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. 2023 Jun 2;28(12):1131–1142. doi: 10.1177/13591053231177254

Dysmenorrhea and psychological wellbeing among females with attention deficit hyperactivity disorder

Katelyn Lockinger 1, Michelle M Gagnon 1,✉
PMCID: PMC10571436  PMID: 37264597

Abstract

Although rarely examined together, ADHD, emotional regulation (ER), and dysmenorrhea may be associated, which could create additive burdens on psychological well-being (PWB). Clinicians working with ADHD populations may need to take these challenges into consideration to maximize treatment outcomes. This study investigated the relationships among ADHD, dysmenorrhea, ER, and PWB within a sample of 266 adult females with a self-reported ADHD diagnosis. ADHD symptom severity was positively correlated with dysmenorrhea severity, but ER skills were not a significant moderator of this relationship. ADHD symptom severity was negatively correlated with PWB; however, this relationship was not moderated by dysmenorrhea severity nor ER ability. Overall, a positive association between ADHD symptom severity and dysmenorrhea severity was found in our sample. Further research is needed to understand the nature of this association, as well as factors that may contribute to PWB among individuals with these comorbid conditions.

Keywords: attention deficit hyperactivity disorder, dysmenorrhea, emotion regulation, pain, women

Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by levels of inattention, disorganization, and/or hyperactivity-impulsivity that are inappropriate for an individual’s developmental stage (American Psychiatric Association, 2013). Although ADHD is commonly overlooked in females, this population typically exhibits significant impairment in adulthood. Adult females with ADHD display more ADHD symptoms and increased symptom severity when compared to men with ADHD (Vildalen et al., 2019). Females with ADHD also exhibit impaired social behavior, peer functioning, and interpersonal relationships when compared to females without ADHD (Vildalen et al., 2019; Young et al., 2020). Females with ADHD commonly have poor emotional regulation (ER) skills, which is associated with a higher overall level of impairment among adults with ADHD (Hirsch et al., 2019). Furthermore, this population experiences elevated rates of depression, anxiety, and suicidal ideation (Fuller-Thomson et al., 2016). Given the cumulative impact of the stressors females with ADHD endure, there is reason to believe that the condition negatively impacts the psychological wellbeing (PWB) of this population.

Although frequently co-occurring, ADHD and pain conditions are rarely recognized and managed simultaneously (Kerekes et al., 2021). Deficits in executive functioning negatively influence pain management and health-related quality of life; therefore, clinicians may need to consider potential interactions between pain and ADHD to maximize treatment outcomes (Caes et al., 2022). Consideration of pain is important among females with ADHD as somatic symptoms may obscure proper psychiatric diagnosis, ER difficulties may amplify pain experiences, and pain can negatively impact an individual’s wellbeing (Raja et al., 2020; Vaughan et al., 2019). Understanding the relationship between ADHD and dysmenorrhea (i.e. menstrual pain) is important as dysmenorrhea has disruptive effects on attention and may exacerbate ADHD symptoms.

Dysmenorrhea refers to dull, throbbing, cramp-like pain typically emanating from the lower abdomen just before and/or during menstruation (Grandi et al., 2012). Primary dysmenorrhea occurs when menstrual pain is not caused by pelvic pathology; conversely, secondary dysmenorrhea (SD) occurs when menstrual pain is caused by underlying pathology (e.g. endometriosis; McKenna and Fogleman, 2021). Dysmenorrhea effects 50-90% of females of reproductive age, with SD accounting for 10% of these cases (McKenna and Fogleman, 2021). The negative impacts of dysmenorrhea are widespread and include impaired physical, social, and occupational functioning; reduced sleep quality; and lower quality of life during menstruation (Baker et al., 1999; Barnard et al., 2003; Iacovides et al., 2014). Depression and anxiety commonly coexist with dysmenorrhea; therefore, the pain and problems females face due to dysmenorrhea are frequently exacerbated by psychological factors (Bajalan et al., 2019).

