 MVA Contusions Bilat T lobes Subject No. Age (years) Education (years) Gender Length of PTA (days) GCS Time postinjury (years) Cause of TBI Brain damage reported on acute phase neuroimaging 1 27 8 M 29 N/A 10 MVA SDH L T-P lobe 2 22 11 M 81 5 4 MVA Contusions Bilat F + R T lobes, R BG, L Thalamus, L Corpus Callosum, DAI 3 41 13 M 56 8 1 Fall SAH, L SDH, Contusion R T lobe 4 32 8 M 147 3 17 MVA Diffuse Edema, EDH L and R, Contusion R F lobe 5 21 8 M 51 5 3 MVA Ped SAH, R SDH, Contusions R T + Bilat F lobes 6 51 8 M 98 4 3 MVA SAH, ICH, Contusions R F Lobe, Corpus Callosum, DAI 7 59 13 M 95 7 5 MVA SAH, Contusions Bilat F + L T + R P lobes 8 30 11 M 83 5 14 MVA Diffuse Edema, SAH, Contusion R F lobe 9 31 11 M 84 4 15 MVA Diffuse Edema, EDH L P-O lobe, Contusions Bilat F-T-P lobes + L Cerebellum, R BG 10 63 8 M 53 6 4 SRHI SAH Bilat, Contusions Bilat F lobes, SDH R P, DAI 11 24 8 M 178 7 6 MVA L SDH, Contusions Bilat F + R O lobes 12 42 13 M 17 7 2 Fall SAH, SDH L T lobe, Contusions Bilat F + R T lobes 13 32 13 M 71 5 14 MVA R Hemispheric Edema, Contusions F-T lobes, R BG 14 49 8 M 172 3 9 MVA Extensive Contusions Bilat F-T lobes 15 31 8 M 142 4 7 MVA EDH L F-T lobe, Contusions Bilat F + L T lobes 16 36 13 M 126 3 10 MVA Diffuse Edema, SAH, Contusions Bilat F + L T lobes, L Thalamus, DAI 17 56 8 M 35 N/A 33 MVA SAH, Contusions Bilat F lobes 18 42 13 M 134 5 1 MVA SAH, Contusions Bilat F lobes, L thalamus, Corpus Callosum, DAI 19 26 8 F 34 5 2 MVA SAH, ICH, Contusions Bilat T-P lobes 20 29 18 F 112 N/A 1 MVA EDH Bilat, Contusions Bilat F + R P + Bilat O lobes 21 37 8 M 118 6 8 MVA SDH Bilat F lobes, Contusions R F lobes, Corpus Callosum, R thalamus, DAI 22 24 8 M 89 N/A 1 MVA Contusions Bilat F-T + Bilat F-P lobes, Corpus Callosum, DAI 23 38 13 F 131 3 1 MVA SAH, L SDH, Contusions L F-T lobes 24 29 11 M 87 7 7 MVA SAH, Contusions Bilat F lobes, L internal capsule, DAI 25 27 13 F 98 3 7 MVA SAH, Contusions Bilat F lobes 26 43 8 F 30 N/A 5 MVA Ped SAH, Contusions L F-P lobes, Corpus Callosum 27 22 13 F 113 4 1 MVA Ped L EDH, R BG, Contusions Bilat F-T lobes, Corpus Callosum, DAI 28 52 8 F 77 N/A 6 MVA Contusions Bilat T lobes Note. PTA = posttraumatic amnesia, GCS = Glasgow Coma Scale; M = male; F = female; MVA = motor vehicle accident; MVA Ped = motor vehicle accident as pedestrian; SRHI = sports-related head injury; ICH = intracerebral hemorrhage; SAH = subarachnoid hemorrhage; SDH = subdural hematoma; EDH = extradural hematoma; DAI = diffuse axonal injury; R = right; L = left; Bilat = bilateral; F = frontal; P = parietal; T = temporal; O = occipital; BG = basal ganglia; N/A = not available. Table 1. Demographic and clinical features of participants with traumatic brain injuries Subject No. Age (years) Education (years) Gender Length of PTA (days) GCS Time postinjury (years) Cause of TBI Brain damage reported on acute phase neuroimaging 1 27 8 M 29 N/A 10 MVA SDH L T-P lobe 2 22 11 M 81 5 4 MVA Contusions Bilat F + R T lobes, R BG, L Thalamus, L Corpus Callosum, DAI 3 41 13 M 56 8 1 Fall SAH, L SDH, Contusion R T lobe 4 32 8 M 147 3 17 MVA Diffuse Edema, EDH L and R, Contusion R F lobe 5 21 8 M 51 5 3 MVA Ped SAH, R SDH, Contusions R T + Bilat F lobes 6 51 8 M 98 4 3 MVA SAH, ICH, Contusions R F Lobe, Corpus Callosum, DAI 7 59 13 M 95 7 5 MVA SAH, Contusions Bilat F + L T + R P lobes 8 30 11 M 83 5 14 MVA Diffuse Edema, SAH, Contusion R F lobe 9 31 11 M 84 4 15 MVA Diffuse Edema, EDH L P-O lobe, Contusions Bilat F-T-P lobes + L Cerebellum, R BG 10 63 8 M 53 6 4 SRHI SAH Bilat, Contusions Bilat F lobes, SDH R P, DAI 11 24 8 M 178 7 6 MVA L SDH, Contusions Bilat F + R O lobes 12 42 13 M 17 7 2 Fall SAH, SDH L T lobe, Contusions Bilat F + R T lobes 13 32 13 M 71 5 14 MVA R Hemispheric Edema, Contusions F-T lobes, R BG 14 49 8 M 172 3 9 MVA Extensive Contusions Bilat F-T lobes 15 31 8 M 142 4 7 MVA EDH L F-T lobe, Contusions Bilat F + L T lobes 16 36 13 M 126 3 10 MVA Diffuse Edema, SAH, Contusions Bilat F + L T lobes, L Thalamus, DAI 17 56 8 M 35 N/A 33 MVA SAH, Contusions Bilat F lobes 18 42 13 M 134 5 1 MVA SAH, Contusions Bilat F lobes, L thalamus, Corpus Callosum, DAI 19 26 8 F 34 5 2 MVA SAH, ICH, Contusions Bilat T-P lobes 20 29 18 F 112 N/A 1 MVA EDH Bilat, Contusions Bilat F + R P + Bilat O lobes 21 37 8 M 118 6 8 MVA SDH Bilat F lobes, Contusions R F lobes, Corpus Callosum, R thalamus, DAI 22 24 8 M 89 N/A 1 MVA Contusions Bilat F-T + Bilat F-P lobes, Corpus Callosum, DAI 23 38 13 F 131 3 1 MVA SAH, L SDH, Contusions L F-T lobes 24 29 11 M 87 7 7 MVA SAH, Contusions Bilat F lobes, L internal capsule, DAI 25 27 13 F 98 3 7 MVA SAH, Contusions Bilat F lobes 26 43 8 F 30 N/A 5 MVA Ped SAH, Contusions L F-P lobes, Corpus Callosum 27 22 13 F 113 4 1 MVA Ped L EDH, R BG, Contusions Bilat F-T lobes, Corpus Callosum, DAI 28 52 8 F 77 N/A 6 MVA Contusions Bilat T lobes Subject No. Age (years) Education (years) Gender Length of PTA (days) GCS Time postinjury (years) Cause of TBI Brain damage reported on acute phase neuroimaging 1 27 8 M 29 N/A 10 MVA SDH L T-P lobe 2 22 11 M 81 5 4 MVA Contusions Bilat F + R T lobes, R BG, L Thalamus, L Corpus Callosum, DAI 3 41 13 M 56 8 1 Fall SAH, L SDH, Contusion R T lobe 4 32 8 M 147 3 17 MVA Diffuse Edema, EDH L and R, Contusion R F lobe 5 21 8 M 51 5 3 MVA Ped SAH, R SDH, Contusions R T + Bilat F lobes 6 51 8 M 98 4 3 MVA SAH, ICH, Contusions R F Lobe, Corpus Callosum, DAI 7 59 13 M 95 7 5 MVA SAH, Contusions Bilat F + L T + R P lobes 8 30 11 M 83 5 14 MVA Diffuse Edema, SAH, Contusion R F lobe 9 31 11 M 84 4 15 MVA Diffuse Edema, EDH L P-O lobe, Contusions Bilat F-T-P lobes + L Cerebellum, R BG 10 63 8 M 53 6 4 SRHI SAH Bilat, Contusions Bilat F lobes, SDH R P, DAI 11 24 8 M 178 7 6 MVA L SDH, Contusions Bilat F + R O lobes 12 42 13 M 17 7 2 Fall SAH, SDH L T lobe, Contusions Bilat F + R T lobes 13 32 13 M 71 5 14 MVA R Hemispheric Edema, Contusions F-T lobes, R BG 14 49 8 M 172 3 9 MVA Extensive Contusions Bilat F-T lobes 15 31 8 M 142 4 7 MVA EDH L F-T lobe, Contusions Bilat F + L T lobes 16 36 13 M 126 3 10 MVA Diffuse Edema, SAH, Contusions Bilat F + L T lobes, L Thalamus, DAI 17 56 8 M 35 N/A 33 MVA SAH, Contusions Bilat F lobes 18 42 13 M 134 5 1 MVA SAH, Contusions Bilat F lobes, L thalamus, Corpus Callosum, DAI 19 26 8 F 34 5 2 MVA SAH, ICH, Contusions Bilat T-P lobes 20 29 18 F 112 N/A 1 MVA EDH Bilat, Contusions Bilat F + R P + Bilat O lobes 21 37 8 M 118 6 8 MVA SDH Bilat F lobes, Contusions R F lobes, Corpus Callosum, R thalamus, DAI 22 24 8 M 89 N/A 1 MVA Contusions Bilat F-T + Bilat F-P lobes, Corpus Callosum, DAI 23 38 13 F 131 3 1 MVA SAH, L SDH, Contusions L F-T lobes 24 29 11 M 87 7 7 MVA SAH, Contusions Bilat F lobes, L internal capsule, DAI 25 27 13 F 98 3 7 MVA SAH, Contusions Bilat F lobes 26 43 8 F 30 N/A 5 MVA Ped SAH, Contusions L F-P lobes, Corpus Callosum 27 22 13 F 113 4 1 MVA Ped L EDH, R BG, Contusions Bilat F-T lobes, Corpus Callosum, DAI 28 52 8 F 77 N/A 6 MVA Contusions Bilat T lobes Note. PTA = posttraumatic amnesia, GCS = Glasgow Coma Scale; M = male; F = female; MVA = motor vehicle accident; MVA Ped = motor vehicle accident as pedestrian; SRHI = sports-related head injury; ICH = intracerebral hemorrhage; SAH = subarachnoid hemorrhage; SDH = subdural hematoma; EDH = extradural hematoma; DAI = diffuse axonal injury; R = right; L = left; Bilat = bilateral; F = frontal; P = parietal; T = temporal; O = occipital; BG = basal ganglia; N/A = not available. In order to describe the cognitive, behavioral and psychological profile of our patients we administered a battery of standardized neuropsychological tests, a self-report scale describing behavioral problems and a self-report measure of mood/anxiety. The study was approved by the Hospital Ethics Committee and informed consent was obtained from all participants. Stimuli and Procedure Moral and socio-conventional task Participants were administered 20 items. Half of the items (10 items) expressed moral transgressions, whereas the other half (10 items) expressed socio-conventional transgressions (10 items). In particular, transgressions that involved harm, injustice, or right violations were considered as moral transgressions (e.g., “kill a person”), while transgressions that involved a violation of convention without the involvement of harm, injustice, or rights violations were considered as socio-conventional transgressions (e.g., “in a restaurant, sticking a chewing gum under the seat”). The items (see Supplementary material online) were formulated to differentially reflect these key features of moral and socio-conventional transgression, on the basis of the theoretical formulation advanced by Turiel (1983), and were designed to capture the broad ranges of situations in which both moral and socio-conventional transgressions can arise. Under this perspective, we decided to include some conventional transgression in which actions seem particularly bad and punishable (e.g., at a traffic light, go through the red light in order not to be late for an appointment), yet without entailing those aspects that defined moral violations. To facilitate administration and comprehension in severe TBI patients, the experimenter read the items aloud. The same procedure was used for the control group. Participants were then asked to express on a 10-point Likert scale, ranging from 1 = not at all difficult, to 10 = very difficult, how much it would be difficult to perform the transgression. The Likert scale was shown in front of the participants (together with the item in written form). This particular question (instead of the classic question on the wrongness of the violation) capitalizes on the important intrinsic link between normative evaluation and action. After a positive judgment about the legitimacy of a given course of action, in fact, we are motivated to act accordingly. This motivating force towards the enactment of a given behavior is indeed classically regarded as the key feature that marks judgments as normative, thereby distinguishing them from the many other judgments we make (Rosati, 2014). We believe that focusing on the difficulty to perform a transgression allows to understand how normative judgments succeed or fail in motivating people’s behaviors, contributing to better define both moral judgment and moral knowledge. In that sense, the question about moral or socio-conventional transgressions, directly and synthetically taps into the essential feature underlying the normative evaluations we wanted to investigate. Neuropsychological measures A battery of standardized neuropsychological tests was administered to the TBI patients in order to measure: (a) the premorbid intellectual function, (b) memory, (c) working memory, (d) information-processing speed, and (e) attention/executive functioning. Lacking Intelligence Quotient (IQ) evaluations before the illness onset, we used the Test di Intelligenza Breve (TIB; Colombo, Sartori, & Brivio, 2002; Sartori, Colombo, Vallar, Rusconi, & Pinarello, 1997), an italian adaptation of the National Adult Reading Test (NART; Nelson, 1982). Memory was assessed by the Rey Auditory-Verbal Learning Test (RAVLT; Carlesimo, Caltagirone, & Gainotti, 1996; Rey, 1964), and the Prose Memory Test (Spinnler & Tognoni, 1987). Working memory was assessed by the Digit Span Forward (Spinnler & Tognoni, 1987), and the Digit Span Backward (Monaco, Costa, Caltagirone, & Carlesimo, 2013). Information-processing speed was assessed by the Symbol Digit Modalities Test, oral version (SDMT; Nocentini, Giordano, Di Vincenzo, Panella, & Pasqualetti, 2006). Attention/Executive functions were assessed by the Digit Cancellation Test (Della Sala, Laiacona, Spinnler, & Ubezio. 