Abstract
Aim
Somatic symptom disorder (SSD) is prevalent in primary healthcare settings and is often challenging to diagnose and treat. This study examined the neurodevelopmental and personality traits of individuals with probable SSD.
Methods
This cross‐sectional study utilized anonymous online surveys. In this study, individuals with a score of 23 or higher on the Somatic Symptom Disorder–B Criteria Scale (SSD‐12) were defined as having probable SSD, and individuals with no somatic symptoms and who scored 0 were defined as the healthy control (HC) group. We compared groups regarding neurodevelopmental traits, personality traits, depression, and anxiety using self‐report questionnaires and analysis of covariance. In addition, we examined the association between neurodevelopmental traits, emotional problems, and SSD in the probable SSD group using structural equation modeling.
Results
A total of 491 people with probable SSD and 532 age‐ and sex‐matched HCs were analyzed. The scores for somatic symptom severity, depression, generalized anxiety, health anxiety, attention deficit/hyperactivity disorder traits, autism spectrum disorder traits, personality traits, and personality disorder traits showed significant differences between the probable SSD group and the HC group. In the probable SSD group, neurodevelopmental traits positively and directly affected emotional problems and SSD.
Conclusion
Most neurodevelopmental and personality traits were associated with probable SSD. When approaching patients suspected of having SSD, clinicians may consider not only somatic symptoms, but also neurodevelopmental traits, personality traits, depression, and anxiety.
Keywords: attention deficit disorder with hyperactivity, autism spectrum disorder, medically unexplained symptoms, neurodevelopmental disorders, personality disorders
We report an analysis of neurodevelopmental and personality traits of patients with somatic symptom disorder (SSD). This study showed that individuals with probable SSD may simultaneously exhibit neurodevelopmental traits, personality traits, and personality disorder traits. For comprehensive approaches to SSD, clinicians may consider not only somatic symptoms but also neurodevelopmental traits, personality traits, and personality disorder traits.
INTRODUCTION
Background of somatic symptom disorder
Somatic symptom disorder (SSD) is a mental disorder characterized by a significant focus on physical symptoms. In the Diagnostic and Statistical Manual of Mental Disorders Fifth Edition (DSM‐5), SSD is defined as the presence of somatic symptoms (criterion A), excessive thoughts, feelings, or behaviors related to these symptoms (criterion B), and the presence of these symptoms for >6 months (criterion C). 1 Previously known as somatoform disorders, these were renamed to “somatic symptoms and related disorders” in the DSM‐5. The estimated prevalence of SSD described in the DSM‐5 is 4%–6%. 2 In previous studies, the prevalence of SSD estimates varied between 6.7% and 17.4% (mean frequency 12.9%) in the general population. 3 , 4 , 5 , 6 SSD is common in primary healthcare settings. However, diagnosis is challenging and SSD leads to greater use of healthcare resources and higher costs. 7 Clinicians face dilemmas when diagnosing and treating patients with SSD. 8
Neurodevelopmental traits relevant to SSD
Neurodevelopmental disorders (NDDs) are mental conditions that occur during development. These disorders typically manifest early in development and are characterized by developmental deficits that impair personal, social, academic, and occupational functioning. 1 Attention deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) have high rates of diagnosis, occurring in 5% and 2.3% of children, respectively. 9 , 10
ADHD is an NDD represented by impaired inattention, disorganization, and hyperactivity‐impulsivity. Children with ADHD may have difficulties paying attention, sitting still, and controlling impulses. 1 ASD is an NDD characterized by impaired social communication and restricted repetitive behavior. The rate of ADHD and ASD comorbidity is also high. 11
Furthermore, individuals with ASD or ADHD have a much higher somatic symptom burden than the general population. 12 , 13 Previous studies have indicated that moderate or severe somatic symptoms were reported by 53.9% of females and 18.75% of males in autistic young adults. Somatic symptoms are notably common among young adults with ASD. 12 Also, in individuals with untreated ADHD, somatic symptoms were significantly higher compared to those without ADHD. 13
Personality traits relevant to SSD
The five‐factor model (FFM), also called the Big Five model, is one of the most frequently used tools for assessing personality. It describes five broad dimensions of the human personality: extraversion, agreeableness, conscientiousness, neuroticism, and openness. Previous studies have found that high levels of neuroticism may predict not only depression and anxiety but also medically unexplained symptoms. 14 , 15
Personality disorder traits (pathological personality traits) relevant to SSD
Personality disorders are an enduring pattern of inner experience and behavior that deviate markedly from the expectations of an individual's culture; they are pervasive and inflexible, have an onset in adolescence or early adulthood, are stable over time, and lead to distress or impairment. 1 There is often a link between personality and somatization disorders. 16 , 17 A previous study reported that personality disorder comorbidity in patients with somatization disorder was 62.9%, compared to 28.2% in controls. 16
To our knowledge, the relationship among probable SSD, neurodevelopmental traits, and personality traits has not yet been explored simultaneously. We examined whether individuals with probable SSD had specific neurodevelopmental and personality traits to intervene more effectively.
METHODS
Procedure
Study design, setting, and participants
We chose a cross‐sectional design for the exploratory research. In this study, we used the Somatic Symptom Disorder–B Criteria Scale (SSD‐12) as a screening tool to evaluate the psychological aspects of SSD defined in the DSM‐5 via an online survey. Based on the total SDD‐12 scores, we planned to compare approximately 500 individuals with probable SSD and 500 individuals without SSD as healthy controls (HCs).
