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. Author manuscript; available in PMC: 2026 Feb 11.
Published before final editing as: J Psychother Integr. 2025 Nov 13:10.1037/int0000379. doi: 10.1037/int0000379

The transdiagnostic role of boredom within personality disorder symptoms and risk-related behaviors: Implications for Dialectical Behavior Therapy

Emily R Weiss 1, Sophia Mullens 2, McWelling Todman 2, Sarah E Barnes 3,4, Kayla A Lord 5, Margaret T Davis 3
PMCID: PMC12889986  NIHMSID: NIHMS2121813  PMID: 41675295

Abstract

Boredom has been historically overlooked in clinical settings. However, substantial research suggests that one’s vulnerability to boredom (boredom proneness) is linked to numerous psychiatric conditions and negative mental health outcomes, including domains and facets implicated in the Alternative Model for Personality Disorders (AMPD). Boredom appears to have specific relevance to the classifications of Borderline and Antisocial Personality Disorders (BPD; APD), and theoretical work has suggested that boredom may be positively affected by an evidence-based treatment for BPD, Dialectical Behavior Therapy (DBT). In two studies, we examined the links between boredom proneness, recent boredom experiences, and personality in terms of traits and behavioral symptoms. Study 1 (n = 290) demonstrated positive associations between boredom proneness, recent boredom, general personality functioning, and traits associated with BPD and APD in a large online sample. Moreover, a unique relationship was observed between boredom and BPD symptoms when controlling for APD traits and general personality functioning. Study 2 (n = 34) examined the role of boredom in an intensive outpatient DBT program, demonstrating links between boredom, suicide ideation, and self-injury urges across treatment timepoints. Boredom was significantly associated with borderline symptom severity and predicted more severe BPD symptoms at the midpoint and endpoint of treatment. Together, these findings suggest that boredom plays a robust role in various dimensions of personality psychopathology, and that addressing boredom within treatments for these conditions may impact outcomes.

Keywords: boredom, borderline personality disorder, dialectical behavior therapy, personality traits, personality disorders

Introduction

Boredom is a ubiquitous feeling state that has been frequently defined as “wanting, but being unable, to engage in satisfying activities” (Eastwood et al., 2012, pg. 482). Despite past work examining related, yet distinct, constructs such as emptiness (Klonsky, 2008) and alexithymia (Eastwood et al., 2017), boredom has been historically understudied in clinical settings (Todman, 2003). However, the results of several decades of research strongly suggest that boredom plays an important self-regulatory role in terms of our efforts to engage with the environment through the optimization of our allocation of attentional resources (e.g., Tam et al., 2021). Feelings of boredom alert us that our cognitive resources are being underutilized and underperforming, while at the same time motivating us to seek an alternative mode of engagement (Bench & Lench, 2013; Todman, 2003; Todman, 2013). Given the apparent centrality of boredom’s proposed self-regulatory function, it is perhaps not surprising that unusually frequent, persistent and/or intense feelings of boredom are often associated with a host of untoward mental health outcomes (e.g., substance use; Chao et al., 2024; disordered eating; Havermans et al., 2015).

The level of chronicity and/or severity of boredom is believed to be a function of two non-orthogonal factors. Specifically, it depends on the prevalence of relatively unavoidable boredom-inducing stimuli and tasks in the daily life that are likely to provoke feelings of state boredom in most individuals (e.g., a job that requires working on a monotonous tasks), and the individual’s trait-like level of vulnerability or susceptibility to boredom (Farmer & Sundberg, 1986; Todman, 2003; Todman, 2013). Importantly, it is likely that almost any factor that causes the allocation of attentional resources to be more difficult or inefficient (e.g., brain trauma; Goldberg & Danckert, 2013; Isacescu & Danckert, 2018) is also likely to increase an individual’s vulnerability to boredom (Isacescu & Danckert, 2018; Isacescu et al., 2017; Mugon et al., 2018; Tam et al., 2021).

Due to its proposed self-regulatory function, boredom might contribute to an individual’s overall level of personality functioning and have transdiagnostic implications. Cross-cutting features are becoming increasingly relevant upon the introduction of the Alternative Model for Personality Disorders (AMPD) in section III of the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) and DSM-5-TR (American Psychiatric Association [APA], 2013; APA 2022). This model outlines a shift toward a dimensional approach in the characterization of personality disorders, both in terms of structure and function. The AMPD posits the existence of a finite set of dimensional traits and facets (e.g., Detachment vs. Extraversion) that collectively define personality features, both with regard to personality disorders and typical personality functioning. However, the severity of the disorder is captured by another dimension, which the AMPD refers to as the Level of Personality Functioning (LPF). Impairments in the LPF and its sub-domains of self- and interpersonal functioning are thought to represent the “core of personality disorder psychopathology” (APA, 2022; p. 772).

Research suggests that boredom, at least in some of its chronic manifestations, is likely to co-occur with cross-cutting domains and facets that impair effective attentional allocation and self-regulation, with relevance to traits defined in the AMPD (e.g., Masland et al., 2020). The five domains defined in the AMPD include Negative Affectivity, Detachment, Disinhibition, and Psychoticism, which can be further broken down into 25 facets spread across these domains. Specifically, boredom has been linked to facets subsumed under Negative Affectivity (i.e., Depressivity; Hostility; Emotional Lability). These include associations between boredom proneness and increased aggressiveness and hostility (Dahlen et al., 2004; Isacescu et al., 2017; Vodanovich et al., 1991), emotional lability (Lorenzi et al., 2024), and extensive research demonstrating positive relationships between both state boredom and boredom proneness and depression (e.g., Fahlman et al., 2013; Goldberg et al., 2011; Lee & Zelman, 2019; Todman, 2013; Yeung et al., 2024). Notably, these associations also link boredom to the AMPD domains of Antagonism (Hostility), and Detachment (Depressivity; Suspiciousness; Anhedonia; Brotherton & Eser, 2015; Goldberg et al., 2011). Similarly, boredom is likely implicated in the domain of Distractibility, with past research implicating boredom in failures in sustained attention (e.g., Danckert & Merrifield, 2018; Eastwood et al., 2012; Malkovsky et al., 2012) and with symptoms of attention deficit-hyperactivity disorder (ADHD) in adults (Kass et al., 2003). Finally, boredom and boredom proneness may play an important role in the domain of Disinhibition, through associations with increased impulsivity (e.g., Chao et al., 2024; Dahlen et al., 2004; Moynihan et al., 2017) and risk-taking behaviors (e.g., Kılıç et al., 2020).

