Sexual Boredom Inventory (SBI): Development and Initial Validation

Abstract

This study presents the development and validation of the Sexual Boredom Inventory (SBI), a 6-item measure assessing sexual boredom as a temporary, context-dependent state. Initial items were drafted from data obtained through qualitative analysis, and the SBI was tested using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) with a sample of adults reporting on their sexual experiences in the past month. A single-factor model was found to be the best fit, with four items dropped during refinement. The SBI demonstrated good internal consistency (Cronbach’s α = .88) and evidence of discriminant validity, with significant negative correlations to sexual pleasure and well-being. Additionally, the SBI was positively correlated with attention difficulties and impulsivity, highlighting a link between sexual boredom and ADHD. Findings suggest that sexual boredom, as a transient experience, is associated with negative sexual outcomes. Further research should confirm these relationships and potential interventions. The SBI can serve as a valuable tool for assessing recent sexual boredom and differentiating it from other sexual concerns.

Introduction

Sexual pleasure and wellbeing are important health considerations for overall health and well-being (Ford et al., 2019), and are affected by many factors, including sexual boredom (de Oliveira et al., 2022; Farvid & Braun, 2017). Sexual boredom was initially operationalized as the trait-tendency of being bored with the sexual aspects of one’s life (Watt & Ewing, 1996). A later definition was offered based on qualitative research with 12 men that described sexual boredom as a temporary experience consisting of boredom with boring sex – fleeting dull, mechanical, or over-rehearsed sex (Tunariu & Reavey, 2003). Participants in this study portrayed sexual boredom as something inevitable in long-term sexually-exclusive relationships, yet intolerable and potentially managed if couples endorsed sex positive strategies to counteract it. In a later study using thematic analysis with a large community sample of people with diverse identities, it was found that sexual boredom could fluctuate and even promote adjustment in sexual relationships if leading to the introduction of novelty (de Oliveira et al., 2021). On the other hand, according to these participants, sexual boredom, if not addressed, could lead to dissatisfying sex and to the progressive waning of sexual desire. Despite the apparent mutability in sexual boredom identified in qualitative research, there is not a measure that captures a state of sexual boredom: the temporary experience of sexual boredom, rather than the disposition to feel sexual boredom.

General boredom (not sexual boredom) refers to the uncomfortable feeling of wanting, but being unable to, engage in satisfying activity (Eastwood et al., 2012; Fahlman et al., 2013), and is often triggered when the environment is perceived as unstimulating, repetitive, or monotonous (Hill & Perkins, 1985; Mikulas & Vodanovich, 1993; Perkins & Hill, 1985; Zuckerman, 1979). Some authors do not conceive of boredom as an emotion (Danckert & Eastwood, 2020). They state that boredom, unlike other emotions, does not take place in response to a specific trigger to serve basic needs. Boredom is, instead, a feeling that is not necessarily linked to an external event but is a felt experience of an ongoing cognitive process (Eastwood & Gorelik, 2019). It has been proposed that boredom occurs because evolution shaped us to experience the discomfort of boredom when our cognitive resources are underutilized so that we seek mental engagement (Danckert & Eastwood, 2020). These authors defend that there is only one type of boredom and that arises when a desire conundrum meets an unoccupied mind. Each of these mechanisms reinforces the other and when they occur, independently of what is causing them, boredom is experienced. This suggests that context-specific boredom, such as leisure, work, relational, or sexual boredom, follow the same mechanisms of general boredom. Some people might be more prone to experience boredom-state; that is, they have a trait that predisposes them to more intense or more frequent experiences of boredom (Farmer & Sundberg, 1986). Individuals with this tendency might also be more likely to experience depression, hopelessness, loneliness, and distractibility, as well to perceive common tasks as effortful (Farmer & Sundberg, 1986). Based on what has been described, boredom is usually considered a negative or aversive state (Mikulas & Vodanovich, 1993; Zuckerman, 1979).