We collected data through an anonymous online survey performed by NTT Com Online Marketing Solutions Corporation (Tokyo) from August 31 to September 20, 2022. The online survey data included demographic characteristics, including sex, education, marital status, employment status, medical history, health conditions, and duration and frequency of healthcare utilization. The participants also completed self‐report questionnaires on mental and physical symptoms, and neurodevelopmental and personality traits.
Participants aged 18 and above were included. Individuals diagnosed with cancer, alcohol or substance use disorders, chronic and rare diseases, cardiovascular diseases, or cerebrovascular diseases were excluded.
Ethics
The protocol for the research project has been approved by a suitably constituted Ethics Committee of an institution, and it conforms to the provisions of the Declaration of Helsinki. Ethical approval was granted by the Research Ethics Committee of the Graduate School of Medicine, Chiba University (approval number: M10399). Before participation, all participants read an informed consent document about this study's overview on the web and then confirmed their consent to voluntarily participate in the survey by clicking “I agree” after having an opportunity to ask their questions to the researchers by e‐mail.
Measurements
In this study, we used the nine self‐report questionnaires.
Selection of probable SSD and HCs
Symptoms of SSD were measured using the SSD‐12. This scale was developed following the update of the SSD diagnostic criteria in the DSM‐5 to evaluate the newly added criterion B. SSD‐12 consists of 12 items measuring patients' recognition of thoughts, feelings, and behaviors regarding their symptoms scored from 0 (never) to 4 (very often). The instrument demonstrated satisfactory internal consistency (Cronbach's α = 0.95) 18 and validity. 19 Here, a score of 23 or higher on the SSD‐12 indicated probable SSD because a previous study indicated that a score of 23 might be more effective for screening. 20 Using this cutoff score, the top 5% of the general population with the highest SSD‐12 scores were identified. 20 , 21
In this study, individuals with somatic symptoms for more than 6 months and a score of 23 or higher on the SSD‐12 were defined as having probable SSD. Individuals with no somatic symptoms and who scored 0 points on the SSD‐12 were defined as the HC group.
Somatic symptom severity
Somatic symptoms were measured using the Patient Health Questionnaire‐15 (PHQ‐15). The PHQ‐15 is a 15‐item questionnaire used to identify patients at risk for SSD in a primary care environment; each symptom scored from 0 (not bothered at all) to 2 (bothered a lot). The validity of the PHQ‐15 has been demonstrated in Japan. 22
Depression
Symptoms of depression were measured with the Patient Health Questionnaire‐9 (PHQ‐9). 23 The PHQ‐9 is a 9‐item screening instrument that determines the severity of depressive symptoms from 0 (not bothered at all) to 3 (bothered almost every day). The questionnaire has demonstrated internal consistency and validity in Japan. 24
Anxiety
Anxiety symptoms were assessed using the Generalized Anxiety Disorder 7‐item scale (GAD‐7). 25 The GAD‐7 is a 7‐item screening instrument that determines the severity of anxiety symptoms from 0 (not bothered at all) to 3 (bothered almost every day). This instrument has demonstrated internal consistency in Japan. 26
Health anxiety
Symptoms of health anxiety were measured with the Short Health Anxiety Inventory (SHAI). 27 The SHAI is an 18‐item screening instrument that determines the severity levels of health anxiety disorder symptoms using four statements for individual selection. The item scores ranged from 0 to 3. This measurement demonstrated internal consistency and validity in Japan. 28
ADHD
ADHD symptoms were measured with the Adult ADHD Self‐Report Scale (ASRS‐v1.1 1.1). 29 The ASRS‐v1.1 consists of a 6‐item Part A and a 12‐item Part B from 0 (never) to 4 (very often). Part A serves as the foundation for the ASRS‐v1.1 Screener (ASRS‐A) and has been validated as a pre‐diagnostic tool to identify adults at risk. 30 Part B offers further details on the respondents' ADHD symptoms. This 18‐item scale can be divided into two symptom domains, inattention and hyperactivity/impulsivity, with each domain consisting of nine items, aligning with the DSM‐IV ADHD criteria. 29 The instrument has demonstrated internal consistency and validity. 29
ASD
ASD symptoms were measured with the autism spectrum quotient (AQ). 31 The AQ is made up of 50 items split into five subscales: communication, social skills, imagination, attention to detail, and attention switching. Higher scores in each subscale indicate poor communication skills, social skills, and imagination, as well as heightened attention to detail and difficulty switching attention. This instrument demonstrated satisfactory internal consistency in Japan. 32
Personality
Personality traits were measured with the Ten‐Item Personality Inventory (TIPI). 33 The TIPI is a 10‐item scale divided into five subscales: extraversion, agreeableness, conscientiousness, neuroticism, and openness of the Big Five personality traits scored from 1 (strongly disagree) to 7 (strongly agree). The instrument demonstrated satisfactory internal consistency and validity in Japan. 34
Personality disorder
The symptoms of personality disorders were measured with the Personality Inventory for DSM‐5‐Brief Form (PID‐5‐BF)‐Adult. 1 The PID‐5‐BF is a 25‐item scale divided into five subscales ranging from 0 (never) to 3 (always): negative affectivity, detachment, antagonism, disinhibition, and psychoticism. The instrument demonstrated satisfactory internal consistency and validity in Japan. 35
Statistical analysis
We used SPSS version 29.0 (IBM) to analyze the data, and two‐sided P‐values were reported. The data are shown as mean ± standard deviation for continuous variables and as frequencies and percentages for categorical variables. We employed chi‐squared tests for categorical variables and analysis of covariance (ANCOVA) for continuous variables. ANCOVA was performed with covariates including gender, age, marital status, education history, and employment status. When the assumptions for parametric tests were not satisfied, we utilized Spearman's rank correlation as a non‐parametric alternative. A significance level of P < 0.05 was adopted.