1992), the Trail Making Test A and B (TMT A-B; Giovagnoli et al., 1996; Reitan, 1958), the Stroop Colour-Word Test (Caffarra, Vezzadini, Dieci, Zonato, & Venneri, 2002; Stroop, 1935), the Letter and Semantic Fluency Tests (Novelli et al., 1986), and the Winsconsin Card Sorting Test (WCST; Heaton, Chelune, Talley Kay & Curtiss, 1993; Laiacona, Inzaghi, De Tanti. & Capitani, 2001). All the tests used as normative data the equivalent score scale (e.g., Capitani & Laiacona, 1997), except for the TIB and SDMT which featured respectively the classical IQ range and a cut-off value (34.2). The equivalent score scale is a standardized scale, used in clinical practice to classify patients’ performance after demographic corrections are made (age, education, and gender). The equivalent score scale includes five points: 0–4. An equivalent score of 0 stands for the fifth percentile of the healthy sample, and is considered as the cut-off value signaling pathological performance. Points 2, 3, and 4 are considered normal. Finally, point 1 is considered a borderline score, between normal and pathological performance. As a standardized scale, the equivalent points scale allows clinicians to compare the performance of patients on psychometrically different neuropsychological tests (different scales, stimuli, responses, time constraints, etc.), and to calculate the mean impairment of the patients (Capitani & Laiacona, 1997). We thus used this scale for clinical evaluations, in order to classify patients’ performance as pathological or not. Results are reported in Table S1 (see Supplementary material online). Results of the neuropsychological assessment showed that our TBI chronic severe patients performed poorly just on a verbal memory long-term test (i.e., RAVLT) when compared with normative scores. Behavioral measures The more frequent behavioral problems after severe TBI are social conduct problems, as impulsivity, irritability, inappropriate social behavior, lack of initiative, and self-centeredness (Kelly, Brown, Todd, & Kremer, 2008; Olver, Ponsford, & Curran, 1996; Marsh & Kersel, 2006). To assess the presence of behavioral disorders after TBI, we administrated the caregiver’s version of Head Injury Behaviour Scale (HIBS), which is a self-report questionnaire containing 20 items describing behavioral problems often associated with TBI (Godfrey et al., 2003; Smith & Godfrey, 1995). Table S2 shows the percentage of behavioral problems in our TBI sample. Furthermore, we collected other information via a clinical interview with the caregiver (after administration of the HIBS) and from the patients’ medical records. Psychological measures Depression and anxiety disorders are frequently diagnosed in survivors of TBI and often co-occur. Emotional distress may result either directly from the injury, or as a consequence of TBI-associated difficulties in daily activities, suboptimal coping style, unemployment, and financial stress (Senathi-Raja, Ponsford, & Schöenberger, 2010). Emotional distress of TBI patients was evaluated using the Hospital Anxiety and Depression Scale (HADS), which is a brief self-report questionnaire. The HADS measures symptoms of depression (HADS-D) and anxiety (HADS-A) over the past week by means of two scales, each with seven items scored on a 4-point Likert scale ranging from 0 to 3. Its use with severe TBI patients is well-documented in extant literature (e.g., Dahm, Wong, & Ponsford, 2013; Schöenberger & Ponsford, 2010). Data Analysis Given the experimental design (i.e., each subject responds to each item), we used a mixed-effects model approach for data analysis. This approach allowed us to simultaneously consider all the factors that potentially could contribute to the understanding of the structure of the data (Baayen, Davidson, & Bates, 2008). These factors include not only the standard fixed-effects factors controlled by the experimenter (in our case, Group of Participants and Type of Item), but also the random effect factors (i.e., factors whose levels are drawn at random from a population; in our case, Participants and Items). Specifically, we performed a mixed-effects model with Responses (i.e., ratings on the 10-point Likert scale) as the dependent variable, Group of Participants (Patients vs. Controls) as between-participants fixed effect, Type of Item (Moral transgression vs. Socio-conventional transgression) as within-participants fixed effect, and Participants (n = 56) and Items (n = 20) as random effects. The two-way interaction between Group and Type was also considered. Observed means as a function of conditions are reported in Table 2. Table 2. Observed means (M) and standard deviations (SD) of the responses as a function of group (TBI vs. Controls) and Type of Item (Moral vs. Socio-conventional Transgressions) Group Moral Transgressions Socio-conventional Transgressions M SD M SD TBI (n = 28) 8.14 1.37 4.78 1.43 Controls (n = 28) 9.25 .58 4.55 1.56 Group Moral Transgressions Socio-conventional Transgressions M SD M SD TBI (n = 28) 8.14 1.37 4.78 1.43 Controls (n = 28) 9.25 .58 4.55 1.56 Table 2. Observed means (M) and standard deviations (SD) of the responses as a function of group (TBI vs. Controls) and Type of Item (Moral vs. Socio-conventional Transgressions) Group Moral Transgressions Socio-conventional Transgressions M SD M SD TBI (n = 28) 8.14 1.37 4.78 1.43 Controls (n = 28) 9.25 .58 4.55 1.56 Group Moral Transgressions Socio-conventional Transgressions M SD M SD TBI (n = 28) 8.14 1.37 4.78 1.43 Controls (n = 28) 9.25 .58 4.55 1.56 Potentially, TBI patients responses may be related to a number of other variables we measured. Selectively for the data from TBI patients, we thus ran additional analyses in which we assessed whether the responses were predicted by (a) neuropsychological measures of information-processing speed and attention/executive functions, (b) mood and anxiety scores as indexed by the HADS scale, or (c) PTA and the localization of the brain lesions. First, we assessed whether each one of these variables determined an increased goodness of fit when entered into the model, in addition to the simple effect of Type of Item. Second, we assessed the presence of a potential interaction between each the different measures and the factor Type of Item. Models with interactions were compared, in terms of goodness of fit, with corresponding models where the factor Type of Items and the examined predictor were considered in an additive relationship. Models were compared using likelihood ratio tests. Further, we assessed whether we could detect any correlation between behavioral problems as indexed by the HIBS scale and the responses provided by the participants during the experiment. We did not use the HIBS Global Score as a predictor, as we reasoned that, if anything, behavioral problems may be a consequence, and not a determinant, of socio-conventional and moral knowledge. As several tests were conducted on the same set of data, we applied a fdr correction to the p-values, in order to control for multiple-comparison issues. Results Moral and Socio-Conventional Task There was a significant Group × Type interaction effect (χ2[1] = 25.5, p < .001), which is presented in Fig. 2. This effect was further investigated in terms of simple effects (De Rosario-Martinez, 2015) via multiple contrasts adjusted with the Benjamini and Hochberg (1995) procedure. Analysis across Type of Items showed that Moral items were considered more difficult to transgress than Socio-conventional items in both groups (Patients: χ2[1] = 72.3, p < .001, Cohen’s d = 2.65; Controls: χ2[1] = 140.8, p < .001, Cohen’sd = 3.11). In addition, the analysis across Groups showed that Moral items were considered significantly more difficult to transgress by Controls compared to Patients (χ2[1] = 12.2, p = .001, Cohen’s d = 1.05), whereas no differences was observed for Socio-conventional items (χ2[1] = 0.5, p = .478, Cohen’s d = –.15). (To assess the potential impact of single items on model outcomes, an influence analysis (Nieuwenhuis, te Grotenhuis & Pelzer, 2012) was conducted. No substantial effect of any single item emerged, thus confirming the robustness of our results.) Therefore, patients recognize that moral transgressions are worse than socio-conventional transgressions but, interestingly, they significantly underestimate the magnitude of this moral transgression compared to controls. Fig. 2. View largeDownload slide Estimated means of responses by Type of Item and Group (npatients = 28, ncontrols = 28). Error bars represent 95% confidence intervals. Fig. 2. View largeDownload slide Estimated means of responses by Type of Item and Group (npatients = 28, ncontrols = 28). Error bars represent 95% confidence intervals. These results appear to confirm the hypothesis that moral knowledge seems spared in patients, and that they are able to distinguish moral from socio-conventional transgressions. However, the results also highlight that TBI patients, compared to controls, assign lower ratings to moral violations (and not to socio-conventional ones). In the Discussion we discuss both aspects. Additional Analyses Neuropsychological measures We focused on neuropsychological measures related to attention/executive functions, which could influence social and moral reasoning (e.g., McDonald et al., 2011; Moore, Clark, & Kane, 2008), using raw scores obtained in neuropsychological tests as predictors for the responses given in the experimental tasks. Raw scores were used to capitalize on variability between participants, thus being able to grasp potential finer grained relationships between the predictors and the responses to the experimental items. Specifically, we considered raw scores from the Symbol Digit Modalities Test, the Digit Cancellation Test, the Stroop Colour-Word Test (two predictors: time interference and error interference), the Trail Making Test A and B (three predictors: TMT A, TMT B, TMT B-A), the Letter Fluency task, the Semantic Fluency task, and the Winsconsin Card Sorting Test (four predictors: global scores, perseverations, non-perseverative errors, and failure to maintain the set). None of the measure, either as a main effect or in interaction with Type of Item, yielded a significant improvement in terms of model fit (all ps > .11). Values for the statistical tests are presented in Table 3. Table 3. Statistical results for the measures of attention/executive functions Predictors χ2 df p Value (fdr) Digit Cancellation Test 0.21 1 .89 Digit Cancellation Test * Type of Item 7.12 1 .15 Stroop (time interference) 0.03 1 .98 Stroop (time interference) * Type of Item 3.88 1 .57 Stroop (error interference) 0.06 1 .98 Stroop (error interference) * Type of Item 0.00 1 .99 SDMT 1.23 1 .70 SDMT * Type of Item 2.20 1 .66 TMT A 2.48 1 .66 TMT A * Type of Item 2.77 1 .66 TMT B 0.26 1 .87 TMT B * Type of Item 0.48 1 .75 TMT B-A 0.00 1 .99 TMT B-A * Type of Item 1.46 1 .66 WCST A (global score) 1.51 1 .66 WCST A (global score) * Type of Item 0.10 1 .96 WCST B (perseverations) 0.90 1 .70 WCST B (perseverations) * Type of Item 1.43 1 .66 WCST C (non-perseverative errors) 1.08 1 .70 WCST C (non-perseverative errors) * Type of Item 0.13 1 .96 WCST D (failure to maintain the set) 0.57 1 .74 WCST D * Type of Item 0.00 1 .99 Letter Fluency 0.05 1 .98 Letter Fluency * Type of Item 8.73 1 .12 Semantic Fluency 0.73 1 .71 Semantic Fluency * Type of Item 3.63 1 .57 Predictors χ2 df p Value (fdr) Digit Cancellation Test 0.21 1 .89 Digit Cancellation Test * Type of Item 7.12 1 .15 Stroop (time interference) 0.03 1 .98 Stroop (time interference) * Type of Item 3.88 1 .57 Stroop (error interference) 0.06 1 .98 Stroop (error interference) * Type of Item 0.00 1 .99 SDMT 1.23 1 .70 SDMT * Type of Item 2.20 1 .66 TMT A 2.48 1 .66 TMT A * Type of Item 2.77 1 .66 TMT B 0.26 1 .87 TMT B * Type of Item 0.48 1 .75 TMT B-A 0.00 1 .99 TMT B-A * Type of Item 1.46 1 .66 WCST A (global score) 1.51 1 .66 WCST A (global score) * Type of Item 0.10 1 .96 WCST B (perseverations) 0.90 1 .70 WCST B (perseverations) * Type of Item 1.43 1 .66 WCST C (non-perseverative errors) 1.08 1 .70 WCST C (non-perseverative errors) * Type of Item 0.13 1 .96 WCST D (failure to maintain the set) 0.57 1 .74 WCST D * Type of Item 0.00 1 .99 Letter Fluency 0.05 1 .98 Letter Fluency * Type of Item 8.73 1 .12 Semantic Fluency 0.73 1 .71 Semantic Fluency * Type of Item 3.63 1 .57 Note: df = degrees of freedom; p value(fdr) = p value corrected via false discovery rate in order to control for multiple comparisons; SDMT = symbol-digit modalities test; TMT = trail making test; WCST = Winsconsin Card Sorting Test. Table 3. Statistical results for the measures of attention/executive functions Predictors χ2 df p Value (fdr) Digit Cancellation Test 0.21 1 .89 Digit Cancellation Test * Type of Item 7.12 1 .15 Stroop (time interference) 0.03 1 .98 Stroop (time interference) * Type of Item 3.88 1 .57 Stroop (error interference) 0.06 1 .98 Stroop (error interference) * Type of Item 0.00 1 .99 SDMT 1.23 1 .70 SDMT * Type of Item 2.20 1 .66 TMT A 2.48 1 .66 TMT A * Type of Item 2.77 1 .66 TMT B 0.26 1 .87 TMT B * Type of Item 0.48 1 .75 TMT B-A 0.00 1 .99 TMT B-A * Type of Item 1.46 1 .66 WCST A (global score) 1.51 1 .66 WCST A (global score) * Type of Item 0.10 1 .96 WCST B (perseverations) 0.90 1 .70 WCST B (perseverations) * Type of Item 1.43 1 .66 WCST C (non-perseverative errors) 1.08 1 .70 WCST C (non-perseverative errors) * Type of Item 0.13 1 .96 WCST D (failure to maintain the set) 0.57 1 .74 WCST D * Type of Item 0.00 1 .99 Letter Fluency 0.05 1 .98 Letter Fluency * Type of Item 8.73 1 .12 Semantic Fluency 0.73 1 .71 Semantic Fluency * Type of Item 3.63 1 .57 Predictors χ2 df p Value (fdr) Digit Cancellation Test 0.21 1 .89 Digit Cancellation Test * Type of Item 7.12 1 .15 Stroop (time interference) 0.03 1 .98 Stroop (time interference) * Type of Item 3.88 1 .57 Stroop (error interference) 0.06 1 .98 Stroop (error interference) * Type of Item 0.00 1 .99 SDMT 1.23 1 .70 SDMT * Type of Item 2.20 1 .66 TMT A 2.48 1 .66 TMT A * Type of Item 2.77 1 .66 TMT B 0.26 1 .87 TMT B * Type of Item 0.48 1 .75 TMT B-A 0.00 1 .99 TMT B-A * Type of Item 1.46 1 .66 WCST A (global score) 1.51 1 .66 WCST A (global score) * Type of Item 0.10 1 .96 WCST B (perseverations) 0.90 1 .70 WCST B (perseverations) * Type of Item 1.43 1 .66 WCST C (non-perseverative errors) 1.08 1 .70 WCST C (non-perseverative errors) * Type of Item 0.13 1 .96 WCST D (failure to maintain the set) 0.57 1 .74 WCST D * Type of Item 0.00 1 .99 Letter Fluency 0.05 1 .98 Letter Fluency * Type of Item 8.73 1 .12 Semantic Fluency 0.73 1 .71 Semantic Fluency * Type of Item 3.63 1 .57 Note: df = degrees of freedom; p value(fdr) = p value corrected via false discovery rate in order to control for multiple comparisons; SDMT = symbol-digit modalities test; TMT = trail making test; WCST = Winsconsin Card Sorting Test. Behavioral Problems There was no correlation between the Global Scores from the HIBS and the responses provided by TBI patients to either Socio-conventional (rs = –.21, p = .70) or Moral items (rs = –.16, p = .73). Thus, there is no evidence of a relationship between the behavioral problems highlighted by the caregivers, and the responses to our experiment. Mood and anxiety (emotional distress) Mean Depression and Anxiety scores obtained with the HADS scale as a function of Group (Control vs. TBI) are reported in Table 4. The difference in terms of mean scores was significant for the Depression score (t[52] = 