Grounded in the framework of general boredom, sexual boredom could be conceptualized as a dimension of general boredom that combines wanting but being unable to get satisfying or pleasurable sex due to experiencing sex as unstimulating, repetitive, or monotonous. While sexual boredom may contribute to sexual dissatisfaction (one’s evaluation of personal sexual experiences) if left unresolved, they are not synonymous. These notions are backed up by the research of Rosa et al. (2019), which showed that the more individuals experience sexual boredom, the more they desire to engage in sexual novelty, but the less willing they are to initiate or comply with sexual novelty. In addition, it is plausible that when sexual stimuli are not interesting or captivating (i.e., stimuli are perceived as boring), sex might feel meaningless or purposeless and our sexual potential could be unfulfilled as our sexual resources are underutilized (de Oliveira, 2023). In this view, sexual boredom is a perceived negative experience that signals the need or desire for change and can result – or not – in the activation of resources to attempt to mitigate its discomfort. Accordingly, sexual boredom is a state that some individuals or relationships can revisit occasionally and that is not necessarily a consequence of their disposition to sexual boredom. The disposition or tendency to experience sexual boredom is measured by the SBS – Sexual Boredom Scale (Watt & Ewing, 1996) and assesses specifically one’s tolerance for sexual monotony and monogamy and need for sexual stimulation. The short-term, situation dependent experience of sexual boredom is not gauged by this scale, which in our understanding entails the need for a state measure of sexual boredom.

Trait measures, such as the SBS, have the ability assess stable and long-term patterns and to predict behavior across different contexts and over time. However, they can miss the nuances of situational influences that are particularly relevant for sexuality. State measures, on the other hand, can offer detailed and context-sensitive insights, allowing for the assessment of changes over time, which is particularly useful in clinical and dynamic research settings. Therefore, a measure of sexual boredom that focuses on the individual’s current sexual experiences might facilitate cross-sectional research by exploring mechanisms and connections with other contextual factors at play, as well as longitudinal research by allowing for the assessment of changes across time. Clinical uses of such a measure might include the refinement of assessment tools and differential diagnosis, as it could help to clarify sexual problems related to sexual desire and sexual satisfaction.

Current study

This paper aims to fill a significant gap in both research and clinical practice with the development and initial validation of the Sexual Boredom Index (SBI) – a state measure of sexual boredom that is not dependent on relationship structure or status and is understood as a temporary, situation-dependent, and fluctuating sexual experience. Specifically, this is a measure of sexual boredom that can vary based on the context or conditions of a given sexual experience, including different partners, activities, and moods. It was hypothesized that higher scores on the SBI would be negatively associated with positive outcomes of sexual activity, such as sexual pleasure and well-being, as indicated by previous research. Due to the link between general boredom and attention and impulsivity, it was hypothesized that the SBI to show a positive relationship with attention deficit/hyperactivity disorder (ADHD).

Methods

Procedure

The current study was part of a larger study using the Sexual Health Assessment of Practices and Experiences questionnaire (SHAPE) developed by the World Health Organization (WHO). The overall purpose of SHAPE is to describe comparable sexual health related outcomes and perceptions in the general population to facilitate harmonization of data across the globe on the topics of sex, sexuality, and sexual rights, and therefore requires the use of a large-scale demographically representative samples. To comply with this requirement recruitment was conducted to through Prodege (https://www.prodege.com/), a market research firm that utilizes pre-recruited panels to collect data. Prodege was responsible for screening the sample based on pre-established inclusion and exclusion criteria. To ensure high quality data, Prodege utilizes dual opt-in email verification, member registration with account verification, and early fraud detection. Additionally, Prodege has ongoing GEO-IP checks, bot traps, pattern detection, and continual monitoring for suspicious activity. Prodege employs quality control that detects bots, survey farms, and multi-tasking survey respondents. Inclusion criteria included being at least 18 years of age, a current resident of the United States, and English-language speaker.