In addition, AMOS version 29.0 (IBM) was used to perform structural equation modeling (SEM) in the probable SSD group to test the association of neurodevelopmental traits, emotional problems, and SSD with the AQ‐50, ASRS‐v1.1, PHQ‐9, GAD‐7, PHQ‐15, SSD‐12, and SHAI. The fit indices, chi‐square (χ 2), χ 2/df (criterion chi‐squared/df), comparative fit index (CFI), Tucker–Lewis Index (TLI), goodness‐of‐fit Index (GFI), adjusted GFI (AGFI), root‐mean‐square error of approximation (RMSEA), and standardized root‐mean‐square residual (SRMR) were used to examine the model fit with the data. For adequate fit, the index values were as follows: χ 2/df < 2, 36 CFI and TLI ≥ 0.95, 37 , 38 GFI and AGFI ≥ 0.90, 39 RMSEA < 0.08, 40 and SRMR < 0.08. 41
RESULTS
Demographic characteristics and healthcare utilization
After obtaining informed consent, 34,060 individuals aged 18–85 years participated in this study via a web survey. Among them, 1583 (4.6%) were considered to have probable SSD based on screening using the SSD‐12. A total of 516 participants did not respond to the questionnaire. A total of 542 participants had probable SSD with predominant pain, and each group was reported separately. In this study, 43 participants with incurable, cardiovascular, or cerebrovascular diseases were excluded. In this survey, 491 probable SSD patients without predominant pain were matched to 532 HCs.
Demographic variables are listed in Table 1. In the probable SSD group, 252 (51.32%) of 491 people were male and 239 (48.68%) were female. In the HC group, 285 (53.57%) of the 491 participants were male and 247 (46.43%) were female.
Table 1.
Demographic variables.
| SSD group (n = 491) | Healthy control group (n = 532) | Statistics (χ2 ‐test) | Effect size | ||||
|---|---|---|---|---|---|---|---|
| Variable | n | % | n | % | χ2 | p | Cramer's V |
| Sex | |||||||
| Male | 252 | 51.32 | 285 | 53.57 | |||
| Female | 239 | 48.68 | 247 | 46.43 | |||
| Age, mean ± SD | 48.34 ± 12.75 | 49.02 ± 12.84 | |||||
| Marital status | 45.127 | <0.001 | 0.21 | ||||
| Married | 204 | 41.55 | 332 | 62.41 | <0.05 | ||
| Single/no partner | 247 | 50.31 | 167 | 31.39 | <0.05 | ||
| Divorced/separated | 40 | 8.15 | 33 | 6.20 | >0.05 | ||
| Education | 16.882 | 0.002 | 0.128 | ||||
| Junior high school | 22 | 4.48 | 9 | 1.69 | <0.05 | ||
| High school | 138 | 28.11 | 115 | 21.62 | <0.05 | ||
| Junior college/technical college/vocational school | 109 | 22.20 | 121 | 22.74 | >0.05 | ||
| University | 203 | 41.34 | 251 | 47.18 | >0.05 | ||
| Graduate school | 19 | 3.87 | 36 | 6.77 | <0.05 | ||
| Employment | 43.629 | <0.001 | 0.207 | ||||
| Full‐time employee | 168 | 34.22 | 278 | 52.26 | <0.05 | ||
| Part‐time employee | 87 | 17.72 | 71 | 13.35 | >0.05 | ||
| Student | 6 | 1.22 | 7 | 1.32 | >0.05 | ||
| Housework | 67 | 13.65 | 74 | 13.91 | >0.05 | ||
| Unemployed/retired | 125 | 25.46 | 70 | 13.16 | <0.05 | ||
| Others | 38 | 7.74 | 32 | 6.02 | >0.05 | ||
| Healthcare utilization | |||||||
| More than once a month | 317 | 64.56 | 59 | 11.09 | 28.863 | <0.05 | 0.241 |
| More than for 6 months | 351 | 71.49 | 92 | 17.29 | 0.015 | 0.900 | |
| No healthcare utilization | 111 | 22.61 | 432 | 81.20 | 386.031 | <0.05 | 0.587 |
| Clinical diagnosis | |||||||
| SSD | 9 | 1.83 | 0 | 0.00 | 9.838 | <0.05 | 0.098 |
Abbreviations: SD, standard deviation; SSD, somatic symptom disorder.
The probable SSD group, compared to the HC group, had a significantly higher proportion of individuals who were single, whose highest level of education was junior high school or high school, who were unemployed or retired, and who used the healthcare system at least once a month.
Comparison of neurodevelopmental and personality traits scores between groups
Table 2 lists the traits of participants in the probable SSD and HC groups. ANCOVA was performed with covariates including gender, age, marital status, education history, and employment status, with healthcare utilization also added as a covariate, as differences in healthcare utilization were observed across demographic groups.
Table 2.