Notably, many of the domains and facets with links to boredom characterize two personality disorder classifications described in the AMPD: borderline personality disorder (BPD) and antisocial personality disorder (APD; Masland et al., 2020). BPD and APD classifications are both characterized by domains of Disinhibition (e.g., Impulsivity) and Antagonism (e.g., Hostility). Further, the BPD classification contains facets of Detachment (e.g., Depressivity) and Negative Affectivity (e.g., Emotional Lability), all of which have been associated with boredom in past research (e.g., Lorenzi et al., 2024; Yeung et al., 2024). Moreover, boredom may have prognostic implications for individuals with high levels of the traits that characterize the BPD and APD classifications. Multiple studies have demonstrated associations between boredom and behavioral outcomes linked to Disinhibition including substance use (e.g., Doering et al., 2023; Krotava & Todman, 2014; LePera, 2011), gambling (Blaszczynski, 1990; Mercer & Eastwood, 2010) and disordered eating (Abramson & Stinson, 1977; Crockett et al., 2015; Havermans et al., 2015; Moynihan et al., 2015).

Crucially, boredom also appears to play a role in two key areas of BPD pathology relating to the facet of Depressivity – specifically, risk for suicide and non-suicidal self-injury (NSSI). Experimentally-induced boredom can increase self-harm behaviors in laboratory settings (Havermans et al., 2015; Nederkoorn et al., 2016; Yusoufzai et al., 2022), with participants who had histories of self-injury more likely to shock themselves sooner and more frequently during the first 15 minutes of the boredom induction (Nederkoorn et al., 2016). Similarly, in a study of individuals who were incarcerated (50% were diagnosed with BPD), boredom frequently served as an emotional antecedent for self-harm (Chapman & Dixon-Gordon, 2007). Regarding risk for suicide, an ecological momentary assessment (EMA) study in an inpatient psychiatric sample demonstrated that feelings of boredom were the strongest predictor of suicide ideation relative to other emotions or feeling states (Ben-Zeev et al., 2012). Similarly, a recent study analyzing participants’ social media posts demonstrated that depictions of boredom were the strongest predictor of scores on the Columbia Suicide Severity Rating Scale (C-SSRS) (Lissak et al., 2024).

In addition to relationships between boredom and AMPD domains and facets characterizing BPD and APD, past work has also implicated boredom in these personality disorders using categorical diagnostic systems (Masland et al., 2020). Indeed, a recent review article highlighted the relevance of boredom to BPD symptoms, and proposed a Boredom Cascade Model through which boredom may interact with identity disturbances and chronic emptiness to exacerbate BPD symptom severity (Masland et al., 2020). Notably, Masland and colleagues (2020) suggested that an evidence-based treatment for BPD, Dialectical Behavior Therapy (DBT; Linehan, 1993), may be particularly useful for managing boredom. Specifically, DBT’s focus on building a life worth living, mindfulness, and distress tolerance all have direct relevance to boredom which has been inversely associated with mindfulness (e.g., Koval & Todman, 2015; Lee & Zelman, 2019), positively associated with feelings of meaninglessness (e.g., Chan et al., 2018), emotion dysregulation (e.g., Crockett et al., 2015) and its consequences (e.g., self-injury; binge eating). Moreover, although DBT was initially designed to treat individuals with BPD (Linehan, 1993), it has been shown to be effective across multiple diagnostic classifications, including for individuals with antisocial behaviors (Wetterborg et al., 2020). As such, examining the role of boredom in DBT may provide valuable clinical insights relevant to disorders classified by multiple traits included in the AMPD.

We are unaware of any previous studies that have attempted to explore the hypothesized relationship between boredom, personality disorder symptoms and DBT treatment response, particularly with respect to suicide risk and NSSI. We attempted to address this gap in the literature by using data from two different but related studies. First, we endeavored to confirm the existence of an empirical link between boredom, personality disorder presentations as defined in the AMPD (BPD and APD), and level of personality functioning in a large internet-based, community sample (Study 1). We hypothesized that both state and trait boredom would be associated with higher endorsement of traits associated with BPD and APD, and greater overall impairments in level of personality functioning as defined by the AMPD.

In Study 2, we explored boredom’s impact on BPD symptom severity in a clinical setting. Specifically, we assessed the boredom levels of patients enrolled in a DBT program across treatment timepoints. Additionally, we examined boredom’s associations with NSSI and suicide ideation at different timepoints in treatment. We hypothesized that boredom proneness and recent state boredom experiences would be associated with worse treatment outcomes (evidenced by more BPD symptom severity) at midpoint and endpoint of treatment. We also hypothesized that individuals reporting current suicide ideation, urges for suicide, and urges for NSSI would report higher levels of both boredom proneness and recent experiences of boredom. Finally, we predicted that the strength of the urges and ideation would be associated with levels of boredom proneness and recent state boredom experiences.

Study 1: Borderline Symptom Severity and Boredom in an Online Sample

Methods

Participants

Participants were recruited via Amazon’s Mechanical Turk (M Turk) platform as part of a larger project, thus not all measures and variables are reported here. They included 290 English-speaking adults residing in the United States (72.8% male/female). The majority of participants were between 25 and 34 years old (74.5%), with 95.9% of participants under the age of 45. Of these participants, 25.2% reported a history of a mental health condition. Detailed demographic data is displayed in Table 1.

Table 1.

Demographics: Borderline Symptom Severity and Boredom in an Online Sample

Frequency Percent
Age 18–24 years old 18 6.2
25–34 years old 198 68.3
35–44 years old 62 21.6
45–54 years old 7 2.4
55–64 years old 5 1.7
65+ years old 0 0
Sex Male 211 72.8
Female 79 27.2
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Measures

Boredom Proneness and State Boredom.

The Short Boredom Proneness Scale (SBPS) (Struk et al., 2017) was used to assess an individual’s general propensity to experience boredom. The SBPS is an 8-item scale with a 7-point Likert-type scale, where higher scores suggest an increased inclination to experience boredom. Recent experiences of boredom were assessed by the State Boredom Measure (SBM), a self-report measure that assesses an individual’s cognitive representations of their boredom experiences over the past two weeks (Todman, 2013). The measure includes eight questions with responses on a Likert-type scale. There are four conceptual clusters of the SBM: frequency, degree of tolerance for episodes of sustained boredom, attributions about the causes of boredom episodes/consequences of boredom, and intensity of the associated unpleasantness/discomfort/distress.

Level of Personality Functioning.

The Level of Personality Functioning Scale (LPFS) was recently introduced in the AMPD to provide an updated measure for the assessment of impairments in personality functioning (APA, 2013; 2022). The model builds upon the assumption that there are commonalities among various personality disorders in self and interpersonal functioning, and there are characteristic impairments in identity, self-direction, empathy and intimacy at five different levels of personality functioning. The Level of Personality Functioning Scale-Brief Form (LPFS-BF; Hutsebaut et al., 2016) and the Level of Personality Functioning Scale-Self Report (LPFS-SR; Morey, 2017) are two measures designed to assess LPFS. The LPFS-BF is a screening tool to yield a global estimate of impairment. This instrument contains 12 items to be rated “yes” or “no”. The LPFS-SR allows for the computation of the four subscales. Two of the three samples received the LPFS-BF, whereas the remaining sample received the LPFS-SR. This permitted a comparison of the LPFS-BF and LPFS-SR in terms of their relationship with the other variables in the study.