Participants answered SHAPE’s self-report survey and additional measures online via QualtricsXM. Participants were asked to take the survey independently and in private, as well as provide informed consent before answering the survey. The study’s consent form included the primary researchers’ contact details and key information about the study, including potential risks, compensation, and details about future dissemination. Each participant was compensated with a $10 gift card for their participation through Prodege. All sample data was de-identified and participants were not required to sign to consent to avoid generating identifying information. These procedures were approved by the Ethics Committee of the University of Minnesota.

Responses were scrutinized for repeated entries, invalid responses or inconsistencies, and missing data. Even though conditions for participating emphasized that participants needed to be at least 18 years old, some participants stated they were underage and their data were therefore excluded. Data from participants who abandoned the study before completing the additional measures were not considered. As a result, from an original pool of 2902, 463 participants were excluded, making our total sample of 2555.

Participants

A total of 2555 English speaking US residents with ages between 18 and 94 years old (M = 47.26, SD = 16.91). Of these, 56.3% identified as women, 42.8% as men, 3% in other way, 0.4% preferred not to say. The majority of participants (70.7%) identified as straight, with 16% identifying as bisexual and 9.2% as gay or lesbian. 57.7% of participants reported to be cohabiting with a partner, and 45.3% to be were married. 39.7% were educated to Bachelor’s degree or higher. White ethnicity was expressed by 76%, Black African American by 11.1%, Hispanic by 11%, Asian by 5.8%, American Indian or Alaska Native by 3.1%, and Native Hawaiian or other Pacific Islander by 0.5%. Finally, participants indicated to be Christian (30.7%), non-religious or spiritual (19.4%), Catholic (17.2%), Protestant (10%), Agnostic (9.7%), Atheist (7.9%), Jewish (3.2%), Buddhist (1.6%), Muslim (1%), and Hindu (0.4%). See Table 1 for full demographic characteristics of the sample.

Table 1.

Participant demographics.

	Total sample N (%) 2555 (100)	EFA sample N (%) 1262 (49.4)	CFA sample N (%) 1293 (50.6)
Sex
Male	1101 (43.1)	537 (42.6)	564 (43.6)
Female	1431 (56.0)	709 (56.2)	722 (55.8)
Other	4 (.2)	3 (0.2)	1 (.01)
Prefer not to say	11 (.4)	6 (0.5)	5 (0.4)
Missing	8 (0.3)	7 (0.6)	1 (0.1)
Gender
Man	1094 (42.8)	539 (42.7)	555 (42.9)
Woman	1370 (53.6)	675 (53.4)	696 (53.8)
Other identity	77 (3.0)	42 (3.3)	35 (2.7)
Prefer not to say	10 (0.4)	6 (0.5)	4 (0.3)
Missing	4 (0.2)	1 (0.1)	3 (0.2)
Sexual orientation
Gay or lesbian	236 (9.2)	124 (9.8)	112 (8.7)
Straight	1806 (70.7)	888 (70.4)	918 (71.0)
Bisexual	408 (16.0)	188 (14.9)	220 (17.0)
Other	66 (2.6)	39 (3.1)	27 (2.1)
Prefer not to say	18 (0.7)	12 (1.0)	6 (0.5)
Don’t know	19 (0.7)	10 (0.8)	9 (0.7)
Missing	2 (0.1)	1 (0.1)	1 (0.1)
Marital Status
Never married	1086 (42.5)	526 (41.7)	560 (43.3)
Married	1158 (45.3)	581 (46.0)	577 (44.6)
Separated	46 (1.8)	24 (1.9)	22 (1.7)
Divorced	211 (8.3)	104 (8.2)	107 (8.3)
Widowed	30 (1.2)	15 (1.2)	15 (1.2)
Prefer not to say	24 (0.9)	12 (1.0)	12 (0.9)
Race/Ethnicity
American Indian/Alaska Native	80 (3.1)	40 (3.1)	40 (3.1)
Asian	147 (5.8)	73 (5.8)	74 (5.7)
Black or African American	283 (11.1)	123 (10.1)	156 (12.1)
Native Hawaiian or pacific	12 (0.5)	6 (0.5)	6 (.05)
Islander
White	1942 (76.0)	961 (76.1)	981 (75.9)
Other	29 (1.1)	14 (1.1)	15 (1.2)
Hispanic/Latinx	280 (11.0)	138 (10.9)	142 (11.0)

