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Categorization and Cognitive Deficits in Compulsive Hoarding

Jessica R. Grisham1*, Melissa M. Norberg2, Alishia D. Williams1, Sarah P. Certoma1, & Raja

Kadib1

1 School of Psychology, University of New South Wales, Sydney NSW 2052, Australia

2 National Cannabis Prevention and Information Centre, University of New South Wales,

Sydney NSW 2052, Australia

*Corresponding author:

Phone: (+61 2) 9385 3031

Fax: (+61 2) 9385 3641

Email: jgrisham@psy.unsw.edu.au

Word Count – 7,603

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Abstract

According to the cognitive-behavioural model of compulsive hoarding, information

processing deficits in the areas of attention, memory, decision-making, and categorization

contribute to hoarding behaviour. The purpose of the current study was to examine whether

individuals with compulsive hoarding exhibited impairment on executive functioning and

categorization tasks. Three groups of participants were recruited (N = 60): individuals with

compulsive hoarding syndrome, individuals with an Axis I mood or anxiety disorder, and

nonclinical control participants. All participants completed self-report measures of cognitive

difficulties, neuropsychological tests of executive functioning and decision-making, and four

categorization tasks. Results suggested that hoarding participants reported more cognitive

failures and more problems with attention and decision-making than nonclinical control

participants. In addition, hoarding participants performed worse than both control groups on

the Stockings of Cambridge (SOC), a neuropsychological test of planning ability, and were

slower and more anxious during a categorization task. These findings suggest that specific

deficits in executive functioning may be associated with the difficulties hoarding patients

have organizing their possessions.

Keywords: categorization; compulsive hoarding; executive functioning; planning; saving

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Categorization and Cognitive Deficits in Compulsive Hoarding

Compulsive hoarding patients exhibit problems grouping their possessions into

categories, which contributes to the disorganization and clutter that are hallmark features of

this disorder (Frost & Hartl, 1996). They treat each object as unique, which leads them to feel

more anxious, sort more slowly, and create numerous categories when a few may suffice.

Wincze, Steketee, and Frost (2007) investigated differences in the way hoarding patients

categorize by contrasting hoarding participants, obsessive-compulsive non-hoarding

participants and non-psychiatric controls on categorization tasks. Participants sorted both

common household items and index cards on which the experimenter had written the name of

an object commonly found in the participant’s home. Although the groups did not differ

when sorting common household items, hoarding participants created more categories than

non-psychiatric controls when sorting personal index cards. They also took more time to sort

personal index cards than both control groups. Lastly, hoarding participants and obsessive-

compulsive non-hoarding participants reported higher anxiety prior to sorting than did non-

psychiatric controls. The results of this study suggested that categorization problems may

occur only when individuals with hoarding sort their own possessions.

On the other hand, Luchian, McNally, and Hooley (2007) demonstrated that

nonclinical hoarding participants engage in under-inclusive behaviour when categorising

non-personal objects. Using similar non-personal objects to Wincze and colleagues’

household items, Luchian and colleagues found that individuals who self-identified as

“packrats” created more categories, took almost twice as long to sort objects, and found

sorting common household items to be more difficult and stressful than did nonhoarding

participants. Inconsistencies between this study and Wincze et al. (2007) may be due to

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sample (nonclinical versus clinical hoarding participants) and methodological differences

between the two studies. One difficulty in comparing the two studies is the manner in which

Wincze and colleagues (2007) represented personal objects in their study. Rather than using

participants’ actual belongings, they used words written on index cards to represent personal

objects. Therefore, their findings may represent a difficulty with sorting paper items (Frost &

Hartl, 1996), and not necessarily difficulties with sorting personal items. Together, findings

from Wincze et al. (2007) and Luchian et al. (2007) suggest that individuals who hoard may

have problems with sorting personal items, nonpersonal items, common household items,

and/or paper items. Thus, the exact circumstances under which hoarding patients have

categorization difficulties remains unknown due to the lack of systematic comparisons

between personal and non-personal objects.

The categorization problems demonstrated by hoarding patients may be linked to

information-processing difficulties proposed to underline hoarding behaviour (Frost & Hartl,

1996; Frost & Steketee, 1998). Hoarding patients report increased symptoms of attention

deficit hyperactivity disorder (ADHD; Hartl, Duffany, Allen, Steketee, & Frost, 2005) and

have been found to perform worse on certain neuropsychological tasks, including measures

of attention and nonverbal intelligence (Grisham, Brown, Savage, Steketee, & Barlow, 2007),

memory (Hartl et al., 2004) and decision-making (Lawrence et al., 2006). According to the

cognitive-behavioural model, the combination of these information-processing deficits

contributes to organizational problems (Grisham et al., 2007). For example, efficient

categorization involves planning, developing strategies for how to best group objects,

sustained attention, sufficient impulse control, and decision-making abilities. With respect to

planning, the individual must identify and organize the steps needed to carry out the goal of

creating distinct categories. He or she needs to consider alternatives, weigh these alternatives,

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and make choices. Furthermore, the individual must be able to stick to the task at hand. All of

these skills are needed in order to make a decision about where an object belongs. Along

these lines, Wincze and colleagues (2007) found that self-reported indecisiveness related

positively with the number of categories created and pre-task anxiety levels.

