Abstract
In hoarding disorder, features including attentional difficulties and emotion dysregulation can contribute to the core symptoms of clutter, difficulties discarding, and excessive acquisition. Boredom is a negative feeling state that shares a high level of overlap with associated features of hoarding, including inattention, depressive symptoms, and impulsivity, and has been implicated in compulsive buying behaviors. Boredom may be a particularly relevant factor in compulsive hoarding; however, this relationship remains significantly under-researched. The present studies aimed to thoroughly investigate associations between boredom and hoarding severity using diverse methodologies. Study 1 (N = 253) replicated, in an online community sample, previously reported positive associations between hoarding severity and recent state boredom while statistically controlling for potentially confounding variables (e.g., depression, indecisiveness), and extended these findings to include boredom proneness. In Study 2, individuals with elevated hoarding symptoms (n = 56) and a history of hoarding problems (n = 43) reported higher levels of recent state and trait boredom than controls (n = 61). Additionally, boredom was associated with performance on simulated acquiring and discarding tasks. Finally, Studies 3a (N = 144) and 3b (N = 146) attempted the first experimental tests of induced boredom on acquiring and discarding behaviors. Although results were mixed and preclude causal conclusions, exploratory analyses revealed that individuals reporting higher in-the-moment boredom took more (p = .008) and discarded fewer (p = .021) items on the simulated tasks. Overall, results suggest that boredom may have crucial implications in hoarding symptom severity.
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1 Introduction
Described as an “experience of being disengaged and stuck in an endless dissatisfying present” [1] (p. 484), boredom can be defined as both a stable, trait-like individual difference (boredom proneness [2]) and as an affective state (state boredom [3]). The subjective experience of boredom, or state boredom, can result from an uninteresting environment and is thought to be situation-dependent [3]. Conversely, certain individuals have a particularly high propensity towards experiencing boredom. This characteristic is defined as boredom proneness, trait boredom [2, 4], or 'situation-independent' boredom [3]. Individuals with a predisposition towards the experience of boredom may fail to effectively use covert coping mechanisms (such as daydreaming), which help to manage the monotony faced in everyday life (e.g., waiting in line at the grocery store [3]).
Both boredom proneness and state boredom are implicated in numerous forms of psychopathology [3]. These include depressive symptoms [5, 6] addictions [7], and eating disorders [8, 9]. Notably, studies have found relationships between boredom and obsessive–compulsive spectrum disorders. For instance, past research has demonstrated a positive relationship between boredom proneness and obsessive–compulsive disorder symptoms [10]. Individuals with trichotillomania have reported decreases in boredom following hair pulling [11], and a study examining individuals with pathological skin picking demonstrated that 86% identified boredom as a trigger for skin picking behavior [12]. However, the potential role of boredom in hoarding pathology has been largely ignored, despite a significant overlap in associated features. These overlaps will be described below using a cognitive behavioral framework. For a conceptual model of the ways boredom may be related to hoarding symptoms, please see Fig. 1.
Conceptual links between boredom and hoarding symptoms
According to cognitive behavioral models of hoarding disorder (HD), maladaptive emotional responses and behavioral patterns are key contributors to difficulties discarding [13,14,15] and excessive acquisition [13]. Individuals with HD may engage in acquiring behaviors to manage negative emotional states, including boredom. Indeed, studies have demonstrated that individuals with HD report lower levels of emotion regulation [16], distress tolerance, and greater fear and intolerance of negative emotional states [17]. In addition, both boredom [18, 19] and hoarding (e.g., [20]) have been linked to increased impulsivity, a factor that may contribute to greater difficulties with acquisition. Previous studies show links between boredom and excessive acquisition in compulsive buying-shopping disorder (CBSD) [21,22,23,24,25], a presentation that shares a high degree of overlap with HD [26,27,28]. Boredom is frequently endorsed as a trigger for buying [29], and individuals report that they often experience boredom before deciding to shop [30]. Thus, boredom may act to negatively reinforce excessive acquisition in hoarding pathology, similar to what has been observed in CBSD.
Relatedly, cognitive behavioral models implicate information processing deficits in hoarding pathology and suggest that these deficits contribute to the core symptoms of excessive clutter and difficulties discarding [13, 14]. Specifically, problems have been observed in attention (e.g., [31,32,33]) and executive functioning (e.g., [34, 35]). Similarly, boredom is consistently associated with failures in attention and attentional difficulties; evidence for this relationship has been obtained across numerous studies (e.g., [1, 36,37,38,39]; see [1] for a review). For instance, boredom proneness is predictive of adult ADHD symptoms [39], and individuals who are high in trait boredom report difficulties in sustained attention [37]. Moreover, boredom proneness uniquely predicts problems with sustained attention [36]. Finally, both boredom proneness [38] and state boredom [40] have been associated with worse performance on vigilance tasks, which require a high degree of sustained attention. Additionally, research has demonstrated that boredom proneness predicts cognitive dysfunction in older adults [41], and boredom proneness is associated with a lower need for cognition in general (i.e., lower tendencies to engage in or enjoy effortful cognitive activities) [42]. Thus, frequent experiences of boredom may exacerbate existing attentional problems and difficulties with executive functioning in individuals with HD.
Relevant to attention and executive functioning, depressive symptoms are among the most common comorbidities in HD (e.g., [43]). Some studies estimate that approximately 50% of individuals with compulsive hoarding meet criteria for major depressive disorder [44, 45]. Prolonged exposures to boredom may increase the individual’s risk of developing depressive symptoms, as studies have consistently demonstrated close relationships between high levels of depressive symptoms and both state and trait boredom (e.g., [2, 5, 6, 46, 47]).
Research has not yet directly explored the relationships between boredom, difficulties discarding, and clutter. Moreover, as HD is complex condition, it is unlikely that these outcomes are solely the result of boredom experiences or boredom proneness. However, boredom may be a relevant factor that interacts with difficulties in attention, depressive symptoms, and other cognitive features, leading to increased distress around discarding, sorting, and organization, and contributing to greater avoidance of these activities. Prominent theories of boredom (e.g., [1, 48, 49]) state that boredom can result from a misalignment of attentional resources with the task at hand. Boredom can result from either a surplus of resources relative to the task demands (i.e., the task is too easy) or insufficient processing capacity relative to the demands of the task (i.e., the task is too complex). In both instances the prospect of engaging with the task is viewed as an unsatisfying investment of one’s cognitive resources. In HD, the task of sorting, and ultimately deciding which items to discard is experienced as an exceedingly difficult task [50].
