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Assessing decision-making capacity at end of life Elissa Kolva, M.A. a, , Barry Rosenfeld, Ph.D. a , Robert Brescia, M.D. b , Christopher Comfort, M.D. b a Fordham University, Bronx, NY 10458, USA b Calvary Hospital, Bronx, NY, 10461, USA abstract article info Article history: Received 14 October 2013 Revised 21 February 2014 Accepted 25 February 2014 Available online xxxx Keywords: Decision-making Capacity End-of-life Cognitive impairment Assessment Objective: Patients with terminal illness often face important medical decisions that may carry ethical and legal implications, yet they may be at increased risk for impaired decisional capacity. This study examined the prevalence of impairment on the four domains of decisional capacity relevant to existing legal standards. Method: Twenty-four adults diagnosed with a terminal illness completed the MacArthur Competence Assessment Tool for Treatment, a semi-structured measure of decision-making capacity and measures of cognitive functioning and psychological distress. Results: Approximately one third of the sample demonstrated serious impairment on at least one domain of decisional capacity. The greatest proportion of impairment was found on subscales that rely heavily on verbal abilities. Decisional capacity was signicantly associated with cognitive functioning and education, but not with symptoms of anxiety or depression. Conclusions: This study is the rst to examine decisional capacity in patients with terminal illness relative to legal standards of competence. Although not universal, decisional impairment was common. Clinicians working with terminally ill patients should frequently assess capacity as these individuals are called on to make important medical decisions. Comprehensive assessment will aid clinicians in their responsibility to balance respect for patient autonomy with their responsibility to protect patients from harm resulting from impaired decisional capacity. © 2014 Elsevier Inc. All rights reserved. Patients with terminal illness are responsible for making impor- tant healthcare decisions. Even after their disease has progressed beyond cure, patients may need to establish advanced directives, decide whether to enter clinical trials or accept palliative care interventions, and decide whether to forego potentially curative treatment and enter hospice care [13]. Some of the decisions faced by terminally ill individuals can be controversial, such as those regarding physician-assisted suicide (where legal), to reject life-sustaining interventions, and to accept interventions that may directly or indirectly hasten death. Further, many medical interventions provid- ed to patients at end of life can be costly and invasive [4,5]. Even very ill patients are expected to actively participate in their own healthcare decision making [6]. However, as their disease progresses, the decision-making capacity for many patients may deteriorate, whether the result of age, hospitalization, treatment side effects or the disease itself [79]. In these situations, an assessment of the patients decision-making capacity is required to determine whether the patient retains the capacity to make competenttreatment decisions. Capacity assessments provide a mechanism for safeguarding patient autonomy and self-determination while protecting them from the harm that might arise from ill-informed decisions [10,11]. Clinicians are largely responsible for determining when patients are incapable of making competent treatment decisions [12]. In decades past, determinations of decision making capacity were based largely on the diagnosis of a mental disorder alone, or on a global assessment of the patients mental status [12]. Many physicians still rely on global assessments of cognitive functioning to assess decision- making capacity [13,14], but the accuracy of these simplistic approaches is questionable. For example, one study found that a frequently used measure of cognitive functioning, the Mini Mental State Examination [15], was a modest predictor of decisional capacity but no cutoff score yielded adequate sensitivity and specicity [16]. Thus, critics have argued that cognitive measures such as the Mini- Mental State Examination (MMSE) are not adequate to evaluate the patients specic capacities to understand, appreciate and reason about information related to a particular treatment [17]. In the last two decades, empirical studies of decisional capacity in patients with advanced illness has led to the development of several instruments intended to measure the key functional abilities that correspond to the different legal standards for decision making competence [12]. Although there is no universal legal standard for competence, researchers have identied four components that are General Hospital Psychiatry xxx (2014) xxxxxx Author note: Many thanks to the following colleagues for their help in collecting data, providing consultation, and managing the study: Leah Newkirk, Jennifer Lord- Bessen and Maryann Santasiero. The authors would also like to thank the study participants, terminally ill men and women who gave of themselves to help us better understand decision-making capacity at end of life. Corresponding author. Department of Psychology, Fordham University, Bronx, NY 10458, USA. Tel.: +1 315 529 4458. E-mail address: [email protected] (E. Kolva). 0163-8343/$ see front matter © 2014 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.genhosppsych.2014.02.013 Contents lists available at ScienceDirect General Hospital Psychiatry journal homepage: http://www.ghpjournal.com Please cite this article as: Kolva E., et al, Assessing decision-making capacity at end of life, Gen Hosp Psychiatry (2014), http://dx.doi.org/ 10.1016/j.genhosppsych.2014.02.013