The purpose of the current study was to clarify the nature of the executive functioning

and categorization difficulties associated with compulsive hoarding. To investigate these

issues, three groups of participants were recruited: individuals whose most prominent

psychiatric symptom was compulsive hoarding, as defined by Steketee and Frost (2003),

individuals with a primary Axis I mood or anxiety disorder who did not meet criteria for

compulsive hoarding, and nonclinical control participants. All participants completed four

categorisation tasks (personal versus non-personal; actual versus index card), as well as self-

report measures of cognitive difficulties and neuropsychological tests of executive

functioning.

We hypothesised that, relative to clinical and nonclinical controls, those in the

hoarding group would report more cognitive failures and more difficulty with sustained

attention and decision-making. In addition, we hypothesised that hoarding patients would

perform worse on tests of executive functioning. With respect to the categorization task, we

predicted that the hoarding group would create more categories, take more time to create

categories, and experience more discomfort before and after the task. We also predicted that

these differences would be more pronounced for personal objects compared to non-personal

objects.

Method

Participants

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Three groups of participants (total N = 60) were recruited from the community via

advertisements in local newspapers: individuals with compulsive hoarding problems (n = 23),

participants with a current mood or anxiety disorder who did not compulsively hoard (n =

17), and nonclinical control participants with no current Axis I disorder (n = 20). Individuals

who were currently psychotic or suicidal or had a neurological disorder (e.g., dementia) were

excluded from the study. Hoarding participants were required to meet compulsive hoarding

criteria as defined by Frost and Hartl (1996): (1) the acquisition of, and failure to discard a

large number of possessions that appear to be useless or of limited value; (2) living spaces

sufficiently cluttered so as to preclude activities for which those spaces were designed; and

(3) significant distress or impairment in functioning caused by the hoarding. Four individuals

who reported subclinical hoarding symptoms were excluded from the hoarding group due to

their failure to meet these criteria, leaving 19 participants in the hoarding group (N =56). All

participants were offered a small financial reward in exchange for their time.

Persons recruited to participate in the comparison groups were matched to the

hoarding group with respect to age, F (2, 53) =2.04, p =.14, and gender, χ2 (2, N=56) = 3.94,

p =.14, due to the potential effect of these characteristics on neuropsychological performance.

The mean age of the sample was 48.0 years (SD = 11.0) and 39 of the participants (70%)

were female. See Table 1 for the Axis I diagnoses of the hoarding and clinical control groups.

Measures

Diagnostic Assessment

Anxiety Disorders Interview Schedule for DSM-IV (ADIS-IV; Brown, Di Nardo, &

Barlow, 1994) is a semi-structured interview to diagnose anxiety, mood, somatoform, and

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substance use disorders and to screen for the presence of other conditions, such as psychosis.

The ADIS has demonstrated good to excellent reliability for the majority of anxiety and

mood disorders (Brown, Di Nardo, Lehman, & Campbell, 2001). A dimensional Hoarding

Rating Scale was also administered to enable interviewers to diagnose compulsive hoarding.

Five hoarding symptoms (clutter, acquisition, difficulty discarding, distress, and impairment)

were rated from 0 (no difficulty) to 8 (extreme difficulty) (Tolin, Frost, & Steketee, in press).

Self-Report Questionnaires

ADHD Symptom Checklist (ADHD-CL; Barkley & Murphy, 1998). The adult version

of the ADHD-CL is an 18 item self-report measure. Participants are required to rate from 0

(never or rarely) to 3 (very often) the intensity of a number of ADHD symptoms. This

measure has demonstrated good reliability and internal consistency (Barkley & Murphy,

1998). An overall mean of 20.0 (SD = 11.71) has been previously reported in a sample of

compulsive hoarding patients (Grisham et al., 2007).

Clutter Image Rating (CIR; Frost, Steketee, Tolin, & Renaud, 2008). The CIR is a

visual rating scale for clutter in three living spaces – the living room, kitchen and bedroom.