In short, the experience is analogous to what often happens when an individual attempts to engage with a puzzle that they conclude is beyond their capacity to solve and have reached the point of diminishing returns (i.e., likely to receive back less than they are investing). They will begin to feel bored, attempt to disengage from the puzzle, and likely avoid similar tasks in the future. In this way, the boredom associated with discarding possessions may be a function of the inherent difficulty experienced when deciding which items to discard. Consequently, by not engaging with the task of discarding, the individual avoids both the distress that comes from the actual discarding, and the feelings of boredom that arise from the unsatisfying return on the cognitive resources that would be employed to make the difficult decision as to which items to discard.
It is possible that this strategy of avoidance helps to maintain the discarding symptoms and excessive clutter observed in HD. Consistent with this conjecture, several studies have reported positive relationships between hoarding severity, indecisiveness, and decisional procrastination [51], which may have significant implications for avoidance of discarding, sorting, and organizational tasks. Notably, chronic decisional procrastination has been associated with higher boredom proneness [52], suggesting that boredom may play a role in maintaining avoidance of discarding through links with indecision and procrastination.
In sum, higher rates of attentional difficulties, cognitive dysfunction, and depressive symptoms tend to exacerbate hoarding symptomology. Boredom may interact with predisposed tendencies to experience these problems or increase the severity of existing issues in these areas. An individual with HD who is highly depressed or struggles with attention and executive functioning may not feel capable of organizing, sorting, and discarding items. In this way, boredom may indirectly contribute to a higher volume of clutter and greater difficulties in discarding possessions.
In addition to symptom overlap, living conditions associated with HD may be highly conducive to experiences of boredom. As the individual’s living space becomes increasingly non-functional due to excessive clutter, the result may be an under-stimulating environment due to a loss of ability to engage in activities of daily living, leading to greater amounts of unoccupied time. Moreover, hoarding is frequently associated with social isolation, especially in older adults [43], as well as high levels of loneliness [53]. Research has shown links between boredom and loneliness [54, 55], including positive associations between state boredom and loneliness in a sample of treatment-seeking patients with HD [56]. The combination of a less functional environment, increased loneliness, and isolation could potentially set the stage for frequent, protracted experiences of boredom. In turn, these experiences may exacerbate hoarding symptoms. Consistent with this idea, recent research [56] has demonstrated that before treatment, hoarding symptom severity in older adults was associated with a host of psychological difficulties, including indecisiveness, high-levels of recent state boredom, self-control deficits, and marginally, with loneliness. Notably, only self-control (negatively) and recent state boredom severity (positively) remained associated with symptom severity following treatment. Thus, high levels of state boredom may be indicative of an attenuated response to treatment in individuals who hoard [56].
Significantly, boredom may have important implications for treatment outcomes and functioning for individuals with this chronic disorder. However, virtually no research on this association has been conducted aside from one study. As such, these findings need replication. Moreover, to our knowledge, no studies have explored the role of boredom proneness in hoarding symptoms. In the present studies, we aimed to replicate the associations described above between boredom and hoarding using self-report and performance-based measures and examine the associations between hoarding and both boredom proneness and state boredom.
1.1 Aims and Hypotheses
In Study 1, we examined self-reported associations between levels of recent state boredom over the preceding two weeks, trait boredom, and hoarding symptom severity in a general online sample. We hypothesized that individuals reporting higher rates of trait boredom and recent state boredom would endorse more severe hoarding symptoms, replicating previous findings for state boredom [56]. We also aimed to extend previous research by determining whether a unique association exists between boredom and hoarding. Due to limited statistical power, the study by Weiss and colleagues [56] could not examine the relationship between recent boredom and hoarding levels independent of the other study variables (depression, loneliness, self-control, and indecisiveness). We aimed to address this limitation by using a larger sample and controlling for these variables. Additionally, previous research has only reported on recent boredom. Study 1 examined whether a similar relationship exists between the predisposition to experience boredom (boredom proneness) and hoarding severity.
In Studies 2 and 3, we aimed to replicate the state boredom and hoarding association using performance-based measures. In Study 2, we predicted that individuals reporting higher rates of recent boredom and boredom proneness would acquire more and discard fewer items on a validated, performance-based measure that simulates acquiring and discarding behaviors [57]. In Study 3, we attempted to clarify the directionality of the hoarding and boredom association. Specifically, we hypothesized that individuals who were induced into a state of boredom would take more and discard fewer items on the performance-based acquiring and discarding measure.
2 Study 1
2.1 Methods and procedure
2.1.1 Participants
Study 1 was correlational, with data collected online from adult, English-speaking, United States residents through Amazon’s Mechanical Turk (MTurk). Studies examining hoarding have utilized college [58] and general online samples [59]. Results suggest that hoarding tendencies exist in the general population. Research has also demonstrated that many MTurk members display probable hoarding pathology [60]. Moreover, hoarding is a transdiagnostic factor seen in obsessive–compulsive personality disorder, obsessive–compulsive disorder [50], schizophrenia [61], dementia [61], and CBSD [25]. Recruiting from the general population allowed us to capture a broader range of individuals who display varying levels of hoarding. Data was collected in two waves. The data collection procedures and measures were identical in both waves; thus, we combined the waves for analysis. Participants' (N = 253) ages ranged from 19 to 76 (M = 38.76, SD = 12.97). Approximately half (49.80%) of participants identified as male, and 73.10% identified as White. The average SI-R scores (M = 28.89) were below the clinical cut-off of 43, which has been recommended for use with adults under 40-years-old [62]. This suggests that on average, the sample did not experience clinical hoarding symptoms. However, as expected, there was significant range in scores, ranging from 0–90. See Table 1 for complete demographic information.
2.1.2 Measures
2.1.2.1 Boredom
Participants completed the Boredom Proneness Scale (BPS) [2], a validated, 28-item measure assessing individual differences in one's tendency to experience boredom. Participants also completed the State Boredom Measure (SBM) [5], a validated, 8-item measure assessing recent boredom experiences in terms of frequency, intensity, duration, and attributions over the preceding two weeks. The BPS and SBM both showed excellent internal consistency in the present study (SBM: α = 0.90; BPS: α = 0.88).
