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. Author manuscript; available in PMC: 2010 Dec 21.
Published in final edited form as: J Clin Exp Neuropsychol. 2010 Dec;32(10):1050–1061. doi: 10.1080/13803391003683062

Capacity to Make Medical Treatment Decisions in Multiple Sclerosis: A Potentially Remediable Deficit

Michael R Basso 1, Philip J Candilis 2, Jay Johnson 3, Courtney Ghormley 4, Dennis R Combs 5, Taeh Ward 6
PMCID: PMC2948068  NIHMSID: NIHMS201696  PMID: 20446143

Abstract

Ability to make decisions about medical treatment is compromised in significant numbers of people with neurological and psychiatric illness, and this incapacity frequently corresponds with compromised neuropsychological function. Although cognitive deficits occur often in people with multiple sclerosis (MS), no research has studied decisional capacity in that disease. The present investigation examined ability to understand treatment disclosures, which is a core component of decisional capacity, in 36 people with MS and 16 normal controls. MS patients with diminished neuropsychological function showed poor understanding of treatment disclosures compared to the control group, and diminished new-learning and executive function correlated with poorer understanding. Nonetheless, with sufficient cueing, the MS patients with diminished neuropsychological function were able to display understanding that was equivalent to the control group. Implications of these results for clinical practice and medical research involving people with MS are discussed.

Keywords: multiple sclerosis, neuropsychological function, informed consent, decision-making


Ability to make independent and autonomous decisions regarding medical treatment is a complex activity of daily living. Prior to making treatment decisions, patients are typically provided information concerning the risks and benefits of possible medical interventions. Ostensibly, they then carefully weigh these issues, and make a rational decision. According to one prominent model (Appelbaum and Grisso, 1998), patients face the choice of accepting or rejecting various medical options by considering four major domains. To make a competent decision, the individual must be able to 1) express a treatment choice; 2) appreciate the personal consequences of their choice; 3) make a rational decision concerning treatment; and 4) understand the treatment and its risks and benefits (Appelbaum & Grisso, 1995; Appelbaum, Lidz, & Meisel, 1987; Appelbaum & Roth, 1982). These capacities were derived from thorough reviews of the medical and legal literature. Although they vary somewhat with other proposed standards (cf. Marson, 2001; Marson, Ingram, Cody, & Harrell, 1995; Marson, Schmitt, Ingram, & Harrell, 1994), they are widely applied and are consistent with existing medical ethics and legal precepts. According to this influential approach, ability to make a decision regarding medical treatment may be compromised by neuropsychological dysfunction. Because disease-related cognitive abnormality is sometimes latent or subtle, medical providers may unwittingly violate the rights or autonomy of their patients, especially those with neurological or psychiatric illness.

Indeed, several studies have examined the impact of neuropsychological impairment upon capacity to make treatment decisions. Furthermore, numerous investigations have studied the capacity to give informed consent in clinical research trials. This follows because the ability to make decisions about medical research participation appears to parallel the capacity to make decisions about medical treatment – both may involve the same core capacities of understanding, appreciation, reasoning, and expression of choice. Together, research concerning capacity to make decisions about medical treatment and medical research reveals that each of these four capacities may be diminished by cognitive impairment, thereby rendering an individual unable to demonstrate appropriate decision-making capacity (Appelbaum & Grisso, 1988; Appelbaum & Grisso, 1995; Appelbaum & Roth, 1982; Appelbaum et al., 1987; Grisso; 1986; Grisso & Appelbaum, 1998; Marson, 2001; Marson et al., 1995; Marson et al., 1994; Roth, Meisel, & Lidz, 1977). Specifically, studies involving people with schizophrenia (Candilis et al, 2006; Carpenter et al., 2000; Combs et al., 2005; Grisso, Appelbaum, Mulvey, & Fletcher, 1995; Moser et al., 2002; Moser et al., 2006; Palmer et al., 2005), HIV (Moser et al., 2002), mania (Howe et al., 2005), Alzheimer’s disease (Gurrera, Moye, Karel, Azar, & Armesto, 2006; Kim, Caine, Currier, Leibovici, & Ryan, 2001; Marson, Chatterjee, Ingram, & Harrell, 1996; Marson & Harrell, 1999; Palmer et al., 2005), diabetes (Candilis et al, 2008), and Parkinson’s disease (Dymek, Atchison, Harrell, & Marson, 2001; Griffith, Dymek, Atchison, Harrell, & Marson, 2005) reveal that patients are often incapable of providing informed consent to treatment or medical research participation. Several recent reviews imply that ability to understand treatments and clinical research is among the decisional components most commonly diminished in people with these disorders (Dunn, Nowrangi, Palmer, Jeste, & Saks, 2006; Moye, Gurrera, Karel, Edelstein, & O’Connell, 2006; Palmer & Savla, 2007).

In addition to investigations using neuropsychologically-impaired groups, some studies have utilized correlational analyses, and examined the relationship between overall cognitive measures (e.g., Mini Mental Status Examination, Dementia Rating Scale (DRS) Total Score, or Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) Total Score) and performance on measures of decisional capacity. Similar to studies involving group contrasts, overall cognitive dysfunction appears to correspond with poor decisional capacity (e.g., Appelbaum & Grisso, 1997; Bambara et al., 2007; Carpenter et al., 2000; Dunn et al., 2002; 2007; Palmer et al., 2005). Although these findings imply that neuropsychological dysfunction corresponds with decisional incapacity, they fail to delineate what aspects of neurocognition correspond with specific components of medical decision-making. Accordingly, a number of studies have begun to elaborate such relationships. Employing a variety of neuropsychological predictors and medical decision-making tools with several clinical populations, executive function, new-learning, and working memory emerge as salient correlates of understanding, reasoning, and appreciation of informed consent disclosures (Dunn, Candilis, & Roberts, 2006;Dymek et al., 2001; Gurrera et al., 2006; Kovnick, Appelbaum, Hoge, and Leadbetter, 2003; Moser et al., 2002; Okonkwo et al., 2008; Palmer, Dunn, Appelbaum, & Jeste, 2004; Palmer & Jeste, 2006).

Across each of these investigations, it is clear that neuropsychological dysfunction corresponds with diminished ability to make competent medical decisions. Notably, capacity to understand medical ailments and treatment choices appears to be especially vulnerable to overall cognitive impairment and more specifically to problems in memory, working memory, and executive function (cf. Dunn, Candilis, & Roberts, 2006; Palmer & Savla, 2007 for compelling reviews). This implies that individuals with such deficits may be prone to misunderstand details of a treatment regimen, or they may have difficulty comprehending its risks and benefits.

Of course, the presence of neurological or psychiatric disorder does not automatically guarantee incompetent decisions. Notably, in the aforementioned studies, only some patients were incapable of providing informed consent. For instance, approximately half of people with Alzheimer’s disease can exhibit capable decision-making, discriminate between studies of varying risk and benefit, and demonstrate similar comprehension of risk and benefit as do healthy elderly control subjects (e.g., Kim et al., 2001; Kim, Cox, & Caine, 2002). Hospitalized patients with schizophrenia or schizoaffective disorder score as well on standardized measures of informed consent capacity as do 69–89% of healthy control subjects (Candilis et al., 2008). Often those who exhibit decisional impairment cannot be identified by common demographic variables or even diagnosis (Carpenter et al., 2000). Furthermore, neuropsychological impairment does not equal decisional-incapacity. Although performance on neuropsychological tests typically accounts for an average of 40% to 60% of variance on measures of medical decision-making, considerable variation in decisional-capacity remains unaccounted for (e.g., Gurrera et al., 2006). Thus, it is important to recognize that much individual variation in decision-making capacity remains despite disease status or the presence of neuropsychological impairment.

In this context, investigations of competent decisions among neurologically-ill patients have been mainly limited to elderly individuals with cortical (Alzheimer’s) and subcortical (Parkinson’s) diseases. Considerably less is known in this regard concerning younger patients with neurodegenerative diseases, such as those with multiple sclerosis (MS). MS is a common neurological condition affecting thousands of Americans. It results in a wide range of sensory, motor, psychiatric, and neurobehavioral symptoms. Cognitive deficits occur in as many as 60% of patients with MS, and executive function, new-learning, and working memory are commonly diminished (Bobholz & Rao, 2003; Martin, Hohlfeld, & McFarland, 1996). For instance, with respect to these domains, performance deficits have been observed on a number of measures, including the Wisconsin Card Sorting Test, California Verbal Learning Test, or Paced Auditory Serial Addition Test, respectively (e.g., Rao, Leo, Bernardin, & Unverzagt, 1991a). Such impairment corresponds with considerable morbidity, with considerable evidence revealing that and neurocognitive dysfunction predicts diminished activities of daily living and increased disability (Benedict et al., 2005; Kessler, Cohen, Lauer, & Kausch, 1992; Rao, Leo, Ellington, et al., 1991).