For each living space, participants are shown photographs of the same room with different

levels of clutter. Participants are required to choose which of the nine photographs looks most

like the different areas in their home (1 = least cluttered, 9 = most cluttered). A mean

composite score is calculated for each participant (range 1-9). The scale has good internal

consistency (α = .84) and good convergent and discriminant validity (Frost et al., 2008). Frost

and colleagues (2008) reported an overall mean of 4.01 (SD = 1.80) among individuals with

significant hoarding difficulties.

Cognitive Failures Questionnaire (CFQ; Broadbent, Cooper, Fitzgerald, & Parkes,

1982). This 25-item questionnaire requires participants to rate on a scale from 0 (never) to 4

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(very often) the frequency with which they make a number of common cognitive mistakes.

The CFQ has demonstrated good convergent and discriminant validity, test-retest reliability

and internal reliability (Broadbent et al., 1982). An overall mean of 40.62 (SD = 17.00) has

been reported for a sample of patients with neurological disorders (e.g., Alzheimer’s,

dementia), while an overall mean of 56.80 (SD = 18.00) has been reported for a sample of

depressed individuals (Wagle, Berrios, & Ho, 1999).

Depression Anxiety Stress Scales (DASS; Lovibond & Lovibond, 1995). The DASS is

a 21-item self-report measure which requires participants to rate on a scale from 0 (does not

apply to me at all) to 4 (applies to me very much) the extent to which each item applies to

them. The items on the DASS tap into depression, anxiety and stress, with subscale scores

ranging from 0 to 42. Depression scores 13 and lower, anxiety scores 9 and lower, and stress

scores 18 and lower indicate symptoms in the mild to normal range (Lovibond & Lovibond,

1995). This measure demonstrates good reliability (Brown, Chorpita, Korotitsch, & Barlow,

1997) and internal consistency (Henry & Crawford, 2005).

Frost Indecisiveness Scale (FIS; Frost & Shows, 1993). The FIS is a 15-item self-

report measure that assesses difficulty making decisions. Participants rate on a scale from 1

(strongly disagree) to 5 (strongly agree) the extent to which each of the statements is true for

them. The FIS has demonstrated good reliability and validity (Frost & Shows, 1993; Rassin,

Muris, Franken, Smit, & Wong, 2007). In a study by Steketee, Frost, and Kyrios (2003),

mean total scores on the FIS were 50.1 (SD = 12.5) for individuals with primary compulsive

hoarding, and 40.6 (SD = 10.0) for individuals with OCD without hoarding.

Obsessive-Compulsive Inventory-Revised (OCI-R; Foa et al., 2002). The OCI-R is an

18-item measure of OCD symptoms containing 7 subscales: doubting, checking, hoarding,

neutralizing, obsessing, ordering, and washing. Participants are required to rate the frequency

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of each symptom on a scale from 0 (never) to 4 (almost always). The scales show good

reliability, internal consistency and convergent validity (Foa et al., 2002). An and colleagues

(2008) reported a mean hoarding subscale score of 6.6 (SD= 3.2) for individuals with primary

compulsive hoarding, and 1.4 (SD = 2.1) for individuals with OCD without hoarding.

Saving Inventory–Revised (SIR; Frost, Steketee, & Grisham, 2004). The SI-R is a 23

item self-report measure that assesses difficulty discarding, clutter and compulsive

acquisition. It has shown good internal consistency and reliability (Frost et al., 2004).

Previous studies have reported an overall mean of 60 for individuals with hoarding (Frost et

al., 2008; Hartl et al., 2005).

Subjective Units of Distress Scale (SUDS). SUDS ratings are used as an idiographic

anxiety barometer to determine how anxious a person feels from 0 (no anxiety) to 100 (most

anxiety). SUDS rating scales have shown good reliability and validity (Thyer, Papsdorf,

Davis, & Vallecorsa, 1984).

Neuropsychological Tests

Wechsler Abbreviated Scale of Intelligence (WASI; Psychological Corporation,

1999). WASI subtests were used to estimate participants’ verbal and nonverbal intelligence.

WASI Vocabulary and Matrix Reasoning are similar to the Vocabulary and Matrix Reasoning

subtests of the WAIS-III (Wechsler, 1997). Both WASI subtests have demonstrated good

reliability (Psychological Corporation, 1999).

Cambridge Neuropsychological Test Automated Battery (CANTAB; Cambridge

Cognition, 1995) is a battery of neuropsychological tests. It consists of 19 tests administered

through a computer. The subtests have been validated and norms are available for each

subtest. The following subtests were used in the current study:

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Affective Go/No-go (AGN). The AGN was selected to assess whether hoarding is

associated with decreased response inhibition and ability to shift attention. In this task a

series of positive, negative and neutral words are presented and subjects are required to press

a key when the word matches the target valence. This task measures participants’ ability to

shift between different concepts (i.e. their ability to shift attention from one valence to

another). The measures of performance on this task are latency to respond and number of

omission errors for each target valence.

