Psychological and electrophysiological indices of inattention in hoarding

Accepted Manuscript

Psychological and Electrophysiological Indices of Inattention in Hoarding Peter A. Baldwin , Thomas J. Whitford , Jessica R. Grisham PII: DOI: Reference:

S0165-1781(18)31006-0 https://doi.org/10.1016/j.psychres.2018.11.009 PSY 11865

To appear in:

Psychiatry Research

Received date: Revised date: Accepted date:

1 June 2018 3 October 2018 5 November 2018

Please cite this article as: Peter A. Baldwin , Thomas J. Whitford , Jessica R. Grisham , Psychological and Electrophysiological Indices of Inattention in Hoarding, Psychiatry Research (2018), doi: https://doi.org/10.1016/j.psychres.2018.11.009

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ACCEPTED MANUSCRIPT Highlights

Hoarding individuals report elevated attention-deficit/hyperactivity symptoms.

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Attentional symptoms most related to hoarding severity.

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Neural marker of inattention not abnormal in hoarding individuals.

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ACCEPTED MANUSCRIPT Psychological and Electrophysiological Indices of Inattention in Hoarding

Peter A. Baldwin1 Thomas J. Whitford1

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Jessica R. Grisham1

School of Psychology, UNSW Sydney.

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Correspondence regarding this article should be directed to Peter A. Baldwin. Postal address: School of Psychology, UNSW Sydney, NSW 2052, Australia. Email:

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[email protected].

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Abstract Individuals with elevated hoarding symptoms report elevated symptoms of ADHD and these symptoms are related to impaired daily functioning. Neuropsychological studies have found specific deficits in attention, and a recent review of attentional data from numerous hoarding studies concluded that inattention likely represents an etiological factor in

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hoarding, rather than a comorbidity. Our study aimed to examine which symptoms of ADHD, inattention or hyperactivity, are related to hoarding symptom severity, and whether

individuals with hoarding symptoms display a neurophysiological marker of poor attention (Theta/Beta Ratio; THBR) that might explain these associations. The THBR indexes theta

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power relative to beta power in the frontal cortex and is often atypical in individuals with ADHD. We hypothesised that individuals would report more severe problems with inattention and would exhibit an elevated theta/beta ratio relative to a healthy control group.

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We also predicted that any relationship between hoarding and inattention would be independent of anxiety and depression symptoms. 17 hoarding-symptomatic participants and

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16 healthy control participants completed self-report measures relating to ADHD, hoarding

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and general psychopathology, and then underwent resting measures of electroencephalography (EEG). Individuals with hoarding symptoms reported greater

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difficulties with inattention and hyperactivity, however they did not exhibit an elevated theta/beta ratio. When taking into account recent anxiety and depression, only inattention

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predicted hoarding symptom severity. Further investigations may help clarify this association and help inform attention-based treatments for hoarding. Key Words

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Hoarding

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ADHD

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Attention

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EEG

Declarations

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Declarations of interest: none

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Psychological and Physiological Indices of Inattention in Hoarding For people who experience hoarding difficulties, everyday decisions about acquiring, storing and discarding possessions cause substantial distress. (Frost et al., 2011; Grisham et al., 2007; Hall et al., 2012; Mackin et al., 2015). The impact of hoarding is wide-ranging and severe. Prevalence estimates of clinically significant hoarding range from 1.5 – 5%

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depending on how hoarding is measured (Bulli et al., 2013; Iervolino et al., 2009; Mueller et al., 2009; Timpano et al., 2011) and difficulty discarding possessions is associated with

severe psychosocial dysfunction (Rodriguez et al., 2013b; Samuels et al., 2008; Tolin et al., 2008).

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People who hoard often face complex health and safety concerns. Dwellings can

buckle under the weight of accumulation, resulting in potentially life-threatening health, structural and fire hazards (Frost et al., 2000). Beyond the consequences of clutter, hoarding

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is associated with low socioeconomic status, severe work impairment (Frost and Gross, 1993; Samuels et al., 2007), high levels of psychiatric comorbidity (Frost et al., 2011; Hall et al.,

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2012) and cognitive deficits that can further complicate decision-making about belongings

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(Grisham et al., 2007; 2010; Tolin et al., 2011). Across recent hoarding studies, evidence has emerged that people who hoard