Numerous beneficial pharmacological treatments for MS have been developed and tested within the past decade (e.g., Geisler et al., 1996; Pliskin et al., 1996). However, each has potential adverse consequences, and was tested in human trials. Participants in these clinical trials, where consequently exposed to significant risk. For patients receiving treatment and participants in clinical trials to make competent medical decisions, they must understand potential benefits and risks of interventions (Appelbaum & Grisso, 1995). Yet, because neuropsychological impairment is common in MS (Beatty et al., 1996; DeLuca, Barbieri-Berger, & Johnson, 1994; Gafman, Rao, Bernardin, & Leo, 1991; Geisler et al., 1996; Kessler et al., 1992; Kujala, Portin, & Ruutiainen, 1996; Pliskin et al., 1996; Rao, Leo, Bernardin, et al., 1991; Rao, Leo, Ellington, et al., 1991; Tsolaki et al., 1994), patients may have difficulty understanding the details of medical intervention. As a result, providers may administer potentially risky treatments to their patients without obtaining adequate informed consent. Furthermore, investigators developing future interventions may unknowingly recruit participants whose ability to comprehend information or make complex decisions may be compromised (Kessler et al., 1992; Rao et al., 1991a). In doing so, clinicians and researchers may inadvertently fail to treat the participants in an appropriate manner. To our knowledge, no investigation has determined whether people with MS are at particular risk of providing inadequate informed consent to medical interventions.

In the present investigation, we attempted to explore this issue. In particular, we focused on understanding elements of an informed consent disclosure. Although this is only one of the four capacities presumed to underlie informed consent capacity, understanding is among the most extensively described and most commonly studied (Dunn et al., 2006). Towards this end, we used the Understanding Treatment Disclosures (UTD) instrument developed as part of the MacArthur Treatment Competence Study. It is one of the first measures implemented to assess informed consent capacity and has demonstrated reliability and validity in patients with psychiatric and neurological disorders (Appelbaum & Grisso, 1995; Grisso & Appelbaum, 1995; Grisso et al., 1995). It is considered a reliable and valid method of measuring understanding of medical disclosures (Dunn, Nowrangi, et al., 2006; Moye et al., 2006). Indeed, abundant research shows that the UTD and its direct descendant, the MacArthur Competence Assessment Tool (MacCAT), possess convergent and criterion validity. Regarding convergent validity, they correlate with other published measures of understanding disease status and treatment choices (cf. Gurrera et al., 2006; Moye et al., 2006). With respect to criterion validity, several studies have shown that the UTD and MacCAT understanding scales correlate with clinician judgments of decisional competency in clinical populations. Clinician judgment is typically considered the “gold-standard” criterion, and is relied upon by the courts in making determinations of decisional-competence (cf., Appelbaum & Grisso, 1995). In this vein, Pruchno et al. (1995) found that the UTD emerged as a major predictor of clinician judgments regarding decisional capacity of demented elderly patients. Likewise, Kim and colleagues (Kim et al., 2001; 2006) repeatedly found that the understanding scale from the MacCAT predicted clinician judgments of decisional competency for patients with either Alzheimer’s disease or schizophrenia. Notably, across these studies, clinicians did not rely upon responses from the UTD or MacCAT in arriving at their determination of decisional competence, implying that the understanding scales from the UTD and MacCAT are potent predictors of an independent clinical judgment. Indeed, they were employed as the sole criterion to determine whether schizophrenic patients were capable of deciding whether to participate in the multi-center Clinical Antipsychotic Trials of Intervention Effectiveness (Stroup et al., 2003). In accordance with reviews of the literature (e.g., Dunn et al., 2007; Moye et al., 2006), this suggests that the MacArthur instruments are generally accepted by the scientific community as valid measures of medical understanding.

The UTD provides the basis for the largest scoreable domain of decision-making capacity identified by Appelbaum and Grisso (understanding relevant information, including risks/benefits and alternatives), while allowing the part-by-part disclosures favored by the MacArthur studies and other investigations. Based on research involving other patient populations (e.g., Appelbaum & Grisso, 1995; Combs et al., 2005; Howe et al., 2005; Kim et al., 2001; Dymek et al., 2001), we hypothesized that neuropsychologically-compromised patients with MS would display poorer understanding of treatment options than either an unimpaired group of MS patients or a control group.

A second objective of the current study was to determine whether understanding of treatments may be enhanced. Among several patient populations, informed consent procedures have been modified to facilitate understanding of treatment issues (Dunn, 2006). For example, simplified explanations, repetition, and recognition cueing have increased patient understanding of treatment regimens in patients with schizophrenia (Appelbaum & Grisso, 1995; Carpenter et al., 2000; Combs et al., 2005; Dunn & Jeste, 2001; Grisso & Appelbaum, 1995; Grisso et al., 1995; Jensen, Madsen, Andersen, & Rose, 1993; Wirshing, Wirshing, Marder, Liberman, & Mintz, 1998). A number of investigations indicate that recognition cueing enhances ability to remember in people with MS (e.g., Gaudino, Chiaravalloti, DeLuca, & Diamond, 2001; Grisso & Appelbaum, 1995). By providing recognition cueing, people with MS – including those with significant neuropsychological impairment – may likewise realize an enhanced understanding of potential medical treatments.

A third objective of the current study was to evaluate what aspects of neuropsychological function contribute to patient understanding of treatment disclosures. Research involving patients with dementia or schizophrenia indicates that ability to understand treatment information corresponds with executive function, attention, and new-learning. In the present investigation, we sought to determine whether these aspects of neurocognition correspond with understanding of treatment disclosures (e.g., Gurrera et al., 2006; Palmer & Jeste, 2006). By identifying what neuropsychological domains correlate with poor understanding may inform and refine efforts to remediate decisional incapacity in people with MS.

Method

Participants

To recruit participants, notices were published in the newsletter of the local National Multiple Sclerosis Society chapter and in newspapers. The principal investigator also met with MS support groups. Ultimately, data were collected from 36 individuals with MS. A diagnosis of MS was confirmed by a board certified neurologist through chart review (including MRI and other laboratory studies) and physical examination, and these diagnoses were according to the Poser et al. (1983) criteria. The control group included 16 adult community participants without MS. These individuals were friends or spouses of the patients with MS. Patients were excluded if they had a psychiatric disorder which preceded onset of MS, current or past substance abuse or dependence, history of learning or developmental disorders, or any neurological disease or injury besides MS. Current psychiatric illness was not a criterion for exclusion. None of the patients was experiencing an acute exacerbation of MS symptoms at the time of study participation. The control group was screened for each of these characteristics. Participants were volunteers, and received no compensation for their participation.

Materials

All were administered a battery of neuropsychological tests which addressed three primary areas presumed necessary in providing informed consent (e.g., Grisso & Appelbaum, 1998; Marson, 2001; Marson et al., 1996), namely new-learning, executive function, and attention. Indeed, each of the measures (or highly similar variants) employed in this study have been utilized in prior investigations of informed consent capacity (Appelbaum & Grisso, 1997; Dunn et al., 2007; Palmer et al., 2007), thereby increasing the consistency of the current data with the existing literature. These areas of function have been shown to contribute to poor decisional capacity in prior studies. Additionally, these aspects of neurocognition are prone to being compromised in people with MS (Bobholz & Rao, 2003; Martin et al., 1996). Owing to time constraints, we opted to utilize relatively brief measures of these areas of function.

California Verbal Learning Test-II (CVLT-II)

All participants were administered the CVLT-II (Delis et al., 2000), which is a standardized clinical measure of new-learning. This was administered to obtain an objective benchmark of ability to learn new information for each participant.

Wisconsin Card Sorting Test-64 (WCST: Kongs, Thompson, Iverson, & Heaton, 2000)

The WCST is a measure of executive function which involves abstract reasoning and concept formation. It is especially sensitive, albeit not specific, to frontal lobe dysfunction.