Cambridge Gambling Task (CGT). Decision-making has been suggested to be

impaired in compulsive hoarding. Hoarding participants may be risk averse, as demonstrated

by their avoidance of discarding because of hypothetical future need. The CGT was included

to measure decision making and risk-taking. On each trial of the CGT, participants are

presented with a number of red and blue cards and must make a decision about which colour

card has a yellow token hidden behind it. They are also asked to select the number of points

they wish to bet on each trial. The bets represent a fixed percentage of the current total points

score (5, 25, 50, 75, and 95%). After selecting a bet, one of the cards is removed to reveal the

actual location of the yellow token, and the chosen bet is added to or subtracted from the total

score depending on whether the prediction was correct. Performance on this task was

measured in terms of two dependent variables. The first was quality of decision making

(proportion correct), which was the proportion of trials on which participants chose the more

likely outcome. The second was risk adjustment (percentage bet), which was the percentage

of accumulated points bet on each trial in relation to the different ratios of coloured boxes.

Intra-Extra Dimensional Set Shift (IED). Mental flexibility and attention are

important aspects of executive functioning that could influence an individual’s ability to sort

and discard objects. This task measures participants’ ability to see concepts, flexibly shift

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between them and maintain attention. Participants must learn to sort coloured shapes

according to a rule before contingencies are reversed and they must shift to the new rule.

There are nine stages in total on the IED. The number of stages completed and the number of

errors made across trials are indicators of performance on this task.

Stockings of Cambridge (SOC). Finally, individuals must be able to plan effectively in

order to make choices about possessions, categorize them, and effectively arrange for their

appropriate placement or disposal. The SOC is a computerized adaptation of the Tower of

London test and measures planning and problem solving. Participants must move coloured

balls in the lower half of the screen to match the pattern in the upper half. The number of

steps required to complete each trial (i.e. the task’s difficulty) increases as the task

progresses. Performance on this task is indicated by thinking time before attempting the

problem (latency to first response), thinking time between executing each step in the solution,

and number of problems solved within the minimum number of moves.

Procedure

Individuals who responded to the advertisements and did not meet any of the

exclusion criteria were mailed out the self-report questionnaires (ADHD-CL, CFQ, FIS, OCI,

and SI-R) and were scheduled for an appointment within one week of mailing out the

questionnaires. Participants were instructed to bring in 20 items that were representative of

the types of items they would have in their home. On the day of the study, a clinically-trained

experimenter answered any questions about the study and obtained signed consent forms and

completed questionnaires. During the testing session, the experimenter administered the

ADIS-IV (Brown et al., 1994) plus the Hoarding Rating Scale to diagnose primary hoarding

symptoms and comorbid Axis I conditions. Participants also completed the DASS and the

CIR.

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All participants completed a battery of neuropsychological tests (CANTAB and

WASI subtests), as well as four categorisation tasks. These categorisation tasks included

sorting 20 personal objects, 20 non-personal objects, 20 personal index cards (i.e., cards

labelled with the objects participants brought in), and 20 non-personal index cards (i.e., cards

labelled with the names of the non-personal objects). A counterbalanced design was

employed to control for order effects. Replicating Wincze et al.’s (2007) study, the 20 non-

personal items reflected five types of items commonly found in hoarding participants’ homes:

reading material (newspaper, magazine, book, journal article), clothing (baseball cap, tie, tee-

shirt, sock), used containers (empty coffee can, empty paper-towel roll, lolly wrapper, worn

paper bag), stationary (pencil, paper clip, elastic band, transparent tape), and bathroom items

(soap bar, tooth paste, deodorant, shaving cream). Prior to the sorting tasks, the investigator

explained the use of the SUDS and instructed participants to rate their anxiety prior to and

following each categorisation task. The following instructions were then read, based on those

used by Wincze et al. (2007):

I am going to ask you to sort [20 common household items/the 20 items

you brought in today/20 index cards on which I’ve written the name of

common household items/20 index cards on which I’ve written the name

of the items that you brought in today]. I would like you to separate these

items into different piles in a way that makes sense to you. A pile can

have as few or many items that you want to place in it. There are no right

or wrong ways to complete this task. I would like to see how long it takes

you to do this, naturally, so I’ll be using my stopwatch, but you should

take as much time as you’d like. Any questions? Tell me when you are

finished.

