Atypical sensory modulation (ASM), a subtype of atypical sensory processing, is a generalized disorder that affects the ability to grade response to stimuli across single or multiple sensory systems. Three subtypes characterize ASM:

1. Sensory underresponsivity (SUR) is clinically demonstrated by delayed or decreased responses to stimulation (Interdisciplinary Council on Developmental and Learning Disorders [ICDL], 2005; Miller, Anzalone, Lane, Cermak, & Osten, 2007; Psychodynamic Diagnostic Manual Task Force, 2006; Zero to Three, 2005);

2. Sensory overresponsivity (SOR) manifests clinically as a condition in which nonnoxious stimuli are perceived as abnormally irritating, unpleasant (Fisher & Dunn, 1983; ICDL, 2005; Miller et al., 2007; Psychodynamic Diagnostic Manual Task Force, 2006; Reynolds & Lane, 2008; Zero to Three, 2005), or painful (Bar-Shalita, Vatine, Parush, Deutsch, & Seltzer, 2012; Bar Shalita, Vatine, Seltzer, & Parush, 2009; Bar-Shalita, Vatine, Yarnitsky, Parush, & Weissman-Fogel, 2014; Fisher & Dunn, 1983).

3. Sensory seeking, or craving, occurs when the person seeks an unusual amount or type of sensation and seems to have an extreme craving for sensation (Miller et al., 2007).

Impaired sensory modulation greatly limits and interferes with participation in daily routines and activities (Bar-Shalita, Vatine, & Parush, 2008; Dunn, 2007). Moreover, the impact of ASM on quality of life (QoL) has been well documented in adults, children, and their families (Carter, Ben-Sasson, & Briggs-Gowan, 2011; Cosbey, Johnston, & Dunn, 2010; Kinnealey, Koenig, & Smith, 2011). Health-related QoL (HRQOL) is conceptualized as having two components: mental and physical health. A third component of participation has also been proposed because participation is essential in HRQOL (Ware, 2003).

It is estimated that 5%–16% of the typical pediatric population demonstrate ASM (Ahn, Miller, Milberger, & McIntosh, 2004; Ben-Sasson, Carter, & Briggs-Gowan, 2009), and the disorder has also been identified in adulthood (Bar-Shalita, Seltzer, Vatine, Yochman, & Parush, 2009; Brown, Tollefson, Dunn, Cromwell, & Filion, 2001; Kinnealey, Oliver, & Wilbarger, 1995). Children with SOR (Bar Shalita, Vatine, et al., 2009) and adults with ASM (Bar-Shalita et al., 2012) were tested by the psychophysical method of quantitative sensory testing by measuring somatosensory thresholds and magnitude estimations of suprathreshold pain stimuli. Results demonstrated generally normal sensation ranges for somatosensory detection and pain threshold levels, with no group differences. However, when examining suprathreshold magnitude estimations of pain, hyperalgesic responses were found; when compared with control participants, children and adults with ASM rated these pain sensations higher and, moreover, reported the lingering sensation as being more painful and lasting longer. Thus, these results validate an atypical response pattern and suggest alterations in pain modulation and pain processing (Bar-Shalita et al., 2012, 2014; Bar-Shalita, Vatine, et al., 2009). These possible neural alterations may interfere with daily functioning because daily environmental sensations may be perceived as painful (Bar-Shalita et al., 2012, 2014; Bar-Shalita, Deutsch, Honigman, & Weissman-Fogel, 2015; Bar-Shalita, Vatine, et al., 2009). Moreover, because pain is a complex multidimensional experience composed of affective processes (Moayedi & Davis, 2013), a better understanding of the association between sensory responsiveness and emotional characteristics of people with ASM is warranted.

Ayres (1972)  suggested that the demonstrated atypical responses to daily environmental sensations are due to a deficit in modulating incoming sensory stimuli, which then manifests as distractibility, stress-related behaviors, and anxiety. Anxiety is thought to result from a hypersensitivity to environmental stimuli that may be due to faulty information processing (Abernethy, 2010). Several investigators have studied anxiety in children, adolescents, and adults and have found notable positive relationships between SOR and anxiety (Kinnealey et al., 2011; Lane, Reynolds, & Thacker, 2010; Neal, Edelmann, & Glachan, 2002), suggesting that the overvigilance in overresponsivity may increase anxiety and negative emotions (Ben-Sasson et al., 2008). Interestingly, Engel-Yeger and Dunn (2011)  studied the association among sensory modulation patterns of response not only with negative but also with positive affect (subjective moods and feelings). They found positive correlations among negative affect and patterns of SOR but also among negative affect and patterns of SUR. Moreover, positive affect was found to be correlated with the sensory-seeking and craving pattern, demonstrating that all patterns of response to sensations are associated with affect. However, the relationship between ASM and the broader concept of psychological distress has not been elucidated. Psychological distress serves as the source of both internalizing (e.g., depression, anxiety) and externalizing (e.g., anger, aggression) disorders, thus accounting for the full range of psychopathology (Ellis, 1997; Ziegler & Leslie, 2003). Thus, there is a need to more fully examine the relationship between ASM and psychological distress.