Digit Span

The Digit Span subtest from the Wechsler Adult Intelligence Scale-III (Wechsler, 1997) was used to measure attention span. This measure is often used to assess auditory attention and concentration.

Neuropsychological Dysfunction

The sum of impaired scores was used to classify patients as demonstrating at least mild neurobehavioral compromise. Each neuropsychological measure contained multiple indices. To reduce redundancy in our analyses, we focused on a single index from each measure including the Total Trial 1–5 Recall T-score on the CVLT-II, perseverative errors from the WCST, and Backward Span from the Digit Span Subtest as this subtest is a more appropriate measure of attention. These indices are typically considered among the most sensitive indicators of cerebral dysfunction for each test. Participants with MS were identified as having compromised cognitive function if scores on any one of these three indices fell at the fifth percentile or lower on each test’s respective normative mean (Delis et al., 2000; Kongs et al., 2000; Wechsler, 1997). This value was chosen because it is a common benchmark of impaired performance in clinical studies of neuropsychological function (cf., Benton et al., 1994). Impairment on any one of these tests would comprise impairment on one third of the considered indices, and this also is a common benchmark used in classifying patients as having diminished function in clinical studies (e.g., Reitan & Wolfson, 1993). Patients who had one or more scores falling in the clinically-impaired range were classified as having at least mildly-compromised neurocognitive function.

Informed Consent Measure

To assess understanding of an informed consent disclosure, participants were administered the Understanding Treatment Disclosures Scale (UTD: Appelbaum & Grisso, 1995). The UTD exclusively assesses understanding of a fictional informed consent disclosure – one of the four capacities of consent delineated by Appelbaum and Grisso’s model (Grisso & Appelbaum, 1998). In this perspective, understanding reflects a person’s ability to comprehend the meaning and intent of information provided during the informed consent process. The UTD is similar to informed consent capacity measures used in previous research (Carpenter et al., 2000; Kim et al., 2001). During administration, participants receive an informed consent vignette describing pharmaceutical treatment of depression. The protocol contains five paragraphs of two-to-five sentences each. Material presented in this vignette includes the five basic elements required of an informed consent protocol (Appelbaum et al., 1987). Specifically, the protocol describes 1) depression and its symptoms, 2) a proposed treatment, 3) symptoms which the treatment is expected to relieve and the likelihood this will occur, 4) potential risks and the likelihood they will occur, and 5) a description of alternative treatments and their potential risks and benefits (Appelbaum & Grisso, 1995). Wording on the UTD is at a 7th grade reading level (Grisso et al., 1995).

Understanding is assessed in three ways on the UTD. During uninterrupted disclosure, an entire informed consent disclosure is read aloud to the participant, and the participant reads along with the examiner. Subsequently, questions are asked of the examinee concerning the disclosure. For instance, to query the participant’s understanding of the disorder, the examiner reads the following question: “I mentioned some unpleasant things, called symptoms, that people with depression experience. In your own words, what did I say are some of those things--what I called “symptoms?” Similar questions are asked concerning the nature and purpose of treatment, potential benefits of treatment, potential risks and discomforts of treatment, and alternative treatments. Criteria are provided to permit the examiner to score the accuracy of participant responses. Responses are scored, and the maximum possible value for uninterrupted disclosure is 10 points.

During element disclosure, the person is again read aloud a description of the treatment, but only in small successive steps. For example, the examinee is read aloud the portion of the informed consent disclosure concerning the nature of depression. The examinee is then asked to tell their understanding of what was presented. If they fail to demonstrate an accurate understanding of the material, the examinee is then asked more specific questions such as, “What are some of the symptoms of depression I just mentioned?” Similar to the uninterrupted disclosure, the maximum possible score is 10 points for the elemental disclosure.

Subsequent to completing each element disclosure, recognition cues are provided. For instance, the person would be asked to indicate whether the following statement was contained in the protocol description: “People who are depressed may enjoy new experiences (FALSE).” The maximum possible score attainable on the recognition items is 10 points. The UTD takes approximately 20 minutes to administer, and demonstrates satisfactory reliability. In addition, intra-class correlations range from .87 to .96 and Kappa coefficients are high (Appelbaum & Grisso, 1995).

Disability Status

To assess severity of disability, the Ambulation Index was used (Hauser et al., 1983). This measure, which is essentially the 25-foot timed walk from the MS Functional Composite (Fischer et al., 2001), has been used to assess physical disability resulting from MS. It is graded according to a seven-point likert scale, with higher scores indicating greater severity of disability (e.g., 0=Asymptomatic to 7=restricted to a wheelchair). Like the MS Functional Composite, it is commonly used to approximate severity of disability associated with MS (Beatty et al., 2003).

Procedure

The protocol was reviewed and approved by the Institutional Review Board at the University of Tulsa. After obtaining informed consent, the CVLT-II was given. During the interval between immediate and delayed recall, the WCST and Digit Span tests were administered. According to the CVLT-II manual, the delay interval between immediate and delayed recall should last no more than 25 minutes. During instances wherein the WCST took approximately 20 minutes to complete, Digit Span was administered after the CVLT-II delayed recall and recognition trials were completed. Afterward, the UTD was completed. Upon completing these tests, the Ambulation Index was administered.

Data Analytic Plan

We hypothesized that neuropsychologically compromised people with MS would have worse understanding of a medical disclosure. To address this hypothesis, we compared UTD scores of a control group to groups of MS patients with and without diminished neuropsychological test scores. Additionally, we anticipated that recognition cueing would improve UTD performance compared to uninterrupted disclosure. To evaluate this hypothesis, UTD performance on the uninterrupted disclosure, elemental disclosure, and recognition indices were compared within subjects. Because poor neuropsychological function may attenuate ability of MS patients to benefit from recognition cueing, the UTD scores of the three participant groups were compared across the three indices using a mixed factor analysis of variance. For the sake of parsimony and to reduce the likelihood of Type I error, these two hypotheses were addressed using a single mixed factor analysis of variance. Three participant groups (control, MS-unimpaired, and MS-cognitively compromised) serve as the between groups factor, and performance across the three UTD indices (uninterrupted disclosure, elemental disclosure, recognition) served as the repeated factor. To further reduce the likelihood of Type I error, Bonferroni group contrasts were used to probe significant main effects.

To determine what aspects of neuropsychological function correspond with ability to understand treatment disclosures, a series of multiple regression analyses were used. Representative scores from the Wisconsin Card Sorting Test, California Verbal Learning Test-2, and Digit Span tests served as independent variables, and scores on the three UTD indices were the dependent variables. Because we are attempting to explain variance on the UTD, independent variables were simultaneously entered. To demonstrate unique variance accounted for by each independent variable, semi-partial correlations are reported (Stevens, 1996).

Results

Demographics

Among the people with MS, 7 obtained impaired scores on the WCST, 1 on the CVLT-II, and 6 on the Digit Span subtest. Of these, 1 was impaired on both the WCST and CVLT-II, and another was impaired on the WCST and Digit Span subtest. Consequently, based on their number of impaired scores, participants were classified as follows: 16 members of the control group (CTRL), 24 unimpaired patients with MS (MS-UN; no cognitive measure below the 5th percentile), 12 cognitively-compromised patients with MS (MS-CC; at least one cognitive measure below the 5th percentile).

To evaluate whether the three participant groups differed in demographic composition, a series of oneway ANOVAs were conducted. These analyses revealed that participant groups did not differ according to education (F(2, 49)=2.04, p=.14, Eta2=.07). However, the groups differed significantly in age (F(2, 49)=4.95, p=.01, Eta2=.17); this difference in age will be addressed as a covariate in the subsequent analyses. Bonferroni contrasts showed that the control group was significantly younger than the unimpaired patient group. Although the contrast between the MS-CC and control groups failed to achieve significance, its effect size (Cohen’s d=−.77) was proximal to the significant contrast between the unimpaired and control group (Cohen’s d=−1.0). There were no differences between the 2 MS groups. Data concerning demographic characteristics and scores on all tests appear in Table 1.

Table 1.