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When participants indicated that they were finished sorting, the investigator logged

the time taken to complete the task, the number of piles created, the items in each pile, and

SUDS ratings. The entire battery took approximately 2-3 hours to complete, plus

approximately 1 hour to complete the self-report questionnaires. Upon completion of the

study, participants were debriefed and received financial reimbursement for their time.

Results

Descriptive Information

To validate participants’ assignment to groups, the groups were compared to each

other on measures of compulsive hoarding, depression, anxiety, and stress (see Table 2). All

analyses were conducted using analysis of variance (ANOVA) and Student-Newman-Keuls

(SNK) post hoc testing. As expected, ANOVA revealed a significant main effect of groups on

the SI-R, F(2,53)= 40.09, p < .001. Post hoc tests demonstrated that the compulsive hoarding

group reported significantly more hoarding symptoms than the two comparison groups.

Consistent with previous studies, the hoarding group scored a 60.1 on this measure (Frost et

al., 2004). There were also significant main effects of group on the OCI-R Hoarding subscale

(F(2,52)= 21.40, p < .001) and the CI-R (F(2,53)= 34.06, p < .001). Again, post hoc tests

revealed that the hoarding group reported more symptoms than the two comparison groups on

both of these measures. ANOVA also revealed a significant main effect of groups for the

DASS depression subscale, F(2, 53)= 22.60, p < .001, DASS anxiety subscale, F(2, 53)=

7.95, p < .01, and DASS stress subscale, F(2, 53)= 18.63, p < .001. Post hoc tests indicated

that both clinical groups reported significantly more anxiety, depression, and stress than

individuals in the community comparison group. Individuals in the hoarding and clinical

comparison groups did not differ with respect to self-reported level of anxiety or stress,

although the clinical comparison group reported significantly more symptoms of depression.

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Self Report Measures of Cognitive Functioning

Groups were also contrasted on self-report measures of ADHD symptoms, indecision,

and cognitive failures (Table 2). ANOVA revealed a significant main effect of groups on the

CFQ, F(2, 53)= 6.10, p < .01, the ADHD-CL Total, F(2, 52)= 12.58, p < .01, and the FIS,

F(2, 53)= 3.73, p < .05. Post hoc tests revealed that the hoarding and clinical comparison

groups did not differ with respect to ADHD symptoms or cognitive failures although both

groups had significantly higher scores than the community comparison group. Similarly, with

respect to the FIS, post hoc tests demonstrated that the hoarding group reported significantly

more indecisiveness than the community comparison group, but not the clinical control

group.

Neuropsychological Tests

Means and standard deviations on each of the neuropsychological measures are

displayed in Table 3. There were no differences between the three groups with respect to

verbal or nonverbal intelligence (Vocabulary and Matrix Reasoning subtests from the WASI).

On a test of planning ability (SOC), ANOVA revealed a significant main effect of groups

with respect to the number of problems solved, F(2, 49)= 5.14, p = .01. Post hoc tests

demonstrated that the hoarding group solved fewer problems than either of the comparison

groups. Contrary to prediction, there were no significant between-group differences with

respect to decision-making (CGT) or ability to shift attention (AGN and IED).

Categorisation Task

Results from the categorisation tasks are summarised in Table 4. Given the potential

effects on variables of interest, participants who brought in less than 20 personal objects were

excluded from the analyses for personal objects and personal index cards. Thus, after

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excluding 3 participants in the hoarding group and 4 in the nonclinical control group for this

reason, n = 16 in the hoarding and nonclinical control group and n = 17 in the clinical control

group (N = 50).

There were several between-groups differences on the categorization tasks. With

respect to the number of piles created, there was a significant main effect of groups for

personal objects, F(2, 46)= 5.09, p = .01, and personal index cards, F(2, 46)= 3.73, p < .05.

Post hoc tests revealed that hoarding participants created significantly more categories than

clinical control participants, but not nonclinical control participants, for both types of

personal possessions. Regarding the time taken to sort items, there was a significant main

effect of groups for personal objects, F(2, 46)= 7.09, p < .01, and non-personal index cards,

F(2, 46)= 4.21, p < .05 and a trend for personal index cards, F(2, 46)= 3.13, p = .05. Post hoc

tests demonstrated that hoarding participants took significantly longer to sort personal objects

relative to both comparison groups. They also took significantly more time than nonclinical

control participants to sort non-personal and personal index cards, although they did not

differ significantly from clinical comparison participants on these indices.