Comparison of neurodevelopmental and personality traits between SSD and control group.
| SSD not pain (n = 491) | Healthy control group (n = 532) | Statistics | p | Effect size | |
|---|---|---|---|---|---|
| Mean (SD) | Mean (SD) | F | η2 | ||
| PHQ‐15 | 10.64 (5.98) | 2.20 (5.03) | 381.657 | <0.0001* | 0.273 |
| PHQ‐9 | 12.75 (7.30) | 1.75 (3.37) | 507.867 | <0.0001* | 0.333 |
| GAD‐7 | 9.17 (6.26) | 0.85 (2.48) | 441.622 | <0.0001* | 0.303 |
| SHAI | 28.43 (10.43) | 8.04 (6.42) | 799.239 | <0.0001* | 0.441 |
| ASRS‐V1.1 | 43.37 (0.64) | 25.71 (0.42) | 268.402 | <0.0001* | 0.209 |
| Inattention | 23.57 (0.34) | 13.73 (0.24) | 290.483 | <0.0001* | 0.223 |
| Hyperactivity/impulsivity | 19.80 (0.34) | 11.99 (0.20) | 190.656 | <0.0001* | 0.158 |
| AQ | 26.9 (6.94) | 21.2 (6.86) | 69.352 | <0.0001* | 0.064 |
| Social skills | 6.73 (2.49) | 5.31 (2.76) | 39.397 | <0.0001* | 0.037 |
| Attention switching | 5.74 (2.05) | 4.28 (1.89) | 58.023 | <0.0001* | 0.054 |
| Attention to detail | 4.74 (2.10) | 4.15 (1.96) | 10.421 | 0.00129* | 0.010 |
| Communication | 4.39 (2.25) | 3.37 (2.19) | 29.878 | <0.0001* | 0.029 |
| Imagination | 4.17 (1.84) | 3.80 (1.73) | 10.823 | 0.00104* | 0.011 |
| TIPI | |||||
| Extraversion | 2.98 (1.32) | 3.75 (1.34) | 53.042 | <0.0001* | 0.050 |
| Agreeableness | 4.66 (1.24) | 4.89 (1.07) | 4.402 | 0.03614* | 0.004 |
| Conscientiousness | 3.71 (1.44) | 4.18 (1.23) | 15.232 | 0.00010* | 0.015 |
| Neuroticism | 4.85 (1.39) | 3.57 (1.18) | 148.436 | <0.0001* | 0.128 |
| Openness | 3.54 (1.40) | 3.78 (1.19) | 7.049 | 0.00805* | 0.007 |
| PID‐5‐BF | |||||
| Negative affectivity | 1.38 (0.69) | 0.772 (0.744) | 109.142 | <0.0001* | 0.097 |
| Detachment | 1.44 (0.67) | 0.986 (0.728) | 25.168 | <0.0001* | 0.049 |
| Antagonism | 0.88 (0.61) | 0.742 (0.711) | 6.041 | 0.01414* | 0.006 |
| Disinhibition | 1.07 (0.70) | 0.812 (0.752) | 13.272 | 0.00028* | 0.013 |
| Psychoticism | 1.15 (0.68) | 0.716 (0.711) | 48.242 | <0.0001* | 0.045 |
Abbreviations: ASRS‐V1.1, ADHD Self‐Report Scale‐V1.1; AQ, Autism Spectrum; GAD‐7, Generalized Anxiety Disorder 7; PHQ‐15, Patient Health Questionnaire‐15; PHQ‐9, Patient Health Questionnaire‐9; PID‐5‐BF, Personality Inventory for DSM‐5‐Brief Form; SD, standard deviation; SHAI, Short Health Anxiety Inventory; SSD, somatic symptom disorder; TIPI, Ten‐Item Personality Inventory.
Level of significance set at p < 0.05.
The probable SSD group exhibited significantly higher levels of somatic symptom severity, depression, anxiety, health anxiety, ASRS‐v1.1 total score, inattention, hyperactivity, AQ total score, poor social skills, poor attention switching, attention to detail, poor communication, poor imagination, neuroticism, negative affectivity, detachment, antagonism, disinhibition, and psychoticism and significantly lower scores of extraversion, agreeableness, conscientiousness, and openness compared with the HC group.
Association between neurodevelopmental traits, personality traits, and SSD
Spearman's rank correlation analysis was performed in the probable SSD group. The results are summarized in Table 3. Spearman's rank correlation was considered significant at P < 0.05. SSD‐12 scores were associated with PHQ‐9 (r = 0.320, P < 0.001), GAD‐7 (r = 0.294, P < 0.001), and ASRS‐v1.1 (r = 0.204, P < 0.001). PHQ‐15 scores were correlated with PHQ‐9 (r = 0.370, P < 0.001), GAD‐7 (r = 0.378, P < 0.001), ASRS‐v1.1 (r = 0.319, P < 0.001), negative affectivity (r = 0.234, P < 0.001), psychoticism (r = 0.224, P < 0.001), and neuroticism (r = 0.218, P < 0.001).
Table 3.
Association between neurodevelopmental traits, personality traits, and SSD (n = 491).