Assessing decision-making capacity at end of life

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General Hospital Psychiatry xxx (2014) xxx–xxx

Contents lists available at ScienceDirect

General Hospital Psychiatry

j ourna l homepage: http : / /www.ghp journa l .com

Assessing decision-making capacity at end of life☆

Elissa Kolva, M.A. a,⁎, Barry Rosenfeld, Ph.D. a, Robert Brescia, M.D. b, Christopher Comfort, M.D. b

a Fordham University, Bronx, NY 10458, USAb Calvary Hospital, Bronx, NY, 10461, USA

a b s t r a c ta r t i c l e i n f o

☆ Author note: Many thanks to the following colleagudata, providing consultation, and managing the study:Bessen and Maryann Santasiero. The authors wouldparticipants, terminally ill men and women who gave ounderstand decision-making capacity at end of life.⁎ Corresponding author. Department of Psychology, F

10458, USA. Tel.: +1 315 529 4458.E-mail address: [email protected] (E. Kolva).

0163-8343/$ – see front matter © 2014 Elsevier Inc. Alhttp://dx.doi.org/10.1016/j.genhosppsych.2014.02.013

Please cite this article as: Kolva E., et al, A10.1016/j.genhosppsych.2014.02.013

Article history:

Received 14 October 2013Revised 21 February 2014Accepted 25 February 2014Available online xxxx

Keywords:Decision-makingCapacityEnd-of-lifeCognitive impairmentAssessment

Objective: Patients with terminal illness often face important medical decisions that may carry ethical andlegal implications, yet they may be at increased risk for impaired decisional capacity. This study examined theprevalence of impairment on the four domains of decisional capacity relevant to existing legal standards.Method: Twenty-four adults diagnosed with a terminal illness completed the MacArthur CompetenceAssessment Tool for Treatment, a semi-structured measure of decision-making capacity and measures ofcognitive functioning and psychological distress.Results: Approximately one third of the sample demonstrated serious impairment on at least one domain ofdecisional capacity. The greatest proportion of impairment was found on subscales that rely heavily on verbalabilities. Decisional capacity was significantly associated with cognitive functioning and education, but notwith symptoms of anxiety or depression.Conclusions: This study is the first to examine decisional capacity in patients with terminal illness relative to

legal standards of competence. Although not universal, decisional impairment was common. Cliniciansworking with terminally ill patients should frequently assess capacity as these individuals are called on tomake important medical decisions. Comprehensive assessment will aid clinicians in their responsibility tobalance respect for patient autonomy with their responsibility to protect patients from harm resulting fromimpaired decisional capacity.

© 2014 Elsevier Inc. All rights reserved.

Patients with terminal illness are responsible for making impor-tant healthcare decisions. Even after their disease has progressedbeyond cure, patients may need to establish advanced directives,decide whether to enter clinical trials or accept palliative careinterventions, and decide whether to forego potentially curativetreatment and enter hospice care [1–3]. Some of the decisions faced byterminally ill individuals can be controversial, such as those regardingphysician-assisted suicide (where legal), to reject life-sustaininginterventions, and to accept interventions that may directly orindirectly hasten death. Further, many medical interventions provid-ed to patients at end of life can be costly and invasive [4,5]. Even veryill patients are expected to actively participate in their own healthcaredecision making [6]. However, as their disease progresses, thedecision-making capacity for many patients may deteriorate, whetherthe result of age, hospitalization, treatment side effects or the diseaseitself [7–9]. In these situations, an assessment of the patient’sdecision-making capacity is required to determine whether the

es for their help in collectingLeah Newkirk, Jennifer Lord-also like to thank the studyf themselves to help us better

ordham University, Bronx, NY

l rights reserved.

ssessing decision-making cap

patient retains the capacity to make “competent” treatment decisions.Capacity assessments provide a mechanism for safeguarding patientautonomy and self-determination while protecting them from theharm that might arise from ill-informed decisions [10,11].