2.89, p < .01), with higher scores for TBI patients, but not for the Anxiety score (t[52] = 1.02, p = .31). For TBI patients, neither the Anxiety score (χ2[1] = 0.00, p = .99), nor the Depression score (χ2[1] = 0.87, p = .70) produced a significant increase in terms of model fit, suggesting that these scores do not modulate the ratings provided by the participants. Further, neither the Anxiety (χ2[1] = 0.04, p = .98), nor the Depression score (χ2[1] = 1.65, p = .66) interacted with Type of Item, suggesting that the difference between responses to moral and socio-conventional items highlighted within our sample of TBI patients is not explained by emotional distress. Table 4. Mean Anxiety and Depression scores calculated from the HADS scale for Controls (CTRL) and TBI patients (TBI) Group Anxiety Depression CTRL 6.84 (3.19) 3.19 (2.15) TBI 7.56 (4.46) 5.15 (2.80) Group Anxiety Depression CTRL 6.84 (3.19) 3.19 (2.15) TBI 7.56 (4.46) 5.15 (2.80) Standard deviations are reported within parentheses. Table 4. Mean Anxiety and Depression scores calculated from the HADS scale for Controls (CTRL) and TBI patients (TBI) Group Anxiety Depression CTRL 6.84 (3.19) 3.19 (2.15) TBI 7.56 (4.46) 5.15 (2.80) Group Anxiety Depression CTRL 6.84 (3.19) 3.19 (2.15) TBI 7.56 (4.46) 5.15 (2.80) Standard deviations are reported within parentheses. PTA and localization of brain lesions PTA duration, which is a strong predictor of outcome in survivor TBI (e.g., Nakase-Richardson, Yablon, & Sherer, 2007; Walker et al., 2010), failed to determine an increase in terms of explained variance (χ2[1] = 1.86, p = .66). Overall, the responses to our experiment do not seem to be modulated by PTA. Additionally, the PTA by Type of Item interaction was not significant (χ2[1] = 0.49, p = .74), suggesting that PTA does not modulate the difference between responses to moral and socio-conventional items. Severe TBI patients commonly show at the same time focal and diffuse brain damage. Focal brain damage includes parenchimal contusions, epidural, subdural and intraparenchymal hematomas, whereas diffuse brain damage entails diffuse axonal injury, diffuse cerebral edema, diffuse vascular injury and hypoxic-ischemic injury (Andriessen, Jacobs, & Vos, 2010). The most common sign of diffuse brain damage is the diffuse axonal injury (DAI). Nevertheless, Bigler (2001) advocated the use of the more general term of diffuse brain injury (DBI), which includes DAI as well as other measures of diffuse damage, such as diffuse cerebral edema, diffuse vascular injury and hypoxic-ischemic injury. The routine neuroimaging tool used in acute phase, CT scan, is less sensitive than MRI scan to detect the DAI (Gentry, Godersky, Thompson, & Dunn, 1988). Since we had the CT scan for all the patients, and the MRI scan just for a part of them, we considered as index of DBI not only the DAI, but also the diffuse cerebral edema, which is commonly detectable in CT scan reports (Unterberg, Stover, Kress, & Kiening, 2004). Therefore, evidence of DBI was provided by the presence of diffuse axonal injury and/or diffuse cerebral edema. To study the relationship between brain lesions and moral and socio-conventional judgment we conducted three analyses. The diffuse damage may have a larger influence on moral and socio-conventional reasoning than focal damage in severe TBI patients. To test this hypotheses we categorize our TBI patients in two groups: DBI (n = 14) versus not DBI (n = 14). Results showed that the classification as a function of presence/absence of DBI failed to explain additional variance both as a main effect (χ2[1] = 1.02, p = .70), and in interaction with Type of item (χ2[2] = 2.00, p = .66). Extant literature on acquired brain injury strongly suggests that ventromedial prefrontal cortex (vmPFC) and orbitofrontal cortex (OFC) play a crucial role in social and moral cognition, even though the most part of the patients involved in these studies shown focal vascular (e.g., Ciaramelli, Sperotto, Mattioli, & Di Pellegrino, 2007; Koenigs et al., 2007) or focal brain tumor lesions (e.g., Saver & Damasio, 1991). To test this hypotheses we categorize our TBI patients in three groups: frontal (10) versus not frontal (n = 4) versus DBI (n = 14). Even this categorization failed to increase the amount of explained variance both when considered as a main effect (χ2[2] = 1.37, p = .75), or in interaction with the factor Type of item (χ2[2] = 3.04, p = .66). The literature on moral cognition has shown a causal role of emotion processing in moral reasoning for healthy people (Greene, Sommerville, Nystrom, Darley, & Cohen, 2001) and for patients with brain injury (Koenigs et al., 2007). Furthermore there is strong evidence of impaired emotional processing in severe TBI (Babbage et al., 2011). Emotional processing involves a frontotemporal network (Gorno-Tempini et al., 2001) that is commonly damaged in severe TBI (Bigler, 2001). We thus conducted a final analysis in which we distinguished TBI patients with lesions encompassing both the frontal and temporal lobe (n = 12) and TBI patients with lesions not involving either the frontal or the temporal lobe (n = 16). This final classification failed to display any significant increase in terms of model fit, both when considered as a main effect (χ2[2] = 0.00, p = .99), or in interaction with the factor Type of Item (χ2[1] = 0.08, p = .70). It is important to warrant caution in the interpretation of these results. The analyses reported at point 2 and 3 compare groups with unequal sample size. Additionally, all three analyses categorize TBI patients within groups featuring small sample size. Given these limitations, we stress that these analyses should be considered as tentative and that specific research would be needed to clearly address each of the three hypotheses outlined above, here approached in merely exploratory terms. Discussion This study examined explicit social and moral knowledge in severe TBI patients. Building on the theoretical framework developed by Turiel (1983), which proposed a distinction between moral and conventional transgressions, we implemented a new set of moral and socio-conventional items that are both more appropriate and more relevant for adults, compared to those used in previous studies (e.g., Blair, 1995; Blair & Cipolotti, 2000; Turiel, 1983; Nucci & Turiel, 1978). Our data shown that TBI patients, like control participants, were able to differentiate between moral and socio-conventional transgressions, as they considered the former more difficult to fulfill. These results suggest that explicit moral and socio-conventional knowledge may be spared in the present sample of TBI patients. Our patients seem to retain knowledge of the difference between the universality of the moral norms and the contingency of the socio-conventional norms. Our findings may thus be consistent with the notion that people with severe TBI retain access to previously acquired knowledge about socio-conventional norms, whereas potential difficulties may arise in applying this knowledge to their behavior (Beer et al., 2006). Interestingly, to the best of our knowledge, we have provided a first evidence suggesting that the knowledge spared in severe TBI patients is not limited to socio-conventional norms, but it may extend to moral norms. Following this rationale, an intriguing research question is the relationship between brain lesions’ sites and the outcome in terms of storage and access of socio-conventional and moral norms. However, any hypothesis of relationship should be taken with caution due to strong and common evidence of diffuse brain injury in severe TBI, although some brain areas involved in social and moral cognition and social and moral behavior (e.g., ventrolateral frontal lobes, inferior orbital cortices, and temporal lobes), are more vulnerable and thus more frequently damaged than others. In our study, however, all the patients were severe TBI with different, multiple, and extensive lesions. Thus, it was difficult to reliably the role of location, load and extension of brain lesions with respect to moral and socio-conventional knowledge. Although it was not the goal of our study, we tried to shed light on this issue by categorizing our patients, using the acute phase neuroimaging reports, in (a) DBI versus non-DBI, (b) frontal versus non-frontal versus DBI, and (c) frontotemporal versus non-frontotemporal. None of these categorizations appears to predict the responses provided by TBI patients in our experiment, nor they exert a selective influence on either moral or socio-conventional items. We may therefore hypothesize that the evidence of a spared moral and socio-conventional knowledge in our patients could be determined by the fact that the brain areas storing and processing this kind of knowledge are not damaged by severe TBI. Another interesting result surfacing from our work is that TBI patients, compared to controls, considered moral transgressions as easier to fulfill. With respect to this issue, our finding may underlie a tendency in TBI patients to underestimate the weight of moral transgressions. From a behavioral point of view, the consequence of abnormal morality is well described by the antisocial behavior (e.g., stealing, aggression against persons or property). And yet, literature and clinical practice show that antisocial behaviors are not common in adult severe TBI. In fact, excluding the acute phase of TBI, the most common behavioral problems after severe TBI revolve around issues of social conduct (e.g., impulsivity, irritability, inappropriate social behavior, lack of initiative and self-centeredness; see Kelly et al., 2008; Marsh & Kersel, 2006; Olver et al., 1996; Baugley, Cooper, & Felmingham, 2006; Dyer, Bell, McCann, & Rauch, 2006). Even when aggressive behaviors are found (Baugley et al., 2006; Dyer et al., 2006), they are of limited severity (i.e., impulsive verbal aggression and anger) and scarcely related to an abnormal moral behavior. Differently, the literature on early-onset prefrontal-lesions (commonly caused by severe TBI) showed a link with an abnormal development of moral behavior (Anderson, Bechara, Damasio, Tranel, & Damasio, 1999). The hypothesis proposed by the authors is that an early-onset brain injury can impair the acquisition of moral knowledge and the following behavioral inadequacy could be therefore explained by an absence of the specific knowledge required for moral behavior. Furthermore, individuals who experienced TBI in childhood are more at risk of developing a range of externalizing disorders associated with antisocial behavior in adulthood (e.g., Fergusson & Lynskey, 1998; McKinlay et al., 2014). However these findings should interpreted with caution. There is little information about how to identify individuals with TBI who might be at risk for developing abnormal social or moral behavior, and there are several factors related to TBI (brain lesions site and extension, pre and postmorbid social environment, premorbid personality, etc.) that could influence the development of antisocial behaviors. We obtained information about behavioral disorders of our TBI patients by via the caregiver’s version of the HIBS. Furthermore, we collected additional information by interviewing the same caregiver and by medical reports. We didn’t find evidence of significant abnormal moral behavior (i.e., antisocial behavior). The HIBS contains just a single potential moral item, which refers to aggressive behavior, and all the caregivers reported that only verbal, and not physical, aggression has been occasionally observed. In contrast, caregivers reported problems in terms of social conduct, as indeed commonly described in severe TBI. As our patients shown an overall good executive functioning, these findings are consistent with the numerous published cases of individuals with bilateral injuries to the frontal lobes displaying postmorbid deficits in social behavior, with normal performances on standard tests of executive functioning (e.g., Barker, Andrade & Romanowski, 2004; Eslinger & Damasio, 1985; Shallice & Burgess, 1991). Although our data did not provide evidence of significant abnormal moral behaviors in patients’ everyday life, future researches should investigate systematically the relationship between moral knowledge and moral behavior in adult severe TBI. Possibly, experimental designs with moral dilemmas (Greene et al., 2001; Lotto, Manfrinati, & Sarlo, 2014) and finer-grained measures of daily behavior could settle this issue. Some limitations of the present study are worth mentioning. First, by measuring how much it would be difficult to perform a moral or a socio-conventional transgression we used just explicit measures. This approach does not fully account for all the different components involved in moral and socio-conventional knowledge. Particularly, it may be interesting to address implicit measures of moral and socio-conventional knowledge. Previous research (McDonald et al., 2011) has exploited the Implicit Association Test (IAT) to measure implicit social cognition and has suggested that there is no evidence, in TBI patients, of any deficit in terms of implicit social knowledge. Similarly, it might be interesting to investigate the implicit aspects of moral knowledge, and future studies may try to integrate explicit measures of moral knowledge with measures based on associative processes (e.g., the moral IAT; Perugini & Leone, 2009). However, it is important to note that this approach has some important limitations. For example, the use of the IAT, although