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1. SSD‐12 | 1 | ||||||||||||||||
| 2. PHQ‐15 | 0.186** | 1 | |||||||||||||||
| 3. SHAI | 0.396** | 0.313** | 1 | ||||||||||||||
| 4. PHQ‐9 | 0.320** | 0.370** | 0.494** | 1 | |||||||||||||
| 5. GAD‐7 | 0.294** | 0.378** | 0.511** | 0.809** | 1 | ||||||||||||
| 6. ASRS v.1.1 | 0.204** | 0.319** | 0.442** | 0.565** | 0.587** | 1 | |||||||||||
| 7. AQ | 0.090* | 0.134** | 0.273** | 0.321** | 0.372** | 0.398** | 1 | ||||||||||
| 8. Extraversion | −0.030 | −0.021 | −0.105* | −0.158** | −0.180** | −0.035 | −0.448** | 1 | |||||||||
| 9. Agreeableness | 0.016 | −0.142** | −0.168** | −0.213** | −0.230** | −0.346** | −0.277** | −0.161** | 1 | ||||||||
| 10. Conscientiousness | −0.043 | −0.114* | −0.176** | −0.218** | −0.142** | −0.314** | −0.256** | 0.124** | 0.258** | 1 | |||||||
| 11. Neuroticism | 0.182** | 0.218** | 0.347** | 0.431** | 0.485** | 0.351** | 0.400** | −0.318** | −0.240** | −0.432 | 1 | ||||||
| 12.Openness | −0.015 | 0.022 | −0.109* | −0.147** | −0.094* | −0.009 | −0.271** | 0.424** | 0.024 | 0.293** | −0.348** | 1 | |||||
| 13. Negative Affectivity | 0.155** | 0.234** | 0.382** | 0.397** | 0.473** | 0.506** | 0.396** | −0.135** | −0.299** | −0.213** | 0.444** | −0.11* | 1 | ||||
| 14. Detachment | 0.111* | 0.149** | 0.282** | 0.347** | 0.340** | 0.374** | 0.427** | −0.245** | −0.239** | −0.172** | 0.281** | −0.208** | 0.509** | 1 | |||
| 15. Antagonism | 0.028 | 0.099* | 0.106* | 0.044 | 0.065 | 0.298** | −0.012 | 0.251** | −0.258** | −0.037 | −0.12** | 0.266** | 0.315** | 0.216** | 1 | ||
| 16. Disinhibition | 0.130** | 0.160** | 0.271** | 0.311** | 0.266** | 0.487** | 0.265** | 0.097* | −0.322** | −0.346** | 0.209** | 0.007 | 0.562** | 0.437** | 0.477** | 1 | |
| 17. Psychoticism | 0.101* | 0.224** | 0.272** | 0.301** | 0.335** | 0.520** | 0.327** | 0.044 | −0.341** | −0.221** | 0.190** | 0.118** | 0.561** | 0.487** | 0.595** | 0.618** | 1 |
Abbreviations: GAD‐7, Generalized Anxiety Disorder 7; PHQ‐15, Patient Health Questionnaire‐15; PHQ‐9, Patient Health Questionnaire‐9; SHAI, Short Health Anxiety Inventory; SSD‐12, Somatic Symptom Disorder–B Criteria Scale.
p < 0.05
p < 0.01.
Effect of neurodevelopmental traits on emotional problems and probable SSD
SEM was conducted in the probable SSD group with neurodevelopmental traits, personality traits, emotional problems, and SSD as latent variables. The model fit worsened when a latent variable for personality traits was included, therefore it was excluded. Figure 1 shows our model with standardized path coefficients (b). The SEM analysis indicated an excellent fit of the measurement model to the data, with χ 2/df = 1.075, P = 0.271, CFI = 0.998, TLI = 0.996, GFI = 0.99, AGFI = 0.972, RMSEA = 0.012, and SRMR = 0.0176 (90% confidence interval 0.00–0.028).
Figure 1.
Effect of neurodevelopmental traits on emotional problems and probable somatic symptom disorder. ASRS‐V1.1, Adult ADHD Self‐Report Scale‐V1.1; AQ, Autism Spectrum Quotient; GAD‐7, Generalized Anxiety Disorder 7; PHQ‐9, Patient Health Questionnaire‐9; PHQ‐15, Patient Health Questionnaire‐15; SHAI, Short Health Anxiety Inventory; SSD‐12, the Somatic Symptom Disorder–B Criteria Scale.
Figure 1 shows that neurodevelopmental traits positively and directly affected emotional problems (b = 0.83, P < 0.001) and SSD (b = 0.48, P = 0.003). However, emotional problems did not positively or directly affect SSD (b = 0.46, P = 0.054).
DISCUSSION
This study examined the neurodevelopmental and personality traits of patients with SSD. According to our understanding, this is the first study to show that individuals with probable SSD may simultaneously exhibit neurodevelopmental and personality disorder traits.
Our study showed differences in the demographics of participants with the probable SSD group and the HC group, as well as in developmental traits, personality traits, personality disorder traits, depression, and anxiety. Furthermore, we showed the effect of neurodevelopmental traits on emotional problems and probable SSD in the probable SSD group. The following section provides a discussion on each aspect.
Demographic features and SSD
In this study, individuals in the probable SSD group had a significantly higher proportion of individuals who were single, whose highest level of education was junior high school or high school, who were unemployed or retired, and who used the healthcare system at least once a month significantly more often compared with the HC group. Previous research has indicated that SSD is more common among individuals with lower levels of education and socioeconomic status. 1 These findings match those of previous studies showing that persistent somatic symptoms are linked to demographic features (fewer years of education, lower socioeconomic status, and unemployment). 2
In this study, the probable SSD group had significantly higher healthcare utilization. This is consistent with previous research showing a substantial correlation between SSD‐12 scores and the frequency of visits to primary care providers. 20 Barsky et al. reported that patients with somatization have approximately twice the annual medical care costs of those without somatization. 42
Neurodevelopmental traits and SSD
Our findings suggest that ADHD (inattention and hyperactivity/impulsivity) and ASD traits (particularly attention switching) are related to probable SSD.
A previous study showed that children and adolescents with ADHD traits (inattention, hyperactivity/impulsivity) experienced higher levels of anxiety and somatic symptoms compared to those without ADHD, 13 and the results of this study for adults were consistent with previous findings for children and adolescents.