Clinicians are largely responsible for determining when patientsare incapable of making competent treatment decisions [12]. Indecades past, determinations of decision making capacity were basedlargely on the diagnosis of a mental disorder alone, or on a globalassessment of the patient’s mental status [12]. Many physicians stillrely on global assessments of cognitive functioning to assess decision-making capacity [13,14], but the accuracy of these simplisticapproaches is questionable. For example, one study found that afrequently used measure of cognitive functioning, the Mini MentalState Examination [15], was a modest predictor of decisional capacitybut no cutoff score yielded adequate sensitivity and specificity [16].Thus, critics have argued that cognitive measures such as the Mini-Mental State Examination (MMSE) are not adequate to evaluate thepatient’s specific capacities to understand, appreciate and reasonabout information related to a particular treatment [17].

In the last two decades, empirical studies of decisional capacity inpatients with advanced illness has led to the development of severalinstruments intended to measure the key functional abilities thatcorrespond to the different legal standards for decision makingcompetence [12]. Although there is no universal legal standard forcompetence, researchers have identified four components that are

acity at end of life, Gen Hosp Psychiatry (2014), http://dx.doi.org/

2 E. Kolva et al. / General Hospital Psychiatry xxx (2014) xxx–xxx

central to judicial determinations of competence and provide thebasis for the model of consent capacity: ability to express a choice(Choice), ability to understand and recall disclosed information(Understanding), ability to appreciate the significance of the decision(Appreciate), and ability to rationally manipulate information into adecision that is consistent with one’s values and preferences(Reasoning) [18,19]. The instruments designed to assess these legalstandards provide greater standardization than assessments basedsolely on a clinical interview and are increasingly considered the “goldstandard” of capacity assessment [20].

Research using standardized measures of decision-making capac-ity has provided insight into patterns of decisional impairment withinspecific patient populations. Impairment in decision-making capacityhas been demonstrated in elderly adults relative to younger adults[21–27], and in those with schizophrenia relative to adults without apsychiatric illness [28–33]. Research on the impact of depression,however, has been more equivocal, as the impact of depression ondecision-making is less severe than for many other mental illnesses(i.e., schizophrenia, schizoaffective disorder, bipolar disorder).Although some studies have found impairment in depressed adultsrelative to healthy adults, these effects may be due to changes incognitive functioning, such as memory and executive functionimpairments [28–30,34–37]. Not surprisingly, progressive, disablingneurological disorders that cause cognitive impairment, such asAlzheimer’s disease and Parkinson’s disease, have also been linked toimpaired decision-making capacity [16,20,38–45].

Despite the importance of decision making in terminally illpatients, only two published studies have specifically examineddecisional capacity in this population. Sorger and colleagues [46]found that hospitalized cancer patients receiving end-of-life care weresignificantly more impaired on several measures intended to tapability to provide informed consent when compared to relativelyhealthy elderly comparison subjects. Physical functioning and agewere the strongest predictors of decision-making capacity in thissample. However, there was no association between decisionalcapacity and other demographic or psychiatric (i.e., depression)variables. Similarly, Burton et al. [47] examined the relationshipbetween cognitive functioning and ability to provide informedconsent in a sample of patients receiving hospice care. Study findingssupported the relationship between impaired decisional capacity andglobal cognitive functioning. Overall, the results of these studiesindicate that advanced illness is associated with impairments indecision-making capacity, but the precise mechanism underlyingthese impairments is not known. Moreover, the measures used toassess decisional capacity have been broad-based measures ofcognitive functioning; no research to date has specifically targetedthe elements of decision making that are relied upon by courts andclinicians.

The present pilot study sought to extend this nascent literature byutilizing a standardized method to assess decision-making capacity inpatients with terminal illness. Specifically, the MacArthur Compe-tence Assessment Tool for Treatment (MacCAT-T) [48,49] was used toexamine decision-making capacity in the four domains directlyrelevant to existing legal standards: choice, understanding, apprecia-tion and reasoning. This study examined the prevalence of impairmenton these four standards of decision-making, as well as associationswith measures of cognitive functioning (MMSE) and psychologicaldistress (i.e., depression and anxiety).