potentially interesting, could be problematic in TBI because of possible impairments in processing speed, attention and executive functions. All these factors can, in principle, exert an important influence on the IAT results, thus complicating any interpretation. In case, it would be important to devise studies where it becomes possible to control for the influence of these confounding factors (Klauer, Schmitz, Teige-Mocigemba & Voss, 2010; McDonald et al., 2011). The feasibility of such studies remains to be evaluated. Further, we did not use a standardized, validated instrument to assess moral and social knowledge, nor we created one. Rather, our approach was to devise an experiment in which participants could be presented with situations encompassing violations of either moral or socio-conventional norms, and the two distinct groups of items were created solely on the basis of the theoretical distinction between moral and conventional transgressions (e.g., Turiel, 1983). Although this approach may cast doubts on the generalizability and consistency of the results, we note that the use of mixed models allows to account for variability related to specific participants and items. Further, we performed an influence analysis which further confirmed that our results were not driven by single items. These aspects speak in favor of the consistency of our results, despite the lack of a validated scale or instrument. Second, our study did not explore the relationship between moral and socio-conventional tasks and emotions processing. Extant literature highlights a debate about the roles of emotional processing in moral reasoning (Greene et al., 2001; Huebner, Dwyer, & Hauser, 2009; Manfrinati, Lotto, Sarlo, Palomba, & Rumiati, 2013; Manfrinati, 2015). However, increasing evidence from healthy and brain-damaged participants suggests that an emotionally mediated brain network is crucial in moral reasoning (Koenigs et al., 2007; Moll & De Oliveira-Souza, 2007). This network seems to include the vmPFC (especially on the right hempisphere), the adjacent orbitofrontal and ventrolateral cortices (OFC/VL), the amygdala, and related structures. The vmPFC, with its rich interconnections with limbic structures, mediates strong automatic reactions to moral violations (Mendez, 2009). Following these hypotheses, a damage of this frontotemporal network, which is commonly damaged in severe TBI (Bigler, 2001), could explain the tendency of our TBI patients to underestimate moral transgressions with respect to the control group. As emotion processing seems to be impaired in severe TBI (Babbage et al., 2011), potentially TBI moral knowledge could be biased by emotion processing disorders. Future studies should thus investigate more explicitly whether (potential) emotional impairments in TBI patients affect the ability to distinguish between moral and socio-conventional transgressions, and whether these impairments may have some backlash on day-to-day behavior. Third, the most part of our neuroimaging data were detected by CT scan reports of acute phase, so we had just a crude measure of the traumatic brain damage complexity. Consequently, lesions in the frontotemporal network may have been undetectable by our neuroimaging tools. Further investigation with lesion analysis methods and more sensitive neuroimaging techniques (i.e., Diffusion Tensor Imaging and Voxel-Based Morphometry), could better analyze the brain damage following TBI (e.g., Levine et al., 2013; Solomon, Raymont, Braun, Butman, & Grafman, 2007; Volebel, Genova, Chiaravalotti & Hoptman, 2012). Finally, we used a self-report measure to assess moral and socio-conventional knowledge. Self-report measures may be influenced by a number of variables, including social desirability and a lack of self-awareness or insight. However, although the use of self-report scales in TBI patients research is sometimes questioned, some studies shown that self-report measures of empathy and mood can be reliably used in the context of severe TBI (de Sousa et al., 2010, 2011; Williams & Wood, 2009; Wood & Williams, 2008). Moreover, our data shown that TBI patient considered moral transgressions as easier to fulfill compared to control participants. This result goes against social desirability. Finally, it is difficult to explain this result in terms of lack of self-awareness, as the underestimation is limited just to moral transgressions, whereas any general feature such as reduced insight or self-awareness should equally affect all the judgments, and not only those of a specific category. That said, it is still possible that our self-reported evaluations are not entirely free from exogenous influences of important factors escaping insight and self-awareness. Furthermore, it is important to note that our study potentially captured just more explicit aspects of social and moral knowledge. Even if this type of knowledge seems maintained, the implicit dimension of moral and social knowledge, not investigated in our study, could provide further interesting perspectives on the relationship between knowledge and behavior. In fact, we cannot rule out the possibility that the implicit aspects of moral and social knowledge may exert an influence on behavior along different trajectories compared to those captured by explicit judgments. In conclusion, whereas previous studies provided evidence of spared explicit social knowledge in TBI patients (Beer et al., 2006; McDonald et al., 2011; Milne, & Grafman, 2001; Turkstra et al., 2004), in this study we have shown that the same seems true at least for explicit moral knowledge. In fact, exactly as control participants, TBI patients rated moral transgressions as more difficult to enact compared to socio-conventional ones, suggesting that even for TBI patients the two categories can be differentiated. Nonetheless, TBI patients, rated the enactment of moral transgression as significantly less difficult, compared to matched controls. Supplementary Material Supplementary material is available at Archives of Clinical Neuropsychology online. Funding M.S. has been supported by Agence Nationale de la Recherche [grant numbers ANR-16-CONV-0002, ANR-11-LABX-0036, ANR-11-IDEX-0001-02]. Conflict of Interest None declared. Acknowledgments The present study is dedicated to the beloved memory of M.M. References Anderson , S. W. , Bechara , A. , Damasio , H. , Tranel , D. , & Damasio , A. R. ( 1999 ). Impairment of social and moral behavior related to early damage in human prefrontal cortex . Nature Neuroscience , 2 , 1032 – 1037 . Google Scholar CrossRef Search ADS PubMed Andriessen , T. M. J. C. , Jacobs , B. , & Vos , P. E. ( 2010 ). Clinical characteristics and pathophysiological mechanisms of focal and diffuse traumatic brain injury . Journal of Cellular and Molecular Medicine , 14 , 2381 – 2392 . Google Scholar CrossRef Search ADS PubMed Baayen , R. H. , Davidson , D. J. , & Bates , D. M. ( 2008 ). Mixed-effects modeling with crossed random effects for subjects and items . Journal of Memory and Language , 59 , 390 – 412 . 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Are Moral and Socio-conventional Knowledge Impaired in Severe Traumatic Brain Injury?

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Oxford University Press
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© The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
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10.1093/arclin/acx099
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Abstract

Abstract Objective The aim of this study was to investigate explicit moral and socio-conventional knowledge in Traumatic Brain Injury (TBI) patients. Method A group of 28 TBI patients was tested on a new set of moral and socio-conventional items. Responses of TBI patients were compared with those of 28 matched controls. Participants had to report how hard would be to perform specific moral or socio-conventional transgressions, using a 10-point Likert scale. We analyzed our data through mixed-effects models, to jointly assess by-participants and by-items variance. The factors considered were Type of Item (Moral vs. Socio-conventional) and Group (TBI vs. Controls). Results Results revealed a significant interaction between Type of Item and Group (χ2[1] = 25.5, p < .001). Simple-effects analyses showed that TBI, as Controls, were able to differentiate moral and socio-conventional transgressions (χ2[1] = 72.3, p < .001), as they deemed the former as more difficult to enact. TBI patients, however, evaluated moral transgressions as easier to fulfill (χ2[1] = 12.2, p = .001). Conclusions TBI patients can clearly differentiate moral and socio-conventional transgressions, suggesting that the explicit knowledge of these two dimensions is spared. TBI patients, however, considered moral transgressions as easier to fulfill with respect to Controls. This finding may suggest a tendency in TBI patients to underestimate the weight of moral transgressions. Neuropsychology, Traumatic brain injury, Social cognition, Morality Introduction Traumatic brain injury (TBI) constitutes a major health and socioeconomic problem that affects all societies throughout the world (Maas, Stocchetti, & Bullock, 2008). For diagnostic and research purposes there is a need to categorize patients along the spectrum of severity (mild, moderate, severe). Moderate-to-severe TBI patients commonly have ongoing physical, cognitive, and psychosocial sequelae. Psychosocial aspects refer to the emotional and behavioral components of the individual’s social functioning, such as the lack of initiative, impulsivity, irritability, socially inappropriate behavior, self-centeredness, and changes in affect (Ponsford, Olver, & Curran, 1995). The presence of emotional and behavioral problems following severe TBI has been associated with poor social adjustment, such as an inability to resume pre-injury activities and relationships (Tate & Broe, 1999). The long-term psychosocial functioning can remain impaired up to 17 years after the injury (Wood & Rutterford, 2006). The recent interest of social neuroscience for the impaired social perceptiveness in TBI patients is beginning to foster a better understanding of social and moral cognition in these patients. Social cognition refers to the ability to recognize and interpret interpersonal cues that enable us to understand and predict the other’s behavior. For severe TBI patients, the most common deficits in terms of social cognition entail the perception of emotions, empathy, and theory of mind (McDonald, 2013). Some empirical studies suggest that explicit social knowledge may be spared in severe TBI patients (Beer, John, Scabini, & Knight, 2006; Milne & Grafman, 2001; McDonald, Saad, & James, 2011; Turkstra, Dixon, & Baker, 2004), whereas others have found evidence of impaired social judgment, thus questioning this claim (Dimitrov, Grafman, & Hollnagel, 1996). With respect to implicit social knowledge, the issue is even more strongly debated (McDonald et al., 2011; Milne & Grafman, 2001). Moral cognition, instead, refers to the ability to follow ethical and accepted rules and norms (Blair & Cipolotti, 2000). A common way to test moral reasoning is through moral dilemmas involving a conflicting choice between two undesirable alternatives. In these dilemmas, both alternatives yield negative consequences, and none of them clearly emerge as the right choice in moral terms (e.g., choosing between killing one person and letting many people die). Moral cognition in relation to TBI has been scarcely investigated. In fact, to the best of our knowledge, there has been no empirical study providing clear evidence of spared explicit moral knowledge in severe TBI adult patients. If anything, a recent preliminary study has shown that adolescents with moderate-severe TBI display poorer moral reasoning abilities compared to healthy controls (Beauchamp, Dooley, & Anderson, 2013). Given the scarce and conflicting evidence regarding social and moral reasoning in TBI, and the potential key-role of these faculties in the understanding of the psychosocial sequelae associated to TBI, the aim of this study was to directly assess moral and social knowledge in TBI patients, in order to shed light on the potential differences with respect to a group of matched controls. The relationship between explicit moral and social knowledge is usually investigated with the moral/conventional paradigm introduced by Turiel (1983). This author proposed a set of features that sharply distinguish moral from conventional transgressions. According to Turiel, people distinguish conventional (precisely, socio-conventional) from moral transgressions. Specifically, normally developing individuals recognize that some transgressions appear to be matters of social conventions because they are contingent, local, and their wrongness is justified by referring to social order. Moral transgressions, by contrast, are perceived to be universally wrong (independent of convention), more punishable, and their wrongness is justified by referring on harm, injustice, and rights violations. Under this perspective, moral norms tend to be treated as universally applicable, whereas the validity of social conventions is more context-dependent. Indeed, moral norms are considered as characterized by a normative force that operates independently of extant structures of authority or social order. The ability to draw this distinction is deemed as a critical sign of moral knowledge, intended as the faculty to evaluate activities under a specific moral perspective