The impact of dysmenorrhea is seldom considered among females with ADHD, despite evidence of pain hypersensitivity within ADHD populations. For example, researchers have found individuals with ADHD may be at heightened risk for experiencing chronic pain conditions (e.g. Kasahara et al., 2021), and to have lower pain thresholds than individuals without ADHD during pain induction tasks (Treister et al., 2015). Within the general population, adults with higher levels of ADHD symptoms are three times more likely to report extreme levels of pain than individuals with fewer ADHD symptoms (Stickley et al., 2016). Furthermore, prospective research indicates three-quarters of females with neurodevelopmental disorders (i.e. ADHD and autism) develop a chronic pain disorder and are five times more likely to experience widespread pain than neurotypical females (Asztély et al., 2019). Dopamine represents a potential link between pain and ADHD such that decreased dopamine levels are associated with pain sensitization and dopamine dysregulation is implicated in the etiology of ADHD; thus, females with ADHD may be more vulnerable to dysmenorrhea (Kerekes et al., 2021).

To date, only one other study has examined the association between dysmenorrhea and ADHD (Kabukçu et al., 2021). The results revealed that adolescents with dysmenorrhea symptoms affecting their daily life reported significantly more ADHD symptoms; furthermore, as the severity of their pain increased so did the severity of their ADHD symptoms (Kabukçu et al., 2021). Further research is needed to verify the relationship between ADHD and dysmenorrhea as well as examine the ways in which these conditions may relate to an individual’s psychological health. For instance, dysmenorrhea and ADHD commonly co-exist with anxiety and/or depression (Bajalan et al., 2019; Fuller-Thomson et al., 2016). Anxiety and depression symptoms should be considered when assessing the relationship between ADHD and dysmenorrhea to ensure it cannot be attributed to co-occurring psychological disorders alone. Moreover, consideration of variables that may mutually affect dysmenorrhea and ADHD, such as ER, may lead to areas for treatment and management.

Both pain and ADHD are associated with ER. Pain is an aversive sensory and emotional experience; consequently, ER is a key element in pain management (Raja et al., 2020). Emotion dysregulation and persistent pain reinforce each other (Márki et al., 2017); conversely, adaptive ER strategies are associated with reduced pain intensity and better mood states before, during, and after painful experiences (Connelly et al., 2007; Ruiz-Aranda et al., 2010). Females with ADHD frequently struggle with ER, which is associated with reduced positive effect, elevated negative affect, higher ADHD symptomology, and increased comorbidity among adults with ADHD (Hirsch et al., 2019). Females with ADHD who struggle with ER may therefore experience heightened menstrual pain, leading to greater physical impairment and poorer PWB (Raja et al., 2020).

The purpose of this study is to examine the relationships among ADHD, dysmenorrhea, and PWB while considering the potential ways ER may impact both pain and PWB. Based on prior research we hypothesized that (1) ADHD symptom severity would be positively correlated with dysmenorrhea severity; (2) the relationship between ADHD symptom severity and dysmenorrhea severity would be moderated by ER skills, such that poorer ER would be associated with more severe dysmenorrhea; (3) ADHD symptom severity would be associated with dysmenorrhea severity over and above the influence of anxiety and depression; (4) ADHD symptom severity would be negatively correlated with PWB; and (5) the relationship between ADHD symptom severity and PWB would be moderated by dysmenorrhea severity and ER skills, with higher levels of dysmenorrhea and poorer ER skills being associated with larger reductions in PWB. Figure 1 depicts the associations tested in this study.

Figure 1.

Figure 1.

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Proposed theoretical relationships among the variables of interest within the present study. Solid lines depict previously reported relationships; dotted lines depict previously unknown and untested relationships.