1. Method

1.1. Participants

Terminally ill patients were recruited from a 200-bed palliativecare hospital in the Metropolitan New York City area. All participantshad a diagnosis of an incurable, life-limiting illness (primarily stage IV

Please cite this article as: Kolva E., et al, Assessing decision-making cap10.1016/j.genhosppsych.2014.02.013

cancer) and a life expectancy of less than 6months. This study utilizeda convenience sample of patients. Prospective patients who werecapable of participating in the study were referred to the investigatorsby their treating physicians. Hospital records were then reviewed todetermine whether patients were English-speaking, alert and respon-sive enough to be able to comprehend information disclosed duringthe informed consent process (i.e., able to communicate, not overtlydelirious). Because the goal of this study was to assess decision-making capacity across a range of abilities, patients with somecognitive impairment were included provided they were able tocomprehend the informed consent material and provide seeminglyrelevant answers to questions. This low threshold for studyparticipation (an “assent” standard) is consistent with both case lawand the research literature on informed consent [19,50], as anacceptable threshold for participation in research when the risks arenegligible. Interviews were conducted in a private room, at thepatient’s bedside. The institutional review boards of all participatinginstitutions approved the study.

Twenty-eight patients were approached for participation and 25patients agreed to participate in the study; one participant elected todiscontinue the study before providing sufficient data to permitanalysis, resulting in a final sample of 24. The average participant agewas 69.2 years (S.D.=13.1; range: 35–88). Themajority of the samplewas female (66.7%, n=16) and Caucasian (83.3%, n=20). Two-thirdsof participants completed at least some college (n=16), and 25% (n=6) were married. The majority of participants identified as Catholic(58.3%, n=14). The participants had a range of diagnoses. The mostcommon diagnosis was breast cancer (n=5, 20.8%). All remainingdiagnoses were held by two or fewer participants. Thirteen partici-pants completed the first [artificial nutrition and hydration (ANH)]version of the MacCAT-T (54.17%) and 11 completed the second [end-stage renal disease (ERD)] version (45.83%). These two groups did notdiffer in age, years of education, gender, race, ethnicity, marital status,religion or MMSE score. There were no significant differences onMacCAT-T subscale scores by MacCAT-T version.

1.2. Procedures

All patients who agreed to participate were interviewed briefly toelicit relevant demographic information including age, sex, race,ethnicity and education. Decision-making capacity was assessed usingthe MacCAT-T, a semi-structured, interview-based instrument thatconsists of a vignette presenting the participant with a medicaldisorder, the recommended treatments and associated risks andbenefits, and potential alternative treatments [19]. Although theMacCAT-T was initially developed to help guide the assessment ofactual proposed treatments, researchers have typically utilizedhypothetical treatment decisions in order to permit a standardizedadministration and inquiry [16,41]. In this study, two versions of theMacCAT-T were administered, one addressing the decision to acceptor reject ANH for cachexia (severe malnutrition or “wastingsyndrome”) and one pertaining to hemodialysis in the context ofERD. In each version, the participant was asked to imagine that he orshe had been diagnosedwith a terminal disease and that the proposedtreatment was necessary to extend life. Participants receivedinadequate, partial or adequate ratings for each MacCAT-T item(scores of 0, 1 and 2 respectively), and these scores were summed togenerate subscale scores for Understanding (0–6), Appreciation (0–4), Reasoning (0–8); and Choice (0–2). Prior research using theMacCAT-T in a sample of adults with psychiatric illness hasdemonstrated a high degree of inter-rater reliability and test-retestreliability over a 1-month period [49,51], although reliability was notassessed in the present study. Past research has also demonstrated amoderate correspondence between MacCAT-T scores and physician’sjudgments of decisional capacity [52,53].

acity at end of life, Gen Hosp Psychiatry (2014), http://dx.doi.org/

Table 1Demographic characteristics of sample

Variable Total Sample

M (SD)

Age 69.2 (13.1)Education (years) 14.9 (3.5)

N (%)

GenderMale 8 (33.3)Female 16 (66.7)

RaceWhite 20 (83.3)Black 3 (12.5)Other 1 (4.2)

EthnicityHispanic 2 (8.3)Not Hispanic 21 (87.5)