Our goal in this study was to examine whether psychological distress symptoms characterize people with ASM and to determine whether important differences exist between people with ASM and typical people in QoL within the general population. Because a risk for a clinical disorder is increased by early presence of low-level symptomatology (Poulton et al., 2000), we explored ASM and QoL as risk factors for psychological distress. This exploration of ASM and QoL as risk factors for psychological distress may yield new understanding and research directions to broaden possible intervention modalities for people with ASM. We hypothesized that people with ASM and reduced QoL would show greater degrees of psychological distress.

The research was approved by the review committee at the Hebrew University of Jerusalem, and all participants completed and signed a consent form before enrolling in the study.

A nonreferred convenience sample of 204 adults participated in the study. Mean age was 27.4 yr (standard deviation [SD] = 3.71; age range = 23–40 yr). The gender distribution was 51.5% (n = 105) men and 48.5% women (n = 99). The study sample was composed of 48.5% university students; the rest were mainly employed participants recruited off campus. Exclusion criteria included pregnancy; neurological deficits including speech, vision, hearing, or behavioral abnormalities; and a family history in siblings, parents, or grandparents that included any form of psychopathology.

Participants were divided into two groups on the basis of their scores on the Sensory Responsiveness Questionnaire—Intensity Scale (SRQ–IS; Bar-Shalita, Seltzer, et al., 2009). The control group, referred to as the comparison group, included participants who scored within the normal cutoff scores (+2 SDs) for the SRQ–IS, whereas the group with ASM (referred to as the sensory modulation disorder [SMD] group) consisted of participants who scored more than 2 SDs from the mean using the cutoff scores for the SRQ–IS. The 2-SD cutoff scores were used to ensure cautious estimation of SMD prevalence (see the Instrumentation and Measures section).

The SRQ–IS (Bar-Shalita, Seltzer, et al., 2009) is a standardized self-report questionnaire assessing responses to daily sensations, and it is used to clinically identify SMD in adolescents and adults ages 14 yr and older. The SRQ–IS presents a set of 58 items that represent typical scenarios encountered occasionally throughout daily life. Each scenario involves one sensory stimulus in one modality, including auditory, visual, gustatory, olfactory, vestibular, and somatosensory stimuli (excluding pain). The items are worded in a manner that attributes a hedonic or aversive valence to the situation (e.g., “It bothers me the way new clothes feel”; “I am bothered by background humming noises [air conditioner, refrigerator, computer fan, etc.]”). The participant rates the intensity of the hedonic and aversive response to the situation using a 5-point scale ranging from 1 (not at all) to 5 (very much). The SRQ–IS has been demonstrated to have content, criterion, and construct validity as well as internal consistency (Cronbach αs = .90–.93) and test–retest reliability (rs = .71–.84, ps < .001–.005; Bar-Shalita, Seltzer, et al., 2009).

In this study, we defined the normal range as the mean (M) + 2 SDs for both scores. The SOR subtype was determined by applying the SRQ–Aversive subscore (32 items), for which scores were higher than the normal mean cutoff score + 2 SDs (M + SD = 1.87 + 0.26). The SUR subtype was determined by applying the SRQ–Hedonic subscore (26 items), for which scores were higher than the normal mean cutoff score + 2 SDs (M + SD = 2.10 + 0.33). Participants scoring higher than one or both cutoff scores composed the adults with ASM (i.e., the SMD group).

The Brief Symptom Inventory (BSI; Derogatis & Coons, 1993) is a standard reliable and valid self-report questionnaire assessing psychological distress. This questionnaire consists of 53 items that elicit clinically relevant psychological symptoms covering nine symptom dimensions: Somatization, Obsessive–Compulsive, Interpersonal Sensitivity, Depression, Anxiety, Hostility, Phobic Anxiety, Paranoid Ideation, and Psychoticism. Respondents rank each item (e.g., “Feeling uneasy in crowds”) on a 5-point scale ranging from 0 (not at all) to 4 (extremely). Rankings characterize the intensity of distress during the past month, including the day of administration. The BSI is scored for each of the nine subscales in addition to two global indicators: (1) the Global Severity Index (GSI), which combines data on the number of symptoms and the intensity of distress and represents an effective single summary indicator of psychopathology, and (2) the Positive Symptom Total (PST), which is a frequency count of questionnaire items that the participant ranked 1–4, excluding those items rated 0.