The results for anxiety pre sorting task revealed a significant overall effect of groups

for every type of possessions: personal objects, F(2, 46)= 7.09, p < .01, non-personal objects,

F(2, 46)= 7.09, p < .01, personal index cards, F(2, 46)= 7.09, p < .01, and non-personal index

cards, F(2, 46)= 7.09, p < .01. For anxiety post-sorting task, there was also a significant

overall effect of groups for every type of possessions: personal objects, F(2, 46)= 7.09, p <

.01, non-personal objects, F(2, 46)= 7.09, p < .01, personal index cards, F(2, 46)= 7.09, p <

.01, and non-personal index cards, F(2, 46)= 7.09, p < .01. Follow-up tests indicated that the

hoarding group rated their anxiety (SUDS) as significantly higher than both comparison

groups, both before and after the task, regardless of the type of item. The only exception was

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pre-task anxiety for the non-personal index cards; on this measure hoarding participants

reported significantly more anxiety than nonclinical control participants, but not clinical

control participants.

Discussion

The results of the current study provide further insight into the nature of cognitive

difficulties associated with compulsive hoarding. On self-report measures hoarding

participants reported more difficulties than nonclinical control participants with respect to

decision-making, cognitive failures and ADHD symptoms, although they were not

significantly more impaired on these measures than clinical control participants. This finding

suggests that self-reported cognitive difficulties are not unique to hoarding patients. In

contrast, Grisham et al. (2007) found that hoarding participants reported more ADHD

symptoms than a mixed anxiety control group. Although the hoarding participants in the two

studies reported virtually identical levels of ADHD symptoms, the clinical control group in

the current study reported more ADHD symptoms than the clinical control group in Grisham

et al. (2007). This increased level of ADHD among current clinical controls may be

attributable to the increased depression symptomatology in this group relative to the previous

study, as there is a high rate of comorbidity between ADHD and depression (Jensen et al.,

2001; Jensen, Shervette, Xenakis, & Richters, 1993). Alternatively, higher ADHD symptoms

in the current clinical comparison group may be due to sampling fluctuations between the two

studies.

Contrary to hypotheses, hoarding participants were not impaired on most

neuropsychological tasks. It is noteworthy that while hoarding participants reported

indecisiveness on a self-report questionnaire, their performance on a decision-making task

was unimpaired. This suggests a slight discrepancy between perceived and actual decision-

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making deficits in compulsive hoarding, which is consistent with memory difficulties (Hartl

et al., 2004). It is also possible that individuals with hoarding problems have decision-making

deficits that are specific to items of personal relevance, which would not be detected by the

Gambling Task. Hoarding participants may only experience decision-making difficulties

when a choice involves options that are emotionally salient or when decisions are tied to

rigid, inflexible beliefs. It is also possible that the CGT was sufficiently structured to help

individuals with compulsive hoarding compensate for decision making difficulty. Including a

decision-making task that is more naturalistic and ecologically valid would help elucidate

whether this is a problem in compulsive hoarding.

A test of planning ability was the only neuropsychological task for which the

hoarding group performed worse than both comparison groups. In this task, participants were

required to complete a number of subgoals and move individual circles while keeping in

mind the main goal of matching the pattern. To score well, the participant had to mentally

plan a series of moves before beginning the sequence. Individuals who hoard may have

demonstrated poor planning on this task due to a failure of inhibitory mechanisms (e.g., they

may have begun trying to solve the problems without sufficient forethought). This finding is

intriguing in light of a recent study reporting that hoarding-related anxiety was negatively

correlated with dorsal prefrontal-striatal and parietal regions, which is consistent with

difficulties in planning (An et al., 2008).

Results of the categorization tasks provided mixed support for the hypothesis that

hoarding participants have categorization difficulties. Visual inspection of Table 4 reveals

that hoarding participants had more difficulty with sorting personal items than non-personal

items. Although the differences were small, hoarding participants created slightly more

categories and remained more anxious after sorting personal items than non-personal items.

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They also took much longer to sort personal index cards relative to the other tasks. When

examining hoarding participants’ sorting behaviour in comparison to clinical and nonclinical

controls, hoarding participants were generally more anxious when asked to sort, regardless of

the type of item, both before and after the task, yet hoarding patients only created more

categories than clinical controls for personal possessions (both objects and index cards).

There were no categorization tasks, however, for which hoarding participants created

significantly more categories than both control groups.

With respect to time taken to sort items, hoarding participants took significantly

longer than both comparison groups to sort personal objects, taking almost twice as long as

nonclinical control participants. This result is consistent with findings from Wincze et al.

(2007) who suggested that hoarding participants are slow to organize their own possessions

because of the unique qualities they attribute to them. Interestingly, hoarding participants

took longer to sort their own personal items when they were represented on an index card and

experienced an increase in anxiety from pre- to post-sorting, although their anxiety decreased

after sorting the actual objects. Hoarding participants may have expected sorting index cards

to be easier than the actual objects given the contrived nature of the task; however, the

vagueness of the items (e.g., no visual detail regarding object characteristics) may have

contributed to the task being harder than expected (i.e., increased sorting time, increased

post-anxiety rating). Future research may benefit from asking participants about their

perceived reasons for number of categories created, sorting time, and anxiety levels

experienced during these experimental tasks.