Marital statusMarried 6 (25.0)Single 10 (41.7)Divorced/separated 4 (16.7)Widowed 3 (12.5)

ReligionCatholic 14 (58.3)Protestant 1 (4.2)Jewish 4 (16.7)Baptist 1 (4.2)Other 1 (4.2)None 1 (4.2)

ReligiousYes 11 (45.8)Somewhat 3 (12.5)No 8 (33.3)

DiagnosisBreast cancer 5 (20.8)Liver cancer 2 (8.3)Lung cancer 2 (8.3)Ovarian cancer 2 (8.3)Prostate cancer 2 (8.3)Hodgkin’s disease 2 (8.3)ALS 1 (4.2)Bladder cancer 1 (4.2)Colon cancer 1 (4.2)Esophageal cancer 1 (4.2)Adrenal cancer 1 (4.2)Myelofibrosis 1 (4.2)Pancreas cancer 1 (4.2)Renal cancer 1 (4.2)Other 1 (4.2)

3E. Kolva et al. / General Hospital Psychiatry xxx (2014) xxx–xxx

Participants also completed a measure of general cognitivefunctioning, the MMSE and the Hospital Anxiety and DepressionScale (HADS) [54]. The MMSE assesses orientation, memory, lan-guage, constructional praxis and attention and is frequently used forthe purpose of assessing decisional capacity [14] and determiningeligibility to provide informed consent to participate in clinicalresearch [13]. The HADS is a 14-item self-report measure of anxietyand depression symptom severity developed for use in medically illpopulations. The HADS does not include the somatic symptoms thattypically confound the assessment of distress in medically ill patientsand has demonstrated strong reliability and validity in a broad rangeof medically ill populations [55].

1.3. Statistical analysis

Descriptive statistics were calculated for demographic, decision-making and psychosocial variables. Demographic differences betweenthe two alternate versions of the MacCAT-T, and between decision-making capacity and psychosocial variables were assessed using t testand chi-square statistics. Correlation coefficients were used toexamine the relationship between performance on the individualMacCAT-T subscales and measures of general cognitive functioning(MMSE) and psychological distress (HADS).

The authors of the MacCAT-T specifically avoided establishing cutscores for the MacCAT-T in order to prevent clinicians from equating acertain level of decision-making with the legal determination ofcompetence or incompetence [16]. However, in this study, there wasno such risk. Past studies of the MacCAT-T have established cut scoresto classify levels of decisional impairment. Thus, scores on theMacCAT-T were used to classify participants as impaired, borderline,or unimpaired on each of the four subscales. The cut scores used in thisstudy were based on those used with the clinical research version ofthe MacCAT by Kim and colleagues [37] and modified based on thedistribution of scores in the sample. On the Understanding subscale,scores in the 0 to 2 range were considered indicative of seriousimpairment whereas scores of 5 or greater were considered unim-paired and scores in between these two extremes were considered“borderline.” On the Appreciation subscale, scores below 2 wereconsidered impaired, scores of 2–3 were classified as borderline andscores of 3 or greater were considered unimpaired. On the Reasoningsubscale, scores below 4were considered to be impaired, scores of 4–7were considered borderline and scores of 7 or greaterwere consideredunimpaired. Finally, a score below 1 on the Choice subscale indicatedserious impairment, scores ranging from 1–1.99 indicated borderlinecapacity and a score of a 2 indicated unimpaired functioning.

2. Results

Participant scores on the MacCAT-T are displayed in Table 1. Allparticipants were able to express a treatment choice, only twoparticipants (8.3%) had borderline capacity, the remainder wereunimpaired (n=22, 91.7%). More than half of the participants (n=14, 58.3%) indicated a preference for life-prolonging treatment (ANH orERD) whereas 10 (41.7%) opted to refuse treatment. However, mostparticipants had at least some difficulty recalling relevant information,as only four participants (16.7%) obtained a score of 5 or greater on theUnderstanding subscale (i.e., were unimpaired) and six (25%) hadserious impairment in retention and recall (i.e., obtained an Under-standing score below 3). Participants had less difficulty with theAppreciation questions, as the majority of participants (n=19; 79.2%)were unimpaired on this subscale (i.e., scores of 3 or 4), whereas onlyone individual (4.2%) exhibited serious impairment (i.e., obtained anAppreciation score below 2). Finally, most participants (62.5%) haddifficulty with the Reasoning subscale items, as only nine participantswere unimpaired (i.e., obtained a Reasoning score of 7 or 8), whereasfour participants (16.7%) obtained Reasoning scores of 4 or below (i.e.,