2.1.2.2 Hoarding severity
Participants completed the Saving Inventory–Revised (SI-R) [63] to assess hoarding severity. The SI-R is a validated, 23-item self-report measure with high internal consistency and convergent validity with other hoarding measures [63]. It demonstrates good test–retest reliability for the total score (0.86) and for the Discarding (0.90), Clutter (0.89), and Acquisition (0.78) subscales [63]. The SI-R showed excellent internal consistency in the present study, ranging from 0.90 to 0.95. Participants also completed The Clutter Image Rating (CIR) [64] as an additional measure of hoarding symptom severity. The CIR is a pictorial measure that contains images of a bedroom, kitchen, and living room. Each image shows a progressively more cluttered version of the same room. Images are numbered 1–9 (least cluttered to most cluttered). Ratings are averaged to create a composite score. The CIR demonstrated excellent internal consistency in the present study, α = 0.92.
2.1.2.3 Self-control
The Self-Control Scale (SCS) [65] is a validated measure assessing individual differences in self-control. Items are rated on a 5-point scale, and internal consistency in the present study was high, α = 0.87.
2.1.2.4 Indecisiveness
The Frost Indecisiveness Scale (FIS) [66] assesses individual differences in decision-making situations and tendencies to postpone decisions. It consists of 15 items scored using a 5-point scale and demonstrated high internal consistency in the present study, α = 0.89. Typically, a summary score is created. However, scores were averaged due to missing data for one item (n = 2).
2.1.2.5 Loneliness
The UCLA Loneliness Scale (UCLA-LS)Footnote 1 [67] is a 20-item scale measuring one's subjective feelings of loneliness and social isolation. Items are rated from "I often feel this way" to "I never feel this way". Items are reverse scored such that higher scores represent more intense feelings of loneliness. The UCLA-LS demonstrated excellent internal consistency, α = 0.96.
2.1.2.6 Depression
The Beck Depression Inventory – Second Edition (BDI-II) [68] was used to measure depressive symptoms. This 21-item scale asks participants to rate their depressive symptoms over the past two weeks on a scale of 0–3. It assesses common symptoms of depression, including changes in mood, energy levels, sleep, and appetite. The BDI-II showed excellent internal consistency, α = 0.97.
2.2 Procedure
This study was approved by the Institutional Review Board (IRB) of The New School for Social Research. All participants were individuals registered as “workers” on MTurk, who accessed the study through a listing on MTurk. Participants were informed of the purpose of the study, provided electronic consent, and were informed that their participation was voluntary and that they could stop the study at any point. An attention check was implemented to screen out random responses and improve data quality. All participants completed the self-report measures and received modest financial compensation.
2.3 Data analysis
Data were analyzed using SPSS Version 29 (Armonk, NY). Summary scores were computed for all variables. Data were checked for potential outliers (Z = > 3 SDs above the mean). Removal of these cases (n = 10 across all measures) did not significantly alter any findings. Thus, the results reported are for the full sample. Scatter plots were used to assess linear relationships between variables. Pearson’s bivariate correlations were used to examine associations between boredom, hoarding symptom severity, and correlates of hoarding. Partial correlations were used to examine the relationships between hoarding symptoms and boredom proneness and recent state boredom while controlling for correlates of hoarding.
3 Results and discussion
3.1 Results
Means and standard deviations for the SI-R and CIR are displayed in Table 1. As predicted, Pearson’s bivariate correlations demonstrated strong correlations between hoarding severity on the SI-R, recent state boredom (r(253) = 0.72, p < 0.001), and boredom proneness (r(253) = 0.64, p < 0.001). Moderate to large associations were observed between scores on the CIR, recent boredom (r(253) = 0.52, p < 0.001), and boredom proneness (r(253) = 0.38, p < 0.001). Additionally, we observed significant correlations between hoarding severity on the SI-R and loneliness, depression, indecisiveness, and self-control in the expected directions. Specifically, participants reporting more depressive symptoms (r(253) = 0.61, p < 0.001), loneliness (r(253) = 0.22, p < 0.001), indecisiveness (r(253) = 0.61, p < 0.001), and lower self-control (r(253) = -0.57, p < 0.001), endorsed higher scores on the SI-R. The same patterns were observed for CIR scores for all variables except for loneliness. All bivariate correlations, including the results for each SI-R subscale, are displayed in Table 2.
Partial correlations controlling for depression, indecisiveness, self-control, and loneliness yielded similar results. Specifically, recent state boredom remained significantly associated with overall hoarding severity on the SI-R (r(247) = 0.48, p < 0.001), acquiring (r(247) = 0.46, p < 0.001), discarding (r(247) = 0.33, p < 0.001), and clutter as measured by the SI-R (r(247) = 0.50, p < 0.001) and the CIR (r(247) = 0.22, p < 0.001). We observed similar patterns for boredom proneness. Specifically, boredom proneness remained associated with overall SI-R scores (r(247) = 0.26, p < 0.001), acquiring (r(247) = 0.26, p < 0.001), discarding (r(247) = 0.18, p = 0.004) and clutter on the SI-R (r(247) = 0.29, p < 0.001) and the CIR (r(247) = 0.20, p = 0.002).
3.2 Discussion
Overall, the results of Study 1 replicated previous findings (Weiss et al. 2020), showing a positive relationship between recent state boredom levels and hoarding symptoms. Additionally, this study demonstrated that individuals endorsing higher levels of boredom proneness also report more hoarding symptoms. Moreover, the relationships between recent state boredom, boredom proneness, and hoarding remained significant when controlling for several potential confounding variables, suggesting that a unique association exists between these constructs. This is also the first study to examine relationships between boredom proneness and hoarding symptoms, as previous research only included recent state boredom [56]. Although significant correlations were observed between boredom proneness and hoarding, the effect sizes were smaller relative to those between recent state boredom and hoarding. This finding is consistent with the idea that state boredom and boredom proneness are distinct constructs [3], and suggests that the experience of state boredom may be more closely related to hoarding symptoms.
Study 1 was limited in several ways. Most notably, it consisted entirely of self-report data and utilized a non-clinical sample. In Study 2, we attempted to expand upon Study 1’s findings and address some of these limitations. Specifically, in Study 2, we chose an internet-based support group for individuals with hoarding symptoms as one of our recruitment sources. Although Study 1 showed a correlational relationship between hoarding symptoms and boredom, it is unclear whether recent state boredom and boredom proneness levels can discriminate between individuals with a clinically significant history of hoarding symptoms and those with no history of hoarding.