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experience difficulties with attention (e.g., Frost et al., 2011; Grisham et al., 2007; Hall et al., 2012; Mackin et al., 2015). Attention-deficit hyperactivity disorder (ADHD) comorbidity

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appears in 28-32% of individuals with clinically significant hoarding (Frost et al., 2011; Hartl et al., 2005) and is associated with greater difficulties in daily living, higher levels of stress and increased domestic squalor (Hall et al., 2012). Neuropsychological studies have found specific deficits in attention, along with related impairments in executive functioning (Blom et al., 2011; Grisham et al., 2007; Luchian et al., 2007; Mackin et al., 2010; Tolin et al., 2011; Wincze et al., 2007). fMRI data suggest that individuals with hoarding difficulties display

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atypical function of the precentral gyrus (Tolin et al., 2012a; 2012b), a pattern also observed in some ADHD cohorts (Ding et al., 2014; Ernst et al., 2003). Taken together, these studies suggest that impaired attention may exacerbate hoarding symptoms. Inattention in some individuals with hoarding difficulties may be accounted for by ADHD comorbidity, however the weight of evidence suggests that the two disorders share

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etiological similarities. Individuals with childhood ADHD appear more likely to develop hoarding symptoms that those without (Fullana et al, 2009), suggesting a predictive

relationship between inattention and hoarding. Additionally, data suggest that inattention in individuals with hoarding difficulties is present in childhood (Hartl et al., 2005) and predicts

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hoarding across adulthood, unlike hyperactivity/impulsivity symptoms (Hacker et al., 2012). These findings suggest that problems with attention in individuals with hoarding difficulties likely precede difficulties with discarding or acquiring.

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Lynch and colleagues (2015) conducted a systematic review of the literature on executive function in individuals with hoarding difficulties to clarify why ADHD and

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hoarding appear to be linked. The authors ruled out methodological explanations and

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concluded that the two disorders likely shared neurophysiological and neuropsychological vulnerabilities, such as similar patterns of frontal lobe dysfunction. This proposition is

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supported by observations from Frost and colleagues (2011) and Tolin and Villavicencio (2011) that while a significant number of individuals with hoarding difficulties report

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impaired attention, relatively few meet criteria for hyperactivity-related ADHD. Indeed, despite consistent evidence linking inattention and hoarding, evidence for impulsivity or hyperactivity on standardised laboratory tasks is mixed (Grisham et al., 2007; Hacker et al., 2012; Rasmussen et al., 2013). Neuropsychological data suggest that specific components of attention are impaired in individuals with hoarding difficulties (Grisham et al., 2007; Mackin et al., 2015; Tolin et al.,

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2011). Two earlier studies found that some people who hoard show deficits on tests of sustained attention (Grisham et al., 2007; Tolin et al., 2011), such as the Conner’s Continuous Performance Test (CCPT; Conners, 2014). Poor discrimination of target stimuli from distractors on the CCPT by individuals with hoarding difficulties (Mackin et al., 2015) could reflect emerging evidence of abnormal anterior cingulate (ACC) function in this cohort, given

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the role of the ACC in error vigilance (Baldwin et al., 2016; Mathews et al., 2015).

Inattention may also explain the observed executive deficits in hoarding cohorts. One study found that individuals with hoarding difficulties displayed poor probabilistic decision-making on the Iowa Gambling Task (Bechara, Damásio, Damásio and Anderson, 1994) relative to

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healthy individuals (Lawrence et al., 2006), although others have failed to replicate this finding (Blom et al., 2011; Grisham et al., 2007; Tolin et al., 2011). More consistently,

studies have found that hoarding-symptomatic individuals struggle with categorising objects,

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tending toward an under-inclusive categorisation style (Grisham et al., 2007; Luchian et al., 2007; Wincze et al., 2007), with categorisation deficits most prominent when using visual

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information (Mackin et al., 2015). Notably, these categorisation processes rely on focused

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and sustained attention (Sarter et al., 2001). Emerging evidence suggests that directly targeting inattention may augment hoarding

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treatment. Early data suggest that hoarding symptoms respond to Methylphenidate – a staple in pharmacological ADHD treatment – although the side-effect profile may be poor tolerated

