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Research Article
Issue Date: June 23, 2015
Published Online: June 24, 2015
Updated: January 01, 2020
Sensory Sensitivity and Strategies for Coping With Pain
Author Affiliations
  • Pamela J. Meredith, PhD, is Senior Lecturer, Occupational Therapy, School of Health and Rehabilitation Sciences, University of Queensland, St. Lucia, Australia; p.meredith@uq.edu.au
  • Georgia Rappel, BOccThy(Hons), was Honours Student, Occupational Therapy, School of Health and Rehabilitation Sciences, University of Queensland, St. Lucia, Australia, at the time of the study
  • Jenny Strong, PhD, MOccThy, is Professor, Occupational Therapy, School of Health and Rehabilitation Sciences, University of Queensland, St. Lucia, Australia
  • Kirsty J. Bailey, BOccThy(Hons), is Occupational Therapist, Queensland Health, Australia
Article Information
Mental Health / Sensory Integration and Processing / Health and Wellness
Research Article   |   June 23, 2015
Sensory Sensitivity and Strategies for Coping With Pain
American Journal of Occupational Therapy, June 2015, Vol. 69, 6904240010. https://doi.org/10.5014/ajot.2015.014621
American Journal of Occupational Therapy, June 2015, Vol. 69, 6904240010. https://doi.org/10.5014/ajot.2015.014621
Abstract

OBJECTIVE. Our goal was to investigate the relationship between sensory processing styles and use of pain coping strategies in an experimental setting to understand individual differences in pain coping.

METHOD. A cross-sectional design was used with a convenience sample of 116 healthy adults. Measures of sensory processing style and mood state were collected before participation in a cold pressor pain-inducement task, and measures of coping strategies were collected afterward. Multiple regression models were constructed to examine relationships between sensory processing and coping strategies.

RESULTS. Sensory sensitivity and sensation avoiding were significantly associated with higher levels of catastrophizing. Sensation seeking was linked with active coping strategies, such as coping self-statements. Low registration was not significantly associated with any particular coping strategy after controlling for salient variables.

CONCLUSION. This study highlights associations between sensory processing and pain coping strategies, which may inform more tailored approaches to clinical practice for people in pain.

Chronic pain is a major health condition that results in considerable distress and disability (Access Economics, 2007). It has been suggested that a subgroup of people exists, known as highly sensitive people, who are more alert to bodily signs and symptoms, more sensitive to pain, and more likely to be aroused by these sensations (Aron, 1996). In turn, some evidence suggests that sensory hypersensitivity is associated with poorer therapeutic outcomes (e.g., from whiplash injury; Sterling, Jull, Vicenzino, & Kenardy, 2003). Although understanding links between sensory sensitivity and pain perceptions may inform therapeutic approaches, these associations, and the potential mechanisms for them, have received little empirical attention.
One potential mechanism through which sensory sensitivity may influence pain outcomes relates to individual choice of pain coping strategies, which have been of interest to pain researchers and practitioners for more than 3 decades (Rosenstiel & Keefe, 1983). Coping strategies are often conceptualized in the pain literature as either active or passive (Snow-Turek, Norris, & Tan, 1996); passive strategies are linked with negative pain outcomes such as prolonged recovery postinjury (Carroll, Cassidy, & Côté, 2006) and postsurgical chronic pain (Edwards, Haythornthwaite, Smith, Klick, & Katz, 2009).
At present, little is known about the associations between sensory sensitivity and pain coping. Therefore, in this study, we investigated these associations to understand individual differences in coping with pain and potential implications for prevention, early intervention, and therapy.
The complex neurophysiological basis of pain has been extensively investigated (Tracey, 2008) and is beyond the scope of this article. Recently, however, interest has increased in the neurological underpinnings of sensory processing (Koziol, Budding, & Chidekel, 2011) and how they relate to pain processing (Bar-Shalita, Vatine, Yarnitsky, Parush, & Weissman-Fogel, 2014). In a recent physiological study of pain processing, Bar-Shalita et al. (2014)  found that people with sensory overresponsivity demonstrated an atypical response to pain induction. The authors concluded that sensory overresponsivity was reflective of an alteration in the central processing of pain. This alteration may result in a specific pattern of coping efforts, which may have implications for functioning.
To date, only one study has investigated associations between sensory processing style and pain coping strategies (Engel-Yeger & Dunn, 2011b). In that study, Dunn’s (1997)  Model of Sensory Processing was used as the theoretical framework for understanding individual differences in processing sensory stimulation. According to this model, four sensory processing styles are defined using two dimensions: neurological threshold and behavioral response. A person may be categorized as either low or high on the neurological threshold dimension, depending on the intensity of a stimulus required for him or her to react. The behavioral response dimension captures the manner in which a person reacts to a stimulus: either actively or passively. People with high neurological thresholds score higher on scales measuring sensation seeking (active response) and low registration (passive response). People with low neurological thresholds score higher on sensation avoiding (active response) and sensory sensitivity (passive response; for more information, see Dunn, 1997).
Engel-Yeger and Dunn (2011b)  found that low registration, sensation avoiding, and sensory sensitivity were all positively linked with pain catastrophizing, which they defined as “an exaggerated negative cognitive response to actual or anticipated pain . . . associated with enhanced pain experience and pain related outcomes” (p. e1). Pain catastrophizing is recognized as a coping strategy that has been associated with heightened pain-related brain activity (Edwards et al., 2009) and disability (Edwards, Campbell, & Fillingim, 2005). However, methodological concerns limit confidence in Engel-Yeger and Dunn’s results. First, demographic and other potential explanatory variables were not controlled. Second, participants were asked to recall a previous painful experience rather than actually experience pain. This approach introduced variability into the nature of the painful experience recalled and level of associated pain (e.g., broken limb vs. mild headache), which may have affected the level of catastrophizing evoked.
Retrospective memory of the painful experience may also have influenced associations between sensory style and pain catastrophizing. For example, Edwards et al. (2005)  reported that catastrophizing cognitions related to past episodes of pain were poorly correlated with those relating to in vivo pain and that only those cognitions measured during the in vivo situation were significantly associated with pain perceptions.
Pain is a highly subjective experience, and it is important to understand how people respond to it at the time they experience the pain rather than as they might typically (or believe they might typically) respond. No research has investigated associations between sensory processing and coping approaches beyond catastrophizing. Together, these concerns highlight the need to replicate the Engel-Yeger and Dunn (2011b)  findings using a uniform, current pain experience while controlling for salient variables and including a wider range of coping approaches.
The aim of this study was to address this need. We generated three hypotheses:
  1. In line with the findings of Engel-Yeger and Dunn (2011b), low registration, sensation avoiding, and sensory sensitivity would be linked with pain catastrophizing.

  2. Sensory sensitivity and low registration (passive sensory styles) would be associated with passive coping strategies.

  3. Sensation avoiding and sensation seeking (active sensory styles) would be associated with active coping strategies.

Given that previous research has revealed associations between sensory styles and both negative affect and gender (Engel-Yeger & Dunn, 2011a, 2011c) and between pain catastrophizing and mood (Karsdorp, Ranson, Schrooten, & Vlaeyen, 2012), it was important for us to control for mood and gender.