Descriptive Statistics

CTRL MS-UN MS-CC
Age 37.56 (9.99) 47.95 (10.85) 45.08 (9.53)
Education 16.00 (2.45) 14.45 (2.39) 15.17 (2.41)
Impaired Scores 0.00 (0.00) 0.00 (0.00) 1.17 (0.39)
Digit Span Backward Span 5.75 (1.39)
Min=4/Max=8
5.00 (1.25)
Min=4/Max=8
4.42 (1.62)
Min=3/Max=7
WCST Perseverative Errors 6.06 (2.40)
Min=4/Max=11
7.17 (3.47)
Min=4/Max=17
18.83 (12.07)
Min=4/Max=42
CVLT Total Trial 1–5 Recall
T-Score
61.12 (9.76)
Min=44/Max=80
53.75 (8.92)
Min=38/Max=76
49.17 (10.57)
Min=29/Max=68
Sex 10 Female/6 Male 19 Female /5 Male 10 Female/2 Male
Ethnicity 1 AsAm/15 Cauc 24 Cauc 1AfAm/11 Cauc
Disease Course 10 R-R
5 P-P or S-P
9 Uncertain
4 R-R
4 P-P or S-P
4 Uncertain
Receiving Depression
Treatment
0 % 25 % 41 %
Ambulation Index 2.92 (2.32) n=12 3.33 (2.00) n=10

Note: Standard deviations appear in parentheses. CTRL=Control Group. MS-UN=MS Unimpaired. MS-CC=MS Cognitively Compromised. AsAm=Asian American. AfAm=African American. Cauc=Caucasian. R-R: Relapsing remitting. P-P: Primary progressive. S-P: Secondary Progressive.

A non-parametric test was conducted to evaluate whether groups differed according to gender composition, and the results indicated the groups did not differ in this regard (X2(2)=2.00, p=.37). Likewise, the groups were similar in ethnic composition (X2(4)=5.65, p=.23). Participants were asked whether they were diagnosed with depression and receiving psychotherapy or taking anti-depressant medication. Although this may not be an especially sensitive indicator of depressive symptoms, it may serve as a specific indicator of clinical depression. There were no differences in rates of treatment between the two patient groups (X2(1)=0.29, p=.59). To further determine whether depression corresponds with performance, scores on the neuropsychological tests and indices from the UTD were correlated with treatment for depression. In no instance did a correlation approach significance. MS disease course was also evaluated using a non-parametric test, and there were no difference between the two patient groups (X2(2)=1.05, p=.31). Owing to time constraints, the Ambulation Index was administered to 22 of the 36 patients with MS. A non-parametric test was computed to determine whether number of people who completed the Ambulation Index differed between patient groups, and there was no significant difference (X2(1)=1.03, p=.31). A non-parametric test was computed to determine whether average Ambulation Index scores differed between groups, and they did not (X2(6)=4.63, p=.59). Table 1 summarizes the descriptive statistics of the participant groups

Understanding Treatment Disclosures

Analyses of Group Performance Across UTD Indices

Data were analyzed to evaluate whether groups differed in their ability to understand the treatment disclosure (i.e., informed consent information). Consequently, scores on the each of the three UTD indices were compared across the three participant groups. As a follow-up analysis, we evaluated whether understanding of the treatment disclosure was enhanced by recognition cueing and the question probes employed during the element disclosure. Thus, scores on the three UTD indices were compared within subjects. Owing to the significant age difference between groups, we controlled for this effect through covariance in the analyses. To address these issues, data were analyzed in a 3 group (CTRL, MS-UN, and MS-CC) X 3 index (uninterrupted disclosure, element disclosure, recognition cueing) mixed factor ANCOVA. Group was the between groups factor, index was repeated within subjects, and age was the covariate.

In no instance did age account for significant variance on the UTD, and effect size estimates for age were small (Eta2 =.06). The effect of group was significant (F(2, 48)=8.02, p=.001, Eta2=.25). In following-up this main effect, scores on the UTD were collapsed across the three indices, and Bonferroni post-hoc contrasts showed that the control group and the unimpaired MS had better understanding than the cognitively-compromised MS group, but the control group and unimpaired MS group performed equivalently across the three indices. No other contrast was significant. The main effect of index was not significant (F(2, 96)=0.40, p=.67, Eta2=.008). The interaction of group and index was significant (F(4, 96)=7.91, p<001, Eta2=.25). Consequently, the simple effects of index for each group were analyzed.

The simple main effect of index was significant for the control group (F(2, 30)=25.16, p<.001, Eta2=.63), the unimpaired MS group (F(2, 46)=23.48, p<.001, Eta2=.51), and the cognitively-compromised MS group (F(2, 22)=26.86, p<.001, Eta2=.71). For the control and unimpaired MS groups, Bonferroni contrasts revealed that understanding scores during uninterrupted disclosure were significantly lower than element disclosure or recognition cueing. Their scores on the element disclosure and recognition cueing portion of the UTD were equivalent. For the cognitively-compromised MS group, Bonferroni contrasts showed that element disclosure and recognition cueing resulted in higher understanding scores than with uninterrupted disclosure. Additionally, recognition cueing led to better understanding than element disclosure.

As a further follow-up of the interaction of group and index, the simple main effect of group on each index score was examined. These analyses were done to compare the understanding of the groups on each index. The groups had significantly different scores on the uninterrupted disclosure (F(2, 49)=12.07, p<.001, Eta2=.30) and element disclosure scales (F(2, 49)=6.92, p=.002, Eta2=.22). For uninterrupted disclosure, post-hoc Bonferroni contrasts between groups showed that the control group and the unimpaired MS group had better understanding than the cognitively-compromised MS group, and these two groups performed equivalently to one another. For element disclosure, the control group had better understanding than the cognitively-compromised MS group. The unimpaired MS group was indiscriminate from the control group and the cognitively-compromised MS group during element disclosure. In contrast to the uninterrupted disclosure and element disclosure indices, no significant differences emerged on the recognition cueing index (F(2, 49)=2.40, p=.10, Eta2=.09). Mean scores of the three groups on the UTD indices appear in Table 2.

Table 2.

Mean UTD Scores by Group

CTRLA MS-UNB MS-CCC Bonferroni Contrasts
Between Groups
n = 16 n = 24 n = 12
UTD Indices Mean (SD) Mean (SD) Mean (SD)
     Uninterrupted disclosure1 8.63 (.89)
Min=7
Max=10
7.79 (1.50)
Min=4
Max=10
5.58 (2.53)
Min=1
Max=8
A & B > C
     Element disclosure2 9.94 (.25)
Min=9
Max=10
8.96 (1.12)
Min=5
Max=10
8.25 (1.95)
Min=3
Max=10
A > C
     Recognition cueing3 9.88 (.34)
Min=9
Max=10
9.38 (.97)
Min=7
Max=10
9.33 (.78)
Min=8
Max=10
NS
Bonferroni Contrasts Across
Scales for Each Group
1 < 2 & 3 1 < 2 & 3 1 < 2 < 3

Note: CTRL=Control Group. MS-UN=MS Unimpaired. MS-CC=MS Cognitively Compromised. The significance level was p<.05 for all Bonferroni contrasts. For contrasts:

A

=Control Group;

B

=Unimpaired MS Group;

C

=Impaired MS Group;

1

=Uninterrupted Disclosure;

2

=Element Disclosure;

3

Recognition Cueing.

Factors Predicting UTD Scores

To determine whether neuropsychological factors account for understanding of treatment disclosures, UTD scores were regressed upon the three neuropsychological indices. Data from all participants in the three groups were included. Tolerances of the CVLT-II Total Trial 1–5 Recall T-score, WCST Perseverative Errors, and Digit Span scaled score ranged from .73 to .95, implying that little multicollinearity existed.

The regression analyses are summarized in Table 3. The results reveal that CVLT-II Total Trial 1–5 Recall T-score (t(48)=2.05, p<.05) and WCST Perseverative Errors (t(48)=−1.95, p=.05) emerged as significant unique predictors of uninterrupted disclosure. Semi-partial correlations with uninterrupted disclosure were moderate. As recall increased, scores on the uninterrupted disclosure index improved, and as perseverative errors increased uninterrupted disclosure decreased. For element disclosure and recognition cueing, no neuropsychological test emerged as a significant predictor. Nonetheless, CVLT-II Total Trial 1–5 Recall was a marginally significant predictor of element disclosure (p=.08), and the semi-partial correlation coefficient was .22, implying that better recall corresponded with better understanding.

Table 3.