Personality Disorder Symptoms.

Participants were administered a modified version of the DSM-5 trait criteria for the Alternative Model for Borderline Personality Disorder and Antisocial Personality Disorder (APA, 2013; 2022). Each of the criteria were adjusted into first-person statements corresponding with a 7-point Likert-type rating scale. Participants indicated the extent to which the alternative DSM-5 criteria for this disorder applied to them. These criteria have been modified to remove jargon, but contain the core components of each of the criteria.

Procedure

Participants were routed from Amazon’s M Turk to the Qualtrics survey platform to complete a questionnaire including the measures described above. In addition, participants completed an attention filter to ensure adequate attentional investment in the survey. Due to concerns about early respondents using artificial intelligence (AI) to complete the survey quickly, the latter half of participants received a slightly modified survey, which included a screening tool to exclude bots from the study. Early respondents with suspected AI use were excluded from the sample in subsequent review, as were participants who completed the survey in under five minutes. Participants in one of the three samples received two novel validation measures to assess and control for two types of response biases commonly found in online studies: the tendency to endorse items that are perceived to be extreme or unusual, and the tendency to endorse items located on the right side of Likert-type scales, regardless of content. The “Faux Questionnaire” (FQ), which includes items such as “ I get thirsty when it snows” is a check for excessively random and extreme content endorsement, whereas the “State Happiness Measure,” (SHM) includes almost identical verbiage to the State Boredom Measure, but replaces the (negatively valanced) word, “boredom” with the (positively valanced) term, “happiness”, thereby providing a check for endorsement patterns that are insufficiently influenced by the content of the items. To improve data quality, data were cleaned such that participants with incomplete survey data, unrealistically fast survey completion times (<5 minutes), or evidence of AI use in their surveys were excluded (n = 310). All participants provided informed consent and this study was approved by the Institutional Review Board at The New School for Social Research.

Data Analyses

Data analyses were completed using SPSS (Version 30, Armonk, NY). Bivariate correlations were conducted to examine relationships between the two boredom measures (SBPS and SBM) and total scores on the BPD symptom rating scale and the LPFS. To examine relationships between boredom and BPD symptoms when controlling for general personality functioning, a partial correlation was conducted between the SBPS, SBM and BPD scale, controlling for LPFS scores. Another partial correlation was conducted controlling for both the LPFS and APD symptoms, in order to examine whether the relationship between BPD and boredom held even when accounting for general personality symptomatology and disorders with overlapping symptoms.

Results

None of the mean scores for the relevant variables across the three independent samples were found to be significantly different from each other and thus were subsequently collapsed to form a single sample. The SBPS and SBM were found to be significantly associated with both the LPFS-BF, r(198) = .52, p < .001, and r(198) = .38, p < .001, respectively, and the LPFS-SR r(92) = .564, p < .001 and r(92) = .60, p < .001, respectively. General personality functioning symptoms (as measured by the LPFS) were significantly correlated with BPD and APD symptoms (See Table 2). General personality functioning was also correlated with both boredom measures, suggesting a relationship between overall personality pathology and state and trait boredom. Both the SBPS and SBM were significantly associated with BPD and APD symptoms; correlations ranged from .62-.69 with all p’s < .001 (Table 2). When controlling for ratings of general personality functioning, BPD symptoms remained significantly correlated with the SBPS (r(195) = .58, p < .001) and the SBM (r(195) = .61, p < .001). Similarly, when controlling for both LPF and APD symptoms, the SBPS and SBM remained significantly associated with BPD scores (r(194) = .34, p < .001; r(194) = .38, p < .001, respectively).

Table 2.

Correlations Between Boredom Measures and Personality Disorder Symptoms

M SD 1. 2. 3. 4. 5.
1. SBPS Total Score 35.91 10.72 —
2. SBM Total Score 37.39 8.29 .628** —
3. BPD Total Score 61.32 15.23 .686** .676** —
4. APD Total Score 48.73 12.90 .659** .621** .849** —
5. LPFS-BF Total Score 5.81 3.37 .524** .377** .518** .492** —
6. LPFS-SR Total Score 374.60 72.34 .564** .599** .472** 487** —
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Note: SBPS = Short Boredom Proneness Scale; SBM = State Boredom Measure; BPD = Borderline Personality Disorder Symptoms; APD = Antisocial Personality Disorder Symptoms; LPFS-BF and LPFS-SR = Level of Personality Functioning Scale Brief Form and Self-Report, respectively.

**

= Correlation is significant at the 0.01 level (2-tailed).

Lastly, for the portion of the sample who received the validity check questionnaires–the FQ and SHM–a partial correlation was conducted controlling for the FQ and SHM, in order to examine whether relationships between BPD symptoms and boredom remained significant when taking into account random and extreme responding. BPD symptoms remained significantly correlated with BPD symptoms (r(95) = .42, p < .001), as was the SBM (r(95) = .52, p < .001).

Study 2: Boredom, Borderline Severity, and Risk-Related Behaviors in a Clinical Sample

Methods

Participants

Participants included 34 adults enrolled in an 8-week DBT intensive outpatient program (IOP). The majority of participants were White (87.5%), non-Hispanic (94%) and female (85.6%). Ages ranged from 19–51, with an average age of 30.47 (SD = 8.48). Demographic and diagnostic data are displayed in Table 3. Baseline (week 1) data were available for 26 participants. Midpoint data (week 5) were available for 22 participants. Endpoint data (week 8) were available for 18 participants. Of note, some participants completed more than 8 weeks of treatment, as treatment length could be extended on a case-by-case basis. However, to keep analyses consistent across all participants, week 8 was used as the endpoint for all participants. Additionally, participants are permitted to complete the IOP more than once. Where possible, data are used from participants’ first episode of care. The second episode of care (completed approximately 12 months later) was used for 2 subjects who were not administered the measures included in this study during their first episode of care within the IOP.

Table 3.