Method
Participants
Participants were 116 healthy men and women. The majority were Australian and single, had completed high school, and were in paid employment. See Table 1 for participant demographics.
Table 1.
Participant Demographic Characteristics (N = 116)
Participant Demographic Characteristics (N = 116)×
Characteristicn (%)
Gender
 Male47 (40.5)
 Female69 (59.5)
Country of origin
 Australia98 (84.45)
 Other (e.g., Canada, United States)18 (15.51)
Relationship status
 Married26 (22.41)
 De facto25 (21.55)
 Separated2 (1.72)
 Divorced1 (0.86)
 Never married61 (52.59)
 Missing1 (0.86)
Education level
 Less than Year 10 of high school2 (1.72)
 Completed Year 10 of high school8 (6.90)
 Completed Year 12 of high school47 (40.52)
 Diploma/apprenticeship/TAFE22 (18.97)
 Bachelor’s degree31 (26.72)
 Master’s degree or higher6 (5.17)
Income source
 Paid employment89 (76.72)
 Self-funded3 (2.59)
 Partner’s income5 (4.31)
 Unemployment benefits1 (0.86)
 Youth allowance3 (2.59)
 Other (e.g., scholarship)15 (12.93)
Employment status
 Full time54 (46.55)
 Part time20 (17.24)
 Not in paid employment3 (2.59)
 Studying full time39 (33.62)
Annual income
 <$25,00037 (31.90)
 $25,000–$35,0005 (3.45)
 $35,000–$45,0006 (5.17)
 $45,000–$55,0004 (3.45)
 $55,000–$65,00014 (12.07)
 $65,000–$75,0005 (3.45)
 >$75,00042 (36.21)
 Not reported3 (2.59)
Participant type
 Known to researcher77 (66.38)
 Unknown to researcher39 (33.62)
Researcher
 160 (51.72)
 256 (48.28)
Table Footer NoteNote. TAFE = Technical and Further Education.
Note. TAFE = Technical and Further Education.×
Table 1.
Participant Demographic Characteristics (N = 116)
Participant Demographic Characteristics (N = 116)×
Characteristicn (%)
Gender
 Male47 (40.5)
 Female69 (59.5)
Country of origin
 Australia98 (84.45)
 Other (e.g., Canada, United States)18 (15.51)
Relationship status
 Married26 (22.41)
 De facto25 (21.55)
 Separated2 (1.72)
 Divorced1 (0.86)
 Never married61 (52.59)
 Missing1 (0.86)
Education level
 Less than Year 10 of high school2 (1.72)
 Completed Year 10 of high school8 (6.90)
 Completed Year 12 of high school47 (40.52)
 Diploma/apprenticeship/TAFE22 (18.97)
 Bachelor’s degree31 (26.72)
 Master’s degree or higher6 (5.17)
Income source
 Paid employment89 (76.72)
 Self-funded3 (2.59)
 Partner’s income5 (4.31)
 Unemployment benefits1 (0.86)
 Youth allowance3 (2.59)
 Other (e.g., scholarship)15 (12.93)
Employment status
 Full time54 (46.55)
 Part time20 (17.24)
 Not in paid employment3 (2.59)
 Studying full time39 (33.62)
Annual income
 <$25,00037 (31.90)
 $25,000–$35,0005 (3.45)
 $35,000–$45,0006 (5.17)
 $45,000–$55,0004 (3.45)
 $55,000–$65,00014 (12.07)
 $65,000–$75,0005 (3.45)
 >$75,00042 (36.21)
 Not reported3 (2.59)
Participant type
 Known to researcher77 (66.38)
 Unknown to researcher39 (33.62)
Researcher
 160 (51.72)
 256 (48.28)
Table Footer NoteNote. TAFE = Technical and Further Education.
Note. TAFE = Technical and Further Education.×
×
Procedure
This study (No. 2012000013) received ethical approval from the University of Queensland’s Behavioral and Social Science Ethical Review Committee. Data were collected for this study in 2012 and 2013 by two research students. Invitations to participate in the study were extended by means of email, word of mouth, and a social media private message to 162 potential participants. Participants were required to be age 18 yr or older and to have no prior history of chronic pain or current pain. Thirty-four adults either did not respond to the invitation or declined to participate for various reasons (most commonly time constraints).
The remaining 128 participants were invited to attend a testing session held at a mutually convenient place and time. Before commencing the experiment, each person was given a participant information sheet and consent form. Upon signing the consent form, participants completed several questionnaires relating to sensory preferences and affective states. They then participated in the cold pressor task (described later) in a private room. The cold pressor has been used extensively in experimental pain research, including research regarding pain sensitivity (Edwards et al., 2005). During the cold pressor task, the researcher was blind to participants’ affective states and sensory preferences.
Finally, participants completed a questionnaire related to coping strategies used during the cold pressor task. Twelve people who completed the protocol were excluded from the study because of their report of a current or past diagnosis of a chronic pain condition, resulting in a sample size of 116 (71.6%). No incentives were given to encourage participation in the study, and potential participants were informed that their participation was voluntary. Participant confidentiality was ensured through deidentification of all information.
Cold Pressor Apparatus
The cold pressor apparatus is a methodologically sound device for the temporary induction of nonharmful pain (Andrews, Meredith, & Strong, 2011; Meredith, Strong, & Feeney, 2006) and was used to provide a standard pain experience for all participants. The apparatus consisted of a container with two compartments: one containing water only, and the other filled with iced water. A pump was used to circulate water between the compartments when not in use. In this study, the water was maintained at 0–2°C, and the temperature was recorded before each use. Standard verbal instructions were provided to each person (Andrews et al., 2011) to submerge their nondominant hand and forearm into the water-only compartment for as long as possible. Although a 4-min ceiling was imposed on the cold pressor task to minimize risk of any adverse physiological effects, participants were not informed of this limit. At the conclusion of the cold pressor task, participants were debriefed. The procedure, in its entirety, took approximately 30 min per person.
Measures
Demographic Questionnaire.
The demographic questionnaire gathered details of each participant’s age, gender, country of origin, marital status, income, education, and previous history of pain conditions or experiences. In addition, we recorded which of the two researchers conducted the experiment and whether the participant was known to the researcher.
21-Item Depression Anxiety Stress Scales.
The 21-Item Depression Anxiety Stress Scales (DASS–21; Lovibond & Lovibond, 1995) is a frequently used self-report measure of adverse mood states (depression, anxiety, and stress). Participants were asked to rate their agreement with several statements pertaining to each mood state experienced during the past week on a 4-point scale (ranging from 0 = did not apply to me at all to 3 = applied to me very much, or most of the time). Scores on three subscales are obtained—Depression, Anxiety, and Stress—each representing the summation of 7 items. Example items include “I felt I had nothing to look forward to” (Depression), “I felt I was close to panic” (Anxiety), and “I felt that I was rather touchy” (Stress). A previous analysis of internal consistency reported α scores of .96, .89, and .93 for the Depression, Anxiety, and Stress subscales, respectively (Carroll et al., 2006). In the current study, Cronbach’s α scores were .82, .59, and .85 for the Depression, Anxiety, and Stress subscales, respectively. Only the Stress subscale was used in analyses as a proxy for mood.