Summary of Regression Analyses

UTD Indices CVLT-II Total Trial 1–5
Recall T-Score
Digit Span Backward
Span
WCST Perseverative
Errors
Uninterrupted
Disclosure
.24* .22 −.23*
Element
Disclosure
.22 .21 −.20
Recognition
Cueing
.14 .14 −.09

Note. Values reported are semi-partial correlations.

*

p ≤ .05.

Discussion

These findings reveal that unimpaired patients with MS understand treatment disclosures as well as people without MS. In no instance did the unimpaired-MS patients perform more poorly than the control group on the UTD. Consequently, such individuals seem as capable as non-patients to make competent decisions regarding treatment or medical research.

In contrast, the cognitively-compromised MS group understood less information than the control group during uninterrupted disclosure, and effect size estimates for this contrast were considerable. Notably, understanding of the cognitively-compromised MS group was only 6.0 out of a possible total of 10 points during uninterrupted disclosure on the UTD. This score was nearly 3.0 standard deviations below the control group mean. Thus, they accurately understood only 60% of the treatment disclosure, suggesting that cognitively-compromised MS patients may have difficulty understanding as much as 40% of the information from an informed consent protocol. This hardly seems sufficient for patients to make an informed decision to consent to treatment or research and reflects the clinical importance of cognitive impairment in the understanding process. Nonetheless, it seems likely that most patients will be afforded the same kind of opportunities as those provided in this initial study – regardless of their capacity. Namely, patients and research participants will be provided with a written consent form that will be verbally explained. Unfortunately, the current findings imply that explaining treatment options in the usual fashion to patients with diminished neuropsychological function is insufficient. Indeed, cognitively-compromised MS patients may be incapable of understanding important elements of disclosure concerning treatment or research, thereby influencing their capacity to provide consent.

Nonetheless, because of probing during the element disclosure, the cognitively-compromised MS group was able to understand 80% of the information contained in the fictional informed consent protocol. This reflected significantly improved understanding from uninterrupted disclosure. Yet, their performance remained significantly lower than the control group. However, with recognition cueing, the cognitively-compromised MS group understood 93% of information provided during the fictional treatment disclosure. This also reflected a significant increase from their score obtained during the uninterrupted disclosure. Moreover, with cueing the cognitively-compromised MS group displayed a level of understanding that was equivalent to the control group, and effect size estimates for this contrast were very small. As such, MS patients with diminished neuropsychological function benefited significantly from repetition and cueing, and their ability to provide consent was enhanced to “normal” levels. Thus, recognition cueing may permit clinicians and clinical investigators to obtain a robust informed consent from patients with MS.

Although the group differences reveal that diminished neuropsychological function places MS patients at risk of poor medical decision-making, these differences fail to indicate which domains of cognitive function are specific risks. Towards this end, the regression analyses revealed that new-learning and executive function predicted understanding of the fictional treatment vignette, and these variables accounted for as much as 28% of the unique variance in performance on the uninterrupted disclosure index from the UTD. Thus, individuals who perform poorly on the California Verbal Learning Test-II and the Wisconsin Card Sorting Test-64 will be least likely to understand details of an informed consent procedure. These data are consistent with prior studies of other clinical populations which revealed similar relationships (cf. Dunn, 2006). Nonetheless, it should be acknowledged that since only 28% of the variance was accounted for by these two measures, other aspects of cognitive function also probably contribute to understanding of treatment disclosures. Indeed, similar to Marson and Harrell (1999), it seems likely that ability to form abstract concepts, understand text and speech, sustain attention, and remember details of informed consent disclosures are necessary to understand medical information. Future research might endeavor to identify whether these, or other, domains are potent predictors of poor understanding.

These data parallel those obtained from patients with schizophrenia, major depressive disorder, mania, Alzheimer’s disease, Parkinson’s disease, and HIV (Appelbaum & Grisso, 1988; Appelbaum & Grisso, 1995; Appelbaum et al., 1999; Appelbaum et al., 1987; Appelbaum & Roth, 1982; Carpenter et al., 2000; Dymek et al., 2001; Griffith et al., 2005; Grisso, 1986; Grisso & Appelbaum, 1998; Grisso et al., 1995; Guerra et al., 2006; Howe et al., 2005; Kim et al., 2001; Marson, 2001; Marson et al., 1996; Marson & Harrell, 1999; Marson et al., 1994; Moser et al., 2006; Moser et al., 2002; Roth et al., 1977). Specifically, each of the aforementioned studies compared patients with disease-related neuropsychological impairment to a normal control group. Across each of these disorders, the patients tended to display poor understanding of medical treatment or medical research disclosures. In the current study, the patients with MS who displayed compromised neuropsychological performance manifested poor understanding of a medical treatment disclosure.

Additionally, similar to previous research (Dunn et al., 2002; Dymek et al., 2001; Gurrera et al., 2006; Kovnick et al., 2003; Moser et al., 2002; Moye et al., 2006; Okonkwo et al., 2008; Palmer et al., 2004; Palmer & Jeste, 2006), specific neuropsychological components had salient relationships with understanding. For instance, among patients with schizophrenia, Palmer et al. (2004) found that executive function, new-learning, and working memory predicted capacity to understand information pertaining to medical decision-making. In the current study, executive function and new-learning corresponded with ability to understand medical treatment choices, and working-memory nearly achieved significance. Although not significant, Digit Span nearly achieved a significant relationship with UTD scores, and its semi-partial correlation was similar to that of the WCST and CVLT. Although these neuropsychological domains are unlikely exclusive predictors of decisional capacity, this pattern of findings implies that they are important for accurate understanding of medical disclosures.

Furthermore, as with earlier studies involving patients with schizophrenia (Appelbaum & Grisso, 1995; Carpenter et al., 2000; Dunn et al., 2006; Grisso et al., 1995; Grisso & Appelbaum, 1995; Jensen et al., 1993; Wirshing et al., 1998), understanding of informed consent disclosure was capable of enhancement. Thus, these data accord well with a growing body of literature concerning enhanced consent procedures. Although they imply that some patients with central nervous system disease are at risk of poor decision-making regarding treatment or research, their incapacity may be remediated.

Yet, these data are incomplete. Specifically, uncertainties regarding the generalizability of these data must be acknowledged. In particular, average scores on the neuropsychological tests were not severely deficient in the impaired MS group. For example, the cognitively-compromised MS group achieved a mean T-score of 49 on the California Verbal Learning Test-II Total Trial 1–5 Recall index. Although, as revealed in Table 1, some scores were severely impaired, mean performance for this group is essentially normal. Thus, our cognitively-compromised group included only a few participants with impaired memory, whereas most had essentially normal recall. As a result, these data may not generalize to people with MS who have severe neurobehavioral deficits. It seems likely that patients with more severe cognitive deficits will demonstrate more severe difficulties understanding treatment disclosures. It is also uncertain whether they will manifest improved understanding of treatment disclosures with recognition cueing, as did the mildly compromised MS patients in the current study.

Related to this issue, the neuropsychological battery administered in the current study may be somewhat insensitive to neuropsychological impairment in people with MS. For instance, backward span of the Digit Span subtest is of uncertain sensitivity in people with MS. Additionally, our battery addressed only some aspects of executive function, working memory, and new-learning. Other domains of function may also predict decisional-capacity. Perhaps with a more extensive battery including more sensitive measures, an increasingly precise understanding of which cognitive domains predict decisional incapacity may be obtained. We are currently addressing this issue in our laboratory.

It should also be acknowledged that our assessment of depression was less than optimal in this study. Specifically, we identified people as depressed if they had been diagnosed by their physician or were receiving treatment for major depression at the time of study participation. Thus, our assessment of depression was largely qualitative, and could have been strengthened by using a quantitative self-report measure of depressive symptoms. With such an instrument, varying degrees of distress may have been captured, thereby permitting us to assess whether subtle depressive features contribute to decisional incapacity. A number of studies have demonstrated that depression, as indexed by quantitative measures of distress, corresponds with poor performance on measures of executive function in people with MS (Arnett et al., 2001). Inasmuch as depression corresponds with poor reasoning, it may likewise correlate with worsening decisional incapacity. This should be examined in future research, especially because depressive distress is so common in people with MS (Voss et al., 2002). These considerations notwithstanding, they should be tempered by the findings of Appelbaum et al. (1999). In a sample of moderately depressed patients, none displayed impaired understanding of an informed consent vignette. Among severely depressed subjects as well, Cohen et al. (2004) found relatively high levels of research decision-making capacity. This implies that depression may not correspond with poor understanding of medical treatment choices. Furthermore, presence of diagnosed depression in the current study failed to correlate with performance on the UTD or the neuropsychological battery. Nonetheless, it may be worthwhile to evaluate whether quantitative measures of depression correspond with decisional incapacity to clarify this situation.