This recruitment source also afforded us the unique opportunity to include individuals with active hoarding symptoms and those who consider themselves to be in remission from their hoarding symptoms and continue to visit the group as a supportive resource. HD is considered a chronic condition [50]. Thus, it is possible that even after symptoms have largely remitted, individuals with a history of hoarding problems continue to show hoarding-related tendencies and vulnerabilities. Including these individuals in the study allowed us to examine whether boredom levels differ in those with a history of hoarding problems compared to individuals with current or no history of symptoms.
Additionally, due to the correlational nature of Study 1, it remains unclear whether boredom is associated with hoarding behavior and decision-making processes when it comes to acquiring and discarding. Thus, in Study 2, we assessed hoarding behaviors using a validated, performance-based task designed to simulate acquiring and discarding behaviors as a behavioral marker of hoarding symptoms [57]. We also included two variables relevant to decision-making in hoarding – impulsivity and indecisiveness. Finally, because evidence indicates associations between boredom and CBSD (e.g., [25]), we included a measure of compulsive acquisition. We aimed to measure the association between boredom and compulsive acquisition in the context of elevated hoarding symptoms.
4 Study 2
4.1 Methods and procedure
4.1.1 Participants
Recruitment for the Hoarding Group (HG) and the Previous Hoarding Group (PHG) took place using a large online support group for hoarding. Comparison data (Comparison Group; CG) were collected from Amazon's MTurk. Data collection for this study was part of a larger project, the results of which are reported elsewhere [57]. All participants were at least 18 years old, literate, and United States residents. Participants included in the HG were those who endorsed current hoarding symptoms and scored above the clinical cut-off on the HRS (≥ 14; [69]; n = 56). Ages ranged from 22–63 years old, with an average age of 33.66 (SD = 8.44). 51.80% identified as female, and 62.50% identified as White. Similarly, PHG participants were those who reported a history of hoarding symptoms but reported that they were not experiencing current symptoms (n = 43). PHG participants had an average age of 30.72 (SD = 5.53; range = 20–52). Most participants identified as male (60.50%) and White (48.80%). Participants were administered the HRS, but as this group was largely exploratory, those scoring above the clinical cut-off were not excluded from participation. Average HRS scores were slightly above the clinical cut-off (M = 17.05; Table 3), although they were significantly lower than those of the HG [57].
Finally, participants in the CG denied current or past hoarding symptoms and scored below the clinical cut-off on the HRS (< 14). Ages in the CG (n = 61) ranged from 22–65 years old, with an average age of 43.66 (SD = 11.66). Most participants identified as female (54.10%) and White (80.30%). Complete demographic information for the sample, as well as descriptive statistics for hoarding symptom measures and behavioral task performance are displayed in Table 3.
4.1.2 Measures
4.1.2.1 Boredom
Consistent with Study 1, participants completed the State Boredom Measure (SBM) [5] to assess recent boredom experiences. The SBM showed excellent internal consistency, Cronbach’s α = 0.87. In this study, participants completed the Short Boredom Proneness Scale (SBPS) [70]. The SBPS has been validated and shows good convergent validity with constructs associated with boredom proneness [70] and showed excellent internal consistency in the present study, Cronbach’s α = 0.96. Participants also completed a supplementary measure of trait boredom, the Boredom Susceptibility Scale (BSS) [71], to assess susceptibility to boredom. The BSS showed acceptable internal consistency in the present study, Cronbach’s α = 0.68.
4.1.2.2 Hoarding symptoms screener
The self-report version of The Hoarding Rating Scale (HRS) [72] was used as a screening measure to ensure that individuals in the HG endorsed clinically significant hoarding symptoms and those in the CG were not experiencing HD symptoms. This 5-item self-report questionnaire uses a cut-off score to indicate the presence of clinically significant hoarding symptoms (≥ 14) and showed excellent internal consistency in the present study, Cronbach’s α = 0.91.
4.1.2.3 Hoarding symptom severity
As in Study 1, participants completed the Saving Inventory-Revised (SI-R) [63] to assess the severity of discarding difficulties, excessive acquisition, and clutter. Also consistent with Study 1, participants completed the Clutter Image Rating (CIR) [64] as an additional measure of clutter severity. The SI-R and CIR showed excellent internal consistency in the present study. CIR Cronbach’s α = 0.93, and SI-R subscales Cronbach’s α = 0.91-0.94.
4.1.2.4 Impulsivity
The Barratt Impulsivity Scale (short form; BIS15) [73] was used to measure impulsivity. This measure contains 15 items and three subscales: non-planning, motor impulsivity, and attentional impulsivity. The BIS15 showed good internal consistency in the present sample, Cronbach’s α = 0.87.
4.1.2.5 Indecisiveness
As in Study 1, participants completed The Frost Indecisiveness Scale (FIS) [66] to measure indecisiveness. The FIS showed good internal consistency in the present sample, Cronbach’s α = 0.89.
4.1.2.6 Compulsive acquisition
The Compulsive Acquisition Scale (CAS) [61] is an 18-item scale that assesses the impulse to purchase or acquire free items. To assess compulsive buying tendencies, we utilized a 12-item subscale assessing acquisition of purchased items only. The CAS Buying Subscale showed excellent internal consistency in the present sample, Cronbach’s α = 0.94.
4.2 Apparatus
Participants completed an online simulation task designed to assess acquiring and discarding behaviors. Initial validation of the task (n = 160) demonstrated good convergent validity with the SI-R-Acquisition subscale (r = 0.68, p < 0.001) and the SI-R-Discarding subscale (r = -0.48, p < 0.001) and good construct-related validity [57]. This behavioral task is adapted from previous paradigms [74, 75] and is described in detail elsewhere [57].
The paradigm used in the present study consists of two tasks: an Acquiring task and a Discarding task. In each task, participants are informed that there is a maximum number of items they can acquire/keep. Participants complete the Acquiring Task first and are instructed to imagine that they can keep any of the objects they see for free. Items are then presented serially on participants’ computer screens, and participants indicate whether they want to take or leave each item. In the Discarding Task, participants are instructed to imagine that they already own all the items. They are then presented with the items they selected from the Acquiring Task and new items that were not included in the Acquiring Task. Participants decide whether to keep or discard each item. Following each task, participants provide ratings for four affective states: anxiety, fear, sadness, and regret. In this study, the variables of interest included 1) the number of items acquired on the Acquiring Task; 2) the number of items left on the Acquiring Task; 3) the number of items discarded on the Discarding Task; and 4) the number of items kept on the Discarding Task.