Methods

Participants

Following receipt of Research Ethics Board approval, participants were recruited using online advertisements on Reddit. Individuals were eligible to participate if they were an adult female (i.e. at least 18 years-old), had an ADHD diagnosis, experienced regular menstrual periods (i.e. at least three periods in the last 6 months), and lived in the United States or Canada. Within 1 month of active recruitment, 435 individuals responded to the survey. Participants who responded to less than 80% of the survey were considered to have withdrawn from the study; consequently, 139 responses were removed. Twenty-eight responses were removed for failing to meet the eligibility criteria. The final sample included 266 individuals. A power calculation was conducted using G*Power (Faul et al., 2007) for each planned analysis. The analysis requiring the most participants (i.e. multiple regression with five predictors; 1-beta = 0.80 and α = 0.05) was used to determine the required sample size and indicated that a minimum sample size of 92 participants was needed to detect medium-size effects.

Measures

Personal History Questionnaire

The Personal History Questionnaire was developed for the purposes of this investigation and involved three sections. Section one queried demographic information. Section two pertained to ADHD history, including age at diagnosis, use of medication and/or non-pharmacological ADHD interventions, and family history of ADHD. Section three queried menstrual history, including level of pain typically experienced during menstruation, presence of risk factors for dysmenorrhea (e.g. early onset of puberty), and use of medication to manage menstrual pain (e.g. birth control).

Adult ADHD Self-Report Scale

The Adult ADHD Self-Report Scale (ASRS) is an 18-item self-report scale of ADHD symptom severity (Kessler et al., 2005). It assesses the frequency of ADHD symptoms on a 5-point Likert scale (0 = “never”; 4 = “always”), with higher scores indicating higher levels of ADHD symptoms. The ASRS has high scale score reliability (Cronbach’s α = 0.93) and concurrent validity with clinician-administered measures (r = 0.72, p < 0.001) among community and clinic-based samples of adults with ADHD (Adler et al., 2012). The scale score reliability of the ASRS was acceptable (Cronbach’s α = 0.78) in the present sample.

Symptom Severity Scale

Dysmenorrhea severity was assessed using the Symptom Severity Scale (SSS; Chesney and Tasto, 1975). The SSS assesses the severity of menstrual symptoms and degree of pain and discomfort an individual experienced during their last menstrual period. The SSS consists of 15 items rated on a 5-point Likert scale (0 = “symptom not present”; 5 = “very severely”). Higher total scores are indicative of increased symptom severity. The SSS had strong construct validity and scale score reliability (Cronbach’s α = 0.93) in a previous sample of Canadian females (Gagnon and Elgendy, 2020). The SSS had good scale score reliability in the current sample (Cronbach’s α = 0.89).

PROMIS short forms

Anxiety and depression symptoms were assessed using the PROMIS Anxiety Short Form 7a (PSF-A) and The PROMIS Depression Short Form 8b (PSF-D) respectively. Both measures are scored on a 5-point Likert-scale (1 = “Never”; 5 = “Always”). The PSF-A consists of 7-items assessing the presence of anxiety symptoms (e.g. “I felt worried”) over the past 7 days. Higher total scores reflect higher anxiety levels. The PSF-A has high scale score reliability (Cronbach’s α = 0.87) and scores on this measure correlate with other previously validated anxiety assessment tools (Marrie et al., 2018). The PSF-D is an eight-item scale that assesses depression symptoms (e.g. “I felt sad”) over the past 7 days. Higher total scores reflect increased depression symptoms. The PSF-D has excellent scale score reliability (Cronbach’s α = 0.95) and strong construct and criterion validity (Marrie et al., 2018). The Cronbach’s alpha of the PSF-A and PSF-D were 0.94 and 0.88 respectively within the present sample.

Difficulties in Emotional Regulation Scale

ER abilities were assessed using the Difficulties in Emotional Regulation Scale (DERS; Gratz and Roemer, 2004). The DERS consists of 36-items on a 5-point Likert scale (1 = “almost never”; 5 = “almost always”) to measure an individual’s emotional regulation deficits. Item scores are summed, and higher scores indicate greater difficulty in ER. The DERS has good construct validity, scale score reliability (Cronbach’s α = 0.89), and test-retest reliability over a period of 8 weeks (Gratz and Roemer, 2004). The DERS has demonstrated strong internal consistency when used among ADHD samples (Ben-Dor Cohen et al., 2021). The DERS had excellent scale score reliability within the current sample (Cronbach’s α = 0.94).