Related to limited generalizability, the ambulation index was not administered to all patients with MS. Approximately half of the unimpaired MS group was administered the index because of time constraints. Consequently, a thorough depiction of mobility status for the unimpaired group is unavailable. In contrast all but two of the cognitively compromised MS patients were administered the ambulation index. Among these participants, modest disability was present on average. Additionally, patients were diagnosed according to the Poser et al. (1983) criteria rather than the revised McDonald criteria (Polman, Reingold, Edan, et al., 2005). This may further limit generalizability of the findings.

These data address understanding, which is but one of four domains of informed consent. These data reveal that the UTD is sensitive to detecting poor understanding of medical treatment disclosures in people with MS, and these data recommend its use in evaluating decisional capacity in that population. Nonetheless, as delineated by Grisso & Appelbaum (1998), capacity to express a treatment choice, and ability to appreciate, understand, and reason through treatment information are also required. Because the four requirements seem to be unique and have small intercorrelations (Appelbaum & Grisso, 1995), all four areas of decisional capacity must be examined in future research. Consequently, our data do not permit us to make general statements regarding decisional competence of people with MS. Furthermore, our method of measuring understanding may be non-specific. In particular, although it appears to measure understanding and comprehension of medical treatment, the UTD may also reflect memory performance. For example, it includes a recognition cueing component, and CVLT-2 Total Trial 1–5 Recall emerged as a salient predictor of UTD performance. It may be that the cognitively-compromised MS patients were displaying diminished memory for a medical disclosure rather than poor understanding on the UTD. Collectively, these limitations should temper any rash conclusions that MS patients with subtle neuropsychological deficits are unable to make independent and autonomous decisions regarding medical treatment or research participation. These considerations notwithstanding, this is the first study to our knowledge that examines medical decision-making in persons with MS and simultaneously offers strategies to enhance consent procedures. To protect the rights and well-being of MS patients, these findings provide a compelling impetus to address the issue with greater energy and attention.

Acknowledgments

This research was funded by grants to the first author from the National Multiple Sclerosis Society, Oklahoma Center for the Advancement of Science and Technology, and the National Institute of Neurological Diseases and Stroke (R01 NS043362-01A2). The first author expresses gratitude to helpful support from the Oklahoma Chapter of the National Multiple Sclerosis Society and to J. Carpenter.

Contributor Information

Michael R. Basso, University of Tulsa

Philip J. Candilis, University of Massachusetts Medical School

Jay Johnson, Tulsa Neurology Clinic.

Courtney Ghormley, Arkansas Neuropsychology.

Dennis R. Combs, University of Texas-Tyler

Taeh Ward, University of Tulsa.