4.3 Procedure
Detailed information about the study procedures, including screening procedures, has been published elsewhere (see [57]). This study was approved by the Institutional Review Board (IRB) of The New School for Social Research. All participants were informed of the purpose of the study, provided electronic consent, and were informed that their participation was voluntary and that they could stop the study at any point. An attention check was used to screen out random responders, and the Masters' Qualification was applied to the MTurk sample to improve data quality. Each participant who completed the study received modest financial compensation.
4.3.1 Data analyses
Data were analyzed using SPSS Version 29 (Armonk, NY). Summary scores were computed for all variables. Scatterplots were used to assess linear relationships between variables in correlational analyses. The data were checked for potential outliers (Z = ≥ 3 SD above the subgroup mean) and analyses were run with and without these cases. With one exception (see below), removal of these cases (n = 6) did not alter any findings; thus, the full sample is reported. One-way analyses of variance (ANOVA) were used to examine differences between the three groups. Pearson’s bivariate correlations were run using the full sample. We opted to utilize the full sample for these analyses due to preliminary nature of the relationship between boredom and hoarding symptoms. Examining participants across various levels of engagement in hoarding behaviors could provide a more nuanced picture of the relationships between these variables.
5 Results and discussion
5.1 Between group differences in hoarding symptoms
Participants in the HG reported significantly higher hoarding symptoms on two self-report hoarding measures (the SI-R and HRS; see Table 5). Notably, the PHG also scored significantly higher than the CG on the SI-R and HRS. Surprisingly, while the HG scored higher than the CG on the CIR, the PHG reported higher scores relative to both groups (see Table 5). The details of these analyses have been previously reported (see [57]), and were not altered when controlling for relevant demographic variables that differed between groups (age, education, marital status).
5.2 Between group differences in boredom
The correlations between boredom and all study measures, including the individual SI-R subscales, are reported in Table 4. As predicted, recent state boredom (SBM) and boredom proneness (SBPS) were significantly correlated with the number of items taken and left on the Acquiring Task and the number of items discarded and kept on the Discarding Task (all p’s < 0.001). The SBM and SBPS also correlated significantly with self-reported hoarding severity, compulsive acquisition, impulsivity, and indecisiveness (all p’s < 0.001). Similarly, correlations were found between our additional measure of boredom, boredom susceptibility (BSS), and all self-report measures (p’s < 0.001). BSS scores were significantly correlated with the number of items taken (r(158) = 0.34, p < 0.001) and left (r(158) = -0.35, p < 0.001) on the Acquiring Task in the expected directions, although the effect sizes were considerably smaller than those observed for the SBPS and SBM. Additionally, the associations between the BSS and performance on the Discarding Task fell short of statistical significance (items kept: r(158) = 0.15, p = 0.056; items discarded: r(158) = 0.15, p = 0.058). However, when excluding the potential outlier cases, the associations between BSS and Discarding Task performance reached statistical significance, although effect sizes remained small (r’s = 0.17, p’s = 0.032-0.033).
Consistent with predictions, one-way ANOVAs demonstrated significant differences between the three groups in terms of recent state boredom (F(2, 157) 88.95, p < 0.001, ηp2 = 0.53), boredom proneness (F(2, 157) = 88.75, p < 0.001, ηp2 = 0.53), and boredom susceptibility (F(2, 157) = 23.18, p < 0.001, ηp2 0.23). The CG reported significantly lower levels of boredom than the HG and PHG on all boredom measures. Pairwise comparisons are displayed in Table 5.
Significant differences in boredom proneness (F(2, 156) = 39.13, p < 0.001, ηp2 = 0.20) and recent state boredom (F(2, 156) = 19.34, p < 0.001, ηp2 = 0.20) remained when controlling for SBM and SBPS scores, respectively. Additionally, the three groups differed significantly regarding several demographic variables: age, marital status (married vs. not married), and education level (college degree vs. no college degree). Including these variables as covariates did not alter the results, and all pairwise comparisons remained the same.
5.3 Discussion
Study 2 replicated the findings of Study 1, again showing significant correlations between hoarding symptom severity, recent boredom, and boredom proneness. These results extended Study 1’s findings in several notable ways. First, this study represents the first empirical test of the relationship between boredom and hoarding-relevant decision-making. Specifically, individuals reporting higher boredom proneness and more recent boredom took more and discarded fewer items on a simulated acquiring and discarding task. Second, this study demonstrated that marked differences in boredom levels exist between individuals with and without clinically significant hoarding symptoms. Individuals scoring above the clinical cut-off on the HRS reported higher levels of boredom proneness, boredom susceptibility, and recent state boredom.
Notably, despite reporting fewer hoarding symptoms [57], boredom susceptibility and recent boredom levels in individuals with a history of hoarding problems (i.e., those identifying themselves as in remission) were not significantly different from those who endorsed active hoarding symptoms. This finding suggests that the tendency to experience elevated rates of boredom at the state level and a predisposition to boredom may be vulnerability markers that persist in cases of HD, even after core symptoms have begun to remit. Consistent with this conjecture is previous research finding that boredom may be predictive of worse HD treatment outcomes [56].
However, this result is preliminary and must be interpreted cautiously, especially given that those with a history of hoarding problems reported relatively high rates of hoarding symptoms on average. Despite scoring significantly lower than those endorsing current symptoms on two of the three self-report measures included in the study (SI-R and HRS), participants’ scores on these measures were elevated, and significantly higher than controls. Additionally, these participants scored higher than the HG on the CIR. A full discussion of this finding is beyond the scope of this paper, and it has been interpreted in more detail elsewhere (see [57]).
In brief, it is important to note that the CIR is a pictorial measure only assessing clutter and does not assess discarding or acquiring. It is possible that those with lower acquiring/discarding symptoms have better insight into the amount of clutter in their homes and provided more accurate ratings of their clutter levels. Alternatively, it is possible that individuals in this group may have reduced their other hoarding behaviors (e.g. excessive acquisition) and thus consider themselves to be in remission despite still having a high degree of clutter [57]. An additional explanation may be that the remitted group was still experiencing active hoarding symptoms, albeit to a lesser degree. This interpretation is consistent with research showing that many individuals with HD remain symptomatic post-treatment [76], and studies showing variable levels of insight in HD [77], and speaks to the chronicity of the disorder.