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(Rodriguez et al., 2013a). Cognitive behaviour therapy (CBT) for hoarding yields large reductions in difficulty discarding but does not address all hoarding symptoms equally (Tolin et al., 2015). A new approach to treating hoarding is combining CBT with cognitive remediation techniques like those used with individuals with neurological disease or injury. Early trials of this approach suggest that cognitive remediation for can enhance CBT for hoarding and directly address neuropsychological difficulties, with notable gains in

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attentional symptoms (Ayers et al., 2014; DiMauro et al., 2014a). These studies add impetus to continued research into the role of inattention in individuals with hoarding difficulties. The neurophysiological bases of hoarding behaviour increasingly inform our understanding of hoarding as a disorder (Grisham and Baldwin, 2015), however hoarding research is yet to examine neural markers of inattention similar to those examined in ADHD

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research. For example, EEG studies of children with ADHD reliably find elevated

frontocentral theta band power (4-6Hz) and lower beta band power (13-21Hz), leading to the development of the Theta/Beta Ratio (THBR) as prognostic indicator of inattention in

children with ADHD (Arns et al., 2013; Barry et al., 2009; 2003; Loo et al., 2013). The

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THBR appears to also be elevated in some adults with ADHD and associated with inattention (Bresnahan et al., 1999; Clarke et al., 2011), although in a recent adult ADHD sample (Loo et al., 2013) adults demonstrated a lowered THBR. Interestingly, Loo et al. (2013) found that

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the presence of depression mediated and moderated the presentation of THBR in their adult sample and proposed that comorbidity may affect THBR expression. The sensitivity of the

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THBR to depression speaks to the importance of considering psychiatric comorbidity in any

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investigation of inattention.

In sum, the research to date strongly suggests that inattention in hoarding warrants

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further investigation. Given that inattention often accompanies more severe impairment in individuals with hoarding difficulties (Frost et al., 2011; Hall et al., 2012), and may underpin

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some of the cognitive deficits that maintain disorganisation in hoarding (Grisham et al., 2007; Luchian et al., 2007; Mackin et al., 2015; Wincze et al., 2007), understanding inattention in hoarding could expand both theory and treatment. There is little research comparing inattention in individuals with hoarding difficulties with healthy individuals, and no previous studies have examined neural markers of inattention in hoarding a cohort. Therefore, the aim of this study was to compare individuals with clinically significant hoarding to a group of

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age-matched healthy individuals with respect to both self-reported ADHD symptoms and a physiological indicator of inattention. Given the reliable data implicating inattentive symptoms in hoarding, but the inconsistent findings regarding hyperactivity and impulsivity, our first hypothesis was that a group of individuals with hoarding difficulties would report higher inattention symptoms on

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an adult ADHD measure than a healthy comparison group but would not report higher

hyperactive or impulsive symptoms. As most previous research suggests that an elevated THBR may be a marker of inattention in adults, our second hypothesis was that individuals with hoarding difficulties would exhibit a higher THBR relative to healthy individuals. We

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also predicted that any relationship between hoarding and inattention would be independent of recent symptoms of depression and anxiety.

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Method

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Sample

Participants with clinically significant hoarding difficulties were recruited via

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community advertising. Eligibility for inclusion in the hoarding group required the likely presence of hoarding disorder (HD) as indicated by the Hoarding Rating Scale Interview

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(Tolin et al., 2010), along with an absence of brain injury, neurological disease or recent

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psychosis. Of the 58 individuals who responded to the advertising, 27 met our eligibility criteria. Of these 27, two participants were excluded because they expressed current suicidality during their clinical interview. Eight participants were excluded for failure to follow instructions during psychophysiological recording, resulting in compromised data. The final hoarding group contained 17 participants (8 females). Of this group, 11 participants identified as Caucasian Australian, and 6 participants identified as Asian or Subcontinental. With respect to education, 12 participants reported university undergraduate qualifications, 4

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participants reported qualifications from vocational or technical colleges, and 1 participant reported no tertiary education. Participants for the healthy comparison group were recruited via community advertising and were excluded if they reported a history of brain injury, stroke, neurological disease, or current problems with mood, anxiety or hoarding. Of the 26 individuals who

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responded, 19 were eligible to participate. Participants were excused if they reported current problems with mood or anxiety during the diagnostic interview (n=2). In addition, 1

participant was excluded for failure to follow instructions during psychophysiological

recording, resulting in compromised data. The final healthy group contained 8 females and 8

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males. Of this group, 8 participants identified as Caucasian Australian, and 8 participants identified as Asian or Subcontinental. With respect to education, 3 participants reported postgraduate qualifications, 7 participants reported undergraduate qualifications, 4

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participants reported qualifications from vocational or technical colleges, and 2 participants

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Self-Report Measures

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reported no tertiary education. Descriptive statistics for both groups are presented in Table 1.