Note. Ages are: Total Sample (M = 47.26, SD = 16.91); EFA Sample (M = 47.39, SD = 16.72); CFA Sample (M = 47.13, SD = 17.10).

Development of the Sexual Boredom Index

The SBI was developed based on a previous qualitative study of de Oliveira et al. (2021) exploring the definitions of sexual boredom in a community sample recruited online. Participants in this study included 653 individuals aged 18 to 75 (M = 33.14; SD = 9.01) of multiple genders, sexual orientations, and relationship types. Their written responses to the question “What is sexual boredom for you?” were analyzed via thematic analyses identifying three main themes: definitions of sexual boredom, predisposing and maintenance factors of sexual boredom, and managing of sexual boredom. The items for the SBI scale were generated based on the definitions of sexual boredom findings from this qualitative study, with the original authors’ permission.

Participants in the study of de Oliveira et al. (2021) defined sexual boredom as a relational experience that combined elements of sexual routine, lack of satisfaction or pleasure, low sexual interest or infrequent sex, and lack of emotional connection during sex. In the current study, we generated the initial list of items using the language expressed from participants in the qualitative findings and three experts iteratively engaged in multiple rounds of discussion to refine individual item wording. The final consensus of this collaborative process resulted in a total of 10 items, provided in Table 2. These aimed to translate aspects of sexual monotony and routine, of interest and excitement, and of stimulation and predictability. Two items (3 and 6) were phrased positively in opposition to the remaining items and therefore were reverse coded. Participants were asked to reflect on their sexual activities over the past month on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree) to assess their current levels of sexual boredom.

Table 2.

Sexual boredom Index initial items, means, variances, corrected item-total correlation and inter-item correlations.

Item (M, s2, corrected item-total correlation)	1.	2.	3.	4.	5.	6.	7.	8.	9.
1. Felt bored when having sex (2.18, 1.19, .73)	-
2. Experienced sex as monotonous (2.42, 1.30, .68)	.65	-
3. Experienced sex as exciting (2.23, 1.06, .46)	.49	.35	-
4. Wished sex were more interesting (2.76, 1.22, .61)	.49	.51	.23	-
5. Felt sex was predictable (2.86, 1.15, .59)	.43	.45	.18	.62	-
6. Felt sex was stimulating (2.19, 1.00, .47)	.44	.33	.75	.20	.18	-
7. Experienced sex as mechanical (2.53, 1.14, .71)	.53	.55	.26	.54	.55	.29	-
8. Felt disconnected during sex (2.34, 1.23, .74)	.62	.56	.37	.49	.48	.38	.62	-
9. had sex because it was routine (2.35, 1.22, .71)	.53	.49	.25	.45	.50	.27	.61	.62	-
10. Has sex because it was expected of me (2.19, 1.00, .64)	.48	.45	.23	.42	.44	.26	.54	.56	.74

Note. All analyses conducted with the EFA sample. Items 3 and 6 were reverse-scored prior to analysis.

Measures to assess validity

Natsal sexual well-being (Natsal-SW)

To contribute to discriminant validity, the NATSAL-SW (Mitchell et al., 2023) is a 13-item measure of sexual wellbeing capturing aspects of security and safety, respect, self-esteem, resilience, forgiveness of past sexual experiences, self-determination, and comfort regarding sexual experience and near-future expectation. Responses are given on a 5-point Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree). Total scores range from 13 to 65, with higher scores indicating greater sexual well-being. In the present study, the scale demonstrated a good internal consistency, with a Cronbach’s alpha of .82.