Future research may further investigate the role of executive control processes (e.g,

working memory capacity, cognitive flexibility, planning ability) in compulsive hoarding. It

is important to consider, however, that sorting duration may be due to a variety of factors,

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such as object characteristics, beliefs about and emotional attachment to an object, and

anxiety (Steketee & Frost, 2003; Wincze et al., 2007). Future studies may examine all of

these factors with a larger sample. It will be particularly important to examine the interplay

between executive functioning and the cognitive appraisals and beliefs associated with

hoarding behaviour.

There are several important clinical implications for the current study. Planning skills

are relevant to sorting and organizing possessions, which sometimes involves planning a

temporary placement of an object while clearing out the space where the object will

ultimately be placed. Hoarding patients may find it challenging to plan several steps ahead in

order to dispose of or organize their possessions. It is possible that directly targeting these

difficulties with planning and categorizing may help alleviate some of the core symptoms of

hoarding. Therapy goals may include practicing planning ahead a series of smaller steps

while pursuing the larger organizational goal. In addition, specific categorization training has

been found to be helpful with individuals with traumatic brain injury (Constantinidou et al.,

2005). Although hoarding patients show much milder deficits, it may be possible to

incorporate some type of categorization training into hoarding treatments.

While this study had several strengths, including the use of structured psychiatric

interviews and gold-standard neuropsychological measures, a clinical comparison group, and

improvements in methodology regarding the categorisation task, there were nonetheless

several limitations. First, the hoarding group presented with a large amount of comorbid

diagnoses, which is common for this population (Grisham & Barlow, 2005). This potential

confound is partially addressed by the inclusion of a clinical control group, which reported

equivalent (or greater) levels of general emotional distress compared to the hoarding group.

The clinical group, however, was diagnostically diverse and reported a higher level of

20

depressive symptoms than the hoarding group. Further, while the comparison groups were

matched to the hoarding group for age and gender, we did not assess education level and thus

the groups may have differed with respect to education. In addition, the study would have

been strengthened by determining medication use for all participants. Finally, while we

included several key neuropsychological tests of executive functioning, future studies may

benefit from the inclusion of a more comprehensive battery of tests, including measures of

naturalistic task performance specific to hoarding.

In conclusion, a limited understanding of cognitive factors associated with

compulsive hoarding may contribute to the modest treatment outcomes for this disorder

(Steketee & Frost, 2003). The results of the current study increase our understanding of the

neuropsychological factors that are related to hoarding behaviour. This type of research is an

essential initial step toward significant improvements in treatment for compulsive hoarding.

21

Table 1

DSM-IV Axis I Diagnoses for Hoarding (N = 19) and Clinical Control (N = 17) Participants

Diagnosis

Hoarding

n %

Clinical Control

n %

Major depressive disorder 10 (52.6) 15 (88.2)

Generalized anxiety disorder 6 (31.6) 4 (23.5)

Social phobia 2 (10.5) 7 (41.2)

Obsessive-compulsive disorder 1 (5.3) 0

Panic disorder without agoraphobia 1 (5.3) 1 (5.9)

Specific phobia 0 2 (11.8)

Posttraumatic stress disorder 0 1 (5.9)

22

Table 2

Means and Standard Deviations for Self-Report Questionnaires (N = 56)

Measure Hoarding M (SD)

Clinical Control M (SD)

Nonclinical Control M (SD)

F

CIR: Total 3.6 (1.5) a 1.3 (.3) b 1.4 (.6) b 34.06***

OCI-R: Hoarding 10.6 (3.7) a 4.9 (3.7) b 3.4 (3.3) b 21.40***

SI-R: Total 60.1 (18.0) a 28.9 (17.9) b 19.8 (9.9) b 40.09***

ADHD-CL: Total 20.7 (9.6) a 19.4 (8.7) a 8.8 b (5.6) 12.58***

CFQ 51.0 (14.3) a 48.2 (13.2) a 37.0 (12.0) b 6.10**

DASS: Depression 15.6 (11.8) b 21.0 (7.2) a 3.5 (3.4) c 22.60***

DASS: Anxiety 12.1 (9.9) a 12.9 (9.8) a 3.5 (3.2) b 7.95**

DASS: Stress 20.1 (10.4) a 23.3 (7.0) a 8.5 (5.4) b 18.63***

FIS: Total 48.6 (12.7) a 44.4 (8.1) a,b 39.7 (9.1) b 3.73*

Note. Student-Newman-Keuls post hoc testing was conducted to examine group differences.