Demographic and Diagnostic Sample Characteristics

N (%) N (%)
Sex Diagnosis
Male 5 (14.70) Borderline personality disorder 16 (47.06)
Female 29 (85.30) Other personality disorder 3 (8.82)
Gender Identity Anxiety disorder 6 (17.65)
Woman 13 (38.20) Bipolar disorder 11 (32.35)
Man 5 (14.70) Depressive disorder 14 (41.18)
Genderqueer 2 (5.90) Unspecified Mood/Affect disorder 4 (11.76)
Gender non-conforming 1 (2.90) Anorexia nervosa NOS 1 (2.94)
Non-binary 4 (5.80) Obsessive-compulsive disorder 2 (5.88)
Missing data 11 (32.40) PTSD/Stress-related disorder 9 (26.47)
Race Substance Use Disorder: Alcohol 4 (11.76)
White 28 (82.30) Substance Use Disorder: Cannabis 1 (2.94)
Asian 3 (8.80) Substance Use Disorder: Cocaine 1 (2.94)
Black or African American 1 (2.90) Substance Use Disorder: Opioid 1 (2.94)
Missing data 2 (5.90) Missing 5 (14.71)
Ethnicity
Hispanic/Latino/a/x 2 (5.90)
Not Hispanic/Latino/a/x 32 (94.10)
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Measures

Boredom Proneness and State Boredom.

The Short Boredom Proneness Scale (SBPS; Struk et al., 2017) and State Boredom Measure (SBM; Todman, 2013) were again used to measure boredom proneness and recent boredom, respectively. As boredom was assessed weekly, the SBM’s prompts were modified to ask about boredom experiences over the past week. The SBPS was administered to participants at baseline and endpoint. Composite scores were created for both measures by summing the items.

Borderline Symptom Severity.

Borderline symptom severity was assessed using the 23-item Borderline Symptom List (BSL-23; Bohus et al., 2009). This scale is validated to assess BPD symptoms and asks participants to report on symptom severity over the past week. Scores are averaged to create a composite score, and severity can be quantified on a scale of none (0 – 0.28) to extremely high (3.48 – 4.00) (Kleindienst et al., 2020). The BSL-23 was administered to participants weekly.

Suicide Ideation and Urges for Suicide and Self-Injury.

To assess suicide ideation and urges, participants completed the Columbia Suicide Severity Rating Scale (C-SSRS) (Posner et al., 2011) on each treatment day as part of routine risk assessment. Participants indicated their level of suicide ideation since their most recent session in the program. Participants also rated their current urges for suicide and self-injury on a scale if 0 (no urges) to 10 (most intense urges).

Procedure

The DBT IOP is an 8 week program consisting of group-based treatment. Groups included content and skills lessons from each of the four DBT modules (emotion regulation, interpersonal effectiveness, mindfulness, distress tolerance). Patients attended the program three days per week. Groups were facilitated by licensed clinicians intensively trained in DBT and by psychology and social work trainees under close supervision. All patients completed daily diary cards, homework assignments, and had access to phone coaching. No individual therapy was provided as part of the program, however, all patients were required to have an individual therapist in the community. It is worth noting that while the DBT IOP contains many of the main components of comprehensive DBT (e.g., phone coaching, diary card reviews, homework review, consultation team for clinicians), there are several differences. These include the shorter duration of the program and the absence of individual DBT sessions.

Measures were administered as part of an ongoing quality assurance program. Thus, not all measures or variables are reported here. Patients accessed the surveys through a secure online link. The C-SSRS and urge ratings were completed on each program day. The BSL-23 and SBM were completed once per week. The SBPS was completed at Baseline (week 1) and Endpoint (week 8). Analysis of these data was approved by the Yale School of Medicine Institutional Review Board.

Data Analysis

All analyses were completed using SPSS Version 29.0 (Armonk, NY). Suicide ideation (SI), urges for NSSI, and urges for suicide were dichotomized to determine whether these variables differed as a function of boredom levels. Independent samples t-tests were conducted for each timepoint (Baseline, Midpoint, Endpoint) with SI, suicide urges, and NSSI urges as independent variables and boredom proneness and recent state boredom as dependent variables. To examine relationships between the severity of SI, suicide and NSSI urges, BPD symptoms, and boredom, correlational analyses were conducted for each timepoint. To determine whether boredom predicted symptom severity across treatment, linear regressions were conducted with Baseline boredom proneness predicting BSL-23 scores at Midpoint and Endpoint. Finally, to examine whether the salience and amount of boredom experienced over treatment predicted outcomes, an average score for each participant was created by averaging SBM composite scores over weeks 1–8 to predict Endpoint BSL-23 scores. Descriptive statistics are displayed in Table 4.

Table 4.

Descriptive Statistics for Study Variables

N Min Max Mean SD
Baseline (Week 1)
 Boredom Proneness (SBPS) 26 15.00 52.00 37.35 9.79
 Recent State Boredom (SBM) 26 15.00 48.00 30.62 10.17
 Borderline Symptom Severity (BSL) 30 0.22 3.65 1.84 0.92
 Suicide Ideation (C-SSRS) 30 .00 5.00 1.13 1.31
 Suicide Urges 30 0 8 1.83 2.52
 NSSI Urges 29 0 10 1.55 2.94
Midpoint (Week 5)
 Recent State Boredom (SBM) 22 12.00 53.00 32.91 11.60
 Borderline Symptom Severity (BSL) 24 0.13 3.57 1.91 1.07
 Suicide Ideation (C-SSRS) 24 .00 4.00 1.25 1.33
 Suicide Urges 24 0 8 2.00 2.70
 NSSI Urges 24 0 9 1.50 2.78
Endpoint (Week 8)
 Boredom Proneness (SBPS) 18 18.00 55.00 39.61 10.45
 Recent State Boredom (SBM) 18 14.00 56.00 33.56 12.92
 Borderline Symptom Severity (BSL) 21 0.30 3.83 1.74 1.17
 Suicide Ideation (C-SSRS) 21 .00 5.00 0.91 1.45
 Suicide Urges 21 .0 10.0 1.50 2.83
 NSSI Urges 21 0 7 0.76 1.79
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Note: BSL = Borderline Symptom List, SBM = State Boredom Measure, SBPS = Short Boredom Proneness Scale, C-SSRS = Columbia Suicide Severity Rating Scale.

Results

Baseline Associations: Week 1

At Baseline, we examined demographic differences in boredom proneness, recent state boredom, and borderline symptoms severity. There were no sex differences (p’s = .76-.95) across any of these variables. Age was not associated with boredom proneness or borderline symptom severity (r(26–30)’s = −.05- −.26; p’s = .20–78). However, younger individuals reported more recent state boredom over the past week (r(26) = −.42, p = .031). Boredom proneness was significantly associated with borderline symptom severity (r(26) = .68, p < .001). Recent state boredom was marginally associated with borderline symptom severity (r(26) = .34, p = .058). Individuals endorsing current suicide ideation reported significantly higher levels of boredom proneness (t(24) = 4.05, p < .001; d = 1.6; Mdiff = 12.23, SE =3.02, 95% CI [6.00, 18.46]), boredom proneness was associated with the intensity of suicide of ideation (r(26) = .66, p <.001). No other relationships were significant at Baseline (all p’s > .05).