Saving Inventory-Revised (SI-R). The SI-R is a 23-item self-report measure of

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hoarding behaviour that yields three subscales that measure excessive acquisition, difficulty discarding and clutter. The SI-R has repeatedly demonstrated excellent internal consistency,

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construct validity and test-retest reliability (Frost et al., 2004). In the present sample, the internal consistency was high ( = .97). Saving Cognition Inventory (SCI). The SCI (Steketee et al., 2003) is a 24-item self-

report measure of the beliefs individuals hold about their possessions in terms of emotional comfort, memory, control of possessions, and responsibility for possessions. The SCI has

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previously demonstrated high internal consistency (Steketee et al., 2003). In the present sample, the internal consistency for the SCI was high ( = .97). Hoarding Rating Scale – Interview (HRS-I). The HRS-I (Tolin et al., 2010) is a 5item structured interview that measures the severity of hoarding difficulties across 5 domains that mirror the DSM-5 (American Psychiatric Association, 2013) criteria for HD. The HRS

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yields a total score and a score profile used to determine if the reported hoarding difficulties reflect HD. The HRS shows high internal consistency and predictive validity with more detailed hoarding measures (Tolin et al., 2018). In the present sample, the internal

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consistency for the HRS-I was high ( = .87).

Mini International Neuropsychiatric Interview Version 6 (MINI-6). The MINI-6 is a diagnostic interview that assesses the extent to which an individual meets DSM-IV TR criteria for major depressive disorder, bipolar disorder, panic disorder, generalised anxiety

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disorder, social anxiety, obsessive-compulsive disorder, psychosis, suicidality, and anti-social personality disorder (Sheehan et al., 1998). The MINI-6 has been validated against longer

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and more established diagnostic interviews (e.g. Structured Clinical Interview for DSM-IV

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TR; First et al., 2002) and demonstrates excellent convergent validity with such measures. Adult ADHD Self-Report Scale Version 1.1 (ASRS). The ASRS (Kessler et al.,

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2005) is an 18-item self-report measure of the severity with which an individual has experienced each of the 18 DSM-IV TR criteria for ADHD over the previous 6 months. The

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ASRS provides a weighted scoring algorithm to determine which of an individual's symptoms are clinically severe, and of those, which best predict an ADHD diagnosis. As each question maps onto a DSM criterion, a score for inattention, impulsivity and hyperactivity can be computed from the relevant scale items. The ASRS has been validated against the World Mental Health Composite International Diagnostic Interview for ADHD

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and demonstrates sound predictive validity (Kessler et al., 2005). In the present sample, internal consistency was high ( = .87). Depression Anxiety Stress Scales (DASS-21). The DASS-21 (Lovibond and S. H. Lovibond, 1995) is a 21-item self-report measure of psychological distress experienced in the past week, rated across three dimensions: depression, anxiety and stress. The DASS-21 has

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demonstrated excellent internal consistency across previous samples (=.91-.96; Brown et al., 1997; Nieuwenhuijsen et al., 2003), and yields a total score of general distress and three subscales that measure depression, anxiety or stress. In the present sample, internal

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consistency was high ( = .89).

Electrophysiological Measures and Data Reduction

EEG data were collected using a BioSemi ActiView system (Biosemi, 2012) and analysed using Brain Vision Analyzer v2.0 (Brain Products GmBH, 2012). Data for two

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studies were collected within each participant session, therefore we used a 64- channel

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electrode cap with Ag/Ag-Cl electrodes referenced to internal sensors in the parietal lobe (CMS/DRL) to maximise the available data for both studies. During pre-processing, data

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were referenced offline to the average of mastoid electrodes. Electrodes were positioned per

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the 10-20 system, and a sampling rate of 2048 Hz was used. Electrodes at the outer canthi of both eyes and over the left orbicular oculi muscle measured eye blink and movement (vertical

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and horizontal electrooculogram). Data were band-pass filtered at 0.05 – 30 Hz with a phase-shift free Butterworth filter

to attenuate high and low frequency noise. EEG was corrected for blink and eye movement using the regression-based algorithm developed by (Gratton et al., 1983). Data were then segmented into eyes-open and eyes-closed 5-minute epochs, based on markers inserted during data acquisition. Filtered and corrected epochs were then Fourier-transformed using a Hamming window covering the full 5-minute epoch to segment the data into frequency

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bands. Absolute power (V2/Hz) in both the theta (3.5 Hz–7.5 Hz) and beta (12.5 Hz–25 Hz) frequency bands was computed at Cz per previous THBR studies (e.g. Loo et al., 2013) for each epoch, and the THBR was calculated as the ratio of theta power to beta power.