Means with different superscripts differ significantly at p < .05 by the Student-Newman-

Keuls post hoc test. ADHD-CL: Total = ADHD-Checklist, total score; CFQ = Cognitive

Failures Questionnaire; CIR =Clutter Image Rating; DASS = Depression, Anxiety and Stress

Scales; FIS: Total = Frost Indecisiveness Scale, SI-R: Total = Saving Inventory – Revised,

total score; OCI = Obsessive Compulsive Inventory – Revised; SI-R = Saving Inventory –

Revised.

*p < .05, **p < .01, ***p<.001

23

Table 3

Means and Standard Deviations for Neuropsychological Measures (N = 56)

Measure Hoarding

M (SD)

Clinical Control

M (SD)

Nonclinical Control

M (SD)

F

Verbal/Nonverbal Intelligence

WASI Vocabulary

WASI Matrix Reasoning

Mental Flexibility

42.56 (17.35)

50.11 (12.59)

48.59 (12.57)

53.82 (6.13)

50.65 (12.68)

54.10 (10.18)

.21

.41

IED Stages completed

IED Total errors adjusted

7.42 (2.14)

55.21 (41.35)

6.94 (2.38)

66.12 (55.05)

8.00 (2.31)

39.75 (55.85)

1.00

1.12

Planning

SOC Initial thinking time, ms

SOC Problems solved

8522.31 (6319.76)

6.63 (2.27)a

11165.63 (11417.12)

8.06 (1.68) b

6691.44 (3744.11)

8.25 (1.80) b

1.58

3.96*

Response Inhibition

AGN Mean correct latency pos

AGN Mean correct latency neg

541.39 (53.26)

553.88 (75.61)

536.68 (82.29)

545.04 (84.51)

521.28 (87.27)

535.42 (90.87)

.38

.24

24

AGN Total omissions positive

AGN Total omissions negative

2.74 (2.58)

2.95 (3.61)

3.35 (5.12)

1.94 (2.34)

2.80 (4.18)

1.70 (2.03)

.12

1.10

Decision Making

CGT Quality decision making

CGT Risk adjustment

.83 (.20)

.13 (.79)

.84 (.22)

.37 (1.28)

.74 (.23)

.83 (1.30)

1.12

1.91

Note. Student-Newman-Keuls post hoc testing was conducted to examine group differences. Means with different superscripts differ

significantly at p < .05 by the Student-Newman-Keuls post hoc test.

*p < .05

25

Table 4

Comparison of Groups on Categorisation Tasks (N = 49)

Hoarding M (SD)

Clinical Controls M (SD)

Nonclinical Controls M (SD

F

Personal objects

# piles 7.75 (2.70) a 5.18 (1.47) b 7.31 (3.07) a 5.09**

Time (secs) 85.94 (28.11) a 59.88 (35.76) b 60.56 (13.49) b 7.09**

Pre-SUDS 42.00 (23.81) a 15.59 (22.97) b 9.19 (9.05) b 12.31***

Post-SUDS 35.63 (23.94) a 15.00 (19.04) b 8.75 (10.25) b 9.15***

Non-personal objects

# piles 6.25 (1.53) 5.06 (1.09) 6.25 (2.15) 2.95

Time (secs) 72.88 (34.06) 59.41 (29.33) 52.38 (20.04) 2.15

Pre-SUDS 31.50 (26.57) a 14.12 (26.18) b 9.38 (8.73) b 4.42*

Post-SUDS 27.31 (25.32) a 8.24 (11.03) b 8.63 (9.98) b 6.78**

Personal index cards

# piles 7.31 (2.92) a 5.24 (1.89) b 7.19 (2.51) a 3.73*

Time (secs) 124.38 (69.63) 102.35 (55.91) 75.88 (32.83) 3.13

Pre-SUDS 31.44 (26.89) a 14.41 (22.97) b 8.13 (8.14) b 5.29**

Post-SUDS 39.38 (30.05) a 16.18 (14.31) b 9.38 (11.38) b 9.74***

Non-personal index cards

# piles 6.38 (1.46) 5.12 (.86) 5.75 (1.92) 3.04

Time (secs) 86.38 (30.05) a 66.35 (50.14) a, b 49.44 (16.89) b 4.21*

Pre-SUDS 28.50 (23.07)a 22.22 (28.09) a, b 8.50 (8.22) b 3.82*

Post-SUDS 30.39 (24.70) a 10.28 (14.19) b 6.81 (9.12) b 10.70***

Note. *p < .05, **p < .01, ***p<.001

26

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