References

  1. Appelbaum PS, Grisso T. Assessing patients’ capacities to consent to treatment. New England Journal of Medicine. 1988;319:1635–1638. doi: 10.1056/NEJM198812223192504. [DOI] [PubMed] [Google Scholar]
  2. Appelbaum PS, Grisso T. The MacArthur treatment competence study I: Mental illness and competence to consent to treatment. Law and Human Behavior. 1995;19:105–126. doi: 10.1007/BF01499321. [DOI] [PubMed] [Google Scholar]
  3. Appelbaum PS, Grisso T. Capacities of hospitalized, medically ill patients to consent to treatment. Psychosomatics. 1997;38:119–125. doi: 10.1016/S0033-3182(97)71480-4. [DOI] [PubMed] [Google Scholar]
  4. Appelbaum PA, Grisso T. MacArthur competence assessment tool for clinical research (MacCAT-CR) Sarasota, FL: Professional Resource Press/Professional Resource Exchange; 2001. [Google Scholar]
  5. Appelbaum PS, Grisso T, Frank E, O’Donnell S, Kupfer DJ. Competence of depressed patients for consent to research. American Journal of Psychiatry. 1999;156:1380–1384. doi: 10.1176/ajp.156.9.1380. [DOI] [PubMed] [Google Scholar]
  6. Appelbaum PS, Lidz CW, Meisel A. Informed consent: Legal theory and clinical practice. New York: Oxford; 1987. [Google Scholar]
  7. Appelbaum P, Roth L. Competency to consent to research: A psychiatric overview. Archives of General Psychiatry. 1982;39:951–958. doi: 10.1001/archpsyc.1982.04290080061009. [DOI] [PubMed] [Google Scholar]
  8. Arnett PA, Higginson CI, Randolph JJ. Depression in multiple sclerosis: Relationship to planning ability. Journal of the International Neuropsychological Society. 2001;7:665–674. doi: 10.1017/s1355617701766027. [DOI] [PubMed] [Google Scholar]
  9. Bambara JK, Griffith HR, Martic RC, Faught E, Wadley VG, Marson DC. Medical decision-making abilities in older adults with chronic partial epilepsy. Epilepsy & Behavior. 2007;10:63–68. doi: 10.1016/j.yebeh.2006.10.003. [DOI] [PubMed] [Google Scholar]
  10. Beatty WW, Goretti B, Siracusa G, Zipoli V, Portaccio E, Amato MP. Changes in neuropsychological test performance over the workday in multiple sclerosis. The Clinical Neuropsychologist. 2003;17:551–560. doi: 10.1076/clin.17.4.551.27942. [DOI] [PubMed] [Google Scholar]
  11. Beatty WW, Wilbanks SL, Blanco CR, Hames KA, Tivis R, Paul RH. Memory disturbance in multiple sclerosis: Reconsideration of patterns of performance on the selective reminding test. Journal of Clinical and Experimental Neuropsychology. 1996;18:56–62. doi: 10.1080/01688639608408262. [DOI] [PubMed] [Google Scholar]
  12. Benedict RH, Wahlig E, Bakshi R, Fishman I, Munschauer F, Zivadinov R, Weinstock-Guttman B. Predicting quality of life in multiple sclerosis: Accounting for physical disability, fatigue, cognition, mood disorder, personality, and behavior change. Journal of Neurological Sciences. 2005;231:29–34. doi: 10.1016/j.jns.2004.12.009. [DOI] [PubMed] [Google Scholar]
  13. Benton AL, Sivan AB, Hamsher K deS, Varney NR, Spreen O. Contributions to neuropsychological assessment: A clinical manual. 2nd ed. New York: Oxford University Press; 1994. [Google Scholar]
  14. Bobholz JA, Rao SM. Cognitive dysfunction in multiple sclerosis: A review of recent developments. Current Opinion in Neurology. 2003;16:283–288. doi: 10.1097/01.wco.0000073928.19076.84. [DOI] [PubMed] [Google Scholar]
  15. Candilis PJ, Geppert CM, Fletcher KE, Lidz CW, Appelbaum PS. Willingness of subjects with thought disorder to participate in research. Schizophrenia Bulletin. 2006;32:159–165. doi: 10.1093/schbul/sbj016. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Candilis PJ, Fletcher K, Geppert C, Lidz CW, Appelbaum PS. A direct comparison of research decision-making capacity: Schizophrenia/schizoaffective, medically ill, and non-ill subjects. Schizophrenia Research. 2008;99:350–358. doi: 10.1016/j.schres.2007.11.022. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Carpenter WT, Gold JM, Lahti AC, Queern CA, Conley RR, Bartko JJ, Kovnick J, Appelbaum PS. Decisional capacity for informed consent in schizophrenia research. Archives of General Psychiatry. 2000;57:533–538. doi: 10.1001/archpsyc.57.6.533. [DOI] [PubMed] [Google Scholar]
  18. Cohen BJ, McGarvey EL, Pinkerton RC, Kryzhanivska L. Willingness and competence of depressed and schizophrenic inpatients to consent to research. Journal of the American Academy of Psychiatry and the Law. 2004;32:134–143. [PubMed] [Google Scholar]
  19. Combs DR, Adams SD, Wood TD, Basso MR, Gouvier WD. Informed consent in schizophrenia: The use of cues in the assessment of understanding. Schizophrenia Research. 2005;77:59–63. doi: 10.1016/j.schres.2004.08.002. [DOI] [PubMed] [Google Scholar]
  20. Delis DC, Kramer JH, Kaplan E, Ober BA. California Verbal Learning Test-II. San Antonio, TX: The Psychological Corporation; 2000. [Google Scholar]
  21. DeLuca J, Barbieri-Berger S, Johnson SK. The nature of memory impairments in multiple sclerosis: acquisition versus retrieval. Journal of Clinical and Experimental Neuropsychology. 1994;16:183–189. doi: 10.1080/01688639408402629. [DOI] [PubMed] [Google Scholar]
  22. Dunn LB, Candilis PJ, Roberts LW. Emerging empirical evidence on the ethics of schizophrenia research. Schizophrenia Bulletin. 2006;32:47–68. doi: 10.1093/schbul/sbj012. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Dunn LB, Jeste DV. Enhancing informed consent for research and treatment. Neuropsychopharmacology. 2001;24:595–607. doi: 10.1016/S0893-133X(00)00218-9. [DOI] [PubMed] [Google Scholar]
  24. Dunn LB, Lindamer LA, Palmer BW, Golshan S, Schneiderman LJ, Jeste PV. Improving understanding of research consent in middle-aged and elderly patients with psychotic disorders. American Journal of Geriatric Psychiatry. 2002;10:142–150. [PubMed] [Google Scholar]
  25. Dunn LB, Nowrangi MA, Palmer BW, Jeste DV, Saks ER. Assessing decisional capacity for clinical research or treatment: A review of instruments. American Journal of Psychiatry. 2006;163:1323–1334. doi: 10.1176/ajp.2006.163.8.1323. [DOI] [PubMed] [Google Scholar]
  26. Dunn LB, Palmer BW, Appelbaum PS, Sakes ER, Aarons GA, Jeste DV. Prevalence and correlates of adequate performance on a measure of abilities related to decisional capacity: Differences among three standards for the MacCAT-CR in patients with schizophrenia. Schizophrenia Research. 2007;89:110–118. doi: 10.1016/j.schres.2006.08.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Dymek MP, Atchison P, Harrell L, Marson DC. Competency to consent to medical treatment in cognitively impaired patients with Parkinson’s disease. Neurology. 2001;56:17–24. doi: 10.1212/wnl.56.1.17. [DOI] [PubMed] [Google Scholar]
  28. Fischer JS, Jak AJ, Kniker JE, Rudick RA. Multiple sclerosis functional composite: Administration and scoring manual. New York: National Multiple Sclerosis Society; 2001. [Google Scholar]
  29. Gaudino EA, Chiaravalloti ND, DeLuca J, Diamond BJ. A comparison of memory performance in relapsing-remitting, primary progressive and secondary progressive, multiple sclerosis. Neuropsychiatry, Neuropsychology, & Behavioral Neurology. 2001;14:32–44. [PubMed] [Google Scholar]
  30. Geisler MW, Sliwinski M, Coyle PK, Masur DM, Doscher C, Krupp LB. The effects of amantadine and pemoline on cognitive functioning in multiple sclerosis. Archives of Neurology. 1996;53:185–188. doi: 10.1001/archneur.1996.00550020101021. [DOI] [PubMed] [Google Scholar]
  31. Grafman J, Rao S, Bernardin L, Leo GJ. Automatic memory processes in patients with multiple sclerosis. Archives of Neurology. 1991;48:1072–1075. doi: 10.1001/archneur.1991.00530220094025. [DOI] [PubMed] [Google Scholar]
  32. Griffith HR, Dymek MP, Atchison P, Harrell L, Marson DC. Medical decision-making in neurodegenerative disease: Mild AD and PD with cognitive impairment. Neurology. 2005;65:483–485. doi: 10.1212/01.wnl.0000171346.02965.80. [DOI] [PubMed] [Google Scholar]
  33. Grisso T. Evaluating competencies: Forensic assessments and instruments. New York: Plenum Press; 1986. [Google Scholar]
  34. Grisso T, Appelbaum PS. The MacArthur Treatment Competence Study. III: Abilities of patients to consent to psychiatric and medical treatments. Law and Human Behavior. 1995;19:149–174. doi: 10.1007/BF01499323. [DOI] [PubMed] [Google Scholar]
  35. Grisso T, Appelbaum PS. Assessing competence to consent to treatment: A guide for physicians and other health professionals. New York: Oxford University Press; 1998. [Google Scholar]
  36. Grisso T, Appelbaum PS, Mulvey EP, Fletcher K. The MacArthur Treatment Competence Study. II. Law and Human Behavior. 1995;19:127–149. doi: 10.1007/BF01499322. [DOI] [PubMed] [Google Scholar]
  37. Gurrera RJ, Moye J, Karel MJ, Azar AR, Armesto JC. Cognitive performance predicts treatment decisional abilities in mild to moderate dementia. Neurology. 2006;66:1367–1372. doi: 10.1212/01.wnl.0000210527.13661.d1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Hauser SL, Dawson DM, Lehrich JR, Beal MF, Kevy SV, Propper RD, Mills JA, Weiner HL. Intensive immunosuppression in progressive multiple sclerosis: A randomized, three-arm study of high-dose intravenous cyclophosphamide, plasma exchange, and ACTH. New England Journal of Medicine. 1983;308:173–180. doi: 10.1056/NEJM198301273080401. [DOI] [PubMed] [Google Scholar]
  39. Howe V, Foister K, Jenkins K, Skene L, Copolov D, Keks N. Competence to give informed consent in acute psychosis is associated with symptoms rather than diagnosis. Schizophrenia Research. 2005;77:211–214. doi: 10.1016/j.schres.2005.03.005. [DOI] [PubMed] [Google Scholar]