Midpoint Associations: Week 5

At Midpoint, recent state boredom was significantly associated with borderline symptom severity (r(22) = .57, p = .005), and individuals endorsing current suicide ideation reported more recent boredom over the past week (t(20) = 2.16, p = .043, d = 0.96; Mdiff =10.27, SE = 4.74, 95% CI [0.37, 20.16]). Those with current urges for suicide tended to report more boredom, although this relationship did not reach statistical significance (t(20) = 2.01, p = .058, d = 0.86; Mdiff = 9.33, SE = 4.64, 95% CI [−0.35, 19.02]). Recent boredom was not associated with urges for NSSI or with the severity of suicide ideation or urges (p’s > .05).

Endpoint Associations: Week 8

Finally, at Endpoint, borderline symptom severity was associated with both recent state boredom (r(18) = .63, p = .005) and boredom proneness (r(18) = 78, p = .001). Individuals endorsing current suicide ideation reported higher levels of boredom proneness (t(13.23) = 2.54, p = .024, d = 1.12; Mdiff =10.38, SE = 4.40, 95% CI [1.04, 19.71]), as did those endorsing current urges for NSSI (t(15.52) = 3.83, p = .004, d = 1.18; Mdiff = 11.06, SE = 3.27, 95% CI [4.11, 18.01]). The severity of suicide urges was significantly associated with recent boredom, (r(18) = .51, p = .034), and those endorsing suicide urges tended to report higher recent boredom (t(16) = 2.10, p = .052, d = 1.01; Mdiff = 11.95, SE = 5.70, 95% CI [−0.14, 24.04]) and boredom proneness (t(16)=2.12, p = .050, d = 1.03; Mdiff = 9.75, SE = 4.60, 95% CI [−0.002, 19.51]). However, these relationships fell short of reaching statistical significance. Relationships between boredom proneness, suicide ideation, and NSSI are displayed in Figure 1.

Figure 1.

Figure 1.

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Boredom Proneness, Suicide Ideation, and NSSI Urges Across Treatment

Note: Higher boredom proneness was observed at Baseline and Endpoint among individuals endorsing SI. Higher boredom proneness was observed among individuals endorsing NSSI at Endpoint only. W1 = Baseline; W8 = Endpoint. *** p < .001; ** = p < .01; * = p < .05. SI is measured by the C-SSRS.

Boredom Predicting Symptom Severity Across Treatment

Neither recent boredom (SBM scores) nor boredom proneness (SBPS scores) changed significantly over the course of treatment (p’s = .26-.65). Mean scores on the BSL did not differ significantly from Baseline to Endpoint (p = .49). However, descriptive analyses showed that 41% of the sample scored within the mild range at Endpoint, relative to 23.50% scoring in the none to mild range at Baseline, suggesting overall lower symptom severity by the end of treatment. Linear regressions demonstrated that Baseline boredom proneness significantly predicted borderline symptom severity at the Midpoint of Treatment (F(1, 15) = 15.54, p = .001, b = .71), accounting for 50% of the variance. Similarly, Baseline boredom proneness predicted Endpoint borderline symptom severity (F(1, 11) = 6.84, p = .024, b = .62), explaining 39% of the variance. The average amount of state boredom experienced by participants also significantly predicted symptom severity at Endpoint, accounting for 32% of the variance (F(1, 19) = 9.11, p = .007, b = .57). These regressions are displayed in Figure 2.

Figure 2.

Figure 2.

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Boredom Predicting Symptom Severity Across Treatment

Note: Boredom predicting borderline symptom severity across timepoints. Baseline Boredom predicting BPD symptom severity at Midpoint (A) and endpoint (B). Composite boredom (mean of each SBM score for each individual across treatment) predicting symptom severity at endpoint (C). BPD symptom severity was measured by the Borderline Symptom List (BSL-23).

Discussion

In two samples, we demonstrated significant relationships between boredom proneness, recent experiences of state boredom, and personality disorder symptom severity across traits associated with two AMPD classifications and with BPD traits specifically. In a large internet-based sample (Study 1), both boredom scales were significantly associated with general levels of personality functioning, consistent with the notion that boredom may be a cross-cutting, transdiagnostic feature with relevance to multiple symptom presentations. It is also notable, however, that even when controlling for more general personality functioning and APD symptoms, links between boredom and BPD symptom severity remained significant. Further, these data suggest that boredom predicted BPD symptoms as well as or better than LPFS criteria, and the relationship between the two variables cannot just be explained by general personality functioning or symptoms of other overlapping disorders. The persistence of this relationship suggests that boredom may have particular relevance to individuals displaying traits consistent with BPD pathology.

Further evidence for the role and relevance of boredom to both BPD and treatment outcomes was seen in our clinical sample (Study 2). Specifically, we observed relationships between trait boredom, borderline symptom severity, and suicide ideation that persisted across treatment in a DBT IOP. We also observed relationships between recent experiences of state boredom and BPD severity, which appeared to strengthen towards the end of treatment. Notably, this pattern is consistent with findings for the risk-related behaviors assessed in this sample, and in other clinical samples demonstrating associations between boredom and more severe symptoms at the end of psychotherapy (Weiss et al., 2020). Specifically, significant relationships between NSSI and boredom proneness were only observed at the end of treatment. Baseline levels of boredom proneness significantly predicted borderline symptom severity at both the midpoint and endpoint of treatment, accounting for approximately one-half and one-third of the variance, respectively. Similarly, the average amount of state boredom experienced over the course of treatment predicted almost a third of the variance in BPD symptom severity: higher levels of state boredom predicted worse symptom severity at the end of treatment.

It is possible that DBT could target and address boredom from a number of different angles–implicitly or explicitly. Previously, Masland and colleagues (2020) provided recommendations for the clinical utility of addressing boredom in throughout DBT. This treatment’s central focus of building a life worth living, instilling a sense of meaning, increasing mindfulness to improve one’s connection to the present moment and to internal states, supporting engagement in activities, managing distress associated with boredom, and improving regulation of emotions, all have implications for the potential reduction of trait boredom and of the salience of boredom experiences (Masland et al., 2020). Specifically, the DBT practice of identifying and working towards life worth living goals throughout the course of treatment could be beneficial to counteract the feelings of meaninglessness that boredom can produce (Chan et al., 2018). Increasing mindfulness through intentional practice may also subsequently reduce vulnerability to boredom, which is both positively associated with mind-wandering, and negatively associated with mindfulness (Koval & Todman, 2015). Finally, as Masland and colleagues (2020) describe, modules aimed at emotion regulation and distress tolerance may help patients learn to tolerate and regulate feelings of boredom, preventing the cascade that ultimately exacerbates symptom severity. Overall, there is good reason to believe that DBT may be a useful tool in both mitigating the negative impact of boredom on BPD symptoms and in reducing boredom experienced secondarily to other symptoms.