Procedure

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Participants completed questionnaires, then undertook a structured diagnostic

interview using the MINI-6 with the first author. Next, participants were set up on the

psychophysiological equipment and two resting EEG epochs were recorded: a 5-minute

epoch with participant’s eyes open, and a 5-minute epoch with participant’s eyes closed.

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Finally, participants received a verbal debrief and monetary compensation.

Data Analyses

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All analyses were conducted in SPSS v21 (IBM, 2012). Between-group differences were assessed using multivariate analysis of variance (MANOVA). Linear relationships

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between ADHD symptoms and hoarding symptoms were assessed using hierarchical multiple regression. Normality was confirmed using the z-score procedure outlined by Field (2009)

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and homogeneity of variance was confirmed using Levene’s (1960) test. The absence of

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multicollinearity was confirmed by inspecting the variance proportions of each eigenvalue in the full model to establish that no two variables demonstrated high loadings on any single

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eigenvalue.

Results

Sample Characteristics Within our hoarding group, ten participants met DSM-IV TR (APA, 2000) criteria for lifetime major depressive disorder, six participants met DSM-IV TR criteria for lifetime

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panic disorder, and four participants met DSM-IV TR criteria for social anxiety. Three participants reported current selective serotonin re-uptake inhibitor (SSRI) pharmacotherapy and one participant reported current tricyclic pharmacotherapy. To ensure the groups were matched for age and differed as expected on psychological measures of hoarding, depression and anxiety, we conducted a MANOVA comparing groups

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on age, SIR, SCI and DASS depression and anxiety scores. Relative to the healthy group, the hoarding group reported clinically significant hoarding symptoms, well above theclinical cutoff score of 41 for the SI-R total, which has been used to distinguish between hoarding and non-hoarding populations for both research (Novara, Bottesi, Dorz, and Sanavio, 2016) and

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clinical purposes (Steketee and Frost, 2014). Hoarding cognitions were within established clinical ranges (Steketee, Frost, and Kyrios, 2003) and psychological distress was in the Severe range (Lovibond and Lovibond, 1995). Descriptive and MANOVA statistics are

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presented in Table 1.

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Table 1 Descriptive and MANOVA Statistics Comparing Group Means for Age and Psychological Variables Mean (SD)

F

p

2

Control

Age

47.8 (13.1)

49.6 (9.8)

.186

.669

.006

SIR-Total

49.4 (14.1)

17.2 (12.2)

49.199

.000*

.613

SCI-Total

129.6 (43.2)

74.6 (29.4)

17.984

.000*

.367

DASS-D

11.8 (13.7)

4.6 (5.3)

3.793

.061

.109

DASS-A

9.8 (10.6)

2.3 (3.2)

7.614

.009*

.197

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Hoarding

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Note. DASS-A = Depression Anxiety Stress Scales Anxiety Symptoms; DASS-D = Depression Anxiety Stress Scales Depression Symptoms; SCI = Saving Cognitions Inventory; SIR = Saving Inventory Revised. * indicates significant at p<0.01

Between-Group Analyses

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Self-reported ADHD symptoms. To test the hypothesis that the hoarding group

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would report more severe inattention but not hyperactivity or impulsivity symptoms than the control group, we conducted a MANOVA comparing ASRS inattention, hyperactivity and

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impulsivity scores between groups. As predicted, the hoarding group reported more severe inattention symptoms, however they also reported more severe hyperactivity symptoms.

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Groups did not differ with respect to impulsivity symptoms.