Among the ASD traits, a previous study reported that children with SSD had significantly more difficulty with only attention switching. 32 On the other hand, in our results there were significant differences between groups in AQ total score and all subcategories. 43
The SEM results showed that neurodevelopmental traits affected emotional problems (depression, anxiety) and SSD. However, emotional problems did not positively or directly affect SSD in the probable SSD group. It may be developmental traits rather than depression or anxiety that predict severe SSD.
Personality traits, personality disorder traits, and SSD
Our study showed that personality traits and personality disorder traits related to probable SSD. Neuroticism (η2 = 0.128) and negative affectivity (η2 = 0.097) had particularly large effect sizes. The previous studies reported that neuroticism and negative affectivity have been identified as independent risk factors for many somatic symptoms, 1 which are related to depression and anxiety, 44 , 45 , 46 and are also associated with SSD. 47 Macina et al. reported that “in three studies (N = 2025) correlations between somatoform disorders/SSD and neuroticism/negative affectivity (d = 0.22–1.041) were present”. 48 Our findings matched the previous study. In this study, all subscale scores on the PID‐5‐BF were significantly higher in the probable SSD group compared to the HC group. No previous studies examining the relationship between the PID‐5‐BF and SSD or probable SSD were found.
Depression, anxiety, and SSD
Our findings show that participants with probable SSD exhibited symptoms of depression and anxiety. These results match those of previous studies showing that comorbid anxiety or depression is common and may exacerbate symptoms and impairments in patients with SSD. 1 , 49 , 50 Additionally, significant associations have been reported between SSD‐12 scores and level of depression and anxiety in the general population, 51 primary care settings, 19 and psychosomatic outpatient samples. 18
Based on our findings, when approaching patients suspected of having SSD, primary care physicians may consider not only somatic symptoms, but also depression, anxiety, and neurodevelopmental and personality traits, therefore comprehensive approaches are considered to be effective for them.
The study has three limitations that should be acknowledged. First, this study's outcome compares the neurodevelopmental and personality traits according to the score of SSD‐12 in a general population. Future research is needed to explore whether SSD patients are also associated with neurodevelopmental and personality traits. Second, this was a voluntary self‐reported online survey. In the future, an online survey using a random sampling method should be conducted in which the probability of being selected for the sample would be equal for all individuals. Third, due to the study's cross‐sectional design, a causal relationship was unclear, therefore further research is required to draw reliable conclusions.
AUTHOR CONTRIBUTIONS
Mirai Miyoshi: Conceptualization; writing the original draft. Rieko Takanashi: Conceptualization; review and editing. Kayoko Taguchi: Conceptualization; supervision; review and editing. Tokiko Yoshida: Conceptualization; review and editing. Kohei Kurita: Conceptualization; statistical analysis. Eiji Shimizu: Conceptualization; project administration; supervision; review and editing.
CONFLICT OF INTEREST STATEMENT
The authors declare no conflicts of interest.
ETHICS APPROVAL STATEMENT
The protocol for the research project has been approved by a suitably constituted Ethics Committee of an institution, and it conforms to the provisions of the Declaration of Helsinki. Ethical approval was granted by the Research Ethics Committee of the Graduate School of Medicine, Chiba University (approval number: M10399).
PATIENT CONSENT STATEMENT
Before participation, all participants read an informed consent document about this study's overview on the web and then confirmed their consent to voluntarily participate in the survey by clicking “I agree” after having an opportunity to ask their questions to the researchers by e‐mail.
CLINICAL TRIAL REGISTRATION
N/A.
ACKNOWLEDGMENTS
The authors thank Professor Toshihide Kuroki and Mr. Kazumasa Horie for their permission to use PID‐5‐BF‐J. We also thank Dr. Toshiyuki Tominaga for permission to use the Japanese version of the SSD‐12. We would like to express our gratitude to Editage (www.editage.com) for their assistance with English language editing. This study received support from Japan Society for the Promotion of Science KAKENHI (grant number: 19K22738, 22K11458).
Miyoshi M, Takanashi R, Taguchi K, Yoshida T, Kurita K, Shimizu E. Neurodevelopmental and personality traits of somatic symptom disorder: a cross‐sectional study. Psychiatry Clin Neurosci Rep. 2025;4:e70082. 10.1002/pcn5.70082
DATA AVAILABILITY STATEMENT
N/A.
REFERENCES
- 1. American Psychiatric Association . Diagnostic and Statistical Manual of Mental Disorders. 5 th edition . American Psychiatric Association; 2013. [Google Scholar]
- 2. American Psychiatric Association . Diagnostic and Statistical Manual of Mental Disorders. Fifth Edition. Text Revision (DSM‐5‐TR American Psychiatric Association; 2022. p. 351–6.