Adolescent/Adult Sensory Profile.
The Adolescent/Adult Sensory Profile (AASP; Brown & Dunn, 2002), a 60-item self-report measure of responses to everyday sensory experiences, is based on Dunn’s (1997)  Model of Sensory Processing and is commonly used in occupational therapy. Each item is scored on a 5-point Likert scale (ranging from 1 = almost never to 5 = almost always), and then items are equally sorted between four quadrants (Quadrant [Q]1, low registration; Q2, sensation seeking; Q3, sensory sensitivity; and Q4, sensation avoiding), each reflecting a different sensory processing pattern. Raw scores for each quadrant are converted using a standardized table to reflect the extent to which a person identifies with each pattern, again on a 5-point scale (1 = much less than most people; 5 = much more than most people). An average is then obtained for these scores, with higher scores indicating greater affinity for the quadrant. Thus, it is possible to score highly in multiple quadrants (i.e., have more than one sensory preference).
Example items for each quadrant include “I don’t notice when people come into the room” (Q1, low registration), “I like to go barefoot” (Q2, sensation seeking), “I dislike having my back rubbed” (Q3, sensory sensitivity), and “I move away when others get too close to me” (Q4, sensation avoiding). Results of a preliminary study support the validity and internal consistency of this measure (Brown, Tollefson, Dunn, Cromwell, & Filion, 2001). Cronbach’s α scores for the AASP were .75 (low registration), .74 (sensation seeking), .72 (sensory sensitivity), and .77 (sensation avoiding), indicating adequate internal consistency.
Coping Strategies Questionnaire.
The Coping Strategies Questionnaire (CSQ; Rosenstiel & Keefe, 1983), a self-report measure, is accepted as the most widely used measure of pain coping strategies (Geisser, Robinson, & Henson, 1994; Swartzman, Gwadry, Shapiro, & Teasell, 1994). It was administered after the cold pressor task to provide an indication of the coping strategies used by participants during the cold pressor experience. Participants rated 48 questions on a scale ranging from 0 (never do) to 6 (very often do), providing the frequency with which different coping strategies were used. The measure consists of six subscales representing different coping strategies: Catastrophizing, Ignoring Pain, Diverting Attention, Hoping/Praying, Increasing Behavioral Activities, and Coping Self-Statements. The CSQ has been demonstrated to have sound internal consistency (Rosenstiel & Keefe, 1983). Cronbach’s α scores for the current study were .86 (Catastrophizing), .86 (Ignoring Pain), .82 (Diverting Attention), .75 (Hoping/Praying), .77 (Increasing Behavioral Activities), and .84 (Coping Self-Statements). Previous research (Snow-Turek et al., 1996) has conceptualized the CSQ subscales as either active (Coping Self-Statements, Increasing Behavioral Activities, Ignoring Pain, and Diverting Attention) or passive (Catastrophizing and Hoping/Praying) in relation to pain. Table 2 presents descriptive data and subscale scores for the AASP, the DASS–21, and the CSQ.
Table 2.
Participant Age and Scores on Measures
Participant Age and Scores on Measures×
VariableaMSDRange
Age, yr29.512.718–64
AASP quadrants
 Low registration3.30.722–5
 Sensation seeking3.00.721–5
 Sensory sensitivity3.10.621–5
 Sensory avoidance3.10.721–5
DASS–21 subscales
 Depression2.63.20–19
 Anxiety2.52.60–13
 Stress5.54.30–20
CSQ subscales
 Catastrophizing7.36.40–33
 Hoping/Praying9.47.20–31
 Increasing Behavioral Activities15.06.90–33
 Ignoring Pain18.48.50–36
 Diverting Attention14.37.70–36
 Coping Self-Statements21.77.60–36
Table Footer NoteNote. AASP = Adolescent/Adult Sensory Profile; CSQ = Coping Strategies Questionnaire; DASS–21 = 21-Item Depression Anxiety Stress Scales; M = mean; SD = standard deviation.
Note. AASP = Adolescent/Adult Sensory Profile; CSQ = Coping Strategies Questionnaire; DASS–21 = 21-Item Depression Anxiety Stress Scales; M = mean; SD = standard deviation.×
Table Footer NoteaN = 116 for all variables except low registration and sensory avoidance, which are N = 115.
N = 116 for all variables except low registration and sensory avoidance, which are N = 115.×
Table 2.
Participant Age and Scores on Measures
Participant Age and Scores on Measures×
VariableaMSDRange
Age, yr29.512.718–64
AASP quadrants
 Low registration3.30.722–5
 Sensation seeking3.00.721–5
 Sensory sensitivity3.10.621–5
 Sensory avoidance3.10.721–5
DASS–21 subscales
 Depression2.63.20–19
 Anxiety2.52.60–13
 Stress5.54.30–20
CSQ subscales
 Catastrophizing7.36.40–33
 Hoping/Praying9.47.20–31
 Increasing Behavioral Activities15.06.90–33
 Ignoring Pain18.48.50–36
 Diverting Attention14.37.70–36
 Coping Self-Statements21.77.60–36
Table Footer NoteNote. AASP = Adolescent/Adult Sensory Profile; CSQ = Coping Strategies Questionnaire; DASS–21 = 21-Item Depression Anxiety Stress Scales; M = mean; SD = standard deviation.
Note. AASP = Adolescent/Adult Sensory Profile; CSQ = Coping Strategies Questionnaire; DASS–21 = 21-Item Depression Anxiety Stress Scales; M = mean; SD = standard deviation.×
Table Footer NoteaN = 116 for all variables except low registration and sensory avoidance, which are N = 115.
N = 116 for all variables except low registration and sensory avoidance, which are N = 115.×
×
Statistical Analyses
Statistical analyses were conducted using Stata Data Analysis and Statistical Software (Versions 11.2 and 13.0; StataCorp, College Station, TX). Initial data checking for normality identified several skewed continuous variables: age, stress, catastrophizing, coping self-statements, and hoping/praying. Catastrophizing, which was the only one of these variables used as an outcome variable, was transformed using square root transformation, successfully creating a normal variable. Preliminary correlation analyses were conducted to explore associations among variables and to screen for multicollinearity. As a result of the lack of normality of some variables, intercorrelations between variables were examined using Spearman’s correlation, with a significance level of p = .05.
To investigate associations between each AASP variable (low registration, sensation seeking, sensory sensitivity, and sensation avoiding) and each coping strategy (coping self-statements, catastrophizing, hoping/praying, ignoring pain, increasing behavioral activities, and diverting attention), 24 multiple regression models were constructed. In each model, one sensory processing variable acted as the independent variable; one coping strategy, as the dependent variable; and age, gender, and stress, as covariates.