and to make judgments about those activities using distinct moral features. In fact, the ability to distinguish moral from social-conventional transgressions has often been considered as a critical point to support the claim that morality constitutes a distinct cognitive domain (Dwyer, 1999; Hauser, 2006; Mikhail, 2011). Morality is characterized as a universal code of conduct that individuals consider as most important. In committing to this normative aspect of morality, people recognize that there are situations in everyday life that requires a moral response, and that some moral responses are more appropriate than others. People are able to provide justification of their conduct in light of such moral norms, and are able to make moral evaluations of one’s own and others’ actions and behaviors. Furthermore, people are committed to regard some behaviors as immoral, including some behaviors that people themselves are tempted to perform (Dwyer, 1999). Despite the space of moral and social transgression is wide, people have shown that they are able to determine which sorts of transgressions are moral and which are conventional (Huebner, Lee, & Hauser, 2010). For these reasons, it is conceivable that moral cognition, that underlies this ability, could represent a specific cognitive dimension (Hauser, 2006; Mikhail, 2011; Turiel, 1979). Research on the moral-conventional distinction has relied almost exclusively on scenarios designed for young children, even where participants are adults or incarcerated psychopaths (Blair, 1995; Blair & Cipolotti, 2000). Furthermore, to the best of our knowledge, there are no studies that have investigated this distinction on a sizeable sample of TBI patients. For these reasons, using a new and more suitable set of moral/socio-conventional items, the present study investigated the features defining this distinction in order to evaluate more precisely patients’ social and moral cognition, and in order to better clarify whether explicit moral and social knowledge were spared in severe TBI chronic patients. Method Participants Twenty-eight outpatients (21 males, 7 females) with a mean age of 36.29 years (SD = 11.92) and a mean education of 10.39 years (SD = 2.73) were recruited from the TBI database of Physical Medicine and Rehabilitation Unit of Papa Giovanni XXIII Hospital of Bergamo. The distribution of age for TBI patients is represented in Fig. 1. Fig. 1. View largeDownload slide Age distribution in the sample of TBI patients (controls were matched). Fig. 1. View largeDownload slide Age distribution in the sample of TBI patients (controls were matched). Inclusion criteria were: presence of severe traumatic brain injury, defined by GCS < 8 or evidence of posttraumatic amnesia > 7 days (Stein, 1996); chronic phase of patients’ recovery (i.e., at least 1 year postinjury); fluency in Italian; age from 18 to 70 years. Exclusion criteria were: presence of pre-accident history of developmental, neurological, or psychiatric disorders; positive history of alcohol or drug dependency; persistent postinjury language deficits or neglect. Twenty-eight control participants (21 males, 7 females) with a mean age of 36.50 years (SD = 11.52) and a mean education of 10.71 years (SD = 2.59) were recruited among friends and family members of the staff at the Physical Medicine and Rehabilitation Unit. The exclusion criteria were: positive history of developmental, neurological, or psychiatric disorders. The TBI and the control group did not differ in age (t = –.07, df = 54, p = .95) and years of education (t = –.45, df = 54, p = .65). TBI and control participants were enrolled in a larger four-sessions study, of which the present research represents a part. Testing occurred, on average, 7.04 years (SD = 6.90) after the injury. The TBI group had a mean length of Post-Traumatic Amnesia (PTA) of 90.75 days (SD = 43.39). The group was characterized by heterogeneity of traumatic injuries in terms of pathophysiology (contusions, hemorrhages, hematomas, diffuse axonal injury, etc.), and location of brain lesions, documented by CT or MRI scans. Demographic and clinical details are provided in Table 1. Table 1. Demographic and clinical features of participants with traumatic brain injuries Subject No. Age (years) Education (years) Gender Length of PTA (days) GCS Time postinjury (years) Cause of TBI Brain damage reported on acute phase neuroimaging 1 27 8 M 29 N/A 10 MVA SDH L T-P lobe 2 22 11 M 81 5 4 MVA Contusions Bilat F + R T lobes, R BG, L Thalamus, L Corpus Callosum, DAI 3 41 13 M 56 8 1 Fall SAH, L SDH, Contusion R T lobe 4 32 8 M 147 3 17 MVA Diffuse Edema, EDH L and R, Contusion R F lobe 5 21 8 M 51 5 3 MVA Ped SAH, R SDH, Contusions R T + Bilat F lobes 6 51 8 M 98 4 3 MVA SAH, ICH, Contusions R F Lobe, Corpus Callosum, DAI 7 59 13 M 95 7 5 MVA SAH, Contusions Bilat F + L T + R P lobes 8 30 11 M 83 5 14 MVA Diffuse Edema, SAH, Contusion R F lobe 9 31 11 M 84 4 15 MVA Diffuse Edema, EDH L P-O lobe, Contusions Bilat F-T-P lobes + L Cerebellum, R BG 10 63 8 M 53 6 4 SRHI SAH Bilat, Contusions Bilat F lobes, SDH R P, DAI 11 24 8 M 178 7 6 MVA L SDH, Contusions Bilat F + R O lobes 12 42 13 M 17 7 2 Fall SAH, SDH L T lobe, Contusions Bilat F + R T lobes 13 32 13 M 71 5 14 MVA R Hemispheric Edema, Contusions F-T lobes, R BG 14 49 8 M 172 3 9 MVA Extensive Contusions Bilat F-T lobes 15 31 8 M 142 4 7 MVA EDH L F-T lobe, Contusions Bilat F + L T lobes 16 36 13 M 126 3 10 MVA Diffuse Edema, SAH, Contusions Bilat F + L T lobes, L Thalamus, DAI 17 56 8 M 35 N/A 33 MVA SAH, Contusions Bilat F lobes 18 42 13 M 134 5 1 MVA SAH, Contusions Bilat F lobes, L thalamus, Corpus Callosum, DAI 19 26 8 F 34 5 2 MVA SAH, ICH, Contusions Bilat T-P lobes 20 29 18 F 112 N/A 1 MVA EDH Bilat, Contusions Bilat F + R P + Bilat O lobes 21 37 8 M 118 6 8 MVA SDH Bilat F lobes, Contusions R F lobes, Corpus Callosum, R thalamus, DAI 22 24 8 M 89 N/A 1 MVA Contusions Bilat F-T + Bilat F-P lobes, Corpus Callosum, DAI 23 38 13 F 131 3 1 MVA SAH, L SDH, Contusions L F-T lobes 24 29 11 M 87 7 7 MVA SAH, Contusions Bilat F lobes, L internal capsule, DAI 25 27 13 F 98 3 7 MVA SAH, Contusions Bilat F lobes 26 43 8 F 30 N/A 5 MVA Ped SAH, Contusions L F-P lobes, Corpus Callosum 27 22 13 F 113 4 1 MVA Ped L EDH, R BG, Contusions Bilat F-T lobes, Corpus Callosum, DAI 28 52 8 F 77 N/A 6 MVA Contusions Bilat T lobes Subject No. Age (years) Education (years) Gender Length of PTA (days) GCS Time postinjury (years) Cause of TBI Brain damage reported on acute phase neuroimaging 1 27 8 M 29 N/A 10 MVA SDH L T-P lobe 2 22 11 M 81 5 4 MVA Contusions Bilat F + R T lobes, R BG, L Thalamus, L Corpus Callosum, DAI 3 41 13 M 56 8 1 Fall SAH, L SDH, Contusion R T lobe 4 32 8 M 147 3 17 MVA Diffuse Edema, EDH L and R, Contusion R F lobe 5 21 8 M 51 5 3 MVA Ped SAH, R SDH, Contusions R T + Bilat F lobes 6 51 8 M 98 4 3 MVA SAH, ICH, Contusions R F Lobe, Corpus Callosum, DAI 7 59 13 M 95 7 5 MVA SAH, Contusions Bilat F + L T + R P lobes 8 30 11 M 83 5 14 MVA Diffuse Edema, SAH, Contusion R F lobe 9 31 11 M 84 4 15 MVA Diffuse Edema, EDH L P-O lobe, Contusions Bilat F-T-P lobes + L Cerebellum, R BG 10 63 8 M 53 6 4 SRHI SAH Bilat, Contusions Bilat F lobes, SDH R P, DAI 11 24 8 M 178 7 6 MVA L SDH, Contusions Bilat F + R O lobes 12 42 13 M 17 7 2 Fall SAH, SDH L T lobe, Contusions Bilat F + R T lobes 13 32 13 M 71 5 14 MVA R Hemispheric Edema, Contusions F-T lobes, R BG 14 49 8 M 172 3 9 MVA Extensive Contusions Bilat F-T lobes 15 31 8 M 142 4 7 MVA EDH L F-T lobe, Contusions Bilat F + L T lobes 16 36 13 M 126 3 10 MVA Diffuse Edema, SAH, Contusions Bilat F + L T lobes, L Thalamus, DAI 17 56 8 M 35 N/A 33 MVA SAH, Contusions Bilat F lobes 18 42 13 M 134 5 1 MVA SAH, Contusions Bilat F lobes, L thalamus, Corpus Callosum, DAI 19 26 8 F 34 5 2 MVA SAH, ICH, Contusions Bilat T-P lobes 20 29 18 F 112 N/A 1 MVA EDH Bilat, Contusions Bilat F + R P + Bilat O lobes 21 37 8 M 118 6 8 MVA SDH Bilat F lobes, Contusions R F lobes, Corpus Callosum, R thalamus, DAI 22 24 8 M 89 N/A 1 MVA Contusions Bilat F-T + Bilat F-P lobes, Corpus Callosum, DAI 23 38 13 F 131 3 1 MVA SAH, L SDH, Contusions L F-T lobes 24 29 11 M 87 7 7 MVA SAH, Contusions Bilat F lobes, L internal capsule, DAI 25 27 13 F 98 3 7 MVA SAH, Contusions Bilat F lobes 26 43 8 F 30 N/A 5 MVA Ped SAH, Contusions L F-P lobes, Corpus Callosum 27 22 13 F 113 4 1 MVA Ped L EDH, R BG, Contusions Bilat F-T lobes, Corpus Callosum, DAI 28 52 8 F 77 N/A 6 MVA Contusions Bilat T lobes Note. PTA = posttraumatic amnesia, GCS = Glasgow Coma Scale; M = male; F = female; MVA = motor vehicle accident; MVA Ped = motor vehicle accident as pedestrian; SRHI = sports-related head injury; ICH = intracerebral hemorrhage; SAH = subarachnoid hemorrhage; SDH = subdural hematoma; EDH = extradural hematoma; DAI = diffuse axonal injury; R = right; L = left; Bilat = bilateral; F = frontal; P = parietal; T = temporal; O = occipital; BG = basal ganglia; N/A = not available. Table 1. Demographic and clinical features of participants with traumatic brain injuries Subject No. Age (years) Education (years) Gender Length of PTA (days) GCS Time postinjury (years) Cause of TBI Brain damage reported on acute phase neuroimaging 1 27 8 M 29 N/A 10 MVA SDH L T-P lobe 2 22 11 M 81 5 4 MVA Contusions Bilat F + R T lobes, R BG, L Thalamus, L Corpus Callosum, DAI 3 41 13 M 56 8 1 Fall SAH, L SDH, Contusion R T lobe 4 32 8 M 147 3 17 MVA Diffuse Edema, EDH L and R, Contusion R F lobe 5 21 8 M 51 5 3 MVA Ped SAH, R SDH, Contusions R T + Bilat F lobes 6 51 8 M 98 4 3 MVA SAH, ICH, Contusions R F Lobe, Corpus Callosum, DAI 7 59 13 M 95 7 5 MVA SAH, Contusions Bilat F + L T + R P lobes 8 30 11 M 83 5 14 MVA Diffuse Edema, SAH, Contusion R F lobe 9 31 11 M 84 4 15 MVA Diffuse Edema, EDH L P-O lobe, Contusions Bilat F-T-P lobes + L Cerebellum, R BG 10 63 8 M 53 6 4 SRHI SAH Bilat, Contusions Bilat F lobes, SDH R P, DAI 11 24 8 M 178 7 6 MVA L SDH, Contusions Bilat F + R O lobes 12 42 13 M 17 7 2 Fall SAH, SDH L T lobe, Contusions Bilat F + R T lobes 13 32 13 M 71 5 14 MVA R Hemispheric Edema, Contusions F-T lobes, R BG 14 49 8 M 172 3 9 MVA Extensive Contusions Bilat F-T lobes 15 31 8 M 142 4 7 MVA EDH L F-T lobe, Contusions Bilat F + L T lobes 16 36 13 M 126 3 10 MVA Diffuse Edema, SAH, Contusions Bilat F + L T lobes, L Thalamus, DAI 17 56 8 M 35 N/A 33 MVA SAH, Contusions Bilat F lobes 18 42 13 M 134 5 1 MVA SAH, Contusions Bilat F lobes, L thalamus, Corpus Callosum, DAI 19 26 8 F 34 5 2 MVA SAH, ICH, Contusions Bilat T-P lobes 20 29 18 F 112 N/A 1 MVA EDH Bilat, Contusions Bilat F + R P + Bilat O lobes 21 37 8 M 118 6 8 MVA SDH Bilat F lobes, Contusions R F lobes, Corpus Callosum, R thalamus, DAI 22 24 8 M 89 N/A 1 MVA Contusions Bilat F-T + Bilat F-P lobes, Corpus Callosum, DAI 23 38 13 F 131 3 1 MVA SAH, L SDH, Contusions L F-T lobes 24 29 11 M 87 7 7 MVA SAH, Contusions Bilat F lobes, L internal capsule, DAI 25 27 13 F 98 3 7 MVA SAH, Contusions Bilat F lobes 26 43 8 F 30 N/A 5 MVA Ped SAH, Contusions L F-P lobes, Corpus Callosum 27 22 13 F 113 4 1 MVA Ped L EDH, R BG, Contusions Bilat F-T lobes, Corpus Callosum, DAI 28 52 8 F 77 N/A 6 MVA Contusions Bilat T lobes Subject No. Age (years) Education (years) Gender Length of PTA (days) GCS Time postinjury (years) Cause of TBI Brain damage reported on acute phase neuroimaging 1 27 8 M 29 N/A 10 MVA SDH L T-P lobe 2 22 11 M 81 5 4 MVA Contusions Bilat F + R T lobes, R BG, L Thalamus, L Corpus Callosum, DAI 3 41 13 M 56 8 1 Fall SAH, L SDH, Contusion R T lobe 4 32 8 M 147 3 17 MVA Diffuse Edema, EDH L and R, Contusion R F lobe 5 21 8 M 51 5 3 MVA Ped SAH, R SDH, Contusions R T + Bilat F lobes 6 51 8 M 98 4 3 MVA SAH, ICH, Contusions R F Lobe, Corpus Callosum, DAI 7 59 13 M 95 7 5 MVA SAH, Contusions Bilat F + L T + R P lobes 8 30 11 M 83 5 14 MVA Diffuse Edema, SAH, Contusion R F lobe 9 31 11 M 84 4 15 MVA Diffuse Edema, EDH L P-O lobe, Contusions Bilat F-T-P lobes + L Cerebellum, R BG 10 63 8 M 53 6 4 SRHI SAH Bilat, Contusions Bilat F lobes, SDH R P, DAI 11 24 8 M 178 7 6 MVA L SDH, Contusions Bilat F + R O lobes 12 42 13 M 17 7 2 Fall SAH, SDH L T lobe, Contusions Bilat F + R T lobes 13 32 13 M 71 5 14 MVA R Hemispheric Edema, Contusions F-T lobes, R BG 14 49 8 M 172 3 9 MVA Extensive Contusions Bilat F-T lobes 15 31 8 M 142 4 7 MVA EDH L F-T lobe, Contusions Bilat F + L T lobes 16 36 13 M 126 3 10 MVA Diffuse Edema, SAH, Contusions Bilat F + L T lobes, L Thalamus, DAI 17 56 8 M 35 N/A 33 MVA SAH, Contusions Bilat F lobes 18 42 13 M 134 5 1 MVA SAH, Contusions Bilat F lobes, L thalamus, Corpus Callosum, DAI 19 26 8 F 34 5 2 MVA SAH, ICH, Contusions Bilat T-P lobes 20 29 18 F 112 N/A 1 MVA EDH Bilat, Contusions Bilat F + R P + Bilat O lobes 21 37 8 M 118 6 8 MVA SDH Bilat F lobes, Contusions R F lobes, Corpus Callosum, R thalamus, DAI 22 24 8 M 89 N/A 1 MVA Contusions Bilat F-T + Bilat F-P lobes, Corpus Callosum, DAI 23 38 13 F 131 3 1 MVA SAH, L SDH, Contusions L F-T lobes 24 29 11 M 87 7 7 MVA SAH, Contusions Bilat F lobes, L internal capsule, DAI 25 27 13 F 98 3 7 MVA SAH, Contusions Bilat F lobes 26 43 8 F 30 N/A 5 MVA Ped SAH, Contusions L F-P lobes, Corpus Callosum 27 22 13 F 113 4 1 MVA Ped L EDH, R BG, Contusions Bilat F-T lobes, Corpus Callosum, DAI 28 52 8 F 77 N/A 6 MVA Contusions Bilat T lobes Note. PTA = posttraumatic amnesia, GCS = Glasgow Coma Scale; M = male; F = female; MVA = motor vehicle accident; MVA Ped = motor vehicle accident as pedestrian; SRHI = sports-related head injury; ICH = intracerebral hemorrhage; SAH = subarachnoid hemorrhage; SDH = subdural hematoma; EDH = extradural hematoma; DAI = diffuse axonal injury; R = right; L = left; Bilat = bilateral; F = frontal; P = parietal; T = temporal; O = occipital; BG = basal ganglia; N/A = not available. In order to describe the cognitive, behavioral and psychological profile of our patients we administered a battery of standardized neuropsychological tests, a self-report scale describing behavioral problems and a self-report measure of mood/anxiety. The study was approved by the Hospital Ethics Committee and informed consent was obtained from all participants. Stimuli and Procedure Moral and socio-conventional task Participants were administered 20 items. Half of the items (10 items) expressed moral transgressions, whereas the other half (10 items) expressed socio-conventional transgressions (10 items). In particular, transgressions that involved harm, injustice, or right violations were considered as moral transgressions (e.g., “kill a person”), while transgressions that involved a violation of convention without the involvement of harm, injustice, or rights violations were considered as socio-conventional transgressions (e.g., “in a restaurant, sticking a chewing gum under the seat”). The items (see Supplementary material online) were formulated to differentially reflect these key features of moral and socio-conventional transgression, on the basis of the theoretical formulation advanced by Turiel (1983), and were designed to capture the broad ranges of situations in which both moral and socio-conventional transgressions can arise. Under this perspective, we decided to include some conventional transgression in which actions seem particularly bad and punishable (e.g., at a traffic light, go through the red light in order not to be late for an appointment), yet without entailing those aspects that defined moral violations. To facilitate administration and comprehension in severe TBI patients, the experimenter read the items aloud. The same procedure was used for the control group. Participants were then asked to express on a 10-point Likert scale, ranging from 1 = not at all difficult, to 10 = very difficult, how much it would be difficult to perform the transgression. The Likert scale was shown in front of the participants (together with the item in written form). This particular question (instead of the classic question on the wrongness of the violation) capitalizes on the important intrinsic link between normative evaluation and action. After a positive judgment about the legitimacy of a given course of action, in fact, we are motivated to act accordingly. This motivating force towards the enactment of a given behavior is indeed classically regarded as the key feature that marks judgments as normative, thereby distinguishing them from the many other judgments we make (Rosati, 2014). We believe that focusing on the difficulty to perform a transgression allows to understand how normative judgments succeed or fail in motivating people’s behaviors, contributing to better define both moral judgment and moral knowledge. In that sense, the question about moral or socio-conventional transgressions, directly and synthetically taps into the essential feature underlying the normative evaluations we wanted to investigate. Neuropsychological measures A battery of standardized neuropsychological tests was administered to the TBI patients in order to measure: (a) the premorbid intellectual function, (b) memory, (c) working memory, (d) information-processing speed, and (e) attention/executive functioning. Lacking Intelligence Quotient (IQ) evaluations before the illness onset, we used the Test di Intelligenza Breve (TIB; Colombo, Sartori, & Brivio, 2002; Sartori, Colombo, Vallar, Rusconi, & Pinarello, 1997), an italian adaptation of the National Adult Reading Test (NART; Nelson, 1982). Memory was assessed by the Rey Auditory-Verbal Learning Test (RAVLT; Carlesimo, Caltagirone, & Gainotti, 1996; Rey, 1964), and the Prose Memory Test (Spinnler & Tognoni, 1987). Working memory was assessed by the Digit Span Forward (Spinnler & Tognoni, 1987), and the Digit Span Backward (Monaco, Costa, Caltagirone, & Carlesimo, 2013). Information-processing speed was assessed by the Symbol Digit Modalities Test, oral version (SDMT; Nocentini, Giordano, Di Vincenzo, Panella, & Pasqualetti, 2006). Attention/Executive functions were assessed by the Digit Cancellation Test (Della Sala, Laiacona, Spinnler, & Ubezio. 1992), the Trail Making Test A and B (TMT A-B; Giovagnoli et al., 1996; Reitan, 1958), the Stroop Colour-Word Test (Caffarra, Vezzadini, Dieci, Zonato, & Venneri, 2002; Stroop, 1935), the Letter and Semantic Fluency Tests (Novelli et al., 1986), and the Winsconsin Card Sorting Test (WCST; Heaton, Chelune, Talley Kay & Curtiss, 1993; Laiacona, Inzaghi, De Tanti. & Capitani, 2001). All the tests used as normative data the equivalent score scale (e.g., Capitani & Laiacona, 1997), except for the TIB and SDMT which featured respectively the classical IQ range and a cut-off value (34.2). The equivalent score scale is a standardized scale, used in clinical practice to classify patients’ performance after demographic corrections are made (age, education, and gender). The equivalent score scale includes five points: 0–4. An equivalent score of 0 stands for the fifth percentile of the healthy sample, and is considered as the cut-off value signaling pathological performance. Points 2, 3, and 4 are considered normal. Finally, point 1 is considered a borderline score, between normal and pathological performance. As a standardized scale, the equivalent points scale allows clinicians to compare the performance of patients on psychometrically different neuropsychological tests (different scales, stimuli, responses, time constraints, etc.), and to calculate the mean impairment of the patients (Capitani & Laiacona, 1997). We thus used this scale for clinical evaluations, in order to classify patients’ performance as pathological or not. Results are reported in Table S1 (see Supplementary material online). Results of the neuropsychological assessment showed that our TBI chronic severe patients performed poorly just on a verbal memory long-term test (i.e., RAVLT) when compared with normative scores. Behavioral measures The more frequent behavioral problems after severe TBI are social conduct problems, as impulsivity, irritability, inappropriate social behavior, lack of initiative, and self-centeredness (Kelly, Brown, Todd, & Kremer, 2008; Olver, Ponsford, & Curran, 1996; Marsh & Kersel, 2006). To assess the presence of behavioral disorders after TBI, we administrated the caregiver’s version of Head Injury Behaviour Scale (HIBS), which is a self-report questionnaire containing 20 items describing behavioral problems often associated with TBI (Godfrey et al., 2003; Smith & Godfrey, 1995). Table S2 shows the percentage of behavioral problems in our TBI sample. Furthermore, we collected other information via a clinical interview with the caregiver (after administration of the HIBS) and from the patients’ medical records. Psychological measures Depression and anxiety disorders are frequently diagnosed in survivors of TBI and often co-occur. Emotional distress may result either directly from the injury, or as a consequence of TBI-associated difficulties in daily activities, suboptimal coping style, unemployment, and financial stress (Senathi-Raja, Ponsford, & Schöenberger, 2010). Emotional distress of TBI patients was evaluated using the Hospital Anxiety and Depression Scale (HADS), which is a brief self-report questionnaire. The HADS measures symptoms of depression (HADS-D) and anxiety (HADS-A) over the past week by means of two scales, each with seven items scored on a 4-point Likert scale ranging from 0 to 3. Its use with severe TBI patients is well-documented in extant literature (e.g., Dahm, Wong, & Ponsford, 2013; Schöenberger & Ponsford, 2010). Data Analysis Given the experimental design (i.e., each subject responds to each item), we used a mixed-effects model approach for data analysis. This approach allowed us to simultaneously consider all the factors that potentially could contribute to the understanding of the structure of the data (Baayen, Davidson, & Bates, 2008). These factors include not only the standard fixed-effects factors controlled by the experimenter (in our case, Group of Participants and Type of Item), but also the random effect factors (i.e., factors whose levels are drawn at random from a population; in our case, Participants and Items). Specifically, we performed a mixed-effects model with Responses (i.e., ratings on the 10-point Likert scale) as the dependent variable, Group of Participants (Patients vs. Controls) as between-participants fixed effect, Type of Item (Moral transgression vs. Socio-conventional transgression) as within-participants fixed effect, and Participants (n = 56) and Items (n = 20) as random effects. The two-way interaction between Group and Type was also considered. Observed means as a function of conditions are reported in Table 2. Table 2. Observed means (M) and standard deviations (SD) of the responses as a function of group (TBI vs. Controls) and Type of Item (Moral vs. Socio-conventional Transgressions) Group Moral Transgressions Socio-conventional Transgressions M SD M SD TBI (n = 28) 8.14 1.37 4.78 1.43 Controls (n = 28) 9.25 .58 4.55 1.56 Group Moral Transgressions Socio-conventional Transgressions M SD M SD TBI (n = 28) 8.14 1.37 4.78 1.43 Controls (n = 28) 9.25 .58 4.55 1.56 Table 2. Observed means (M) and standard deviations (SD) of the responses as a function of group (TBI vs. Controls) and Type of Item (Moral vs. Socio-conventional Transgressions) Group Moral Transgressions Socio-conventional Transgressions M SD M SD TBI (n = 28) 8.14 1.37 4.78 1.43 Controls (n = 28) 9.25 .58 4.55 1.56 Group Moral Transgressions Socio-conventional Transgressions M SD M SD TBI (n = 28) 8.14 1.37 4.78 1.43 Controls (n = 28) 9.25 .58 4.55 1.56 Potentially, TBI patients responses may be related to a number of other variables we measured. Selectively for the data from TBI patients, we thus ran additional analyses in which we assessed whether the responses were predicted by (a) neuropsychological measures of information-processing speed and attention/executive functions, (b) mood and anxiety scores as indexed by the HADS scale, or (c) PTA and the localization of the brain lesions. First, we assessed whether each one of these variables determined an increased goodness of fit when entered into the model, in addition to the simple effect of Type of Item. Second, we assessed the presence of a potential interaction between each the different measures and the factor Type of Item. Models with interactions were compared, in terms of goodness of fit, with corresponding models where the factor Type of Items and the examined predictor were considered in an additive relationship. Models were compared using likelihood ratio tests. Further, we assessed whether we could detect any correlation between behavioral problems as indexed by the HIBS scale and the responses provided by the participants during the experiment. We did not use the HIBS Global Score as a predictor, as we reasoned that, if anything, behavioral problems may be a consequence, and not a determinant, of socio-conventional and moral knowledge. As several tests were conducted on the same set of data, we applied a fdr correction to the p-values, in order to control for multiple-comparison issues. Results Moral and Socio-Conventional Task There was a significant Group × Type interaction effect (χ2[1] = 25.5, p < .001), which is presented in Fig. 2. This effect was further investigated in terms of simple effects (De Rosario-Martinez, 2015) via multiple contrasts adjusted with the Benjamini and Hochberg (1995) procedure. Analysis across Type of Items showed that Moral items were considered more difficult to transgress than Socio-conventional items in both groups (Patients: χ2[1] = 72.3, p < .001, Cohen’s d = 2.65; Controls: χ2[1] = 140.8, p < .001, Cohen’sd = 3.11). In addition, the analysis across Groups showed that Moral items were considered significantly more difficult to transgress by Controls compared to Patients (χ2[1] = 12.2, p = .001, Cohen’s d = 1.05), whereas no differences was observed for Socio-conventional items (χ2[1] = 0.5, p = .478, Cohen’s d = –.15). (To assess the potential impact of single items on model outcomes, an influence analysis (Nieuwenhuis, te Grotenhuis & Pelzer, 2012) was conducted. No substantial effect of any single item emerged, thus confirming the robustness of our results.) Therefore, patients recognize that moral transgressions are worse than socio-conventional transgressions but, interestingly, they significantly underestimate the magnitude of this moral transgression compared to controls. Fig. 2. View largeDownload slide Estimated means of responses by Type of Item and Group (npatients = 28, ncontrols = 28). Error bars represent 95% confidence intervals. Fig. 2. View largeDownload slide Estimated means of responses by Type of Item and Group (npatients = 28, ncontrols = 28). Error bars represent 95% confidence intervals. These results appear to confirm the hypothesis that moral knowledge seems spared in patients, and that they are able to distinguish moral from socio-conventional transgressions. However, the results also highlight that TBI patients, compared to controls, assign lower ratings to moral violations (and not to socio-conventional ones). In the Discussion we discuss both aspects. Additional Analyses Neuropsychological measures We focused on