Sexual pleasure scale (SPS)

To contribute to discriminant validity, the SPS was utilized. It was initially developed by Sanchez et al. (2005) with a sample of college students and later validated by Pascoal et al. (2016) with a sample of coupled heterosexual individuals. This self-report instrument was designed to measure sexual pleasure, comprising three items that evaluate how pleasurable individuals find sexual relations, activities, and intimacy. Responses are given on a 7-point Likert scale, ranging from 1 (not pleasurable) to 7 (extremely pleasurable). Total scores range from 3 to 21, where higher scores indicate greater sexual pleasure. The scale demonstrated strong internal consistency in the aforementioned studies, with Cronbach’s alphas of .84 and of .94, respectively.

Adult ADHD self-report scale (ASRS)

The final measure for discriminant validity was the ASRS (Kessler et al., 2005). This was developed by WHO and is an 18-item self-report screening scale of adult attention deficit/hyperactivity disorder for the general population. Each question focuses on a symptom that occurred over the past 6 months on a 5-point Likert scale with the following response options: never (0), rarely (1), sometimes (2), often (3), and very often (4). The questionnaire includes subscales of Inattention and of Hyperactivity-Impulsivity, comprising 9 items each. Total scores range from 0 to 36 for each subscale, with higher scores indicating higher levels of inattention or hyperactivity. Inattention includes two items referring to the experience of general boredom (1—“How often do you make careless mistakes when you have to work on a boring or difficult project?”; 2—“How often do you have difficulty keeping your attention when you are doing boring or repetitive work?”) that will be used as an extra validity control. In the present study, Cronbach’s alphas were .93 for inattention, .91 for hyperactivity-impulsivity, and .96 for the total score.

Data analysis

The items and factor structure for the SBI were assessed through several steps. First, the total sample was used to examine item means and variances, inter-item, correlations, and correlations between each item and the item-total remainder score to identify items that capture the range of responses, discriminate between participants, and relate reliably to one another and the total score. Initial item analyses were conducted using SPSS version 28.

After evaluating items, the data was randomly split into two halves. To identify the number of factors present in the data, exploratory factor analysis (EFA) with Geomin oblique factor rotation and maximum likelihood estimation was conducted with one half of the using Mplus version 8.11 (Muthén & Muthén, 2017). In the EFA, eigenvalues and parallel analysis were assessed to identify the number of factors (DeVellis, 2012; Hayton et al., 2004). While the eigenvalue > 1 rule is often interpreted for determining the number of factors, this is unreliable and may result in too many factors identified in the model (Bandalos & Boehm-Kaufman, 2009). In parallel analysis, a matrix of randomly generated data is compared to the observed data, with eigenvalues generated for each. The number of factors in the observed data is identified by eigenvalues greater than the eigenvalues in the randomly generated dataset. After identifying the number of factors, factor loadings were examined. In determining items to omit with standardized factor loadings below .40 and less than .20 difference between factors (if loading onto multiple factors) were considered for omission from the scale.