Postregression diagnostics were conducted after each model was run, including tests for normality of residuals, homoskedasticity, outliers, and multicollinearity. Where the residuals were normally distributed, no transformations were necessary (Chen, Ender, Mitchell, & Wells, 2003). If postregression diagnostics revealed any violation of assumptions, the regression model was rerun with outliers removed. If this action failed to remedy the issue, a transformation of the dependent variable was conducted, and models were rerun using the transformed dependent variable. On the basis of this process, hoping/praying and coping self-statements were transformed on several occasions using square root and square functions, respectively. To control for the risk of Type I error, a Bonferroni adjustment was applied, with p < .002 adopted for regression analyses; however, because this study is exploratory in nature, ps of .05 are also reported.
Results
Preliminary correlational analyses revealed few associations between study variables and which of the researchers gathered the data or between whether the participants were known or unknown to the researchers. Age and gender were correlated with many of the experimental variables and were retained as covariates, along with stress (see summary of correlations in Table 3).
Table 3.
Correlations Between Variables Using Spearman’s ρ (N = 116)
Correlations Between Variables Using Spearman’s ρ (N = 116)×
Variable12345678910111213141516
1. Age
2. Gender–.34***
3. Researcher–.01–.01
4. Participant type.23**–.10–.29**
5. Low registration–.17.25**.13–.20*
6. Sensation seeking–.19*.23**.13–.04.17
7. Sensory sensitivity–.25**.24.03–.14.32***–.05
8. Sensation avoiding–.14.09.10–.14.19*–.22*.51***
9. Depression–.07.47.20*–.07.19*–.01.14.07
10. Anxiety–.21*.19*.04.00.22*.01.29**.21*.47***
11. Stress–.09.18.17–.13.16.02.23*.12.55***.68***
12. Catastrophizing–.29**.19*.17–.14.20*–.04.34***.28**.26**.33***.34***
13. Hoping/praying–.19*.25**–.08–.06.06.15.23*.09–.02.22*.20*.48***
14. Ignoring pain–.19*.08.15–.08.22*.26**.12.00.10.12.15.08.15
15. Diverting attention–.12.27**.18–.16.22.20*.29**.04.10.21*.27**.43***.53***.28***
16. Increasing behavioral activities–.29**.31***.04–.09.04.33***.21*.07.00.23**.12**.34**.46***.35***.57***
17. Coping self-statements–.14.05.02–.13.17.30***.11.06–.03.13.06.04.27.66***.33***.32***
Table Footer Note*p ≤ .05. **p ≤ .01. ***p ≤ .001.
p ≤ .05. **p ≤ .01. ***p ≤ .001.×
Table 3.
Correlations Between Variables Using Spearman’s ρ (N = 116)
Correlations Between Variables Using Spearman’s ρ (N = 116)×
Variable12345678910111213141516
1. Age
2. Gender–.34***
3. Researcher–.01–.01
4. Participant type.23**–.10–.29**
5. Low registration–.17.25**.13–.20*
6. Sensation seeking–.19*.23**.13–.04.17
7. Sensory sensitivity–.25**.24.03–.14.32***–.05
8. Sensation avoiding–.14.09.10–.14.19*–.22*.51***
9. Depression–.07.47.20*–.07.19*–.01.14.07
10. Anxiety–.21*.19*.04.00.22*.01.29**.21*.47***
11. Stress–.09.18.17–.13.16.02.23*.12.55***.68***
12. Catastrophizing–.29**.19*.17–.14.20*–.04.34***.28**.26**.33***.34***
13. Hoping/praying–.19*.25**–.08–.06.06.15.23*.09–.02.22*.20*.48***
14. Ignoring pain–.19*.08.15–.08.22*.26**.12.00.10.12.15.08.15
15. Diverting attention–.12.27**.18–.16.22.20*.29**.04.10.21*.27**.43***.53***.28***
16. Increasing behavioral activities–.29**.31***.04–.09.04.33***.21*.07.00.23**.12**.34**.46***.35***.57***
17. Coping self-statements–.14.05.02–.13.17.30***.11.06–.03.13.06.04.27.66***.33***.32***
Table Footer Note*p ≤ .05. **p ≤ .01. ***p ≤ .001.
p ≤ .05. **p ≤ .01. ***p ≤ .001.×
×
Associations Between Passive Sensory Processing Styles and Coping Strategies
Low Registration.
Low registration, which indicates a high sensory threshold and passive behavioral response, was found to be correlated with ignoring pain (r = .22, p < .05), diverting attention (r = .22, p < .05), and catastrophizing (r = .20, p < .05). These relationships were not retained in regression analyses after controlling for stress, age, and gender (Table 4). Stress contributed significantly and positively to regression models for catastrophizing and diverting attention; gender was significant for increasing behavioral activities, diverting attention, and hoping/praying; and age contributed significantly to catastrophizing and ignoring pain.
Table 4.
Regression Statistics for Associations Between Pain Coping Behavior and Sensory Processing, Demographic, and Stress Variables (N = 116)
Regression Statistics for Associations Between Pain Coping Behavior and Sensory Processing, Demographic, and Stress Variables (N = 116)×
VariablePain Coping Behavior (t Score)
CatastrophizingIncreasing Behavioral ActivitiesDiverting AttentionIgnoring PainHoping/PrayingCoping Self-Statements
Low registration1.450.081.471.8–0.021.51
 Age−3.19**−1.8−0.57−3.26**−1.43−1.51
 Gender0.52.82**2.09*−0.442.21*−0.17
 Stress3.52***1.342.89**1.611.240.57
R2.23.15.17.15.10.05
F(4, 110)8.28***4.86**5.77***4.95***3.01*1.53
Sensory sensitivity2.99**1.091.98*0.111.85*0.31
 Age−2.96**−1.65−0.4−3.34**−1.48−1.61
 Gender0.382.75**2.12*–0.151.710.08
 Stress3.05**1.112.55*1.670.510.63
R2.28.16.185.126.12.03
F(4, 111)10.56 ***5.35***6.31***4.0**3.78**0.99
Sensation seeking−1.282.59*1.82.34*1.472.72**
 Age−3.51**1.38−0.47−3.14**−1.23−1.35
 Gender1.03−1.521.98−0.631.89−0.44
 Stress3.68***2.39*3.02**1.751.230.70
R2.228.20.18.167.12.09
F(4, 111)8.24***6.98***6.11***5.57***3.71**2.87*
Sensation avoiding2.55*0.320.19−0.420.860.85
 Age−3.22**−1.59−0.32−3.12−1.32−1.41
 Gender0.722.85**2.29*−0.171.850.05
 Stress3.40***1.333.00**1.790.840.61
R2.26.14.15.11.08.03
F(4, 110)9.85***4.57**4.83**3.47*2.51*1.67
Table Footer Note*p ≤ .05. **p ≤ .01. ***p ≤ .001.
p ≤ .05. **p ≤ .01. ***p ≤ .001.×
Table 4.