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The ASRS segments scale items into those most predictive of an ADHD diagnosis (Part A), and those less predictive of diagnosis but relevant to clinical presentation (Part B). To determine if the hoarding group endorsed a greater number of symptoms predictive of ADHD that the control group, we conducted a MANOVA comparing scores on ASRS Part A and Part B across groups. Individuals in the hoarding group endorsed a greater number of both Part A and Part B symptoms than control individuals. Part A symptoms were below

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levels associated with ADHD diagnosis, however Part B symptoms were within diagnostic range (14-24; Kessler et al., 2007). Theta-Beta ratio. To test the hypothesis that individuals in the hoarding group would exhibit a lowered THBR relative to healthy individuals, we conducted a MANOVA to compare THBR across groups under both eyes-open and eyes-closed conditions. Both groups

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showed a mean THBR within the range typically found in healthy individuals (M = 3.86, SD = 2.27; Arns, Conners, and Kraemer, 2013). Counter to prediction, the observed betweengroup differences in THBR were not significant. Descriptive and parametric statistics for all

Table 2

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three MANOVAs are presented in Table 2.

MANOVA Statistics Comparing Group Means on ASRS and THBR Mean (SD)

2

F

p

21.131

.000*

.413

Control

ASRS-Att

18.75 (5.12)

12.06 (2.77)

ASRS-Hyp

9.94 (3.94)

6.56 (2.75)

7.881

.009*

.208

ASRS-Imp

4.75 (2.74)

3.56 (2.52)

1.620

.213

.051

ASRS-Part A

12.00 (4.17)

6.25 (2.11)

21.33

.000*

.408

20.75 (8.68)

13.56 (3.54)

9.511

.004*

.235

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ASRS-Part B

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Hoarding

2.65 (.40)

3.15 (.48)

.471

.493

.011

THBR-EC

2.25 (.71)

2.32 (.68)

.112

.741

.001

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THBR-EO

Note. ASRS-IA = Adult ADHD Self Report Scale Inattention Symptoms; ASRS-HY = Adult ADHD Self Report Scale Hyperactivity Symptoms; ASRS-IM = Adult ADHD Self Report Scale Impulsivity Symptoms; ASRS-Part A = ASRS Part A Total Score; ASRS-Part B = ASRS Part B Total Score; THBR-EO = Theta/Beta Ratio Eyes Open; THBR-EC = Theta/Beta Ratio Eyes Closed. * indicates significant at p<0.01

Regression Analyses Although groups differed on both inattention and hyperactivity symptoms, this may have been confounded by the presence of anxiety and depression symptoms. Our quasi-

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experimental design precluded the use of ANCOVA to remove the influence that other psychiatric symptoms may have on between-group differences in ADHD symptoms (Miller and Chapman, 2001). Therefore, to test the hypothesis that any relationship between hoarding and inattention would be independent of problems with anxiety or mood, we computed a hierarchical regression model predicting hoarding symptoms from ADHD symptoms while

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holding constant recent anxiety and depression symptoms across the full sample. In the first step of the model, we entered DASS-depression and DASS-anxiety scores. Next, we entered each of the ASRS subscale scores as simultaneous predictors of SIR-total scores. Holding constant recent anxiety and depression symptoms, only inattention symptoms remained a

Table 3

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significant predictor of hoarding symptoms (see Table 3).

Hierarchical Regression Predicting Hoarding Symptoms from ADHD Symptoms

t

p

R2

R2 change

.306

1.043

.306

.253

-

.218

.745

.462

.275

1.019

.318

.459

.206*

DASS-A

-.235

-.780

.443

ASRS-IA

.462

2.234

.034*

ASRS-HY

.327

1.170

.253

ASRS-IM

-.135

-.661

.514

Step 1

DASS-D DASS-A

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DASS-D

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Step 2

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

Note. Dependent variable = Saving Inventory Revised Total Score. ASRS-IA = Adult ADHD Self Report Scale Inattention Symptoms; ASRS-HY = Adult ADHD Self Report Scale Hyperactivity Symptoms; ASRS-IM = Adult ADHD Self Report Scale Impulsivity Symptoms; DASS-A = Depression Anxiety Stress Scales Anxiety Symptoms; DASS-D = Depression Anxiety Stress Scales Depression Symptoms;  = standardised regression coefficient. * significant at p<.05

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Discussion Our study aimed to compare the types of ADHD symptoms endorsed by individuals with clinically significant hoarding difficulties relative to healthy individuals, and to investigate if individuals with hoarding difficulties exhibit a neurophysiological marker of inattention. Previous literature suggests that hoarding and ADHD consistently share deficits