Psychological Well-being Scale

PWB was measured using the Psychological Well-being Scale (PWBS; Ryff, 1989). The PWBS assesses wellbeing through the following six subscales: Self Acceptance, Positive Relations with Others, Autonomy, Environmental Mastery, Purpose in Life, and Personal Growth. The PWBS has 42 items rated on a 7-point Likert scale (1 = “strongly agree”; 7 = “strongly disagree”). Higher scores across items indicate greater wellbeing (Ryff, 1989). The PWBS has previously demonstrated adequate construct validity, good scale score reliability (Cronbach’s α = 0.93), and test-retest reliability over a 6-week period (Ryff, 1989). The PWBS exhibits strong reliability when used among ADHD samples (Wilmshurst et al., 2011). The Cronbach’s alpha of the PWBS in the present sample was 0.94.

Procedure

Interested participants followed the link provided on the online advertisement to the study. The study questionnaires were hosted on SurveyMonkey. Participants were required to review consent information and provide informed consent prior to gaining access to the study. Participants were then asked to complete the study measures, which were presented in the same order across participants. Eligibility criteria were confirmed in the first section of the questionnaire. If participants failed to meet the eligibility criteria, participants were unable to complete the rest of the questionnaire and were thanked for their interest but were informed that they were ineligible to participate. After completing the questionnaire, participants were debriefed using a written summary with further information about the purpose of the research.

Data preparation

All statistical analyses were conducted using the Statistical Package for the Social Science (SPSS) 28 (IBM Corp, 2021). Missing data were addressed using person mean replacements to maximize data utilization (Downey and King, 1998). Nineteen participants required item replacements on one or more items; item mean replacements were only completed if no more than 20% of a participant’s items were missing within a measure. Preliminary analyses were conducted to calculate means, standard deviations, ranges, and correlations of the study variables and are presented in Table 1. Skew and kurtosis were assessed for each variable and all study variables approximated the normal distribution.

Table 1.

Descriptive statistics and correlations between study variables.

Variable n M SD Range 1 2 3 4 5 6
1. ASRS 266 66.68 7.41 42–90 —
2. SSS 266 36.40 9.87 15–67 0.43** —
3. DERS 266 104.90 25.11 46–164 0.40** 0.31** —
4. PWBS 266 176.63 31.44 106–258 −0.24** −0.23** −0.59** —
5. PSF-A 265 21.51 5.38 7–35 0.28** 0.37** 0.43** −0.44** —
6. PSF-D 265 21.70 7.61 8–40 0.24** 0.34** 0.55** −0.61** 0.67** —
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ASRS: Adult ADHD Self-Report Scale, possible scores are 0–90; SSS: Symptom Severity Scale, possible scores are 0–75; DERS: Difficulties in Emotional Regulation Scale, possible scores are 36–180; PWBS: Psychological Well-being Scale, possible scores are 42–294; PFS-A: PROMIS Anxiety Short Form 7a, possible scores are 7–35; PSF-D: The PROMIS Depression Short Form 8b, possible scores are 8–40.

**

p < 0.001.

The relationship between ADHD symptom severity and dysmenorrhea severity (hypothesis 1) and between ADHD symptom severity and PWB (hypothesis 4) were examined using Pearson’s product moment correlations. The moderating role of ER skills in the relationship between ADHD symptom severity and dysmenorrhea (hypothesis 2) was examined with a moderation analysis conducted via PROCESS, a macro for SPSS in which the outcome variable was SSS scores, the predictor variable was ASRS scores, and the moderator was DERS scores (Hayes, 2022). A hierarchical multiple regression was conducted to test the hypothesis that ADHD symptom severity would be associated with dysmenorrhea severity over and above the influence of anxiety and depression (hypothesis 3). SSS scores were significantly correlated with age, r = −0.14, p = 0.02 and education, r = −0.22, p < 0.001; therefore, age and education were included in the first step of the regression to control for these variables. PSF-A and PSF-D scores were entered in the second step of the regression, ASRS scores were entered in step three, and PWBS scores were entered as the outcome variable. Lastly, a moderation analysis was conducted to test the hypothesis that the association between ASRS scores and PWBS scores would be moderated by DERS scores and SSS scores using Model 2 of the PROCESS macro (Hayes, 2022). The outcome variable was participant scores on the PWBS. The predictor variable was ASRS scores. The moderators were DERS scores and SSS scores.