Please cite this article as: Kolva E., et al, Assessing decision-making capacity at end of life, Gen Hosp Psychiatry (2014), http://dx.doi.org/10.1016/j.genhosppsych.2014.02.013

serious impairment). In total, one third of the sample (n=8) wasimpaired on at least one of the four subscales and three (12.5%) wereimpaired on two subscales; no participants were impaired on three ormore subscales. However, the Understanding, Appreciation andReasoning subscales were significantly correlated with one another(r'sN.40, P=.03 for each). However, none of theMacCAT subscalesweresignificantly correlated with ability to make a choice (r’s b .20; p=n.s.).

The average MMSE score was 26.17 (S.D.=3.72; range: 17–30),which falls within the average range of functioning. However, fiveparticipants (20.83%) fell within the impaired range of functioning(b24). Sample mean scores on the HADS were relatively high, with amean of 8.42 (S.D.=5.0, range: 0–20) on the depression subscale and7.12 (S.D.=5.4, range: 0–20) on the anxiety subscale. Half of thesample (n=12) reported clinically significant depressive symptoms(≥8 on the depression subscale) and 42% (n=10) reported clinicallysignificant anxiety symptoms (≥8 on the anxiety subscale).

2.1. Correlates of decision-making capacity

Correlational analyses revealed few significant associations be-tween MacCAT subscale scores and measures of cognitive (MMSE andyears of education) and psychological functioning [HADS Anxiety

Table 3Correlations between MacCAT-T subscales, cognitive and psychosocial variables

MMSE HADS-A HADS-D Education

Choice − .06 .06 .15 .04Understanding .60⁎⁎ − .02 .15 .30Appreciation .12 .10 .32 .39Reasoning .26 .17 .04 .44⁎

Note:⁎Pb .05⁎⁎Pb .01

4 E. Kolva et al. / General Hospital Psychiatry xxx (2014) xxx–xxx

subscale (HADS-A) and HADS Depression subscale (HADS-D); seeTable 2]. Specifically, the Understanding subscale was significantlyand strongly correlated with performance on the MMSE, r=.60, P=.002, and years of education was significantly correlated with theReasoning subscale, r=.44, P=.04. Although a number of othermoderate effect sizes were observed (.20–.39), these associationswere not statistically significant. None of the MacCAT subscales weresignificantly associated with the HADS anxiety or depressive sub-scales. (See Table 3.)

A second level of analysis focused on differentiating participantswho demonstrated impaired decision-making on any MacCAT sub-scale (n=8; 33.3%) from those who did not. Only two variablessignificantly differentiated these two groups, MMSE score, t(df=22)=4.56, p=.002, d=1.94, and years of education, t(df=21)=3.57, p=.02, d=1.55. No other demographic (gender, age, race/ethnicity) orpsychological (HADS-A, HADS-D) variable significantly differentiatedthese two groups. A logistic regression analysis was used to determinewhether these two variables provided a unique contribution to theprediction of impairment. This model, which explained 48% of thevariance in impairment classification, yielded a significant effect forMMSE, B=−0.56, p=.04, OR=0.57, but the incremental utility ofeducation did not reach statistical significance, B=−0.61, P=.06,OR=0.54.

2.2. Analysis of treatment choice

A final level of analysis addressed whether the presence ofclinically significant depressive symptoms (HADS-D N8) or decisionalimpairment (impairment on any MacCAT-T subscale) impactedpatient decisions to accept or reject life-prolonging treatment.Although a somewhat greater proportion of depressed patientsopted to reject treatment in the hypothetical vignette compared tothose without significant depression (50% versus 33%), but thisdiscrepancy was not significant, χ2 (2, N=24)=0.69, p=.41, Φ=.17.Conversely, patients with some decisional impairment were morelikely to desire treatment compared to those with no decisionalimpairment (75% versus 50%), but this association also failed to reachsignificance, χ2 (2, N=24)=1.37, p=.24, Φ=.24.