Additionally, although we observed significant correlations between all boredom measures on the Acquiring Task, the BSS correlation effect sizes were considerably smaller than those observed for the other boredom measures. This may be in part related to the lower internal reliability observed for the BSS in the present study. Additionally, the observed differences between the two trait measures of boredom proneness and susceptibility support the idea that boredom proneness and boredom susceptibility are separate constructs [78]. Past research has linked boredom proneness to a lack of internal stimulation, and boredom susceptibility to a lack of external stimulation and greater engagement in sensation-seeking behaviors [78].
Study 2 built upon our previous work in several ways. Specifically, this study compared non-hoarding individuals to those with active symptoms and included a behavioral assessment of discarding and acquisition. However, a limitation of this study was that boredom was assessed using self-report measures. Only assessing self-reported boredom makes it difficult to determine whether boredom is an antecedent or a consequence of hoarding symptomology, or whether a third variable can account for the observed relationships. Additionally, the correlations between self-report measures (hoarding and boredom) were notably stronger than those between self-reported boredom and behavioral task performance. Study 3 attempted to clarify the nature of the observed relationship by using experimental, behavioral methods to examine boredom and hoarding behaviors. This study aimed to determine whether the experience of boredom can lead to increases in hoarding behaviors. Specifically, we experimentally induced participants into a state of boredom and examined their performance on the simulated Acquiring and Discarding tasks. We hypothesized that participants randomly assigned to a boredom induction condition would acquire more (Study 3a) and discard fewer (Study 3b) items than those assigned to a control condition.
6 Study 3
6.1 Methods and procedure
6.1.1 Participants
Participants (N = 290) were English-speaking, United States adult residents recruited from Amazon’s MTurk. Study 3a participants (N = 144; mean age = 36.54, SD = 11.04; 52.80% male; 84.70% White) were randomly assigned to a Boredom Induction Condition (BIC) or Control Condition (CC) and completed the Acquiring Task described in Study 2.Footnote 2 Study 3b participants (N = 146; mean age = 40.76, SD = 10.64; 56.30% male; 79.50% White) were assigned to a Boredom Induction Condition or Control Condition and completed the Discarding Task described in Study 2. Demographic data for each condition in Studies 3a and 3b are displayed in Table 6.
6.1.2 Measures
6.1.2.1 Self-reports
As in Studies 1 and 2, participants completed the Saving Inventory -Revised (SI-R) [63] to assess hoarding severity and the Short Boredom Proneness Scale (SPBS) [70] and the State Boredom Measure (SBM) [5], to assess individual differences in boredom vulnerabilities and recent boredom experiences, respectively. All measures showed good internal consistency; in both Study 3a and 3b, Cronbach’s α ranged from 0.93-0.98.
6.1.2.2 Boredom induction and control task
The boredom induction consisted of an excerpt from the short story, Beware of the Dog [79] presented as text blocks on participants’ screens. Participants counted and summed the vowels in the story, entering the totals into boxes dispersed throughout the text. Controls read the story and did not count vowels. This vowel-counting task has been validated for online use [80]. However, based on a recent pilot study [81], we shortened the tasks’ durations from 15 minutes to five minutes. Participants in each condition rated their boredom, anxiety, enjoyment, amusement, and annoyance on a scale of 1 (not at all) to 5 (extremely). They rated both tasks along the same dimensions.
6.1.3 Procedure
Participants in Study 3a first completed the self-report measures described above. An attention check was implemented in both Study 3a and 3b to screen out random responding and improve data quality. Following this, they were randomly assigned to the Boredom Induction or Control Condition. After completing their respective task, all participants completed the Acquiring Task described in Study 2. The procedures for Study 3b were identical to those of Study 3a, except participants completed the Discarding Task instead of the Acquiring Task. We opted to divide the Discarding and Acquiring Tasks into separate studies to reduce participant burden, and due to concerns that the second behavioral task (i.e., Discarding Task) would otherwise occur too long after the induction had taken place.
6.1.4 Data analyses
Data were analyzed using SPSS Version 29 (Armonk, NY). Summary scores were computed for all variables. In Studies 3a and 3b, independent samples t-tests were used to examine differences between the BIC and the CC in terms of perceived boredom, items acquired, and items discarded. Levene’s test was used to determine equality of means. The data were checked for potential outliers (Z = ≥ 3 SD above the mean) and analyses were run with and without these cases. Removal of 1 case in Study 3b did not alter any findings, thus, the full sample is reported. In both studies, data were cleaned such that participants who provided seemingly random responses to the vowel-counting task were excluded from analyses. In exploratory analyses, ANOVAs, analyses of covariance (ANCOVA), Pearson’s bivariate correlations, and partial correlations were used to examine relationships between study variables.
7 Results and discussion
7.1 Primary analyses
In Study 3a, participants assigned to the Boredom Induction Condition reported higher levels of boredom than those assigned to the Control Condition, t(123.60) = -3.21, p = 0.002, d = -0.55, Mdiff = 0-0.71, 95% CI [-1.14, -0.27]. However, the BIC did not acquire more items on the Acquiring Task, t(142) = 1.02, p = 0.311, d = 0.17, Mdiff = 1.09, 95% CI[-1.03, 3.21]. Similarly, in Study 3b, the participants in the Boredom Induction Condition endorsed significantly higher levels of boredom than those in the Control Condition, t(128.72) = -4.21, p < 0.001, d = -0.71, Mdiff = 0.0.91, 95% CI [-1.34,-0.48]. However, the BIC did not discard fewer items on the Discarding Task, t(144) = 0.44, p = 0.657, d = 0.07, Mdiff = 0.35, 95% CI [-1.20,1.90].