Results

Demographic, ADHD, and dysmenorrhea characteristics

Demographic characteristics are summarized in Table 2. The mean age of participants was 30.94 (SD = 6.59, range 18–51). Most participants (89.1%) identified as women. Most of the sample (71.1%) lived in the United States. The sample was predominately white (85%) and had a relatively high level of educational attainment.

Table 2.

Summary of participant demographic characteristics.

Characteristics
Age, M (SD; range) 30.94 (6.59; 18–51)
Ethnic Origin, n (%)
Arab 1 (0.4%)
Black 7 (2.6%)
Chinese 4 (1.5%)
Filipino 1 (0.4%)
Latin American 7 (2.6%)
South Asian 4 (1.5%)
West Asian 3 (1.1%)
White 226 (85%)
First Nations 2 (0.8%)
Inuit 1 (0.4%)
Metis 1 (0.4%)
Multi-Ethnic 15 (5.6%)
Other 1 (0.4%)
Gender Identity, n (%)
Cisgender/transgender man 2 (0.8%)
Cisgender/transgender woman 237 (89.1%)
Non-Binary 22 (8.3%)
Other 2 (0.8%)
Country of Residence, n (%)
Canada 76 (28.6%)
United States 189 (71.1%)
Level of Education, n (%)
High school graduate 5 (1.9%)
Some post-secondary education 48 (18%)
Completed post-secondary education 145 (54.5%)
Graduate degree (MA or PhD) 67 (25.2%)
Other 1 (0.4%)
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N = 266.

On average, the participants reported receiving their ADHD diagnosis at the age of 26 (SD = 8.43, range = 4–50). Most participants (81.2%) took ADHD medication. Some participants (38%) used non-medical treatment for their symptoms (e.g. ADHD coaching or counseling). Most participants (61.7%) reported a family history of ADHD.

Participants’ mean age of menarche was 12 years-old (SD = 1.55, range = 7–18). Ninety-five percent of participants reported experiencing pain regularly during menstruation. Specifically, 0.4% never experienced pain, 4.5% rarely experienced pain, 16.9% sometimes experienced pain, 39.1% usually experienced pain, and 39.1% always experienced pain during menstruation. Twelve percent reported having secondary dysmenorrhea, 44% were on birth control, 18.8% had given birth, and 83.1% regularly used medication to manage their menstrual pain. On a scale from 0 to 10, participants reported their highest level of menstrual pain at 5.6, average level of menstrual pain at 4.0, and lowest level of menstrual pain at 2.0 on average.

ADHD and dysmenorrhea severity

Consistent with hypothesis 1, participants’ scores on the ASRS and SSS were moderately positively correlated, r = 0.43, p < 0.001. In the simple moderation analysis utilized to test hypothesis 2, the overall model was significant, F (3, 262) = 22.71, p < 0.001, R2 = 0.21. ASRS scores were not significantly associated with SSS scores, b = 0.35, t (262) = 6.07, p = 0.21. DERS scores were not significantly associated with SSS scores, b = −0.02, t (262) = −0.11, p = 0.91. The interaction between DERS scores and ASRS scores was not statistically significant, b = 0.001, 95% CI [−0.004, 0.006], t = 0.48, p = 0.63.