3. Discussion

Understanding the decisional capacity of terminally ill patients iscrucial for improving clinical consultation at end of life. Even in thefinal days or weeks of life, terminally ill patients may face important –even life-or-death – medical decisions such as whether to sign a do-not-resuscitate order or accept life-prolonging interventions. Giventhe potential legal and financial ramifications of these decisions, the

Table 2MacCAT-T scores

Capacity measure and score N %

Choice (score range 0–2)2 22 91.71 2 8.30 0 0.0

Understanding (score range 0–6)5–6 4 16.73.01–4.99 14 58.30–3 6 25.0

Appreciation (score range 0–4)3–4 19 79.22 4 16.70–1 1 4.2

Reasoning (score range 0–8)7–8 9 37.55–6 11 46.80–4 4 16.7

Please cite this article as: Kolva E., et al, Assessing decision-making cap10.1016/j.genhosppsych.2014.02.013

analysis of decision-making capacity in relation to the commonly usedlegal standards for identifying decisional competence is particularlyimportant [18]. Early studies of decision-making capacity in termi-nally ill patients have highlighted the high prevalence of impaireddecisional capacity, but have called for the use of structured, validatedmeasures of decisional capacity [46,47]. The present study is the firstto employ the MacCAT-T, a measure of decisional capacity thatspecifically targets common legal standards, in a terminally ill sample.

As expected, study participants demonstrated a range of decision-making abilities across the MacCAT-T subscales. Whereas nearly allparticipants were able to express a treatment decision, higher rates ofimpairment were found on subscales that required more complexcognitive abilities such as learning and memory, reasoning andapplication of new information in the context of personal goals andvalues. However, a surprisingly large proportion of participants (75%)did not evidence significant decisional impairment on any of theMacCAT subscales. These findings echo the results found in studies inother medically ill populations including Alzheimer’s disease [39],malignant glioma [56], and mild cognitive impairment [40]; merelyhaving a life-limiting illness is not pathognomonic for impaireddecisional capacity. However, when present, decisional impairmentmay impact treatment choice. The present study demonstrated agreater (though not significant) likelihood of accepting life-prolong-ing treatment among those with some decisional impairment. Greaterhealth care costs, resulting from increased medical intervention, inthe final weeks of life are associated with greater physical distress andworse quality of death [5]. Patients with impaired decisional capacitymay be more likely to make decisions that place them at greater riskfor harm. Clearly, the results of this study highlight the importance ofboth systematically assessing decision-making capacity as well as theimpact of impairment on end-of-life treatment decisions.

The standards of capacity represented in the MacCAT-T are oftendescribed as hierarchical with regard to the amount of protectionafforded by each test [57]. The Choice standard is generally regardedas the least restrictive, placing a premium on autonomy but withrelatively little opportunity to differentiate impaired and unimpaireddecision-making. Understanding is typically thought to require morecognitive demand and may be necessary but not sufficient foradequate Appreciation and Reasoning [58]. In the present study, thepatterns of impairment on the three “higher level” MacCAT-Tsubscales suggest that these subscales are not necessarily hierarchicalin nature, as some participants were impaired on the Understandingsubscale but appeared to have intact Appreciation and/or Reasoningabilities. However, the absence of well-established cut-scores forclassifying decisional capacity as “impaired” limits conclusions aboutthe relationship between the subscales and the underlying legalstandards measured. This caveat notwithstanding, the patterns ofdecisional capacity observed in this study highlight the importance ofa multi-faceted assessment of decision making in clinical evaluations.Unfortunately, most clinicians who assess decision making in theirpatients rely solely on gross measures of cognitive functioning orunsystematic measures of understanding, typically by asking theirpatient to repeat back information previously disclosed or indicateagreement [59].

acity at end of life, Gen Hosp Psychiatry (2014), http://dx.doi.org/

5E. Kolva et al. / General Hospital Psychiatry xxx (2014) xxx–xxx

Our analyses also indicated that Understanding was the onlyMacCAT-T subscale that was significantly correlatedwith ameasure ofcurrent cognitive functioning (MMSE). This association is notsurprising, as both the MMSE and Understanding subscale relyprimarily on attention and memory. However, this significantcorrelation highlights the limited nature of Understanding as a soleor primary technique for assessing decisional capacity. Conversely,while the MMSE may be useful for identifying impaired recall, it wasunrelated to performance on the remaining MacCAT-T subscales.Thus, relying solely on gross measures of cognitive function to assesscapacity [13,14] likely results in a failure to identify impairment inother domains of decision-making.