Once the overall factor structure was identified, a confirmatory factor analysis (CFA) approach was conducted with the EFA sample to assess model fit and factor loadings. Several indicators of model fit were assessed to evaluate the model. These include the χ² statistic, comparative fit index (CFI), Tucker-Lewis Index (TLI), root mean squared error of approximation (RMSEA), and the standardized root mean square residual (SRMR). For the χ² statistic, a sample’s covariance matrix is compared to the matrix of the estimated model, and good fit is indicated by a non-significant result. While this reflects that the estimated model does not significantly differ from the observed data, the χ² statistic is sensitive to sample size and can detect small differences with a large enough sample (Ullman, 2013). For CFI, values range from 0 to 1; generally, excellent fit is indicated by values greater than .95 and good fit is indicated by values greater than .90 (Hu & Bentler, 1999). Similarly, TLI values range from 0 to 1, with TLI values greater than .90 indicated adequate fit (Bentler & Bonett, 1980). Regarding RMSEA, perfect model fit is indicated by a value of 0, while excellent fit is indicated by values less than .06; poor fit is indicated by values greater than .10. Perfect fit for SRMR is similarly indicated by a value of 0, with good fit indicated by values of .05 or less, adequate fit by .08 or less, and poor fit greater than .10. Modification indices were also explored to identify items that were strongly correlated with one another. Items were considered for removal from the exploratory CFA if they correlated strongly with another and appeared to have similar wording or meaning. The model was tested iteratively, making one adjustment at a time, until the final model demonstrated adequate fit and factor structure.

After testing the exploratory model, the second random half of the data was used for confirmatory factor analysis (CFA) to test the final model using Mplus version 8.11. Similar to the exploratory CFA, multiple indices of model fit were examined to assess model fit and factor structure (see above). After conducting the CFA, inter-item reliability was assessed using Cronbach’s alpha. The validity and utility of the SBI was explored by correlating the final scale with the Natsal-SW, SPS, and ASRS.

Results

The Sexual Boredom Index item means, variances, inter-item correlations, and total remainder score correlations are presented in Table 2. Broadly, item means and variances were similar, and most items were correlated moderately-to-strongly with each other. However, items 3 and 6 demonstrated strong correlations with each other and small correlations with other items. Similarly, all items exhibited moderate-to-strong correlations with the item-total remainder score, although items 3 and 6 had the lowest of these correlations (.46 and .47, respectively). Initially, all items were entered into the EFA, which tested models of 1 to 3 factor and Table 3 presents results of eigenvalues and parallel analysis for the EFA. The initial EFA with all 10 items indicated a 2-factor model best fit the data; however, most items loaded onto factor 1 and only items 3 and 6 loaded onto factor 2, as demonstrated by Table 3. Given the performance of items 3 and 6 (i.e., low inter-item correlations with other items, lower item-total remainder score, and loading onto their own factor), these items were dropped from further analysis and the EFA conducted again. Results indicated that a single-factor solution best fit the data and all items loaded significantly onto the single factor above the .40 threshold.

Table 3.

Sexual boredom Index exploratory factor analysis.

	Factor 1	Factor 2	Factor 3
EFA 1: All Items
Eigenvalues (parallel Analysis)	5.16 (1.14)	1.46 (1.10)	0.79 (1.07)
Factor Loadings
1.	.72	.54	-
2.	.69	.39	-
3.	.34	.93	-
4.	.67	.25	-
5.	.67	.19	-
6.	.35	.81	-
7.	.78	.30	-
8.	.77	.42	-
9.	.80	.27	-
10.	.73	.25	-
EFA 2: omit Items 3 & 6
Eigenvalues (parallel Analysis)	4.74 (1.12)	0.79 (1.08)	.71 (1.04)
Factor Loadings
1.	.73	-	-
2.	.70	-	-
4.	.67	-	-
5.	.66	-	-
7.	.78	-	-
8.	.78	-	-
9.	.79	-	-
10.	.73	-	-

Note. Results of parallel analysis indicate a 2-factor solution fit the data best in EFA 1 and a 1-factor solution fit the data best in EFA 2. Reported factor loadings are standardized. All factor loadings are significant at p < .05.

A CFA approach with modification indices was then conducted with the EFA sample to assess model fit. Results of model fit are presented in Table 4 and item factor loadings are presented in Table 4. The initial model did not fit the data well, and a review of modification indices suggested strong covariance between items 9 and 10 and between items 4 and 5. Between items 9 and 10, item 10 had the lower factor loading and were subsequently dropped from the model, resulting in improved, but not acceptable, model fit. Given the large covariance between items 4 and 5, and item 5 having a slightly lower factor loading than item 4, item 5 was dropped from the model. This resulted in improvement of model fit and acceptable fit for CFI, TLI, and SRMR, and slightly below adequate fit for RMSEA.