7.2 Exploratory analyses and discussion
Notably, participants in the boredom induction included in both studies reported relatively mild rates of in-vivo boredom (Acquiring: M = 2.77, SD = 1.42; Discarding: M = 2.73; SD = 1.46) despite scoring higher than controls (Acquiring: M = 2.06, SD = 1.07; Discarding: M = 1.82, SD = 1.12). Thus, the intensity of the shortened boredom induction may not have been potent enough to induce meaningful differences in perceived boredom. Similarly, it is possible that some participants in the CC found the control task more boring than neutral. We conducted exploratory analyses dividing participants based on reports of in-the-moment boredom, regardless of original condition (CC vs. BIC) assignment. The boredom rating scale ranged from 1 (not at all bored) to 5 (extremely bored). Participants were included in the high boredom group if they reported at least a 3 (moderate boredom) on this scale. In Study 3a, participants reporting at least moderate boredom (n = 59) took more items on the Acquiring Task (M = 15.14, SD = 5.97) than those reporting no-to-mild boredom (n = 85; M = 12.27, SD = 6.47), t(142) = -2.69, p = 0.008, d = 0.48. In Study 3b, participants reporting moderate-to-extreme boredom (n = 55) discarded fewer items on the Discarding Task (M = 8.58, SD = 5.35) than those reporting no-to-mild boredom (n = 91; M = 10.74; SD = 4.11), t(92.34) = 2.56, p = 0.012; d = 0.47. These results are displayed in Fig. 2. Notably, the differences remained significant when controlling for original condition assignments in Study 3a (F(1, 143) = 7.44, p = 0.007, np2 = 0.05) and Study 3b (F(1, 141) = 8.98, p = 0.003, np2 = 0.06). Similarly, the more in-the-moment boredom participants reported, the more items they took (r(144) = 0.24, p = 0.004) and the fewer items they discarded (r(146) = 0.23, p = 0.005) on the simulation tasks.
Items acquired and discarded by high- and low-boredom participants. Note: Error bars represent SD
Notably, participants reporting more in-the-moment boredom scored higher on the SI-R in both studies (r(146) = 0.35, p < 0.001; r(144) = 0.41, p < 0.001), despite randomization to the boredom induction and control conditions. It is possible that associations between behavioral task performance and in-vivo boredom were attributable to more severe hoarding pathology in the high boredom groups. However, evidence suggests that these effects are not entirely due to differences in baseline hoarding. Specifically, regardless of condition, partial correlations revealed that participants with higher boredom-proneness discarded fewer items (r(143) = -0.42, p < 0.001), acquired more items (r(141) = 0.58, p < 0.001), and endorsed more SI-R symptoms (r’s = 0.75–79, p’s < 0.001). Similarly, the more recent boredom participants reported, the fewer items they discarded (r(143) = -0.41, p < 0.001), the more they acquired (r(141) = 0.59, p < 0.001), and the higher their SI-R symptoms (r’s = 0.74–78, p’s < 0.001).
Relatedly, the differences in items acquired and discarded by participants reporting high levels of in-the-moment boredom may be attributable to the higher levels of boredom proneness (p’s < 0.01) and recent boredom (p’s < 0.01). Thus, we cannot conclude the causal relationships between experimentally induced boredom and acquiring and discarding behaviors. Nonetheless, these exploratory analyses demonstrated that higher feelings of subjective boredom were associated with fewer items discarded and more items acquired on the performance-based tasks and provide further evidence for a relationship between hoarding tendencies and boredom. Additionally, the exploratory analyses revealed that there was notable variability in participants’ boredom levels, with some participants reporting high boredom resulting from the induction, and even from the control task. This variability is likely due to differences in boredom proneness observed in the population at large and highlights the importance of considering individuals’ unique vulnerability to boredom in clinical contexts.
Overall, future work is still needed to determine the directionality and causality of the relationship between boredom and hoarding symptoms. In Studies 3a and 3b, the primary hypotheses were not supported. Induced boredom did not influence participants to take more or discard fewer items than controls on the acquiring and discarding simulation tasks. However, this may have been due to the mild boredom reported by participants in the boredom induction conditions. This boredom induction typically lasts 15 minutes. It is possible that shortening the induction to five minutes reduced its intensity and was not potent enough to induce meaningful differences in perceived boredom.
Exploratory analyses using participants’ reports of perceived, in-vivo boredom yielded preliminary results consistent with the hypotheses. Specifically, participants reporting moderate-to-extreme boredom took more and discarded fewer items than those reporting no-to-mild boredom. These results may have been attributable to the higher baseline hoarding severity among the high-boredom group. However, baseline hoarding symptoms are unlikely to fully explain these differences. Specifically, individuals with more severe hoarding symptoms reported more intense in-the-moment boredom, despite successful randomization between the boredom induction and control conditions in both studies. This suggests that these individuals experienced boredom more intensely regardless of condition assignment. Additionally, the relationships between boredom and hoarding were seen across several measures in both studies. Higher self-reported boredom proneness and recent boredom experiences were associated with behavioral task performance in the expected directions, replicating our previous studies and providing additional evidence for a relationship between these variables.
8 General discussion
Compulsive hoarding is a pervasive experience, experienced by individuals across diverse cultures and contexts [82]. Hoarding’s severity and consequences have resulted in widespread media coverage (e.g., the television program Hoarders: Buried Alive). Its far-reaching impact highlights an urgent need to understand the conditions under which it develops. This series of studies aimed to determine whether exposure to environmental factors, such as boredom, increases hoarding tendencies. Overall, these studies provided support for the association between hoarding symptoms and boredom. Replicating our previous findings [56], boredom was significantly associated with hoarding symptom severity as measured by the SI-R across three studies. These studies also extend previous findings by examining associations between boredom and hoarding symptoms from a behavioral standpoint and by using experimental methods.
Taken together, these results suggest that boredom is a potentially relevant factor in HD. Should further research confirm these findings in more robust samples of individuals formally diagnosed with HD, boredom may warrant careful consideration in HD treatment and assessment. The association between boredom proneness and symptom severity suggests that individuals with HD may have a greater vulnerability toward experiencing boredom. This is consistent with numerous studies showing that the trait form of boredom is, in fact, highly correlated with various forms of psychopathology [3].
Although boredom proneness is considered a personality variable and thus not easily modified, the current findings form a foundation for future research to examine the relevance of addressing boredom in the context of HD treatment. A high propensity to experience boredom may cause the non-functional, often isolative, living environments that accompany the severe forms of this disorder to be especially problematic. Specifically, such environments could be more likely to lead to protracted experiences of boredom in individuals who are highly vulnerable to boredom. As discussed above, this could potentially lead to a vicious cycle. Specifically, living conditions (e.g., non-functionality of the home, social isolation, loneliness) may lead to increased boredom, which contributes to more severe hoarding symptoms by interacting with risk factors (e.g., attentional problems, depressive symptoms, avoidance and procrastination of discarding, impulsive acquiring urges), thus creating an even more limited and non-functional environment and subsequently leading to more boredom.