neuropsychological measures related to attention/executive functions, which could influence social and moral reasoning (e.g., McDonald et al., 2011; Moore, Clark, & Kane, 2008), using raw scores obtained in neuropsychological tests as predictors for the responses given in the experimental tasks. Raw scores were used to capitalize on variability between participants, thus being able to grasp potential finer grained relationships between the predictors and the responses to the experimental items. Specifically, we considered raw scores from the Symbol Digit Modalities Test, the Digit Cancellation Test, the Stroop Colour-Word Test (two predictors: time interference and error interference), the Trail Making Test A and B (three predictors: TMT A, TMT B, TMT B-A), the Letter Fluency task, the Semantic Fluency task, and the Winsconsin Card Sorting Test (four predictors: global scores, perseverations, non-perseverative errors, and failure to maintain the set). None of the measure, either as a main effect or in interaction with Type of Item, yielded a significant improvement in terms of model fit (all ps > .11). Values for the statistical tests are presented in Table 3. Table 3. Statistical results for the measures of attention/executive functions Predictors χ2 df p Value (fdr) Digit Cancellation Test 0.21 1 .89 Digit Cancellation Test * Type of Item 7.12 1 .15 Stroop (time interference) 0.03 1 .98 Stroop (time interference) * Type of Item 3.88 1 .57 Stroop (error interference) 0.06 1 .98 Stroop (error interference) * Type of Item 0.00 1 .99 SDMT 1.23 1 .70 SDMT * Type of Item 2.20 1 .66 TMT A 2.48 1 .66 TMT A * Type of Item 2.77 1 .66 TMT B 0.26 1 .87 TMT B * Type of Item 0.48 1 .75 TMT B-A 0.00 1 .99 TMT B-A * Type of Item 1.46 1 .66 WCST A (global score) 1.51 1 .66 WCST A (global score) * Type of Item 0.10 1 .96 WCST B (perseverations) 0.90 1 .70 WCST B (perseverations) * Type of Item 1.43 1 .66 WCST C (non-perseverative errors) 1.08 1 .70 WCST C (non-perseverative errors) * Type of Item 0.13 1 .96 WCST D (failure to maintain the set) 0.57 1 .74 WCST D * Type of Item 0.00 1 .99 Letter Fluency 0.05 1 .98 Letter Fluency * Type of Item 8.73 1 .12 Semantic Fluency 0.73 1 .71 Semantic Fluency * Type of Item 3.63 1 .57 Predictors χ2 df p Value (fdr) Digit Cancellation Test 0.21 1 .89 Digit Cancellation Test * Type of Item 7.12 1 .15 Stroop (time interference) 0.03 1 .98 Stroop (time interference) * Type of Item 3.88 1 .57 Stroop (error interference) 0.06 1 .98 Stroop (error interference) * Type of Item 0.00 1 .99 SDMT 1.23 1 .70 SDMT * Type of Item 2.20 1 .66 TMT A 2.48 1 .66 TMT A * Type of Item 2.77 1 .66 TMT B 0.26 1 .87 TMT B * Type of Item 0.48 1 .75 TMT B-A 0.00 1 .99 TMT B-A * Type of Item 1.46 1 .66 WCST A (global score) 1.51 1 .66 WCST A (global score) * Type of Item 0.10 1 .96 WCST B (perseverations) 0.90 1 .70 WCST B (perseverations) * Type of Item 1.43 1 .66 WCST C (non-perseverative errors) 1.08 1 .70 WCST C (non-perseverative errors) * Type of Item 0.13 1 .96 WCST D (failure to maintain the set) 0.57 1 .74 WCST D * Type of Item 0.00 1 .99 Letter Fluency 0.05 1 .98 Letter Fluency * Type of Item 8.73 1 .12 Semantic Fluency 0.73 1 .71 Semantic Fluency * Type of Item 3.63 1 .57 Note: df = degrees of freedom; p value(fdr) = p value corrected via false discovery rate in order to control for multiple comparisons; SDMT = symbol-digit modalities test; TMT = trail making test; WCST = Winsconsin Card Sorting Test. Table 3. Statistical results for the measures of attention/executive functions Predictors χ2 df p Value (fdr) Digit Cancellation Test 0.21 1 .89 Digit Cancellation Test * Type of Item 7.12 1 .15 Stroop (time interference) 0.03 1 .98 Stroop (time interference) * Type of Item 3.88 1 .57 Stroop (error interference) 0.06 1 .98 Stroop (error interference) * Type of Item 0.00 1 .99 SDMT 1.23 1 .70 SDMT * Type of Item 2.20 1 .66 TMT A 2.48 1 .66 TMT A * Type of Item 2.77 1 .66 TMT B 0.26 1 .87 TMT B * Type of Item 0.48 1 .75 TMT B-A 0.00 1 .99 TMT B-A * Type of Item 1.46 1 .66 WCST A (global score) 1.51 1 .66 WCST A (global score) * Type of Item 0.10 1 .96 WCST B (perseverations) 0.90 1 .70 WCST B (perseverations) * Type of Item 1.43 1 .66 WCST C (non-perseverative errors) 1.08 1 .70 WCST C (non-perseverative errors) * Type of Item 0.13 1 .96 WCST D (failure to maintain the set) 0.57 1 .74 WCST D * Type of Item 0.00 1 .99 Letter Fluency 0.05 1 .98 Letter Fluency * Type of Item 8.73 1 .12 Semantic Fluency 0.73 1 .71 Semantic Fluency * Type of Item 3.63 1 .57 Predictors χ2 df p Value (fdr) Digit Cancellation Test 0.21 1 .89 Digit Cancellation Test * Type of Item 7.12 1 .15 Stroop (time interference) 0.03 1 .98 Stroop (time interference) * Type of Item 3.88 1 .57 Stroop (error interference) 0.06 1 .98 Stroop (error interference) * Type of Item 0.00 1 .99 SDMT 1.23 1 .70 SDMT * Type of Item 2.20 1 .66 TMT A 2.48 1 .66 TMT A * Type of Item 2.77 1 .66 TMT B 0.26 1 .87 TMT B * Type of Item 0.48 1 .75 TMT B-A 0.00 1 .99 TMT B-A * Type of Item 1.46 1 .66 WCST A (global score) 1.51 1 .66 WCST A (global score) * Type of Item 0.10 1 .96 WCST B (perseverations) 0.90 1 .70 WCST B (perseverations) * Type of Item 1.43 1 .66 WCST C (non-perseverative errors) 1.08 1 .70 WCST C (non-perseverative errors) * Type of Item 0.13 1 .96 WCST D (failure to maintain the set) 0.57 1 .74 WCST D * Type of Item 0.00 1 .99 Letter Fluency 0.05 1 .98 Letter Fluency * Type of Item 8.73 1 .12 Semantic Fluency 0.73 1 .71 Semantic Fluency * Type of Item 3.63 1 .57 Note: df = degrees of freedom; p value(fdr) = p value corrected via false discovery rate in order to control for multiple comparisons; SDMT = symbol-digit modalities test; TMT = trail making test; WCST = Winsconsin Card Sorting Test. Behavioral Problems There was no correlation between the Global Scores from the HIBS and the responses provided by TBI patients to either Socio-conventional (rs = –.21, p = .70) or Moral items (rs = –.16, p = .73). Thus, there is no evidence of a relationship between the behavioral problems highlighted by the caregivers, and the responses to our experiment. Mood and anxiety (emotional distress) Mean Depression and Anxiety scores obtained with the HADS scale as a function of Group (Control vs. TBI) are reported in Table 4. The difference in terms of mean scores was significant for the Depression score (t[52] = 2.89, p < .01), with higher scores for TBI patients, but not for the Anxiety score (t[52] = 1.02, p = .31). For TBI patients, neither the Anxiety score (χ2[1] = 0.00, p = .99), nor the Depression score (χ2[1] = 0.87, p = .70) produced a significant increase in terms of model fit, suggesting that these scores do not modulate the ratings provided by the participants. Further, neither the Anxiety (χ2[1] = 0.04, p = .98), nor the Depression score (χ2[1] = 1.65, p = .66) interacted with Type of Item, suggesting that the difference between responses to moral and socio-conventional items highlighted within our sample of TBI patients is not explained by emotional distress. Table 4. Mean Anxiety and Depression scores calculated from the HADS scale for Controls (CTRL) and TBI patients (TBI) Group Anxiety Depression CTRL 6.84 (3.19) 3.19 (2.15) TBI 7.56 (4.46) 5.15 (2.80) Group Anxiety Depression CTRL 6.84 (3.19) 3.19 (2.15) TBI 7.56 (4.46) 5.15 (2.80) Standard deviations are reported within parentheses. Table 4. Mean Anxiety and Depression scores calculated from the HADS scale for Controls (CTRL) and TBI patients (TBI) Group Anxiety Depression CTRL 6.84 (3.19) 3.19 (2.15) TBI 7.56 (4.46) 5.15 (2.80) Group Anxiety Depression CTRL 6.84 (3.19) 3.19 (2.15) TBI 7.56 (4.46) 5.15 (2.80) Standard deviations are reported within parentheses. PTA and localization of brain lesions PTA duration, which is a strong predictor of outcome in survivor TBI (e.g., Nakase-Richardson, Yablon, & Sherer, 2007; Walker et al., 2010), failed to determine an increase in terms of explained variance (χ2[1] = 1.86, p = .66). Overall, the responses to our experiment do not seem to be modulated by PTA. Additionally, the PTA by Type of Item interaction was not significant (χ2[1] = 0.49, p = .74), suggesting that PTA does not modulate the difference between responses to moral and socio-conventional items. Severe TBI patients commonly show at the same time focal and diffuse brain damage. Focal brain damage includes parenchimal contusions, epidural, subdural and intraparenchymal hematomas, whereas diffuse brain damage entails diffuse axonal injury, diffuse cerebral edema, diffuse vascular injury and hypoxic-ischemic injury (Andriessen, Jacobs, & Vos, 2010). The most common sign of diffuse brain damage is the diffuse axonal injury (DAI). Nevertheless, Bigler (2001) advocated the use of the more general term of diffuse brain injury (DBI), which includes DAI as well as other measures of diffuse damage, such as diffuse cerebral edema, diffuse vascular injury and hypoxic-ischemic injury. The routine neuroimaging tool used in acute phase, CT scan, is less sensitive than MRI scan to detect the DAI (Gentry, Godersky, Thompson, & Dunn, 1988). Since we had the CT scan for all the patients, and the MRI scan just for a part of them, we considered as index of DBI not only the DAI, but also the diffuse cerebral edema, which is commonly detectable in CT scan reports (Unterberg, Stover, Kress, & Kiening, 2004). Therefore, evidence of DBI was provided by the presence of diffuse axonal injury and/or diffuse cerebral edema. To study the relationship between brain lesions and moral and socio-conventional judgment we conducted three analyses. The diffuse damage may have a larger influence on moral and socio-conventional reasoning than focal damage in severe TBI patients. To test this hypotheses we categorize our TBI patients in two groups: DBI (n = 14) versus not DBI (n = 14). Results showed that the classification as a function of presence/absence of DBI failed to explain additional variance both as a main effect (χ2[1] = 1.02, p = .70), and in interaction with Type of item (χ2[2] = 2.00, p = .66). Extant literature on acquired brain injury strongly suggests that ventromedial prefrontal cortex (vmPFC) and orbitofrontal cortex (OFC) play a crucial role in social and moral cognition, even though the most part of the patients involved in these studies shown focal vascular (e.g., Ciaramelli, Sperotto, Mattioli, & Di Pellegrino, 2007; Koenigs et al., 2007) or focal brain tumor lesions (e.g., Saver & Damasio, 1991). To test this hypotheses we categorize our TBI patients in three groups: frontal (10) versus not frontal (n = 4) versus DBI (n = 14). Even this categorization failed to increase the amount of explained variance both when considered as a main effect (χ2[2] = 1.37, p = .75), or in interaction with the factor Type of item (χ2[2] = 3.04, p = .66). The literature on moral cognition has shown a causal role of emotion processing in moral reasoning for healthy people (Greene, Sommerville, Nystrom, Darley, & Cohen, 2001) and for patients with brain injury (Koenigs et al., 2007). Furthermore there is strong evidence of impaired emotional processing in severe TBI (Babbage et al., 2011). Emotional processing involves a frontotemporal network (Gorno-Tempini et al., 2001) that is commonly damaged in severe TBI (Bigler, 2001). We thus conducted a final analysis in which we distinguished TBI patients with lesions encompassing both the frontal and temporal lobe (n = 12) and TBI patients with lesions not involving either the frontal or the temporal lobe (n = 16). This final classification failed to display any significant increase in terms of model fit, both when considered as a main effect (χ2[2] = 0.00, p = .99), or in interaction with the factor Type of Item (χ2[1] = 0.08, p = .70). It is important to warrant caution in the interpretation of these results. The analyses reported at point 2 and 3 compare groups with unequal sample size. Additionally, all three analyses categorize TBI patients within groups featuring small sample size. Given these limitations, we stress that these analyses should be considered as tentative and that specific research would be needed to clearly address each of the three hypotheses outlined above, here approached in merely exploratory terms. Discussion This study examined explicit social and moral knowledge in severe TBI patients. Building on the theoretical framework developed by Turiel (1983), which proposed a distinction between moral and conventional transgressions, we implemented a new set of moral and socio-conventional items that are both more appropriate and more relevant for adults, compared to those used in previous studies (e.g., Blair, 1995; Blair & Cipolotti, 2000; Turiel, 1983; Nucci & Turiel, 1978). Our data shown that TBI patients, like control participants, were able to differentiate between moral and socio-conventional transgressions, as they considered the former more difficult to fulfill. These results suggest that explicit moral and socio-conventional knowledge may be spared in the present sample of TBI patients. Our patients seem to retain knowledge of the difference between the universality of the moral norms and the contingency of the socio-conventional norms. Our findings may thus be consistent with the notion that people with severe TBI retain access to previously acquired knowledge about socio-conventional norms, whereas potential difficulties may arise in applying this knowledge to their behavior (Beer et al., 2006). Interestingly, to the best of our knowledge, we have provided a first evidence suggesting that the knowledge spared in severe TBI patients is not limited to