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in attention but not hyperactivity or impulsivity, therefore we predicted that individuals with hoarding difficulties would report more severe inattention symptoms that healthy individuals, but not more severe symptoms of hyperactivity or impulsivity. We also predicted that

individuals with hoarding difficulties would exhibit a higher theta-beta ratio (THBR) than

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healthy individuals, given the evidence linking elevated THBR with attentional deficits. Taking into consideration the potential for other psychiatric symptoms to explain the

relationship between hoarding and inattention, we predicted that the relationship between

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hoarding and inattention symptoms would be independent of recent anxiety and depression. Our prediction regarding between-group differences in ADHD symptoms was

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partially supported. The hoarding group reported elevated inattention and hyperactivity

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symptoms relative to the control group, however there were no between-group differences in symptoms of impulsivity. The prediction regarding hoarding individuals exhibiting a

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neuropsychological indicator of inattention was not supported. The hoarding group did not differ from the healthy group in THBR. Our hypothesis regarding the relationship between

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hoarding and inattention symptoms independent of more general problems with anxiety and mood was supported. When recent anxiety and depression were held constant, only inattention predicted hoarding symptom severity. This suggests that the symptom differences observed between our groups may have been confounded by the presence of comorbid factors such as elevated anxiety or mood disturbance.

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These findings add to previous observations that individuals who hoard experience difficulties with inattention, and it seems increasingly unlikely that this reflects ADHD comorbidity. Though our hoarding group reported elevated symptoms of inattention and hyperactivity, only two group members reported a symptom profile consistent with an ADHD diagnosis. This parallels previous hoarding samples in which researchers found moderate to

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severe levels of inattentive symptoms, but a relative absence of other aspects of ADHD (Frost et al., 2011; Tolin and Villavicencio, 2011). Additionally, when recent anxiety and

depression were taken into account in our analyses, inattention predicted hoarding symptom severity whereas hyperactivity did not. This echoes previous findings (Tolin and

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Villavicencio, 2011) and further suggests that key features of ADHD, such as hyperactivity, are not consistently related to hoarding symptoms independent of other comorbidities. Given the apparent influence of comorbidity in our sample, one potential explanation

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for absence of the hypothesised effect of the THBR may be the range and severity of depression symptoms reported by our sample. Though the between-group differences did not

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reach significance, the means suggested a trend for a THBR attenuation in our hoarding

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group. There is evidence that the THBR in ADHD adults may be attenuated in the presence of comorbid depression (Loo et al., 2013). On average, our hoarding participants reported

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severe depression symptoms, however there was substantial variation within the group. Additionally, depression symptoms were not a unique predictor of hoarding symptom

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severity. While depression is a common comorbidity in hoarding (Frost et al., 2011; Hall et al., 2012), individuals with hoarding difficulties demonstrate only mild to moderate depressive symptoms in some clinical samples (Grisham et al., 2005), and some epidemiological data suggest that the proportion of individuals reporting difficulty discarding who suffer from depressive illness is relatively low (18.27%; (Rodriguez et al., 2013b).

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Therefore, it is possible that heterogeneity of depression within our hoarding sample may have diluted the depressive symptomatology most associated with THBR attenuation. Though the role of different aspects of depression in THBR attenuation is unclear (Loo et al., 2013), specific depressive presentations can weaken other neurophysiological processes that also appear to be attenuated hoarding (Baldwin et al., 2016; Mathews et al., 2015; Weinberg

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et al., 2015). The size of our sample precluded follow-up analyses to compare individuals with high and low depression, which may be an important consideration for future studies. A more detailed understanding of inattention in hoarding could improve the effects of treatment, particularly the latest approaches combining CBT with cognitive training. Early

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evidence suggests that individuals with hoarding difficulties can benefit from cognitive remediation therapies, and that attentional symptoms respond particularly well to these

treatment approaches (Ayers et al., 2014; DiMauro, Genova, Tolin, and Kurtz, 2014). Though

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cognitive remediation appears to have generalised effects on selective attention in individuals with hoarding difficulties (DiMauro et al., 2014b), neuropsychological data more strongly

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suggest deficits in sustained attention (Grisham et al., 2007; Mackin et al., 2015; Tolin et al.,

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2011). As such, it is unclear by what mechanism cognitive remediation might improve hoarding symptoms, and what the optimal targets of such therapies might be.