8.1 Limitations
Despite this project’s potential value, several limitations are worth noting. This series of studies aimed to reach a wide range of individuals. As such, the results were bound by the limitations of online research. Specifically, although each study implemented an attention check was used to screen out random responders, recently published recommendations have suggested that more stringent data quality checks be utilized for research with crowdsourcing platforms, such as including a VPN/bot check, and including multiple truthfulness- and attention-check questions [83]. Future studies would benefit from replicating these findings while implementing these recommendations. Additionally, the simulated nature of the Acquiring and Discarding tasks included in Studies 2 and 3a-b may have decreased ecological validity relative to in-person versions of these task where participants make decisions about tangible objects. Similarly, although participants were told to imagine a personal connection with the objects (i.e., that they owned them or could take them home), the results may have differed if participants were asked to make these decisions about their personal possessions. It is possible that the simulated nature of the tasks decreased their potency, and larger effects might be observed with paradigms that include tangible, personal items. Future studies should aim to test these hypotheses using tangible discarding and acquiring paradigms and examine the influence of personal relevance of the items on these relationships.
As discussed in our previous work [57], participants in Study 2’s Hoarding and Previous Hoarding Groups endorsed either current or previous hoarding symptoms, respectively, and symptoms were assessed via self-report measures. No formal diagnoses were confirmed. It is possible that some individuals included in the Hoarding Group in Study 2 did not meet the full criteria for HD or had co-occurring disorders. Relatedly, although the Comparison Group in Study 2 was screened for hoarding symptoms, they were not screened for the presence of other mental illnesses. The lack of a clinical comparison group represents an important limitation of the current research, as boredom is associated with numerous psychiatric conditions [3]. Thus, the results of this study cannot determine whether boredom displays a unique relationship with hoarding pathology. Relatedly, we cannot rule out the possibility that a third variable is responsible for the observed relationships between boredom and hoarding symptoms. However, our preliminary evidence suggests that a unique relationship may exist. Specifically, Study 1 demonstrated that these associations appear to be independent of several correlates of boredom and hoarding: depressive symptoms, indecision, loneliness, and self-control difficulties. Future research should aim to clarify the specificity of the boredom and hoarding associations we observed in the present studies, by examining additional correlates, comparing boredom across psychiatric conditions, and using experimental or experience sampling methods.
Similarly, all studies utilized community samples. Data collected from the general population, or from individuals self-identifying as struggling with hoarding, may not fully generalize to individuals diagnosed with HD. However, these studies provide a starting point for more in-depth work exploring hoarding and boredom using clinical samples. Ultimately, research in this area could contribute to a more nuanced understanding of the factors that precipitate and exacerbate HD’s development. The studies’ samples also contained limited diversity in terms of racial and gender identity. The majority of participants in all studies identified as White (49–80%) and within the gender binary (100%). Although hoarding is more commonly observed in older adults (55–94) [50], participants in the present studies were younger on average (mean ages 30–40 years old). This is likely due to the recruitment from online sources, which may be more accessible to adults within this age range. It is unknown whether the results would generalize to older individuals or a more racially and gender-diverse sample of individuals. Future research would benefit from replicating these findings with a more diverse sample in terms of age, gender, and racial and ethnic identity. Finally, although attentional difficulties may play an important role in the relationships between boredom and hoarding, attention was not explicitly assessed in the present studies. Future research examining the links between inattention, boredom, and hoarding symptoms would provide valuable insights into the potential role of boredom in the well-documented inattention-hoarding relationship.
8.2 Implications
The results could have impactful clinical and practice-based implications. The living conditions associated with HD often pose severe health and safety risks [84]. These hazards are particularly dangerous in older adulthood, where fall risks and squalid conditions can lead to dire consequences [43]. Critically, HD is three times more prevalent in older adults [85], indicating the urgency of identifying and mitigating risk factors in this vulnerable population. This study provided further insight into an especially relevant risk factor for older adults, who may be at risk for prolonged boredom [86]. Environmental factors and life changes such as retirement, physical limitations, or isolation from losing loved ones could make increased boredom unavoidable.
8.3 Conclusion
The results from these studies demonstrated robust relationships between hoarding symptom severity, boredom proneness, and recent boredom experiences across three studies and diverse methodologies. Specifically, strong, positive correlational relationships were observed between self-reported boredom and hoarding symptoms (Studies 1–3), and individuals reporting clinically significant hoarding symptoms endorsed significantly higher boredom levels than those without hoarding pathology (Study 2). We also observed positive associations between self-reported boredom and performance on simulated acquiring and discarding tasks (Study 2). The latter finding suggests that boredom may influence decision-making in hoarding pathology. The direct test of boredom's influence on decision-making regarding acquiring and discarding yielded mixed results (Studies 3a and 3b). However, preliminary, exploratory analyses from these studies suggest that a relationship may exist between in-the-moment boredom and decisions to acquire or discard objects.
Overall, this series of studies provides support for an extremely understudied yet potentially clinically relevant association between recent state boredom, trait boredom, and hoarding symptom severity. These findings, combined with a large degree of overlap between boredom and features implicated in cognitive behavioral models of HD, suggest that high rates of boredom may have negative outcomes on hoarding symptom severity.
Data availability
The data that support findings of studies presented is not publicly available and is available from authors upon reasonable request.
Code availability
Not applicable.
Notes
This version of the UCLA-LS was selected to be consistent with the version used in Weiss et al., 2020, as the current investigation served to replicate the findings of this study.
The Acquiring and Discarding Tasks were run in two separate studies to reduce participant burden.
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Acknowledgements
Emily R. Weiss would like to thank Dr. Joan G. Miller for her mentorship and contributions to this project. Emily R. Weiss would also like to thank Dr. Margaret T. Davis for her mentorship, and Julianna Riccardi, Sapna Desai, Vincent DelaCruz, and Weicheng Zhao for their assistance with this project.
Funding
This work was supported by the Psi Chi International Honor Society in Psychology [Graduate Student Research Grant (2020 & 2022); Regional Research Award] and a New School for Social Research Travel Award. Emily Weiss is funded by the National Institute of Mental Health, National Institute on Drug Abuse under Grant Number: 5 T32 DA 22975-15.
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Conceptualization: ERW, MT, DMR. Methodology: ERW, MT. Formal analysis and investigation: ERW, MT. Writing—original draft preparation: ERW; Writing—review and editing: MT, DMR; Funding acquisition: ERW; Supervision: MT, DMR.
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Weiss, E.R., Todman, M. & Roane, D.M. Filling the void: boredom’s associations with hoarding symptom severity. Discov Psychol 4, 35 (2024). https://doi.org/10.1007/s44202-024-00145-2
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DOI: https://doi.org/10.1007/s44202-024-00145-2