It is notable that neither boredom proneness or recent boredom experiences decreased over the course of treatment. However, given the findings that higher baseline boredom proneness predicted worse symptom severity at the end of treatment, it may be useful to consider further assessment and intervention around boredom within the DBT model. The lack of change in boredom across treatment may be explained by a number of factors. Boredom proneness is considered to be a trait variable (Farmer & Sundberg, 1986). To our knowledge, studies have not examined whether external factors can impart changes in boredom proneness, however, it is possible that a short-term treatment is not sufficient to alter a relatively stable personality characteristic.

Taken with our findings that boredom was related to increased urges for specific target behaviors, it may be the case that the function of target behaviors (i.e., binge eating, NSSI, substance use), at least for some individuals and in some cases, was to escape feelings of boredom (Masland et al., 2020). Indeed, past work has suggested that individuals who are exposed to a boredom induction in laboratory settings are more likely to engage in self-injury, relative to those exposed to paradigms designed to induce other negative states (e.g., sadness; Nederkoorn et al., 2016). Thus, when one reduces or abstains from engagement in these target behaviors, it may result in fewer strategies available for managing boredom. This may explain the lack of change observed in boredom experiences across treatment.

Relatedly, although multiple DBT interventions may be effective for boredom management, boredom is not routinely addressed or included in treatment in an explicit manner. Both patients and clinicians may overlook boredom’s role in presenting problems, resulting in it being excluded or omitted from interventions used to target relevant behaviors (e.g., within a chain analysis). It may be useful to include boredom explicitly in DBT interventions, for instance, by having patients track and rate boredom on their daily diary cards. This could help patients begin to recognize and accurately identify the experience of boredom, and identify links between boredom and engagement in behaviors such as binge eating, NSSI, and suicide ideation. Actively including boredom within treatment interventions may also provide an opportunity for patients and clinicians to collaboratively apply skills use to recognizing and mitigating feelings of boredom, as well as identifying when boredom is acting as a controlling variable for engagement in target behaviors.

Limitations

There are limitations to these studies that may be addressed in future research. In Study 1, data was conducted with a non-clinical sample of online workers. Thus, there are questions about generalizability to clinical samples, and about the reliability of the data. More research is needed with individuals who have been diagnosed with relevant personality disorders, and can speak more accurately to this experience. Given that Amazon’s M Turk provides a sample of random online responders, there are few ways to safeguard against bots, random responding and rushed responding. While these limitations cannot be fully addressed, Study 1 included several measures to mitigate these risks, such as an attention filter, an AI screener question, and–in the final wave– several reliability questionnaires to detect random responding and symptom over-reporting. Notably, in addition to data cleaning procedures, when controlling for random responding and over-reporting often associated with online samples, the relationships between boredom measures and BPD symptoms remained. Finally, as with all correlational research, this study cannot shed light on the causality of the relationships, and there are possible confounding variables not examined.

Study 2 addressed several of these limitations; the research was conducted with a clinical sample, and the data was collected live, as opposed to with an online sample. The relatively small sample size in Study 2 is a limitation. Relatedly, full data (Baseline, Midpoint, Endpoint) were not available for all participants, further reducing the sample size for longitudinal analyses, and precluding comparisons between the between-group analyses at each time point. Despite this, it is notable that associations between BPD and boredom were replicated in both studies, adding providing support for relationships between boredom and personality disorder symptoms. Additionally, only BPD symptoms were examined in Study 2. DBT has been shown to be effective for multiple diagnostic classifications (e.g., Bankoff et al., 2012), behaviors that fit into other trait domains within the AMPD (e.g., Wetterborg et al., 2020), and Study 1 showed that boredom was associated with both APD and level of personality functioning in addition to BPD symptoms. Study 2’s focus on BPD symptoms precludes an in-depth understanding of the role of boredom in treatment for cross-cutting personality traits and overall personality functioning. Future research should consider replicating and extending these findings using dimensional personality measures, as well as measures of general personality functioning, such as the LPFS.

Finally, in both studies, there are constraints on generality that must be considered when interpreting the findings. These constraints include that data were collected from samples of United States residents, and information regarding certain demographic characteristics (e.g., nativity status; immigration history) were unavailable. Thus, results may not generalize to individuals within different cultural contexts, and the influence of these demographic characteristics on our findings is not known. Similarly, Study 2 examined a DBT IOP, which contains several structural differences from comprehensive DBT; results may differ when examining programs with longer treatment durations and the inclusion of individual DBT sessions. Future research should aim to expand these findings in more diverse samples to enhance generalizability and better understand the impact of demographic factors on the observed relationships.

Conclusions

These findings, combined with past literature showing links between boredom and AMPD domains and facets, suggest that boredom has relevance to behavioral and treatment outcomes for individuals with high degrees of personality disorder traits. These implications may be particularly relevant for those displaying traits consistent with the AMPD classifications of BPD and APD. Given these overlaps, DBT may be an effective treatment for addressing boredom both within BPD (Masland et al., 2020) and across individuals with personality disorders more broadly. In these studies, we observed significant links between boredom proneness and recent boredom experiences, general personality functioning, AMPD personality traits, borderline symptom severity, and two highly relevant target behaviors in DBT (suicide ideation; NSSI). Moreover, baseline boredom proneness significantly predicted BPD symptom severity at the end of treatment, suggesting that incorporating interventions to address boredom within a DBT framework may affect treatment outcomes.

Public Health Significance Statement.

Boredom is an unpleasant feeling state that is often overlooked in clinical settings, despite associations with mental health issues and risky and dangerous behaviors such as self-injury. These studies demonstrated that high levels of boredom were associated with more severe personality disorder symptoms, risk-related behaviors, and predicted symptom severity at the end of an intensive treatment program. Addressing boredom in treatment settings may lead to improved treatment outcomes.

Funding

This work was supported by the National Institute of Mental Health [R01MH13172] and National Institute on Drug Abuse [5 T32 DA 22975-15].

Footnotes

Author Note

Margaret T. Davis is a member of the Educational Committee for Emotions Matter. This organization was not involved in the manuscript in any way, but serves the same population as the present study. The authors have no other disclosures to report.

Data from Study 1 is available from authors upon reasonable request. Data from Study 2 is not available due to the sensitive nature (i.e., data from a clinical program) of the data collected. Preliminary versions of results from Study 2 have been presented as a poster and included in an oral presentation.