The BSI: Administration, Scoring, and Procedures Manual (Derogatis, 1993) provides normative data for four different samples, including nonpatient adults, adolescents ages 13–17 yr, adult psychiatric outpatients, and adult psychiatric inpatients (Derogatis & Coons, 1993). In the current study, we used the nonpatient adults’ normative data. This questionnaire has been standardized into Hebrew (Gilbar & Ben-Zur, 2002). In this study, we applied the nine subscale scores as well as the GSI (Gilbar & Ben-Zur, 2002) and PST global indicators.

The Short Form–36 Health Survey, Version 2 (SF–36; Ware, Kosinski, & Gandek, 2005), is a standardized, multipurpose, self-report health survey assessing QoL that yields scores in health and well-being in four areas encompassing physical health (Physical Functioning, Role Physical, Bodily Pain, and General Health) and four areas encompassing emotional health (Vitality, Social Functioning, Role Emotional, and Mental Health). It has been used extensively in social science and health-related research to discriminate among gradations of disability (Jason et al., 2011), and it has demonstrated reliability and validity (Ware et al., 2005). This questionnaire has been standardized into Hebrew (Lewin-Epstein, Sagiv-Schifter, Shabtai, & Shmueli, 1998). Item responses range from 2- to 6-point scales. Respondents are asked to think about the past month when answering.

A convenience sample of participants was contacted by phone. The purpose of the study and other preliminary information were provided by the researcher, and exclusion criteria were verified. With the participant’s consent, an appointment was made at his or her convenience. After completing a consent form and a medical and demographic questionnaire that obtained information about the participants and their families, the SRQ–IS, BSI, and SF–36 were then completed. Order was randomized to avoid sequential effects and to balance the possible influence of fatigue and attention span. The session lasted for approximately 45 min, with the researcher present in the same room and available to answer any questions.

Statistical analyses were performed with SAS (Version 9.3; SAS Institute, Cary, NC). Continuous variables (age, BSI, SF–36, SRQ–IS) were summarized by means and standard deviations and compared with t tests or Wilcoxon tests when relevant. Categorical variables (gender, SMD category) were summarized by a count and percentage and compared with χ² tests. Pearson’s correlation coefficient was presented between pairs of continuous variables with a level of significance. Linear regression was performed to assess the multiple correlation coefficient (R ) and regression coefficients; standardized coefficients and effect sizes (partial η-square) are also presented. BSI normative ranges are presented in Table 1 (as the M + 3 SDs) to enable comparison with BSI results in the current study. All statistical tests were two sided and tested at a 5% level of significance. Because this was an exploratory study, in that there were no previously existing data relating SMD and BSI, adjustments for multiple testing were not performed and nominal p values are presented. In addition, effect sizes (Cohen’s d ) and respective 95% confidence intervals are presented.

Group placement was determined with the SRQ–IS. We found that 12.75% (n = 26) of the total sample (N = 204) met the criterion for SMD (defined as +2 SDs from the mean), and 11.27% (n = 23) and 1.47% (n = 3) of the total sample met the criterion for SOR and SUR, respectively. An equal gender distribution (13 women, 13 men) was found for the SMD group. The comparison group (n = 178 participants without SMD) included 86 women and 92 men. Gender distribution was not significant between groups (χ² = 0.03, p = .87). Mean age for the SMD and comparison groups was 29.2 yr (SD = 4.38) and 27.1 yr (SD = 3.53), respectively; this difference was significant, t(201) = 2.81, p = .005.

Initially, we tested whether the BSI total and subscales differed between participants with SOR and participants with SUR within the SMD group, and we found no statistically significant differences (Wilcoxon tests—data not shown). Both participants with SOR and participants with SUR were combined to form the SMD group. All BSI subscore means were higher for the SMD group versus the comparison group; however, these differences were only statistically significant for the total indices of the GSI (higher psychopathology) and PST (more symptoms) as well as for the BSI subscales Interpersonal Sensitivity, Paranoid Ideation, and Psychoticism (see Table 1). Although higher in the SMD group, mean scores of all indices were in the average range (see Table 1). Moreover, scores of all participants, except 1 participant in the comparison group, were also in the average range on the basis of norms reported for Israeli adults (Gilbar & Ben-Zur, 2002).