Regression Statistics for Associations Between Pain Coping Behavior and Sensory Processing, Demographic, and Stress Variables (N = 116)
Regression Statistics for Associations Between Pain Coping Behavior and Sensory Processing, Demographic, and Stress Variables (N = 116)×
VariablePain Coping Behavior (t Score)
CatastrophizingIncreasing Behavioral ActivitiesDiverting AttentionIgnoring PainHoping/PrayingCoping Self-Statements
Low registration1.450.081.471.8–0.021.51
 Age−3.19**−1.8−0.57−3.26**−1.43−1.51
 Gender0.52.82**2.09*−0.442.21*−0.17
 Stress3.52***1.342.89**1.611.240.57
R2.23.15.17.15.10.05
F(4, 110)8.28***4.86**5.77***4.95***3.01*1.53
Sensory sensitivity2.99**1.091.98*0.111.85*0.31
 Age−2.96**−1.65−0.4−3.34**−1.48−1.61
 Gender0.382.75**2.12*–0.151.710.08
 Stress3.05**1.112.55*1.670.510.63
R2.28.16.185.126.12.03
F(4, 111)10.56 ***5.35***6.31***4.0**3.78**0.99
Sensation seeking−1.282.59*1.82.34*1.472.72**
 Age−3.51**1.38−0.47−3.14**−1.23−1.35
 Gender1.03−1.521.98−0.631.89−0.44
 Stress3.68***2.39*3.02**1.751.230.70
R2.228.20.18.167.12.09
F(4, 111)8.24***6.98***6.11***5.57***3.71**2.87*
Sensation avoiding2.55*0.320.19−0.420.860.85
 Age−3.22**−1.59−0.32−3.12−1.32−1.41
 Gender0.722.85**2.29*−0.171.850.05
 Stress3.40***1.333.00**1.790.840.61
R2.26.14.15.11.08.03
F(4, 110)9.85***4.57**4.83**3.47*2.51*1.67
Table Footer Note*p ≤ .05. **p ≤ .01. ***p ≤ .001.
p ≤ .05. **p ≤ .01. ***p ≤ .001.×
×
Sensory Sensitivity.
Sensory sensitivity, which indicates a low sensory threshold and passive behavioral response, was significantly and positively associated with catastrophizing (r = .34, p < .001), and this relationship held after controlling for age, gender, and stress (see Table 4). Although sensory sensitivity was also initially associated with diverting attention (r = .29, p < .01) and hoping/praying (r = .23, p < .05) in correlational analyses, this association did not reach the conservative .002 significance level in regression analyses after controlling for covariates. Although positively correlated with increasing behavioral activities (r = .21, p < .05), this relationship was not retained after controlling for age, gender, and stress in regression analyses. Stress was found to be positively linked to catastrophizing, age was linked with catastrophizing and ignoring pain sensations, and gender was associated with diverting attention from pain.
Associations Between Active Sensory Processing Styles and Coping Strategies
Sensation Seeking.
Sensation seeking, which indicates a high sensory threshold and active behavioral response, was initially correlated with ignoring pain (r = .26, p < .01), diverting attention (r = .20, p < .05), increasing behavioral activities (r = .33, p < .001), and coping self-statements (r = .30, p < .001). Although the initial relationship with diverting attention was lost when controlling for age, gender, and stress, sensation seeking remained significantly associated with coping self-statements, increasing behavioral activities, and ignoring pain when controlling for these variables in regression analyses (see Table 4). Indeed, sensation seeking was the strongest predictor of increasing behavioral activities. Nevertheless, associations with increasing behavioral activities and ignoring pain did not reach the conservative .002 significance level. Stress was a significant predictor of catastrophizing and diverting attention; gender was associated with increasing behavioral activities, diverting attention, and hoping/praying; and age was related to catastrophizing and ignoring pain.
Sensation Avoiding.
Sensation avoiding, which indicates a low sensory threshold and active behavioral response, was found to be positively linked only with catastrophizing in both correlation (r = .28, p < .01; see Table 3) and regression analyses (see Table 4). This relationship was retained after controlling for age, gender, and stress. In analyses involving other sensory processing styles, stress was positively associated with catastrophizing and diverting attention, age was associated with catastrophizing, and gender was linked with increasing behavioral activities and diverting attention.
Associations Between Demographic Variables and Coping Strategies
Age was consistently and negatively associated with both catastrophizing and ignoring pain in all four sensory processing quadrants, although the association between age and ignoring pain in the sensation avoiding quadrant did not reach significance. In the quadrants of low registration, sensory sensitivity, and sensation avoiding, women were more likely to use increasing behavioral activities than men.
Discussion
This study extends the work of Engel-Yeger and Dunn (2011b)  and provides evidence that AASP categories are related to the coping strategies used during a painful experience. As anticipated in Hypothesis 1, and in keeping with earlier findings, results showed that both sensory sensitivity and sensation avoiding (the low-threshold sensory processing patterns) were related to pain catastrophizing and that these associations were retained when controlling for age, gender, and stress. In contrast to expectations, however, associations between low registration and catastrophizing were not retained after controlling for covariates, with stress and age accounting for the variance in catastrophizing. Thus, only the AASP categories with low sensory thresholds were more prone to pain catastrophizing. Although Engel-Yeger and Dunn (2011b)  found associations between catastrophizing and all three of these sensory variables, demographic and mood variables were not included in their study; however, they emphasized the importance of including these variables in future investigations.
Active and Passive Coping
Although approaches to the classification of coping vary in the literature, for the purposes of this study, we adopted the dichotomy between active and passive coping styles (Peres & Lucchetti, 2010). This distinction is also theoretically consistent with the active and passive terminology used by Dunn (1997)  in developing the Sensory Processing Model; however, similar coping dichotomies exist (e.g., approach [active] and avoidant [passive] coping). Passive coping is considered to be used when the person surrenders control or relies on external supports to cope with pain (Peres & Lucchetti, 2010). It has been characterized by feelings of helplessness (Snow-Turek et al., 1996) and has been associated with both psychopathology (e.g., depression; Brown & Nicassio, 1987) and poorer pain outcomes (Edwards et al., 2009). In contrast, Peres and Lucchetti (2010)  noted that active pain coping involves an internal locus of control, whereby the person aims to control the pain through using his or her own resources (e.g., exercising, positive self-statements). Active coping has been inversely associated with psychopathology (Snow-Turek et al., 1996).
With this in mind, we expected sensory sensitivity and low registration (passive sensory approaches) to be associated with passive coping strategies (catastrophizing and hoping/praying), as stated in Hypothesis 2. Moreover, we expected sensation avoiding and sensation seeking (active sensory approaches) to be associated with active coping strategies (ignoring pain, coping self-statements, diverting attention, and increasing behavioral activities), as stated in our third hypothesis.
As noted earlier, both sensory sensitivity and low registration were initially related to catastrophizing; however, contradicting Hypothesis 2, the association was lost for low registration after controlling for age, gender, and stress. In addition, sensation avoiding, an active sensory pattern, was associated with catastrophizing. This finding is more consistent with the conceptualization of avoidance as a passive coping strategy and challenges the conceptualization of sensation avoidance as an active sensory pattern. This result is also consistent with the view that it is the low sensory threshold dimension (sensory sensitivity and sensation avoiding) rather than the active or passive nature of the coping approach (low registration and sensation seeking) that accounts for the association between sensory perceptions and pain catastrophizing (i.e., participants with lower sensory thresholds were more likely to catastrophize). The other passive coping style, hoping/praying, was not found to be associated with any particular sensory pattern. This result may not be surprising given the debate about whether hoping/praying, or religious coping in general, should be considered passive (Peres & Lucchetti, 2010). In contrast to expectations, sensory sensitivity was linked with diverting attention, which is typically viewed as an active coping strategy.