References

  1. Abramson EE, & Stinson SG (1977). Boredom and eating in obsese and non-obsese individuals. Addictive Behaviors, 2, 181–185. [DOI] [PubMed] [Google Scholar]
  2. American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders: DSM-5 (5th ed.). American Psychiatric Association, Washington, DC. [Google Scholar]
  3. American Psychiatric Association. (2022). Diagnostic and statistical manual of mental disorders: DSM-5 (5th ed., text rev). American Psychiatric Association, Washington, DC. [Google Scholar]
  4. Bankoff SM, Karpel MG, Forbes HE, & Pantalone DW (2012). A systematic review of dialectical behavior therapy for the treatment of eating disorders. Eating disorders, 20(3), 196–215. [DOI] [PubMed] [Google Scholar]
  5. Ben-Zeev D, Young MA, & Depp CA (2012). Real-time predictors of suicidal ideation: mobile assessment of hospitalized depressed patients. Psychiatry research, 197(1–2), 55–59. [DOI] [PubMed] [Google Scholar]
  6. Bench SW, & Lench HC (2013). On the function of boredom. Behavioral sciences, 3(3), 459–472. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Blaszczynski A. (1990). Boredom Proneness in Pathological Gambling. Psychological Reports, 67(5). 10.2466/pr0.67.5.35-42 [DOI] [Google Scholar]
  8. Bohus M, Kleindienst N, Limberger MF, Stieglitz R-D, Domsalla M, Chapman AL, Steil R, Philipsen A, & Wolf M. (2009). The short version of the Borderline Symptom List (BSL-23): development and initial data on psychometric properties. Psychopathology, 42(1), 32–39. [DOI] [PubMed] [Google Scholar]
  9. Brotherton R, & Eser S. (2015). Bored to fears: Boredom proneness, paranoia, and conspiracy theories. Personality and Individual Differences, 80, 1–5. 10.1016/j.paid.2015.02.011 [DOI] [Google Scholar]
  10. Chan CS, Van Tilburg WA, Igou ER, Poon CY, Tam KY, Wong VU, & Cheung S. (2018). Situational meaninglessness and state boredom: Cross-sectional and experience-sampling findings. Motivation and Emotion, 42, 555–565. [Google Scholar]
  11. Chao T, Todman M, Foltin RW, Evans SM, & Bedi G. (2024). Laboratory method to induce state boredom increases impulsive choice in people who use cocaine and controls. Am J Drug Alcohol Abuse, 50(1), 42–53. 10.1080/00952990.2023.2248544 [DOI] [PubMed] [Google Scholar]
  12. Chapman AL, & Dixon-Gordon KL (2007). Emotional antecedents and consequences of deliberate self-harm and suicide attempts. Suicide and Life-Threatening Behavior, 37(5), 543–552. [DOI] [PubMed] [Google Scholar]
  13. Crockett AC, Myhre SK, & Rokke PD (2015). Boredom proneness and emotion regulation predict emotional eating. J Health Psychol, 20(5), 670–680. 10.1177/1359105315573439 [DOI] [PubMed] [Google Scholar]
  14. Dahlen ER, Martin RC, Ragan K, & Kuhlman MM (2004). Boredom proneness in anger and aggression: effects of impulsiveness and sensation seeking. Personality and Individual Differences, 37(8), 1615–1627. 10.1016/j.paid.2004.02.016 [DOI] [Google Scholar]
  15. Danckert J, & Merrifield C. (2018). Boredom, sustained attention and the default mode network. Exp Brain Res, 236(9), 2507–2518. 10.1007/s00221-016-4617-5 [DOI] [PubMed] [Google Scholar]
  16. Dimeff LA, & Linehan MM (2008). Dialectical behavior therapy for substance abusers. Addiction science & clinical practice, 4(2), 39. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Doering EL, Weybright E, Anderson AJ, Murphy K, & Caldwell L. (2023). Associations between trait boredom and frequency of cannabis, alcohol, and tobacco use in college students. Cannabis, 149–164. 10.26828/cannabis/2023/000177 [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Eastwood JD, Cavaliere C, Fahlman SA, & Eastwood AE (2007). A desire for desires: Boredom and its relation to alexithymia. Personality and Individual differences, 42(6), 1035–1045. 10.1016/j.paid.2006.08.027 [DOI] [Google Scholar]
  19. Eastwood JD, Frischen A, Fenske MJ, & Smilek D. (2012). The Unengaged Mind: Defining Boredom in Terms of Attention. Perspect Psychol Sci, 7(5), 482–495. 10.1177/1745691612456044 [DOI] [PubMed] [Google Scholar]
  20. Fahlman SA, Mercer-Lynn KB, Flora DB, & Eastwood JD (2013). Development and validation of the multidimensional state boredom scale. Assessment, 20(1), 68–85. 10.1177/1073191111421303 [DOI] [PubMed] [Google Scholar]
  21. Farmer R, & Sundberg ND (1986). Boredom proneness--the development and correlates of a new scale. Journal of personality assessment, 50(1), 4–17. [DOI] [PubMed] [Google Scholar]
  22. Goldberg Y, & Danckert J. (2013). Traumatic brain injury, boredom and depression. Behav Sci (Basel), 3(3), 434–444. 10.3390/bs3030434 [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Goldberg YK, Eastwood JD, LaGuardia J, & Danckert J. (2011). Boredom: An Emotional Experience Distinct from Apathy, Anhedonia, or Depression. Journal of Social and Clinical Psychology, 30(6), 647–666. 10.1521/jscp.2011.30.6.647 [DOI] [Google Scholar]
  24. Haktanır A, & Callender KA (2020). Meta-analysis of dialectical behavior therapy (DBT) for treating substance use. Research on education and psychology, 4(Special Issue), 74–87. [Google Scholar]
  25. Havermans RC, Vancleef L, Kalamatianos A, & Nederkoorn C. (2015). Eating and inflicting pain out of boredom. Appetite, 85, 52–57. 10.1016/j.appet.2014.11.007 [DOI] [PubMed] [Google Scholar]
  26. Hutsebaut J, Feenstra DJ, & Kamphuis JH (2016). Development and preliminary psychometric evaluation of a brief self-report questionnaire for the assessment of the DSM–5 level of Personality Functioning Scale: the LPFS brief form (LPFS-BF). Personality Disorders: Theory, Research, and Treatment, 7(2), 192. [Google Scholar]
  27. Isacescu J, & Danckert J. (2018). Exploring the relationship between boredom proneness and self-control in traumatic brain injury (TBI). Exp Brain Res, 236(9), 2493–2505. 10.1007/s00221-016-4674-9 [DOI] [PubMed] [Google Scholar]
  28. Isacescu J, Struk AA, & Danckert J. (2017). Cognitive and affective predictors of boredom proneness. Cogn Emot, 31(8), 1741–1748. 10.1080/02699931.2016.1259995 [DOI] [PubMed] [Google Scholar]