Table 4.

Exploratory CFA approach.

	E-cFA 1	E-cFA 2	E-cFA 3
Model Fit
X2	602.61, p < .001	313.13, p < .001	143.30, p < .001
CFI	.89	.93	.96
TLI	.85	.90	.94
RMSEA	.15	.13	.11
SRMR	.05	.04	.03
Factor Loadings
1.	.73	.75	.77
2.	.70	.72	.73
4.	.67	.69	.66
5.	.66	.67	-
7.	.78	.78	.77
8.	.78	.78	.80
9.	.79	.74	.73
10.	.73	-	-

Note. A CFA approach was conducted with the EFA sample to examine improvement in model fit. Standardized factor loadings are reported. All factor loadings p < .001. The final model as determined by acceptable fit across multiple indices is identified in bold font.

After conducting the EFA and exploratory CFA, a final CFA was conducted with the second random-half of the total sample (i.e., a new sample). Results of model fit are presented in Table 5. Overall, model fit was adequate for most indices, including CFI, TLI, and SRMR, and slightly below adequate model fit for RMSEA. All factor loadings were acceptable, and the final model is presented in Table 5. Inter-item reliability as assessed by Cronbach’s alpha was good (.88). Regarding validity, the final Sexual Boredom Index was significantly correlated with Natsal-SW (r = −.48, p < .001); SPS (r = −.44, p < .001); and ASRS Inattention (r = .30, p < .001), ASRS Hyperactivity (r = .29, p < .001), and ASRS Total (r = .30, p < .001).

Table 5.

Confirmatory factor analysis.

	CFA
Model Fit
X2	171.91, p < .001
CFI	.96
TLI	.93
RMSEA	.12
SRMR	.03
Factor Loadings
1. Felt bored when having sex	.78
2. Experienced sex as monotonous	.70
4. Wished sex were more interesting	.64
7. Experienced sex as mechanical	.76
8. Felt disconnected during sex	.84
9. Had sex because it was routine	.73

Note. The CFA was conducted with the CFA sample. Standardized factor loadings are reported. All factor loadings p < .001.

Discussion

This article presents the development and validation studies of the SBI, a 6-item measure of sexual boredom with sexual activity in the last month. Scale development and evaluation were carried out on an initial set of 10 items based on previous qualitative analysis that identified several features of sexual boredom. A single-factor model emerged as the best fit, and 4 of the original items were dropped. The scale demonstrated good reliability (Cronbach’s alpha = .88) and evidence of discriminant validity, as showed by the significant, negative correlations with sexual pleasure and sexual well-being. The negative relationship between the tendency to sexual boredom and sexual pleasure was previously identified in research (de Oliveira et al., 2022). These results suggest that the experience of sexual boredom, even if temporary, is linked with negative outcomes. Moreover, sexual boredom was positively correlated with difficulties related to attention and impulsivity, similar to general boredom (Farmer & Sundberg, 1986; Zuckerman, 1979).