In partial support of Hypothesis 3, sensation seeking (an active sensory approach) was significantly associated with coping self-statements and, to a lesser extent, with increasing behavioral activities and ignoring pain (active coping strategies). This finding is consistent with expectations and with previous evidence of a lack of association between sensation seeking and both catastrophizing (Engel-Yeger & Dunn, 2011b) and negative mood (Engel-Yeger & Dunn, 2011a, 2011c). It suggests that, in the context of a painful experience, sensation seeking may constitute a protective factor.
As noted earlier, and in contrast to expectations for Hypothesis 3, sensation avoiding (an active, low sensory threshold category) was associated only with catastrophizing. One possible explanation for this finding is the evidence, reported in prior literature (Engel-Yeger & Dunn, 2011a, 2011c), of associations between sensation avoiding and adverse mood states, which may influence a person’s tendency to choose a passive coping strategy. However, this result was retained when controlling for stress. As discussed in relation to sensory sensitivity, people with low sensory thresholds may have heightened sensitivity (low thresholds) to pain and therefore be more likely to be overwhelmed and respond with maladaptive coping strategies. Given that both sensory sensitivity and sensation avoiding (Engel-Yeger & Dunn, 2011a, 2011c), and maladaptive coping (Edwards et al., 2009; Karsdorp et al., 2012), have been associated with negative affect, this result is theoretically consistent. These findings suggest that high scores on sensation avoiding or sensory sensitivity (low sensory threshold) may constitute vulnerability factors and potentially be associated with poorer pain outcomes.
Note that only one of the two active sensory categories, sensation seeking, was associated with active pain coping strategies. This result suggests that the combination of both high sensory threshold and a more active behavioral approach was required to support use of active pain coping strategies. Either high sensory threshold or active behavioral coping alone was not sufficient.
Implications of Stress, Gender, and Age
Research examining the relationships among stress, coping, and sensory approach is limited. However, stress or symptoms of pathological stress (e.g., posttraumatic stress disorder [PTSD]) have been cited as influential factors in acute pain coping (Hekmat, Staats, & Staats, 2005) and pain perception (Geisser et al., 1994). Although not formulated as a hypothesis, we did expect that stress would be consistently and positively associated with catastrophizing. For example, PTSD symptoms have been found to be associated with catastrophizing (Horsham & Chung, 2013). In the past, distress has been linked to diverting attention from pain (Crisson & Keefe, 1988), particularly when the person feels helpless during the pain experience.
Evidence has also shown clear gender differences in pain perception and coping. For example, Keogh and Herdenfeldt (2002)  noted that, although men were more likely to use behavioral distraction strategies, women tended to use more social support and positive self-talk. Results of the current study, however, suggested that female gender was consistently associated with increased use of behavioral (active) strategies. The reason for this finding is unclear, but it may be related to nuances of the current study sample. For example, women in this study were uncharacteristically more likely to report being low registration and sensation seeking, both sensory patterns that have a high sensory threshold. Given that both of these sensory patterns have been associated with more adaptive functioning, the gender links with behavioral strategies found in this study appear intuitive. Further investigation into the impact of demographic variables on associations between sensory patterns and the pain coping strategies used by women could provide clarity for this finding.
It is noteworthy that age was negatively related to several coping strategies. Specifically, older age was linked with less use of all pain coping approaches, particularly catastrophizing and ignoring pain. Although some evidence suggests that older people may cope better with pain by using greater impulse control, more positive appraisal of painful experiences (Diehl, Coyle, & Labouvie-Vief, 1996), and higher levels of stoicism (Cook & Chastain, 2001), the associations between age and coping are complex. For example, Watkins, Shifren, Park, and Morrell (1999)  found that in a sample of 121 people with rheumatoid arthritis aged 34–84 yr, all reported using more active coping strategies when experiencing mild pain and more maladaptive coping strategies when in severe pain, regardless of age. The authors recommended that “research regarding illness and coping is most informative when it captures the individual–situational interaction of dealing with stressors such as chronic pain” (p. 217). Of note, older people in the current study were also more likely to be male and less likely to be sensation seeking or sensory sensitive.
Limitations and Future Research
This study extends the work of Engel-Yeger and Dunn (2011b)  by providing a standardized pain experience, controlling for demographic variables and stress, and considering a wider range of coping strategies. Nevertheless, results are preliminary. Many multiple regression analyses were conducted, increasing the risk of making a Type I error; to mitigate this risk, however, we adopted a conservative significance level of .002. Caution should also be taken in interpreting the results of analyses using transformed variables: Although the significance and direction of the associations are interpretable, it is important that differences not be quantified in terms of original variables.
Using a convenience sample and self-report measures also increased the risk of social desirability bias (Andrews et al., 2011). To partially address this drawback, the researchers were blind to each participant’s mood state, coping style, and sensory style. Although the study addressed active and passive coping, other coping conceptualizations (e.g., approach or avoidant, emotion or task focused) exist, which warrant consideration in relation to associations between sensory preferences and pain coping. Finally, because of the cross-sectional nature of the study, the ability to draw causal inference is limited. Therefore, future longitudinal research could increase confidence in the identified associations.
Implications for Occupational Therapy Practice
Although further investigation of this topic is required, this preliminary evidence supports the argument that individual sensory processing style is related to pain coping; therefore, sensory processing style has the potential to affect pain outcomes. This finding has the following implications for occupational therapy practice:
  • Knowledge of this relationship may assist occupational therapy practitioners in identifying clients with vulnerabilities to maladaptive coping strategies, which may lead to poorer pain outcomes (Edwards et al., 2009).

  • Future studies are needed to understand the potential application of sensory processing in the pain arena, which may assist occupational therapy practitioners to support the management of people in pain using sensory-informed approaches.

Conclusion
The aim of this study was to investigate the relationships among sensory processing styles, pain coping strategies, and stress. Findings supported previous research that found that low sensory threshold was associated with more maladaptive, passive coping (catastrophizing). Moreover, sensation seeking was associated with active coping strategies, such as increasing behavioral activities and coping self-statements. Stress was found to be a significant factor in both pain catastrophizing and diverting attention from pain.
Acknowledgments
The research team would like to acknowledge the expert statistical advice of Asad Khan. The authors of this article declare that there are no conflicts of interest at the time of submission.
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Tracey, I. (2008). Imaging pain. British Journal of Anaesthesia, 101, 32–39. http://dx.doi.org/10.1093/bja/aen102 [Article] [PubMed]
Tracey, I. (2008). Imaging pain. British Journal of Anaesthesia, 101, 32–39. http://dx.doi.org/10.1093/bja/aen102 [Article] [PubMed]×
Watkins, K. W., Shifren, K., Park, D. C., & Morrell, R. W. (1999). Age, pain, and coping with rheumatoid arthritis. Pain, 82, 217–228. http://dx.doi.org/10.1016/S0304-3959(99)00047-0 [Article] [PubMed]
Watkins, K. W., Shifren, K., Park, D. C., & Morrell, R. W. (1999). Age, pain, and coping with rheumatoid arthritis. Pain, 82, 217–228. http://dx.doi.org/10.1016/S0304-3959(99)00047-0 [Article] [PubMed]×
Table 1.