  29. Kass SJ, Wallace C, & Vodanovich SJ (2003). Boredom proneness and sleep disorders as predictors of adult attention deficit scores. Journal of Attention Disorders, 7(2), 83–91. [DOI] [PubMed] [Google Scholar]
  30. Kılıç A, Van Tilburg WA, & Igou ER (2020). Risk-taking increases under boredom. Journal of Behavioral Decision Making, 33(3), 257–269. [Google Scholar]
  31. Kleindienst N, Jungkunz M, & Bohus M. (2020). A proposed severity classification of borderline symptoms using the borderline symptom list (BSL-23). Borderline Personality Disorder and Emotion Dysregulation, 7(1). 10.1186/s40479-020-00126-6 [DOI] [Google Scholar]
  32. Klonsky ED (2008). What is emptiness? Clarifying the 7th criterion for borderline personality disorder. Journal of Personality Disorders, 22(4), 418–426. 10.1521/pedi.2008.22.4.418 [DOI] [PubMed] [Google Scholar]
  33. Koval SR, & Todman M. (2015). Induced Boredom Constrains Mindfulness: An Online Demonstration. Psychology and Cognitive Sciences - Open Journal, 1(1), 1–9. 10.17140/pcsoj-1-101 [DOI] [Google Scholar]
  34. Krotava I, & Todman M. (2014). Boredom severity, depression and alcohol consumption in belarus. Journal of Psychology and Behavioral Science, 2(1), 73–83. [Google Scholar]
  35. Lee FKS, & Zelman DC (2019). Boredom proneness as a predictor of depression, anxiety and stress: The moderating effects of dispositional mindfulness. Personality and Individual Differences, 146, 68–75. 10.1016/j.paid.2019.04.001 [DOI] [Google Scholar]
  36. LePera N. (2011). Relationships between boredom proneness, mindfulness, anxiety, depression, and substance use. The New School Psychology Bulletin, 8(2), 15–25. [Google Scholar]
  37. Linehan M. (1993). Cognitive-behavioral treatment of borderline personality disorder. Guilford press. [Google Scholar]
  38. Lissak S, Ophir Y, Tikochinski R, Brunstein Klomek A, Sisso I, Fruchter E, & Reichart R. (2024). Bored to death: Artificial Intelligence research reveals the role of boredom in suicide behavior. Frontiers in psychiatry, 15, 1328122. [Google Scholar]
  39. Lorenzi CA, de Jong DC, & Faulkenberry RS (2024). The Roles of Affective Lability, Boredom, and Mindfulness in Predicting Number of Sex Partners within Women. Sexes, 5(3), 262–274. 10.3390/sexes5030020 [DOI] [Google Scholar]
  40. Malkovsky E, Merrifield C, Goldberg Y, & Danckert J. (2012). Exploring the relationship between boredom and sustained attention. Exp Brain Res, 221(1), 59–67. 10.1007/s00221-012-3147-z [DOI] [PubMed] [Google Scholar]
  41. Masland SR, Shah TV, & Choi-Kain LW (2020). Boredom in Borderline Personality Disorder: A Lost Criterion Reconsidered. Psychopathology, 53(5–6), 239–253. 10.1159/000511312 [DOI] [PubMed] [Google Scholar]
  42. Mercer KB, & Eastwood JD (2010). Is boredom associated with problem gambling behaviour? It depends on what you mean by ‘boredom’. International Gambling Studies, 10(1), 91–104. [Google Scholar]
  43. Morey LC (2017). Development and initial evaluation of a self-report form of the DSM–5 Level of Personality Functioning Scale. Psychological Assessment, 29(10), 1302. [DOI] [PubMed] [Google Scholar]
  44. Moynihan AB, Igou ER, & van Tilburg WAP (2017). Boredom Increases Impulsiveness. Social Psychology, 48(5), 293–309. 10.1027/1864-9335/a000317 [DOI] [Google Scholar]
  45. Moynihan AB, van Tilburg WA, Igou ER, Wisman A, Donnelly AE, & Mulcaire JB (2015). Eaten up by boredom: consuming food to escape awareness of the bored self. Front Psychol, 6, 369. 10.3389/fpsyg.2015.00369 [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Mugon J, Struk A, & Danckert J. (2018). A Failure to Launch: Regulatory Modes and Boredom Proneness. Front Psychol, 9, 1126. 10.3389/fpsyg.2018.01126 [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Nederkoorn C, Vancleef L, Wilkenhoner A, Claes L, & Havermans RC (2016). Self-inflicted pain out of boredom. Psychiatry Res, 237, 127–132. 10.1016/j.psychres.2016.01.063 [DOI] [PubMed] [Google Scholar]
  48. Posner K, Brown GK, & Stanley B. (2011). The Columbia-Suicide Severity Rating Scale: initial validity and internal consistency findings from three multisite studies with adolescents and adults. American Jouranl of Psychiatry, 162(12), 1266–1277. 10.1176/appi.ajp.2011.10111704 [DOI] [Google Scholar]
  49. Struk AA, Carriere JS, Cheyne JA, & Danckert J. (2017). A short boredom proneness scale: Development and psychometric properties. Assessment, 24(3), 346–359. [DOI] [PubMed] [Google Scholar]
  50. Tam KY, Van Tilburg WA, Chan CS, Igou ER, & Lau H. (2021). Attention drifting in and out: The boredom feedback model. Personality and Social Psychology Review, 25(3), 251–272. [DOI] [PubMed] [Google Scholar]
  51. Todman M. (2003). Boredom and psychotic disorders: Cognitive and motivational issues. Psychiatry, 66(2), 146–167. [DOI] [PubMed] [Google Scholar]
  52. Todman M. (2013). The dimensions of state boredom: Frequency, Duration, Unpleasantness, Consequences, and Causal Attributions. Educational Reserch International, 1(1), 32–40. [Google Scholar]
  53. Vodanovich SJ, Verner KM, & Gilbride TV (1991). Boredom proneness: its relationship to positive and negative affect. Psychological Reports, 69, 1139–1146. [DOI] [PubMed] [Google Scholar]
  54. Wetterborg D, Dehlbom P, Långström N, Andersson G, Fruzzetti AE, & Enebrink P. (2020). Dialectical behavior therapy for men with borderline personality disorder and antisocial behavior: A clinical trial. Journal of Personality Disorders, 34(1), 22–39. [DOI] [PubMed] [Google Scholar]
  55. Yeung RC, Danckert J, van Tilburg WAP, & Fernandes MA (2024). Disentangling boredom from depression using the phenomenology and content of involuntary autobiographical memories. Sci Rep, 14(1), 2106. 10.1038/s41598-024-52495-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. Yusoufzai MK, Vancleef L, Lobbestael J, & Nederkoorn C. (2022). Painfully bored: the role of negative urgency and history of Non-Suicidal Self-Injury in Self-Administering painful stimuli. Motivation and Emotion, 46(5), 689–701. 10.1007/s11031-022-09970-1 [DOI] [Google Scholar]

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