socio-conventional norms, but it may extend to moral norms. Following this rationale, an intriguing research question is the relationship between brain lesions’ sites and the outcome in terms of storage and access of socio-conventional and moral norms. However, any hypothesis of relationship should be taken with caution due to strong and common evidence of diffuse brain injury in severe TBI, although some brain areas involved in social and moral cognition and social and moral behavior (e.g., ventrolateral frontal lobes, inferior orbital cortices, and temporal lobes), are more vulnerable and thus more frequently damaged than others. In our study, however, all the patients were severe TBI with different, multiple, and extensive lesions. Thus, it was difficult to reliably the role of location, load and extension of brain lesions with respect to moral and socio-conventional knowledge. Although it was not the goal of our study, we tried to shed light on this issue by categorizing our patients, using the acute phase neuroimaging reports, in (a) DBI versus non-DBI, (b) frontal versus non-frontal versus DBI, and (c) frontotemporal versus non-frontotemporal. None of these categorizations appears to predict the responses provided by TBI patients in our experiment, nor they exert a selective influence on either moral or socio-conventional items. We may therefore hypothesize that the evidence of a spared moral and socio-conventional knowledge in our patients could be determined by the fact that the brain areas storing and processing this kind of knowledge are not damaged by severe TBI. Another interesting result surfacing from our work is that TBI patients, compared to controls, considered moral transgressions as easier to fulfill. With respect to this issue, our finding may underlie a tendency in TBI patients to underestimate the weight of moral transgressions. From a behavioral point of view, the consequence of abnormal morality is well described by the antisocial behavior (e.g., stealing, aggression against persons or property). And yet, literature and clinical practice show that antisocial behaviors are not common in adult severe TBI. In fact, excluding the acute phase of TBI, the most common behavioral problems after severe TBI revolve around issues of social conduct (e.g., impulsivity, irritability, inappropriate social behavior, lack of initiative and self-centeredness; see Kelly et al., 2008; Marsh & Kersel, 2006; Olver et al., 1996; Baugley, Cooper, & Felmingham, 2006; Dyer, Bell, McCann, & Rauch, 2006). Even when aggressive behaviors are found (Baugley et al., 2006; Dyer et al., 2006), they are of limited severity (i.e., impulsive verbal aggression and anger) and scarcely related to an abnormal moral behavior. Differently, the literature on early-onset prefrontal-lesions (commonly caused by severe TBI) showed a link with an abnormal development of moral behavior (Anderson, Bechara, Damasio, Tranel, & Damasio, 1999). The hypothesis proposed by the authors is that an early-onset brain injury can impair the acquisition of moral knowledge and the following behavioral inadequacy could be therefore explained by an absence of the specific knowledge required for moral behavior. Furthermore, individuals who experienced TBI in childhood are more at risk of developing a range of externalizing disorders associated with antisocial behavior in adulthood (e.g., Fergusson & Lynskey, 1998; McKinlay et al., 2014). However these findings should interpreted with caution. There is little information about how to identify individuals with TBI who might be at risk for developing abnormal social or moral behavior, and there are several factors related to TBI (brain lesions site and extension, pre and postmorbid social environment, premorbid personality, etc.) that could influence the development of antisocial behaviors. We obtained information about behavioral disorders of our TBI patients by via the caregiver’s version of the HIBS. Furthermore, we collected additional information by interviewing the same caregiver and by medical reports. We didn’t find evidence of significant abnormal moral behavior (i.e., antisocial behavior). The HIBS contains just a single potential moral item, which refers to aggressive behavior, and all the caregivers reported that only verbal, and not physical, aggression has been occasionally observed. In contrast, caregivers reported problems in terms of social conduct, as indeed commonly described in severe TBI. As our patients shown an overall good executive functioning, these findings are consistent with the numerous published cases of individuals with bilateral injuries to the frontal lobes displaying postmorbid deficits in social behavior, with normal performances on standard tests of executive functioning (e.g., Barker, Andrade & Romanowski, 2004; Eslinger & Damasio, 1985; Shallice & Burgess, 1991). Although our data did not provide evidence of significant abnormal moral behaviors in patients’ everyday life, future researches should investigate systematically the relationship between moral knowledge and moral behavior in adult severe TBI. Possibly, experimental designs with moral dilemmas (Greene et al., 2001; Lotto, Manfrinati, & Sarlo, 2014) and finer-grained measures of daily behavior could settle this issue. Some limitations of the present study are worth mentioning. First, by measuring how much it would be difficult to perform a moral or a socio-conventional transgression we used just explicit measures. This approach does not fully account for all the different components involved in moral and socio-conventional knowledge. Particularly, it may be interesting to address implicit measures of moral and socio-conventional knowledge. Previous research (McDonald et al., 2011) has exploited the Implicit Association Test (IAT) to measure implicit social cognition and has suggested that there is no evidence, in TBI patients, of any deficit in terms of implicit social knowledge. Similarly, it might be interesting to investigate the implicit aspects of moral knowledge, and future studies may try to integrate explicit measures of moral knowledge with measures based on associative processes (e.g., the moral IAT; Perugini & Leone, 2009). However, it is important to note that this approach has some important limitations. For example, the use of the IAT, although potentially interesting, could be problematic in TBI because of possible impairments in processing speed, attention and executive functions. All these factors can, in principle, exert an important influence on the IAT results, thus complicating any interpretation. In case, it would be important to devise studies where it becomes possible to control for the influence of these confounding factors (Klauer, Schmitz, Teige-Mocigemba & Voss, 2010; McDonald et al., 2011). The feasibility of such studies remains to be evaluated. Further, we did not use a standardized, validated instrument to assess moral and social knowledge, nor we created one. Rather, our approach was to devise an experiment in which participants could be presented with situations encompassing violations of either moral or socio-conventional norms, and the two distinct groups of items were created solely on the basis of the theoretical distinction between moral and conventional transgressions (e.g., Turiel, 1983). Although this approach may cast doubts on the generalizability and consistency of the results, we note that the use of mixed models allows to account for variability related to specific participants and items. Further, we performed an influence analysis which further confirmed that our results were not driven by single items. These aspects speak in favor of the consistency of our results, despite the lack of a validated scale or instrument. Second, our study did not explore the relationship between moral and socio-conventional tasks and emotions processing. Extant literature highlights a debate about the roles of emotional processing in moral reasoning (Greene et al., 2001; Huebner, Dwyer, & Hauser, 2009; Manfrinati, Lotto, Sarlo, Palomba, & Rumiati, 2013; Manfrinati, 2015). However, increasing evidence from healthy and brain-damaged participants suggests that an emotionally mediated brain network is crucial in moral reasoning (Koenigs et al., 2007; Moll & De Oliveira-Souza, 2007). This network seems to include the vmPFC (especially on the right hempisphere), the adjacent orbitofrontal and ventrolateral cortices (OFC/VL), the amygdala, and related structures. The vmPFC, with its rich interconnections with limbic structures, mediates strong automatic reactions to moral violations (Mendez, 2009). Following these hypotheses, a damage of this frontotemporal network, which is commonly damaged in severe TBI (Bigler, 2001), could explain the tendency of our TBI patients to underestimate moral transgressions with respect to the control group. As emotion processing seems to be impaired in severe TBI (Babbage et al., 2011), potentially TBI moral knowledge could be biased by emotion processing disorders. Future studies should thus investigate more explicitly whether (potential) emotional impairments in TBI patients affect the ability to distinguish between moral and socio-conventional transgressions, and whether these impairments may have some backlash on day-to-day behavior. Third, the most part of our neuroimaging data were detected by CT scan reports of acute phase, so we had just a crude measure of the traumatic brain damage complexity. Consequently, lesions in the frontotemporal network may have been undetectable by our neuroimaging tools. Further investigation with lesion analysis methods and more sensitive neuroimaging techniques (i.e., Diffusion Tensor Imaging and Voxel-Based Morphometry), could better analyze the brain damage following TBI (e.g., Levine et al., 2013; Solomon, Raymont, Braun, Butman, & Grafman, 2007; Volebel, Genova, Chiaravalotti & Hoptman, 2012). Finally, we used a self-report measure to assess moral and socio-conventional knowledge. Self-report measures may be influenced by a number of variables, including social desirability and a lack of self-awareness or insight. However, although the use of self-report scales in TBI patients research is sometimes questioned, some studies shown that self-report measures of empathy and mood can be reliably used in the context of severe TBI (de Sousa et al., 2010, 2011; Williams & Wood, 2009; Wood & Williams, 2008). Moreover, our data shown that TBI patient considered moral transgressions as easier to fulfill compared to control participants. This result goes against social desirability. Finally, it is difficult to explain this result in terms of lack of self-awareness, as the underestimation is limited just to moral transgressions, whereas any general feature such as reduced insight or self-awareness should equally affect all the judgments, and not only those of a specific category. That said, it is still possible that our self-reported evaluations are not entirely free from exogenous influences of important factors escaping insight and self-awareness. Furthermore, it is important to note that our study potentially captured just more explicit aspects of social and moral knowledge. Even if this type of knowledge seems maintained, the implicit dimension of moral and social knowledge, not investigated in our study, could provide further interesting perspectives on the relationship between knowledge and behavior. In fact, we cannot rule out the possibility that the implicit aspects of moral and social knowledge may exert an influence on behavior along different trajectories compared to those captured by explicit judgments. In conclusion, whereas previous studies provided evidence of spared explicit social knowledge in TBI patients (Beer et al., 2006; McDonald et al., 2011; Milne, & Grafman, 2001; Turkstra et al., 2004), in this study we have shown that the same seems true at least for explicit moral knowledge. In fact, exactly as control participants, TBI patients rated moral transgressions as more difficult to enact compared to socio-conventional ones, suggesting that even for TBI patients the two categories can be differentiated. Nonetheless, TBI patients, rated the enactment of moral transgression as significantly less difficult, compared to matched controls. Supplementary Material Supplementary material is available at Archives of Clinical Neuropsychology online. Funding M.S. has been supported by Agence Nationale de la Recherche [grant numbers ANR-16-CONV-0002, ANR-11-LABX-0036, ANR-11-IDEX-0001-02]. Conflict of Interest None declared. Acknowledgments The present study is dedicated to the beloved memory of M.M. References Anderson , S. W. , Bechara , A. , Damasio , H. , Tranel , D. , & Damasio , A. R. ( 1999 ). Impairment of social and moral behavior related to early damage in human prefrontal cortex . Nature Neuroscience , 2 , 1032 – 1037 . Google Scholar CrossRef Search ADS PubMed Andriessen , T. M. J. C. , Jacobs , B. , & Vos , P. E. ( 2010 ). Clinical characteristics and pathophysiological mechanisms of focal and diffuse traumatic brain injury . Journal of Cellular and Molecular Medicine , 14 , 2381 – 2392 . Google Scholar CrossRef Search ADS PubMed Baayen , R. H. , Davidson , D. J. , & Bates , D. M. ( 2008 ). Mixed-effects modeling with crossed random effects for subjects and items . Journal of Memory and Language , 59 , 390 – 412 . 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Archives of Clinical NeuropsychologyOxford University Press

Published: Oct 27, 2017

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