Participant Demographic Characteristics (N = 116)
Participant Demographic Characteristics (N = 116)×
Characteristicn (%)
Gender
 Male47 (40.5)
 Female69 (59.5)
Country of origin
 Australia98 (84.45)
 Other (e.g., Canada, United States)18 (15.51)
Relationship status
 Married26 (22.41)
 De facto25 (21.55)
 Separated2 (1.72)
 Divorced1 (0.86)
 Never married61 (52.59)
 Missing1 (0.86)
Education level
 Less than Year 10 of high school2 (1.72)
 Completed Year 10 of high school8 (6.90)
 Completed Year 12 of high school47 (40.52)
 Diploma/apprenticeship/TAFE22 (18.97)
 Bachelor’s degree31 (26.72)
 Master’s degree or higher6 (5.17)
Income source
 Paid employment89 (76.72)
 Self-funded3 (2.59)
 Partner’s income5 (4.31)
 Unemployment benefits1 (0.86)
 Youth allowance3 (2.59)
 Other (e.g., scholarship)15 (12.93)
Employment status
 Full time54 (46.55)
 Part time20 (17.24)
 Not in paid employment3 (2.59)
 Studying full time39 (33.62)
Annual income
 <$25,00037 (31.90)
 $25,000–$35,0005 (3.45)
 $35,000–$45,0006 (5.17)
 $45,000–$55,0004 (3.45)
 $55,000–$65,00014 (12.07)
 $65,000–$75,0005 (3.45)
 >$75,00042 (36.21)
 Not reported3 (2.59)
Participant type
 Known to researcher77 (66.38)
 Unknown to researcher39 (33.62)
Researcher
 160 (51.72)
 256 (48.28)
Table Footer NoteNote. TAFE = Technical and Further Education.
Note. TAFE = Technical and Further Education.×
Table 1.
Participant Demographic Characteristics (N = 116)
Participant Demographic Characteristics (N = 116)×
Characteristicn (%)
Gender
 Male47 (40.5)
 Female69 (59.5)
Country of origin
 Australia98 (84.45)
 Other (e.g., Canada, United States)18 (15.51)
Relationship status
 Married26 (22.41)
 De facto25 (21.55)
 Separated2 (1.72)
 Divorced1 (0.86)
 Never married61 (52.59)
 Missing1 (0.86)
Education level
 Less than Year 10 of high school2 (1.72)
 Completed Year 10 of high school8 (6.90)
 Completed Year 12 of high school47 (40.52)
 Diploma/apprenticeship/TAFE22 (18.97)
 Bachelor’s degree31 (26.72)
 Master’s degree or higher6 (5.17)
Income source
 Paid employment89 (76.72)
 Self-funded3 (2.59)
 Partner’s income5 (4.31)
 Unemployment benefits1 (0.86)
 Youth allowance3 (2.59)
 Other (e.g., scholarship)15 (12.93)
Employment status
 Full time54 (46.55)
 Part time20 (17.24)
 Not in paid employment3 (2.59)
 Studying full time39 (33.62)
Annual income
 <$25,00037 (31.90)
 $25,000–$35,0005 (3.45)
 $35,000–$45,0006 (5.17)
 $45,000–$55,0004 (3.45)
 $55,000–$65,00014 (12.07)
 $65,000–$75,0005 (3.45)
 >$75,00042 (36.21)
 Not reported3 (2.59)
Participant type
 Known to researcher77 (66.38)
 Unknown to researcher39 (33.62)
Researcher
 160 (51.72)
 256 (48.28)
Table Footer NoteNote. TAFE = Technical and Further Education.
Note. TAFE = Technical and Further Education.×
×
Table 2.
Participant Age and Scores on Measures
Participant Age and Scores on Measures×
VariableaMSDRange
Age, yr29.512.718–64
AASP quadrants
 Low registration3.30.722–5
 Sensation seeking3.00.721–5
 Sensory sensitivity3.10.621–5
 Sensory avoidance3.10.721–5
DASS–21 subscales
 Depression2.63.20–19
 Anxiety2.52.60–13
 Stress5.54.30–20
CSQ subscales
 Catastrophizing7.36.40–33
 Hoping/Praying9.47.20–31
 Increasing Behavioral Activities15.06.90–33
 Ignoring Pain18.48.50–36
 Diverting Attention14.37.70–36
 Coping Self-Statements21.77.60–36
Table Footer NoteNote. AASP = Adolescent/Adult Sensory Profile; CSQ = Coping Strategies Questionnaire; DASS–21 = 21-Item Depression Anxiety Stress Scales; M = mean; SD = standard deviation.
Note. AASP = Adolescent/Adult Sensory Profile; CSQ = Coping Strategies Questionnaire; DASS–21 = 21-Item Depression Anxiety Stress Scales; M = mean; SD = standard deviation.×
Table Footer NoteaN = 116 for all variables except low registration and sensory avoidance, which are N = 115.
N = 116 for all variables except low registration and sensory avoidance, which are N = 115.×
Table 2.
Participant Age and Scores on Measures
Participant Age and Scores on Measures×
VariableaMSDRange
Age, yr29.512.718–64
AASP quadrants
 Low registration3.30.722–5
 Sensation seeking3.00.721–5
 Sensory sensitivity3.10.621–5
 Sensory avoidance3.10.721–5
DASS–21 subscales
 Depression2.63.20–19
 Anxiety2.52.60–13
 Stress5.54.30–20
CSQ subscales
 Catastrophizing7.36.40–33
 Hoping/Praying9.47.20–31
 Increasing Behavioral Activities15.06.90–33
 Ignoring Pain18.48.50–36
 Diverting Attention14.37.70–36
 Coping Self-Statements21.77.60–36
Table Footer NoteNote. AASP = Adolescent/Adult Sensory Profile; CSQ = Coping Strategies Questionnaire; DASS–21 = 21-Item Depression Anxiety Stress Scales; M = mean; SD = standard deviation.
Note. AASP = Adolescent/Adult Sensory Profile; CSQ = Coping Strategies Questionnaire; DASS–21 = 21-Item Depression Anxiety Stress Scales; M = mean; SD = standard deviation.×
Table Footer NoteaN = 116 for all variables except low registration and sensory avoidance, which are N = 115.
N = 116 for all variables except low registration and sensory avoidance, which are N = 115.×
×
Table 3.