The model summary for the regression analysis conducted to test hypothesis 3 is in Table 3. In step 1, age and education level accounted for 5% of the variance in SSS scores, ∆F (2, 257) = 7.65, p < 0.001. The addition of PSF-A scores and PSF-D scores in Step 2 led to an R2 increase of 0.14, ∆F (2, 255) = 21.83, p < 0.001. The addition of ASRS scores in Step 3 led to an R2 increase of 0.10, ∆F (1, 254) = 34.84, p < 0.001. The full model accounted for 27.7% of the variation in SSS scores and was significant, F (5, 254) = 20.89, p < 0.001. In the final step education level, β = 0.16, p = 0.003; PSF-A scores, β = 0.16, p = 0.03; PSF-D scores, β = 0.15, p = 0.03; and ASRS scores, β = 0.33, p < 0.001 contributed significantly to the model.

Table 3.

Hierarchical regression analysis for variables predicting PD severity.

Predictors B 95% CI for B SE B β Adjusted R 2 ∆R2
LL, UL
Step 1 0.05 0.06
Age −0.46 −0.33, 0.04 0.10 −0.10
Education Level −2.69* −4.40, −0.97 0.87 −0.19*
Step 2 0.18 0.14
Age −0.13 −0.30, 0.04 0.09 −0.09
Education Level −2.31* −3.91, −0.71 0.81 −0.17*
PSF-A 0.41* 0.13, 0.68 0.14 0.22*
PSF-D 0.25* 0.05, 0.44 0.10 0.19*
Step 3 0.28 0.10
Age −0.04 −0.20, 0.13 0.08 −0.03
Education Level −2.26* −3.76, −0.76 0.76 −0.16*
PSF-A 0.29* 0.03, 0.55 0.13 0.16*
PSF-D 0.20* 0.02, 0.38 0.09 0.15*
ASRS 0.44** 0.29, 0.59 0.08 0.33**
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N = 265.

CI: Confidence Interval; LL: lower limit; UL: upper limit; ASRS: Adult ADHD Self-Report Scale; PSF-A: PROMIS Anxiety Short Form 7a; PSF-D: PROMIS Depression Short Form 8b; ∆R2: Change in R2; β: Standardized coefficient (Beta).

*

p < 0.05; **p < 0.001.

Associations with psychological well-being

Consistent with hypothesis 4, there was a small but significant negative correlation between ASRS scores and PWBS scores, r = −0.24, p < 0.001. ASRS scores were significantly correlated with the following PWBS subscales: Environmental Mastery, r = −0.30, p < 0.001; Positive Relations with Others, r = −0.14, p = 0.02; Self-Acceptance, r = −0.25, p < 0.001; and Purpose in Life, r = −0.15, p = 0.01.

In the moderation analysis conducted to test hypothesis 5, there was a significant main effect of ASRS scores on PWBS scores, b = −1.78, t (260) = −2.03, p < 0.05. There was no significant main effect of SSS scores on PWBS scores, b = −0.31, t (260) = −0.21, p = 84. DERS scores significantly predicted PWBS scores, b = −1.87 t (260) = −3.25, p = < 0.05. There was no significant interaction between ASRS and SSS scores, b = 0.002, 95% CI [−0.04, 0.05], t = 0.078, p = 0.94, indicating the relationship between ASRS scores and PWBS scores was not moderated by SSS scores. There was a significant interaction between ASRS and DERS scores, b = 0.02, 95% CI [0.0003, 0.0338], t = 2.01, p = 0.045, indicating the relationship between ASRS scores and PWBS scores was moderated by DERS scores. The interaction between ASRS scores and DERS scores accounted for a small but significant amount of variance in PWBS scores, R2 Change = 0.01, p < 0.05. The overall model was significant, F (5, 260) = 29.24, p < 0.001, R2 = 0.36.

Discussion

The purpose of this study was to examine the interrelations of ADHD, dysmenorrhea, ER skills and PWB. Understanding associations among these variables is imperative as clinicians working with ADHD populations may need to take challenges with dysmenorrhea, ER, and PWB into consideration throughout treatment. Key incremental advances of our study include assessing the relationship between ADHD symptom severity and dysmenorrhea severity within a sample of adults previously diagnosed with ADHD while considering the potential influence of anxiety and depressive symptoms, evaluating the PWB of this population, and examining the influence of ER in these relationships. Overall, the results suggest the hardships faced by females with ADHD go beyond high levels of the core symptoms of their disorder, such as emotional dysregulation and dysmenorrhea.