The SMD group had considerably lower scores than the comparison group for Physical Health Total and two subscales of the physical domain: Role Physical and Body Pain (lower QoL; Table 2). Between-groups differences in the SF–36 Mental Health domain were not significant.

In a preliminary simple correlation analysis, BSI total score (GSI) was significantly correlated with SF–36 Physical Health Total and Mental Health Total scores (r = −.47, p < .0001, and r = −.48, p < .0001, respectively) as well as with SRQ–Aversive subscore (r = .46, p < .0001). However, BSI total score (GSI) was not significantly correlated with the SRQ–Hedonic subscore (r = .01, p = .87).

We used multivariate linear regression to examine whether SMD and QoL were predictors of psychological distress using the variables that correlated with GSI. Results showed that the following variables were significant predictors of GSI: SRQ–Aversive, F (1, 200) = 45.09, p < .0001; SF–36 Physical Health Total, F (1, 200) = 13.92, p = .0002; and SF–36 Mental Health Total, F (1, 200) = 12.87, p = .0004. The resulting multivariate correlation coefficient was .64. The regression coefficients that were used to predict the GSI score from the three variables (SRQ–Aversive, SF–36 Physical Health Total, and SF–36 Mental Health Total) are shown in Table 3.

In this novel study, we investigated psychological distress in community-based, nonreferred adults with typical sensory modulation and ASM. The findings revealed that adults with ASM (i.e., the SMD group) have more psychological symptoms than comparison group adults without SMD, although means of both groups were within the normal range. The Physical Health domain of QoL was considerably decreased in adults with SMD, and SMD together with reduced QoL both predicted psychological distress.

Psychological distress was considerably higher in participants with SMD. Although both groups scored within the normal range, the higher psychological distress in the SMD group may reflect a risk factor. Examination of the subscale scores that differed between the groups helps to elucidate the findings.

There was a notable group difference on the Paranoid Ideation subscale; participants with SMD had considerably more symptoms. Paranoia denotes the baseless fear that someone intends to cause harm (Freeman et al., 2005), and research has indicated that paranoid thinking is evident in 15%–20% of the general population (Freeman et al., 2005; Olfson et al., 2002). The Threat-Anticipation Model is used to identify causes of paranoid thinking (Freeman, Garety, Kuipers, Fowler, & Bebbington, 2002), and among those identified as particularly important are interpersonal sensitivity and social factors such as adverse events and environments (Freeman, Pugh, et al., 2008). In the current study, we found a statistically significant group difference in interpersonal sensitivity, suggesting that interpersonal sensitivity may also contribute to paranoid thinking in people with SMD. As for adverse events and environments, because the most immediate trigger for a paranoid thought is the misinterpretation of an everyday experience (Freeman, Pugh, et al., 2008), impairment in sensory processing may be a contributing factor in paranoid ideation (Freeman, Gittins, et al., 2008).

SMD may be a condition in which environmental stimuli are misinterpreted and may be adversely experienced, potentially resulting in paranoia. In another study, in which the general population was examined, participants were tested in the neutral social environment of an underground train ride with the presence-inducing power of virtual reality. Paranoid ideation was predicted by perceptual anomalies, such as olfactory and gustatory experiences, and was shown to be associated with anxiety, depression, worry, negative ideas about self, and interpersonal sensitivity (Freeman, Gittins, et al., 2008). These results challenged the traditional clear-cut distinctions between psychotic and emotional problems, and they introduced the idea that paranoid thoughts may be considered on a severity continuum even in the general population (Freeman, Gittins, et al., 2008).

Psychotic symptoms have not been previously examined in people with SMD. Although this study demonstrates that participants in both groups scored within the normal range, indicating nonclinical levels of psychoticism, the SMD group scored considerably higher than the group without SMD. According to Eysenck and Eysenck (1976), low levels of psychoticism indicate empathy, altruism, and socialization and are partially determined by psychosocial variables (Piekarska, 2012). Hence, the SMD group may demonstrate less empathy, altruism, and socialization than the comparison group without SMD. Because reductions in social skills and community involvement have also been found to be correlated with increased sensory sensitivity (Kinnealey et al., 1995), research is needed to examine the relationship among SMD and empathy, altruism, and socialization. Indeed, people with SMD have been described as spending too much time coping with their responses to environmental stimuli, which manifest as exhaustion and feelings of social isolation, which then may contribute to decreased empathy and altruism. Moreover, isolation has been identified as a factor that could affect the ability to fully participate and engage in daily occupations (Kinnealey et al., 1995).