Correlations Between Variables Using Spearman’s ρ (N = 116)
Correlations Between Variables Using Spearman’s ρ (N = 116)×
Variable12345678910111213141516
1. Age
2. Gender–.34***
3. Researcher–.01–.01
4. Participant type.23**–.10–.29**
5. Low registration–.17.25**.13–.20*
6. Sensation seeking–.19*.23**.13–.04.17
7. Sensory sensitivity–.25**.24.03–.14.32***–.05
8. Sensation avoiding–.14.09.10–.14.19*–.22*.51***
9. Depression–.07.47.20*–.07.19*–.01.14.07
10. Anxiety–.21*.19*.04.00.22*.01.29**.21*.47***
11. Stress–.09.18.17–.13.16.02.23*.12.55***.68***
12. Catastrophizing–.29**.19*.17–.14.20*–.04.34***.28**.26**.33***.34***
13. Hoping/praying–.19*.25**–.08–.06.06.15.23*.09–.02.22*.20*.48***
14. Ignoring pain–.19*.08.15–.08.22*.26**.12.00.10.12.15.08.15
15. Diverting attention–.12.27**.18–.16.22.20*.29**.04.10.21*.27**.43***.53***.28***
16. Increasing behavioral activities–.29**.31***.04–.09.04.33***.21*.07.00.23**.12**.34**.46***.35***.57***
17. Coping self-statements–.14.05.02–.13.17.30***.11.06–.03.13.06.04.27.66***.33***.32***
Table Footer Note*p ≤ .05. **p ≤ .01. ***p ≤ .001.
p ≤ .05. **p ≤ .01. ***p ≤ .001.×
Table 3.
Correlations Between Variables Using Spearman’s ρ (N = 116)
Correlations Between Variables Using Spearman’s ρ (N = 116)×
Variable12345678910111213141516
1. Age
2. Gender–.34***
3. Researcher–.01–.01
4. Participant type.23**–.10–.29**
5. Low registration–.17.25**.13–.20*
6. Sensation seeking–.19*.23**.13–.04.17
7. Sensory sensitivity–.25**.24.03–.14.32***–.05
8. Sensation avoiding–.14.09.10–.14.19*–.22*.51***
9. Depression–.07.47.20*–.07.19*–.01.14.07
10. Anxiety–.21*.19*.04.00.22*.01.29**.21*.47***
11. Stress–.09.18.17–.13.16.02.23*.12.55***.68***
12. Catastrophizing–.29**.19*.17–.14.20*–.04.34***.28**.26**.33***.34***
13. Hoping/praying–.19*.25**–.08–.06.06.15.23*.09–.02.22*.20*.48***
14. Ignoring pain–.19*.08.15–.08.22*.26**.12.00.10.12.15.08.15
15. Diverting attention–.12.27**.18–.16.22.20*.29**.04.10.21*.27**.43***.53***.28***
16. Increasing behavioral activities–.29**.31***.04–.09.04.33***.21*.07.00.23**.12**.34**.46***.35***.57***
17. Coping self-statements–.14.05.02–.13.17.30***.11.06–.03.13.06.04.27.66***.33***.32***
Table Footer Note*p ≤ .05. **p ≤ .01. ***p ≤ .001.
p ≤ .05. **p ≤ .01. ***p ≤ .001.×
×
Table 4.
Regression Statistics for Associations Between Pain Coping Behavior and Sensory Processing, Demographic, and Stress Variables (N = 116)
Regression Statistics for Associations Between Pain Coping Behavior and Sensory Processing, Demographic, and Stress Variables (N = 116)×
VariablePain Coping Behavior (t Score)
CatastrophizingIncreasing Behavioral ActivitiesDiverting AttentionIgnoring PainHoping/PrayingCoping Self-Statements
Low registration1.450.081.471.8–0.021.51
 Age−3.19**−1.8−0.57−3.26**−1.43−1.51
 Gender0.52.82**2.09*−0.442.21*−0.17
 Stress3.52***1.342.89**1.611.240.57
R2.23.15.17.15.10.05
F(4, 110)8.28***4.86**5.77***4.95***3.01*1.53
Sensory sensitivity2.99**1.091.98*0.111.85*0.31
 Age−2.96**−1.65−0.4−3.34**−1.48−1.61
 Gender0.382.75**2.12*–0.151.710.08
 Stress3.05**1.112.55*1.670.510.63
R2.28.16.185.126.12.03
F(4, 111)10.56 ***5.35***6.31***4.0**3.78**0.99
Sensation seeking−1.282.59*1.82.34*1.472.72**
 Age−3.51**1.38−0.47−3.14**−1.23−1.35
 Gender1.03−1.521.98−0.631.89−0.44
 Stress3.68***2.39*3.02**1.751.230.70
R2.228.20.18.167.12.09
F(4, 111)8.24***6.98***6.11***5.57***3.71**2.87*
Sensation avoiding2.55*0.320.19−0.420.860.85
 Age−3.22**−1.59−0.32−3.12−1.32−1.41
 Gender0.722.85**2.29*−0.171.850.05
 Stress3.40***1.333.00**1.790.840.61
R2.26.14.15.11.08.03
F(4, 110)9.85***4.57**4.83**3.47*2.51*1.67
Table Footer Note*p ≤ .05. **p ≤ .01. ***p ≤ .001.
p ≤ .05. **p ≤ .01. ***p ≤ .001.×
Table 4.
Regression Statistics for Associations Between Pain Coping Behavior and Sensory Processing, Demographic, and Stress Variables (N = 116)
Regression Statistics for Associations Between Pain Coping Behavior and Sensory Processing, Demographic, and Stress Variables (N = 116)×
VariablePain Coping Behavior (t Score)
CatastrophizingIncreasing Behavioral ActivitiesDiverting AttentionIgnoring PainHoping/PrayingCoping Self-Statements
Low registration1.450.081.471.8–0.021.51
 Age−3.19**−1.8−0.57−3.26**−1.43−1.51
 Gender0.52.82**2.09*−0.442.21*−0.17
 Stress3.52***1.342.89**1.611.240.57
R2.23.15.17.15.10.05
F(4, 110)8.28***4.86**5.77***4.95***3.01*1.53
Sensory sensitivity2.99**1.091.98*0.111.85*0.31
 Age−2.96**−1.65−0.4−3.34**−1.48−1.61
 Gender0.382.75**2.12*–0.151.710.08
 Stress3.05**1.112.55*1.670.510.63
R2.28.16.185.126.12.03
F(4, 111)10.56 ***5.35***6.31***4.0**3.78**0.99
Sensation seeking−1.282.59*1.82.34*1.472.72**
 Age−3.51**1.38−0.47−3.14**−1.23−1.35
 Gender1.03−1.521.98−0.631.89−0.44
 Stress3.68***2.39*3.02**1.751.230.70
R2.228.20.18.167.12.09
F(4, 111)8.24***6.98***6.11***5.57***3.71**2.87*
Sensation avoiding2.55*0.320.19−0.420.860.85
 Age−3.22**−1.59−0.32−3.12−1.32−1.41
 Gender0.722.85**2.29*−0.171.850.05
 Stress3.40***1.333.00**1.790.840.61
R2.26.14.15.11.08.03
F(4, 110)9.85***4.57**4.83**3.47*2.51*1.67
Table Footer Note*p ≤ .05. **p ≤ .01. ***p ≤ .001.
p ≤ .05. **p ≤ .01. ***p ≤ .001.×
×