- 3. Löwe B, Levenson J, Depping M, Hüsing P, Kohlmann S, Lehmann M, et al. Somatic symptom disorder: a scoping review on the empirical evidence of a new diagnosis. Psychol Med. 2022;52:632–648. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Creed F, Barsky A. A systematic review of the epidemiology of somatisation disorder and hypochondriasis. J Psychosom Res. 2004;56:391–408. [DOI] [PubMed] [Google Scholar]
- 5. Rief W, Mewes R, Martin A, Glaesmer H, Brähler E. Evaluating new proposals for the psychiatric classification of patients with multiple somatic symptoms. Psychosom Med. 2011;73:760–768. [DOI] [PubMed] [Google Scholar]
- 6. van Geelen SM, Rydelius PA, Hagquist C. Somatic symptoms and psychological concerns in a general adolescent population: exploring the relevance of DSM‐5 somatic symptom disorder. J Psychosom Res. 2015;79:251–258. [DOI] [PubMed] [Google Scholar]
- 7. Nazzal Z, Maraqa B, Abu Zant M, Qaddoumi L, Abdallah R. Somatic symptom disorders and utilization of health services among Palestinian primary health care attendees: a cross‐sectional study. BMC Health Serv Res. 2021;21:615. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Dunphy L, Penna M, EL‐Kafsi J. Somatic symptom disorder: a diagnostic dilemma. BMJ Case Rep. 2019;12:e231550. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Hirota T, King BH. Autism spectrum disorder: a review. JAMA. 2023;329:157–168. [DOI] [PubMed] [Google Scholar]
- 10. Polanczyk GV, Willcutt EG, Salum GA, Kieling C, Rohde LA. ADHD prevalence estimates across three decades: an updated systematic review and meta‐regression analysis. Int J Epidemiol. 2014;43:434–442. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Lai MC, Kassee C, Besney R, Bonato S, Hull L, Mandy W, et al. Prevalence of co‐occurring mental health diagnoses in the autism population: a systematic review and meta‐analysis. The Lancet Psychiatry. 2019;6:819–829. [DOI] [PubMed] [Google Scholar]
- 12. Williams ZJ, Gotham KO. Current and lifetime somatic symptom burden among transition‐aged autistic young adults. Autism Res. 2022;15:761–770. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Okyar E, Bozatlı L, Görker I, Okyar S. Anxiety and somatic symptoms in children and adolescents diagnosed with attention‐deficit hyperactivity disorder. Psychiatry J. 2023;2023:5523312. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. de Vroege L, Woudstra‐de Jong JE, Videler AC, Kop WJ. Personality factors and cognitive functioning in patients with somatic symptom and related disorders. J Psychosom Res. 2022;163:111067. [DOI] [PubMed] [Google Scholar]
- 15. Menon V, Shanmuganathan B, Thamizh JS, Arun AB, Kuppili PP, Sarkar S. Personality traits such as neuroticism and disability predict psychological distress in medically unexplained symptoms: a three‐year experience from a single centre. Person Ment Health. 2018;12:145–154. [DOI] [PubMed] [Google Scholar]
- 16. Garcia‐Campayo J, Alda M, Sobradiel N, Olivan B, Pascual A. Personality disorders in somatization disorder patients: a controlled study in Spain. J Psychosom Res. 2007;62:675–680. [DOI] [PubMed] [Google Scholar]
- 17. Bornstein RF, Gold SH. Comorbidity of personality disorders and somatization disorder: a meta‐analytic review. J Psychopathol Behav Assess. 2008;30:154–161. [Google Scholar]
- 18. Toussaint A, Murray AM, Voigt K, Herzog A, Gierk B, Kroenke K, et al. Development and validation of the Somatic Symptom Disorder–B Criteria Scale (SSD‐12). Psychosom Med. 2016;78:5–12. [DOI] [PubMed] [Google Scholar]
- 19. Toussaint A, Riedl B, Kehrer S, Schneider A, Löwe B, Linde K. Validity of the Somatic Symptom Disorder–B Criteria Scale (SSD‐12) in primary care. Fam Pract. 2018;35:342–347. [DOI] [PubMed] [Google Scholar]
- 20. Kop WJ, Toussaint A, Mols F, Löwe B. Somatic symptom disorder in the general population: associations with medical status and health care utilization using the SSD‐12. Gen Hosp Psychistry. 2019;56:36–41. [DOI] [PubMed] [Google Scholar]
- 21. Toussaint A, Hüsing P, Kohlmann S, Löwe B. Detecting DSM‐5 somatic symptom disorder: criterion validity of the Patient Health Questionnaire‐15 (PHQ‐15) and the Somatic Symptom Scale‐8 (SSS‐8) in combination with the Somatic Symptom Disorder–B Criteria Scale (SSD‐12). Psychol Med. 2020;50:324–333. [DOI] [PubMed] [Google Scholar]
- 22. Muramatsu K, Kamijima K, Yoshida M, Otsubo T, Miyaoka H, Muramatsu Y, et al. The patient health questionnaire, Japanese version: validity according to the mini‐international neuropsychiatric interview–plus. Psychol Rep. 2007;101:952–960. [DOI] [PubMed] [Google Scholar]
- 23. Kroenke K, Spitzer RL, Williams JBW. The PHQ‐9. J Gen Intern Med. 2001;16:606–613. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. Inagaki M, Ohtsuki T, Yonemoto N, Kawashima Y, Saitoh A, Oikawa Y, et al. Validity of the Patient Health Questionnaire (PHQ)‐9 and PHQ‐2 in general internal medicine primary care at a Japanese rural hospital: a cross‐sectional study. Gen Hosp Psychistry. 2013;35:592–597. [DOI] [PubMed] [Google Scholar]
- 25. Spitzer RL, Kroenke K, Williams JBW, Löwe B. A brief measure for assessing generalized anxiety disorder: the GAD‐7. Arch Intern Med. 2006;166:1092–1097. [DOI] [PubMed] [Google Scholar]