This is the first investigation, to our knowledge, to demonstrate that females with ADHD report high levels of menstrual pain. A 95% comorbidity rate was reported in the current sample. ADHD symptom severity was positively correlated with dysmenorrhea severity, as hypothesized and found by others (Kabukçu et al., 2021). Furthermore, ADHD symptom severity was associated with dysmenorrhea severity over and above the influence of anxiety and depression. Taken together, these results suggest there is a unique relationship between ADHD symptom severity and dysmenorrhea severity. Clinicians working with populations with ADHD or dysmenorrhea should therefore consider the potential effects of both conditions across clinical settings due to the possibility of symptoms of one condition influencing symptoms of the other (Gagnon et al., 2022). The relationship between ADHD symptom severity and dysmenorrhea severity may be explained through dopamine dysregulation such that decreased dopamine levels are associated with both pain sensitization and ADHD (Kabukçu et al., 2021; Kerekes et al., 2021). Conversely, the association between dysmenorrhea severity and ADHD symptom severity may occur due to the disruptive effect menstrual pain has on attention (Keogh et al., 2014).

PWB and ADHD symptom severity were negatively correlated as hypothesized. Possible explanations for this association include high levels of core symptoms, comorbid psychological distress, and late age of ADHD detection that prevented most participants from accessing resources required to adaptively manage their ADHD until adulthood (Vildalen et al., 2019). The average age of ADHD diagnosis within the present sample was 26 years-old, which supports the notion that females with ADHD frequently receive their diagnoses at later ages than males (Brown et al., 1991; Grevet et al., 2006). Remaining undiagnosed until adulthood is associated with negative outcomes for females with ADHD, such as affective symptoms (Rucklidge and Kaplan, 1997). ADHD symptom severity was most strongly negatively correlated with the Environmental Mastery and Self-Acceptance subscales of the PWBS. This aligns with previous research findings that women with ADHD have poor self-esteem, struggle with disorganization, respond to life stressors with emotion, and feel they have a lack of control over their situations (Quinn and Madhoo, 2014). Similarly, ADHD symptom severity was negatively correlated with the Positive Relations with Others subscale, reflecting the impairment females with ADHD typically face within interpersonal relationships (Young et al., 2020). Contrary to the hypothesis, the relationship between ADHD symptom severity and PWB was not moderated by dysmenorrhea severity. Since menstrual pain is cyclical, it is possible that dysmenorrhea may not affect constructs such as PWB that are thought to be relatively stable over time.

Participants in the present study displayed high levels of emotional dysregulation, indicated by average DERS scores approximately one standard deviation above the normative reference value (Giromini et al., 2017). Difficulties in ER moderated the relationship between ADHD symptom severity and PWB which aligns with the researchers’ hypothesis and previous findings that poor ER is associated with dysfunctional coping strategies and life dissatisfaction among females with ADHD (Young et al., 2020). However, the moderating effect of ER on the relationship between PWB and ADHD symptom severity is unlikely to be clinically meaningful due to the small effect size. The relationship between ADHD symptom severity and dysmenorrhea severity was not moderated by difficulties in ER. This finding was unexpected as adaptive ER has been associated with reduced pain intensity (Connelly et al., 2007; Ruiz-Aranda et al., 2010). ER may not influence pain severity among individuals with ADHD as they may exhibit a predisposition to pain that cannot be remediated by emotion-focused pain coping strategies. Nevertheless, a focus on ER skills may improve functioning of those affected by ADHD and dysmenorrhea separately.