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Continued research into the neurocognitive underpinnings of inattention in hoarding may clarify such mechanisms. For example, dysfunction in the precentral gyrus during

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decision-making has been observed in both ADHD and individuals with hoarding difficulties, and is thought to impair focused attention by hindering environmental filtering (Ernst et al., 2003; Grisham and Baldwin, 2015). If future research can clarify this mechanism in HD, this might recommend that remedial treatments focus on boosting selective attention and facilitate attentional selection when making decisions about possessions.

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Clarifying the neural basis of inattention in hoarding may also help guide pharmacological treatments for HD. Both ADHD and hoarding are associated with anterior cingulate abnormalities during decision-making (Ernst et al., 2003; Grisham and Baldwin, 2015). Anterior cingulate dysfunction appears to impede the efficacy of some selective serotonin reuptake inhibitors (Mayberg et al., 1997; Pizzagalli et al., 2001), which may

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explain the differing rates of improvement in response to SSRI treatment across hoarding samples (Brakoulias et al., 2015). Serotonin-noradrenaline re-uptake inhibitor (SNRI) therapies shown effective for attentional symptoms in adults with ADHD (Findling,

Schwartz, Flannery, and Manos, 1996; Hedges, Reimherr, Rogers, Strong, and Wender,

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1995) also appear to produce substantial clinical improvements in individuals with hoarding difficulties (Saxena, 2011; Saxena and Sumner, 2014). A trial of the gold-standard pharmacological intervention for ADHD, Methylphenidate (Ritalin), in individuals with

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hoarding difficulties produced some promising clinical effects but was poorly tolerated (Rodriguez et al., 2013a). Both ADHD and hoarding appear to benefit from noradrenergic

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augmentation but it is unclear if the symptomatic relief observed in hoarding relates to

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normalisation of putative neural causes of inattention, as they appear to do in ADHD (Rubia et al., 2014); Swanson, Baler, and Volkow, 2011). By understanding the neural basis of

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inattention in hoarding we may better identify pharmacological agents that more effectively normalise impaired neural processes.

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The results of our study should be interpreted in the light of some limitations.

Resource demands, attrition and the availability of suitable participants ultimately limited our sample size. As such, our analyses were relatively underpowered and should be replicated in larger clinical samples before firmer conclusions are drawn. The ASRS is a well-established measure of ADHD symptoms, however its intended use as a diagnostic screening instrument limited the content validity of our investigation of inattention. Future studies should seek

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broader measures of inattention, such as standardised behavioural tasks. Despite all participants meeting criteria for HD on the HRS-I, the severity of hoarding symptoms reported by our hoarding group was lower than that of other samples (Tolin et al., 2015; Williams and Viscusi, 2016). This may reflect slightly lower hoarding-related distress in a non-treatment-seeking cohort;, however replication of the present results in other hoarding

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samples is important to strengthen inferences about inattention in hoarding. Participants’ level of fatigue and qualitative experience of participation was not assessed. As alertness may impact electrophysiological measures, future studies should incorporate such assessments. . Finally, as discussed, our sample size precluded any post-hoc examinations of how

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the type and severity of depressive symptoms might explain the observed results, and the quasi-experimental design prevented the use of ANCOVA. Future studies might address this limitation by supplementing future comparison groups with individuals who report sub-

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clinical depression, similar to the method employed by Miller, Chapman, Chapman, and Kwapil (1993). In this way, any attentional impairments exhibited by individuals with

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hoarding difficulties could reliably be inferred to be different from those observed in

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individuals with elevated depressive symptomatology. Despite these limitations, the current study advances our understanding of the overlap

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between ADHD and hoarding and presents many new avenues of enquiry. It appears increasingly likely that the relationship between these psychiatric syndromes reflects shared

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attentional impairments, which speaks more to aetiology than true comorbidity. Though our data failed to identify any neurophysiological basis for this overlap, many questions remain unanswered. By clarifying the neurophysiological underpinnings of attentional deficits in hoarding we may enhance emerging cognitive remediation therapies and refine pharmacotherapy protocols for hoarding. Considering the severe impact that hoarding has at

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individual, familial and societal levels, increasing our understanding of why people hoard is a

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crucial factor in lifting the burden of HD.

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Funding This research did not receive any specific grant from funding agencies in the public,

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commercial, or not-for-profit sectors.

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