  40. Jensen AB, Madsen B, Andersen P, Rose C. Information for cancer patients entering a clinical trial--An evaluation of an information strategy. European Journal of Cancer. 1993;29:2235–2238. doi: 10.1016/0959-8049(93)90213-y. [DOI] [PubMed] [Google Scholar]
  41. Kessler HR, Cohen RA, Lauer K, Kausch DF. The relationship between disability and memory dysfunction in multiple sclerosis. International Journal of Neuroscience. 1992;62:17–34. doi: 10.3109/00207459108999754. [DOI] [PubMed] [Google Scholar]
  42. Kim SYH, Caine ED, Currier GW, Leibovici A, Ryan JM. Assessing the competence of persons with Alzheimer’s disease in providing informed consent for participation in research. American Journal of Psychiatry. 2001;158:712–717. doi: 10.1176/appi.ajp.158.5.712. [DOI] [PubMed] [Google Scholar]
  43. Kim SY, Cox C, Caine ED. Impaired decision-making ability in subjects with Alzheimer’s disease and willingness to participate in research. American Journal of Psychiatry. 2002;159:797–802. doi: 10.1176/appi.ajp.159.5.797. [DOI] [PubMed] [Google Scholar]
  44. Kim SY. When does decisional impairment become decisional incompetence? Ethcial and methodological issues in capacity research in schizophrenia. Schizophrenia Bulletin. 2006;32:92–97. doi: 10.1093/schbul/sbi062. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Kongs SK, Thompson LL, Iverson GL, Heaton RK. Wisconsin Card Sorting Test-64 Card Version. Lutz, FL: Psychological Assessment Resources; 2000. [Google Scholar]
  46. Kovnick JA, Appelbaum PS, Hoge SK, Leadbetter RA. Competence to consent to research among long-stay inpatients with chronic schizophrenia. Psychiatric Services. 2003;54:1247–1252. doi: 10.1176/appi.ps.54.9.1247. [DOI] [PubMed] [Google Scholar]
  47. Kujala P, Portin R, Ruutiainen J. Memory deficits and early cognitive deterioration in MS. Acta Neurologica Scandanavica. 1996;93:329–335. doi: 10.1111/j.1600-0404.1996.tb00005.x. [DOI] [PubMed] [Google Scholar]
  48. Marson DC. Loss of competency in Alzheimer’s disease: Conceptual and psychometric approaches. International Journal of Law and Psychiatry. 2001;24(2–3):267–283. doi: 10.1016/s0160-2527(01)00064-4. [Special issue] [DOI] [PubMed] [Google Scholar]
  49. Marson DC, Chatterjee A, Ingram KK, Harrell LE. Toward a neurologic model of competency: Cognitive predictors of capacity to consent in Alzheimer’s disease using three different legal standards. Neurology. 1996;46:666–672. doi: 10.1212/wnl.46.3.666. [DOI] [PubMed] [Google Scholar]
  50. Marson D, Harrell L. Executive dysfunction and loss of capacity to consent to medical treatment in patients with Alzheimer’s disease. Seminars in Clinical Neuropsychiatry. 1999;4:41–49. doi: 10.1053/SCNP00400041. [DOI] [PubMed] [Google Scholar]
  51. Marson DC, Ingram KK, Cody HA, Harrell LE. Assessing the competency of patients with Alzheimer’s disease under different legal standards: A prototype instrument. Archives of Neurology. 1995;52:949–954. doi: 10.1001/archneur.1995.00540340029010. [DOI] [PubMed] [Google Scholar]
  52. Marson DC, Schmitt FA, Ingram KK, Harrell LE. Determining the competency of Alzheimer patients to consent to treatment and research. Alzheimer Disease and Associated Disorders. 1994;8 Suppl. 4:5–18. [PubMed] [Google Scholar]
  53. Martin R, Hohlfeld R, McFarland HF. Multiple sclerosis. In: Brandt T, Caplan LR, Dichgans J, Diener HC, Kennard C, editors. Neurological disorders: Course and treatment. New York: Academic Press; 1996. pp. 483–506. [Google Scholar]
  54. Moser DJ, Reese RL, Hey CT, Schultz SK, Arndt S, Beglinger LJ, Duff KM, Andreasen NC. Using a brief intervention to improve decisional capacity in schizophrenia research. Schizophrenia Bulletin. 2006;32:116–120. doi: 10.1093/schbul/sbi066. [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Moser D, Schultz S, Arndt S, Benjamin M, Fleming F, Brems C, Paulsen JS, Appelbaum PS, Andreasen NC. Capacity to provide informed consent for participation in schizophrenia and HIV research. American Journal of Psychiatry. 2002;159:1201–1207. doi: 10.1176/appi.ajp.159.7.1201. [DOI] [PubMed] [Google Scholar]
  56. Moye J, Gurrera RJ, Karel MJ, Edelstein B, O’Connell C. Empirical advances in the assessment of the capacity to consent to medical treatment: Clinical implications and research needs. Clinical Psychology Review. 2006;26:1054–1077. doi: 10.1016/j.cpr.2005.04.013. [DOI] [PubMed] [Google Scholar]
  57. Okonkwo OC, Griffith HR, Belue K, Lanza S, Zamrini EY, Harrell LE, Brockington JC, Clark D, Raman R, Marson DC. Cognitive models of medical decision-making capacity in patients with mild cognitive impairment. Journal of the International Neuropsychological Society. 2008;14:297–308. doi: 10.1017/S1355617708080338. [DOI] [PubMed] [Google Scholar]
  58. Palmer BW, Dunn LB, Appelbaum PS, Jeste DV. Correlates of treatment- related decision-making capacity among middle-aged and older patients with schizophrenia. Archives of General Psychiatry. 2004;61:230–236. doi: 10.1001/archpsyc.61.3.230. [DOI] [PubMed] [Google Scholar]
  59. Palmer BW, Dunn LB, Appelbaum PS, Mudaliar S, Thal L, Henry R, Shahrokh G, Jeste DV. Assessment of capacity to consent to research among older persons with schizophrenia, Alzheimer disease, or diabetes mellitus: Comparison of a 3-item questionnaire with a comprehensive standardized capacity instrument. Archives of General Psychiatry. 2005;62:726–733. doi: 10.1001/archpsyc.62.7.726. [DOI] [PubMed] [Google Scholar]
  60. Palmer BW, Dunn LB, Depp CA, Eyler LT, Jeste DV. Decisional capacity to consent to research among patients with bipolar disorder: Comparison with schizophrenia patients and healthy controls. Journal of Clinical Psychiatry. 2007;68:689–696. doi: 10.4088/jcp.v68n0505. [DOI] [PubMed] [Google Scholar]
  61. Palmer BW, Jeste DV. Relationship of individual cognitive abilities to specific components of decisional capacity among middle-aged and older patients with schizophrenia. Schizophrenia Bulletin. 2006;32:98–106. doi: 10.1093/schbul/sbj002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  62. Palmer BW, Savla GN. The association of specific neuropsychological deficits with capacity to consent to research or treatment. Journal of the International Neuropsychological Society. 2007;13:1047–1059. doi: 10.1017/S1355617707071299. [DOI] [PubMed] [Google Scholar]
  63. Pliskin NH, Hamer DP, Goldstein DS, Towle VL, Reder AT, Noronha A, Arnason BG. Improved delayed visual reproduction test performance in multiple sclerosis patients receiving interferon beta-1b. Neurology. 1996;47:1463–1468. doi: 10.1212/wnl.47.6.1463. [DOI] [PubMed] [Google Scholar]
  64. Polman CH, Reingold SC, Edan G, et al. Diagnostic criteria for multiple sclerosis: 2005 revisions to the “McDonald Criteria.”. Annals of Neurology. 2005;58:840–846. doi: 10.1002/ana.20703. [DOI] [PubMed] [Google Scholar]
  65. Poser CM, Paty DW, Scheinberg L, McDonald WI, Davis FA, Ebers GC, Johnson KP, Sibley WA, Silberberg DH, Tourtellotte WW. New diagnostic criteria for multiple sclerosis: Guidelines for research protocols. Annals of Neurology. 1983;13:227–231. doi: 10.1002/ana.410130302. [DOI] [PubMed] [Google Scholar]
  66. Pruchno RA, Smyer MA, Rose MS, Hartman-Stein PE, Laribee-Henderson DL. Competence of long-term care residents to participate in decisions about their medical care: A brief objective assessment. The Gerontologist. 1995;35:622–629. doi: 10.1093/geront/35.5.622. [DOI] [PubMed] [Google Scholar]
  67. Rao SM, Leo GJ, Bernardin L, Unverzagt F. Cognitive dysfunction in multiple sclerosis: I. Frequency, patterns, and prediction. Neurology. 1991;41:685–691. doi: 10.1212/wnl.41.5.685. [DOI] [PubMed] [Google Scholar]
  68. Rao SM, Leo GJ, Ellington L, Nauertz T, Bernardin L, Unverzagt F. Cognitive dysfunction in multiple sclerosis: II. Impact on employment and social functioning. Neurology. 1991;41:692–696. doi: 10.1212/wnl.41.5.692. [DOI] [PubMed] [Google Scholar]
  69. Reitan RM, Wolfson D. The Halstead-Reitan Neuropsychological Test Battery: Theory and clinical interpretation. Tucson, AZ: Neuropsychology Press; 1993. [Google Scholar]
  70. Roth LH, Meisel A, Lidz CW. Tests of competency to consent to treatment. American Journal of Psychiatry. 1977;134:279–284. doi: 10.1176/ajp.134.3.279. [DOI] [PubMed] [Google Scholar]
  71. Stevens J. Applied multivariate statistics for the social sciences. 3rd ed. Mahwah, NJ: Lawrence Erlbaum Associates, Inc; 1996. [Google Scholar]
  72. Stroup TS, McEvoy JP, Swartz MS, et al. The National Institute of Mental Health Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) project: Schizophrenia trial design and protocol development. Schizophrenia Bulletin. 2003;29:15–31. doi: 10.1093/oxfordjournals.schbul.a006986. [DOI] [PubMed] [Google Scholar]
  73. Tsolaki M, Drevelegas A, Karachristianou S, Kapinas K, Divanoglou D, Routsonis K. Correlation of dementia, neuropsychological and MRI findings in multiple sclerosis. Dementia. 1994;5:48–52. doi: 10.1159/000106694. [DOI] [PubMed] [Google Scholar]
  74. Voss WD, Arnett PA, Higginson CI, Randolph JJ, Campos MD, Dyck DG. Archives of Clinical Neuropsychology. 2002;17:103–115. [PubMed] [Google Scholar]
  75. Wechsler D. Wechsler Adult Intelligence Scale-III. San Antonio, TX: The Psychological Corporation; 1997. [Google Scholar]
  76. Wirshing DA, Wirshing WC, Marder SR, Liberman RP, Mintz J. Informed consent: Assessment of comprehension. American Journal of Psychiatry. 1998;155:1508–1511. doi: 10.1176/ajp.155.11.1508. [DOI] [PubMed] [Google Scholar]

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