The final SBI includes aspects of sexual monotony, routine, lack of interest, and disconnection during sex. Disconnection during sex was described in the qualitative study of de Oliveira et al. (2021) as the lack of an emotional connection during sex. In the context of the SBI, this might also include distractibility, especially because our results suggest a relationship with inattention. Further research should investigate the role of ADHD in sexual boredom and test if interventions aimed at attention, including mindfulness, could potentially help counteract sexual boredom. In addition, because sexual boredom was correlated with impulsive hyperactivity, it may be worthwhile to explore the relationship between sexual boredom and compulsive or risky sexual behavior. Previous research on boredom proneness and compulsive sexual behavior has supported a moderate-to-strong relationship between these variables (e.g., Coleman et al., 2023). Other studies have found that general boredom was connected with impulsivity through meaninglessness (Moynihan et al., 2017). Future research could explore how sexual boredom over the last 30 days relates with compulsive sexual behavior to further understand the mechanisms at play in compulsive sexual behavior or other risky sexual behaviors. Finally, researchers will further need to clarify whether there are gender differences in the experiences of sexual boredom and how this might be connected to structural inequalities and pressures (e.g., to perform or to get pregnant). Past research found men to present with higher tendency to experience sexual boredom (de Oliveira et al., 2023; Watt & Ewing, 1996), yet the context in which the differences among genders occur still requires exploration.

Sexual boredom, as a dimension of general boredom, is the cognitive-emotional process involving wanting but being unable to have pleasurable or meaningful sex due to a combination of experiencing sex as monotonous and uninteresting and feeling disconnected during sex. Boredom is in some ways an unmet need. This temporary experience may or may not be linked to the tendency to feel boredom or sexual boredom, and it may be frequent or infrequent depending on context. A consequence of sexual boredom could be the behavioral activation of strategies to counteract this state as, similarly to general boredom, this is uncomfortable and signals a need for higher engagement and, possibly, change.

The SBI was generated based on individuals’ perspectives on sexual boredom and not solely on experts’ views of the construct being measured. Further, scale evaluation and refinement was conducted with a large sample reflecting U.S. demographics. However, the fact that this study was integrated in a broader study meant that we did not have the opportunity to evaluate all forms of validation, including with some converging measures that would have been helpful. Specifically, the Sexual Boredom Scale, previously developed to measure sexual boredom-trait scale could have conveniently been use to attest convergent validity. In addition, construct validity was not assessed via test/re-test as participants were recruited for one-time participation. However, providing other researchers the opportunity to use this scale in their work and further validate it on different samples using different measures is an important contribution to the field and will help advance our scientific understanding of sexual boredom.

Sexual boredom intersects with broader emotional, attentional, and relational domains, making it a key focus in clinical practice. The Sexual Boredom Inventory (SBI) can be a valuable tool in clinical assessment, aiding in the identification of recent or current sexual boredom and contributing to the differential diagnosis of sexual dysfunction. Given its association with lower sexual pleasure and well-being, addressing sexual boredom in therapy is likely to enhance overall sexual health.

The findings related to ADHD and distractibility offer new treatment avenues. Since sexual boredom is linked to attention difficulties, mindfulness-based interventions may prove beneficial. Clinicians could focus on helping clients cultivate present-moment awareness during sexual activity, which may reduce distractibility and alleviate sexual boredom. The novel link between ADHD and sexual boredom suggests that clinicians should consider screening for ADHD in clients who report significant sexual boredom, particularly when accompanied by distractibility or impulsivity. Tailoring interventions to improve attention regulation may lead to better outcomes in these cases.

Additionally, the correlation between sexual boredom, impulsivity, and potentially compulsive or risky sexual behavior highlights the need for careful assessment. Clinicians should be mindful of these links and work to prevent negative outcomes by identifying and addressing the root causes of boredom-related impulsivity. The SBI’s identification of emotional disconnection during sex underscores the importance of relational and emotional intimacy in sexual satisfaction. Therapists could work to strengthen emotional bonds between partners, which may alleviate feelings of boredom and enhance sexual fulfillment. Emotionally focused therapy (EFT) could be a particularly useful approach in restoring intimacy and connection.

Finally, sexual boredom may also serve as a catalyst for positive change. Rather than viewing boredom as purely negative, therapists can guide clients to see it as a signal for higher engagement and growth. Encouraging exploration of new forms of sexual engagement, communication, and novelty in relationships could break the cycle of monotony.

Data availability statement

Data associated with this paper can be accessed per reasonable request to the corresponding author following publication.