- 26. Muramatsu K, Miyaoka H, Ueshima K, et al Validation and utility of a Japanese version of the GAD‐7. Jpn. J. Psychosom. Med. 2009;51:79. [in Japanese]. [Google Scholar]
- 27. Salkovskis PM, Rimes KA, Warwick HMC, Clark DM. The Health Anxiety Inventory: development and validation of scales for the measurement of health anxiety and hypochondriasis. Psychol Med. 2002;32:843–853. [DOI] [PubMed] [Google Scholar]
- 28. Yamauchi G, Matsuoka H, Mi Himachi, Sasagawa S, Sakano Y. Development and validation of Japanese Short Health Anxiety Inventory. Jpn. Soc. Psychosom. Med. 2009;49:1295–1304. [Google Scholar]
- 29. Kessler RC, Adler L, Ames M, Demler O, Faraone S, Hiripi E, et al. The World Health Organization Adult ADHD Self‐Report Scale (ASRS): a short screening scale for use in the general population. Psychol Med. 2005;35:245–256. [DOI] [PubMed] [Google Scholar]
- 30. Anbarasan D, Kitchin M, Adler LA. Screening for adult ADHD. Curr Psychiatry Rep. 2020;22:72. [DOI] [PubMed] [Google Scholar]
- 31. Baron‐Cohen S, Wheelwright S, Skinner R, Martin J, Clubley E. The autism‐spectrum quotient (AQ): evidence from Asperger syndrome/high‐functioning autism, males and females, scientists and mathematicians. J Autism Dev Disord. 2001;31:5–17. [DOI] [PubMed] [Google Scholar]
- 32. Wakabayashi A, Tojo Y, Baron‐Cohen S, Wheelwright S. The Autism‐Spectrum Quotient (AQ) Japanese versions: evidence from high‐functioning clinical group and normal adults. Jpn J Psychol. 2004;75:78–84. [in Japanese]. [DOI] [PubMed] [Google Scholar]
- 33. Gosling SD, Rentfrow PJ, Swann WB. A very brief measure of the big‐five personality domains. J Res Pers. 2003;37:504–528. [Google Scholar]
- 34. Atsushi O, Shingo A, Cutrone P. Development, reliability, and validity of the Japanese version of Ten Item Personality Inventory (TIPI‐J). Jpn Soc Personal Psychol. 2012;21:40–52. [in Japanese]. [Google Scholar]
- 35. Kazumasa H, Chiho S, Toshihide K. Development of the Japanese version of the Personality Inventory for DSM‐5 Brief Form (PID‐5‐BF‐J) and examination of its reliability and validity. Bull Cent Clin Psychol Hum Dev Kyushu Univ. 2022;13:17–23. [Google Scholar]
- 36. Kline RB. Principles and Practice of Structural Equation Modeling, 4th Edition. Guilford Press; 2016. [Google Scholar]
- 37. Bentler PM, Bonett DG. Significance tests and goodness of fit in the analysis of covariance structures. Psychol Bull. 1980;88:588–606. [Google Scholar]
- 38. Bentler PM. Comparative fit indexes in structural models. Psychol Bull. 1990;107:238–246. [DOI] [PubMed] [Google Scholar]
- 39. Bollen KA, Long JS. Testing Structural Equation Models. Sage Publications; 1993. [Google Scholar]
- 40. Browne MW, Cudeck R. Alternative ways of assessing model fit. Sociol Methods Res. 1992;21:230–258. [Google Scholar]
- 41. Hu L, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal. 1999;6:1–55. [Google Scholar]
- 42. Barsky AJ, Orav EJ, Bates DW. Somatization increases medical utilization and costs independent of psychiatric and medical comorbidity. Arch Gen Psychiatry. 2005;62:903–910. [DOI] [PubMed] [Google Scholar]
- 43. Hatta K, Hosozawa M, Tanaka K, Shimizu T. Exploring traits of autism and their impact on functional disability in children with somatic symptom disorder. J Autism Dev Disord. 2019;49:729–737. [DOI] [PubMed] [Google Scholar]
- 44. Sanchez‐Roige S, Gray JC, MacKillop JK, Chen CH, Palmer AA. The genetics of human personality. Genes Brain Behav. 2018;17:e12439. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45. Smith DJ, Escott‐Price V, Davies G, Bailey MES, Colodro‐Conde L, Ward J, et al. Genome‐wide analysis of over 106 000 individuals identifies 9 neuroticism‐associated loci. Mol Psychiatry. 2016;21:749–757. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46. Knowles KA, Olatunji BO. Specificity of trait anxiety in anxiety and depression: meta‐analysis of the State‐Trait Anxiety Inventory. Clin Psychol Rev. 2020;82:101928. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47. van Dijk SDM, Hanssen D, Naarding P, Lucassen P, Comijs H, Oude Voshaar R. Big five personality traits and medically unexplained symptoms in later life. Eur Psychiatry. 2016;38:23–30. [DOI] [PubMed] [Google Scholar]
- 48. Macina C, Bendel R, Walter M, Wrege JS. Somatization and somatic symptom disorder and its overlap with dimensionally measured personality pathology: a systematic review. J Psychosom Res. 2021;151:110646. [DOI] [PubMed] [Google Scholar]
- 49. Bailer J, Kerstner T, Witthöft M, Diener C, Mier D, Rist F. Health anxiety and hypochondriasis in the light of DSM‐5. Anxiety, Stress, & Coping. 2016;29:219–239. [DOI] [PubMed] [Google Scholar]
- 50. Liao S‐C, Ma H‐M, Lin Y‐L, Huang W‐L. Functioning and quality of life in patients with somatic symptom disorder: the association with comorbid depression. Compr Psychiatry. 2019;90:88–94. [DOI] [PubMed] [Google Scholar]
- 51. Toussaint A, Löwe B, Brähler E, Jordan P. The Somatic Symptom Disorder–B Criteria Scale (SSD‐12): factorial structure, validity and population‐based norms. J Psychosom Res. 2017;97:9–17. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
N/A.