We measured QoL in this study using the SF–36 (Ware et al., 2005), a broadly based, self-report measure of functional status (Jason et al., 2011). Our findings validate, to some extent, other reports (Carter et al., 2011; Cosbey et al., 2010). However, whereas Kinnealey et al. (2011), applying the same measure, reported lower scores in both QoL aspects of physical and mental functioning, our findings indicate reduction in solely the physical aspect. Still, in an editorial in the British Journal of Psychiatry,Kendell (2002)  argued that the established distinction between mental and physical illness is archaic and offered the pain phenomenon as an example to claim that although it is a common characteristic of supposedly physical illness, it is in fact a psychological phenomenon. Interestingly, in the current study, the most differentiating aspect disturbing QoL was found to be Bodily Pain. This subscale is used to explore whether one has bodily pain and to what extend the pain restricts work and household performance. Ayres (1972)  suggested that the defensive–protective behaviors seen in children with SMD are accompanied by stress responses to nocioceptive qualities of nonnoxious sensory stimuli. In line with this, Fisher and Dunn (1983)  noted that tactile stimuli normally perceived as nonnoxious are perceived as aversive in SMD. Bar-Shalita and colleagues (Bar-Shalita et al., 2012, 2014; Bar-Shalita, Vatine, et al., 2009) found that not only do people with SMD have hyperalgesia but that these sensations linger long after the termination of stimuli. Finding that QoL of participants with SMD is most affected by pain validates previous reports and stresses the importance of the pain aspect in SMD. Another aspect of physical QoL found to be important in SMD is the Role Physical subscale. This subscale is used to focus on items assessing the need to cut down or limit activities or work and accomplishing less than desired (Jason et al., 2011). These findings show the interference of SMD with life roles, thus validating the vulnerability of QoL in this population and highlighting the need to intervene and treat people with this disorder.

Most important, our study’s results indicate that SMD and QoL together predict psychological distress (r = .64). Although QoL usually serves as an outcome measure, Anwar et al. (2014)  introduced QoL as a predictive marker and argued that QoL is most informative clinically, influencing patient outcomes by directing therapy (Winter, Yeo, & Brody, 2013). This is a novel view of QoL that may add to better practice but that warrants further exploration. Findings also further validate the argument that hypersensitivity to environmental stimuli, which may be due to faulty information processing and cause overvigilance, disrupts the emotional processes (Smucny, Olincy, Eichman, Lyons, & Tregellas, 2013) and increases negative emotionality (Abernethy, 2010; Ben-Sasson et al., 2008). Indeed, it has been suggested that abnormal patterns of sensory processing may precede the onset of schizophrenia and may even lead to its foundation (Javitt, 2009; Smucny et al., 2013). Thus, SMD might serve as a risk factor for developing other health conditions.

The current study has several limitations. Although we present a study done in the general population in which SMD was found in 12.75% of the study sample, which is consistent with the statistical probability reported in pediatric populations, the SMD group consisted of only 26 participants, with the majority showing SOR. Examining participants with SOR and SUR to see whether there are differences in patterns of psychological distress between these groups is important; however, the small number of participants with SUR did not allow detailed comparison. Moreover, although the study population varied in geographical and vocational variables, with approximately 50% of the participants being university students, this was a convenience sample.

The findings of this study have several implications for occupational therapy practice:

• Participants with SMD showed more psychological distress symptoms than comparison group participants without SMD, though both groups were within the typical range. Although SMD does not indicate psychopathology, it may be a risk factor for mental health concerns.

• Understanding SMD can contribute to understanding trajectories that may lead to mental health concerns. Occupational therapy may serve a preventive role in health promotion for participants with SMD.

• This study may contribute to understanding SMD manifestations in adulthood, including the importance of using psychological distress measures in the evaluation process of SMD.

• QoL of participants with SMD was reduced in measures relating to body pain, life roles, and work. These areas should also be targeted in the evaluation process of participants with SMD to contribute to best practice for this population.

People in the general population who scored in the highest 2% on a measure of SMD demonstrated more psychological distress symptoms and reduced QoL. Moreover, SMD and QoL were found to predict psychological distress. Several investigators have indicated that the risk for a clinical disorder is increased by the early presence of low-level symptomatology (Freeman, Pugh, et al., 2008; Poulton et al., 2000). Because psychological distress is a risk factor associated with other mental health conditions (Ellis, 1997; Ziegler & Leslie, 2003), this study provides evidence that SMD may serve as a risk factor for mental health concerns. This finding has important clinical implications in setting a wide scope of measures needed to provide best practice for people with SMD.

We thank Amara Najuan, Arad Daphna, Avimor Noam, Melamde Myranda, and Steiner Ayelet for assisting with data collection; we also thank Lisa Deutsch for statistical consultation.