The findings from the current research must be viewed in light of the study’s limitations. The research was correlational in nature, thus the causes behind the relationships discovered cannot be inferred. The narrow scope utilized within the present study may be considered a limitation. While measuring dopamine dysregulation went beyond the scope of the study, doing so may have provided more clarity on the relationship between ADHD symptom severity and dysmenorrhea severity. Similarly, including additional variables known to have a negative impact on females with ADHD may have increased the model’s ability to explain factors contributing to the negative association between ADHD symptom severity and PWB. We utilized a convenience sample that lacked ethnic and gender diversity which limits the generalizability of the results. The sample may have further been influenced by selection bias such that that individuals who are more severely impacted by ADHD and dysmenorrhea may have been more willing to participate, especially when considering that participants were recruited from online women’s ADHD communities that often serve a supportive function, no incentive for participation was provided, and discourse on mental health and menstruation is sensitive in nature.

Despite these limitations, we can offer several areas for future direction. Future research should adopt a longitudinal approach to better understand the temporal order of the relationship between ADHD symptom severity and dysmenorrhea severity. Such research should compare participants’ ADHD symptoms during menstruation and non-painful points in their menstrual cycle to determine the potential impact of dysmenorrhea on ADHD symptoms. Further research on ADHD, dysmenorrhea, and PWB should recruit a non-affected comparison group to better understand the unique experiences of females with ADHD. Future research should consider implementing a strength-based lens while assessing ER among women with ADHD as this may identify areas of relative strength that may be utilized to promote overall functioning within this population. Finally, our research suggests there is a relationship between ADHD symptom severity and dysmenorrhea severity; furthermore, the PWB and ER skills of this population were lower than what might be expected. Consequently, treatment approaches which may improve these comorbid experiences, such as mindfulness-based interventions, should be considered (Gu et al., 2018; Mitchell et al., 2017; Singleton et al., 2014).

In sum, we examined the relationships among ADHD, dysmenorrhea, ER, and PWB. The results indicated there was a positive association between dysmenorrhea severity and ADHD symptom severity. This relationship was not moderated by ER ability, nor could it be explained by symptoms of depression and anxiety alone. Thus, the present study is the first to illustrate there is a relatively robust relationship between ADHD symptom severity and dysmenorrhea severity. The results further revealed that PWB was negatively associated with ADHD symptom severity; however, neither dysmenorrhea severity nor ER abilities moderated this relationship to a clinically meaningful extent. Future research is required to understand the causes behind these relationships. Nevertheless, the present study suggests there is a need to consider dysmenorrhea within treatment for females with ADHD.

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Footnotes

Data sharing statement: The current article is accompanied by the relevant raw data generated during and/or analyzed during the study, including files detailing the analyses and either the complete database or other relevant raw data. These files are available in the Figshare repository and accessible as Supplemental Material via the Sage Journals platform. Ethics approval, participant permissions, and all other relevant approvals were granted for this data sharing.

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding: The authors received no financial support for the research, authorship, and/or publication of this article.

Ethics approval: This research received ethics approval from the University of Saskatchewan Research Ethics Board (PSY-REC 2021-2022-472-016).

ORCID iD: Michelle M. Gagnon Inline graphic https://orcid.org/0000-0002-2400-1898

Supplemental material: Supplemental material for this article is available online.

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Supplemental material, sj-docx-1-hpq-10.1177_13591053231177254 for Dysmenorrhea and psychological wellbeing among females with attention deficit hyperactivity disorder by Katelyn Lockinger and Michelle M Gagnon in Journal of Health Psychology

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Supplemental material, sj-sps-2-hpq-10.1177_13591053231177254 for Dysmenorrhea and psychological wellbeing among females with attention deficit hyperactivity disorder by Katelyn Lockinger and Michelle M Gagnon in Journal of Health Psychology

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This article is distributed under the terms of the Creative Commons Attribution 4.0 License (http://www.creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).

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Supplemental material, sj-spv-3-hpq-10.1177_13591053231177254 for Dysmenorrhea and psychological wellbeing among females with attention deficit hyperactivity disorder by Katelyn Lockinger and Michelle M Gagnon in Journal of Health Psychology

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