The association observed between years of education and theMacCAT Reasoning subscale also raises several interesting questionsgiven the evidence to suggest that education corresponds to bothoverall cognitive abilities as well as “cognitive reserve” in patients atrisk for cognitive impairment [60–62]. One interpretation of thisfinding is that cognitive reserve buffers the effects of illness ondecision-making. Alternatively, the Reasoning and Understandingsubscales, which rely heavily on verbal fluency in their assessment ofdecision-making, may fail to recognize intact decision-making inindividuals with limited verbal skills. This explanation is consistentwith previous research indicating that verbally based measures ofdecision-making are less accurate than more behavioral indices forindividuals with severe mental illnesses [63].

Finally, the absence of any significant association betweenMacCATsubscales and measures of depression and anxiety warrants attention.This finding is largely consistent with past studies of the impact ofpsychological distress on decisional capacity, in that the impact ofdepression and anxiety is generally dwarfed by the impact ofcognitive impairment and severe mental illness [28–30,34–37,53,64]. It may be the case that depression and anxiety only exertan impact on decision-making when the symptoms become partic-ularly severe (e.g., a psychotic depression), and such individuals arerarely found in clinical research. Although our analysis indicated asmall, and non-significant association between severe depression andboth Appreciation and treatment choice (with depressed participantssomewhat more likely to reject treatment compared to non-depressed participants), further research is clearly needed to betterunderstand the impact of depression on decision-making processesand outcomes.

This study is not without limitations. In order to establishacceptability and feasibility of the MacCAT-T in this setting, wesolicited a convenience sample of terminally ill cancer patients whowere identified by their treating physician as likely capable ofparticipating in the study (i.e., alert, verbal). This likely resulted in amore cognitively intact sample thanwould have been found hadmoresystematic and inclusive screening procedures been used (e.g.,sequential admissions to the facility). Similarly, patients who wereseen as seriously depressed or agitated by the treating physician wereunlikely to be recommended for study participation, which likelyreduced the severity of psychological symptoms in this sample. Inshort, this sample likely underestimates the frequency of decisionaland cognitive impairment.

The absence of established cut-scores for the MacCAT-T also limitsthe conclusiveness of our classifications of patients as having impaireddecision-making abilities. We based our classifications on the cut-scores previously utilized in other medically ill samples [13], but theMacCAT-T developers deliberately avoided recommending cut-scoresbecause of the complexity in assessing decisional competence. Otherresearchers have typically based cut-scores on a comparison tophysically healthy samples, or utilized clinician judgments aboutdecision-making capacity. Unfortunately, the pilot nature of this studyprecluded this approach. Finally, this study did not include an analysisof the inter-rater reliability of MacCAT-T scores, and included a verysmall sample size. The small sample size may have resulted in

Please cite this article as: Kolva E., et al, Assessing decision-making cap10.1016/j.genhosppsych.2014.02.013

insufficient power to detect effects between the MacCAT-T subscalescores and categories of decisional impairment on the MacCAT-T, andtheir relationship to cognitive functioning and psychological distress.These limitations, which reflect the logistical challenges of conductingresearch in a palliative care setting, nevertheless limit the conclu-siveness of study findings.

Despite these limitations, this study represents an important firststep in applying systematic methods of assessing decision-making,that are directly relevant to existing legal standards, to importantdecisions faced by terminally ill patients. The findings, whilepreliminary, substantiate concerns for the adequacy of traditionalmethods of assessing decisional capacity, and highlight the need forfurther research. Future studies that target a larger, and morerepresentative sample of terminally ill patients, and include both aclinician assessment of capacity and an appropriate comparisongroup, will allow for a more complete understanding of decision-making capacity in terminally ill patients. Such research is critical toboth protecting the rights of terminally ill patients, while simulta-neously protecting impaired decision makers from potential harm.

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