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. Author manuscript; available in PMC: 2021 May 1.
Published in final edited form as: Eur J Pain. 2021 Jan 24;25(5):1041–1052. doi: 10.1002/ejp.1725

Age differences in cognitive–affective processes in adults with chronic pain

Caitlin B Murray 1, Kushang V Patel 2,3, Hanah Twiddy 4, John A Sturgeon 2, Tonya M Palermo 1,2
PMCID: PMC8055045  NIHMSID: NIHMS1676455  PMID: 33405280

Abstract

Background:

Chronic pain is associated with significant physical and psychological impairments across the adult lifespan. However, there is a relative gap in knowledge on individual differences that predict pain-related functioning. The current study highlights one important source of individual variation: age.

Methods:

We used cross-sectional data from a large treatment-seeking cohort of 2,905 adults (M age = 46.6 [13.1]; 71.8% women) presenting to a tertiary pain centre in the United Kingdom to determine age differences in cognitive-affective processes (catastrophizing, acceptance, self-efficacy), including their differential patterns and effects on disability and depression.

Results:

Older adults (ages 65–75) were found to experience higher pain acceptance and pain self-efficacy compared to both middle-aged (ages 40–64) and young adult (ages 18–39) age groups. Older adults also experienced lower levels of catasophizing compared to middle-age adults. Testing age as a moderator, we found that the relationships of pain self-efficacy and acceptance with depression as well as the relationship between pain self-efficacy and disability were comparatively weakest among older adults and strongest among young adults. Similarly, the relationship between pain catastrophizing and depression was relatively stronger for young and middle-aged adults compared to older adults.

Conclusions:

Age-related differences in psychological mechanisms that influence pain-related functioning present unique challenges and opportunities for scientists and clinicians to improve our understanding and treatment of pain across the lifespan. Additional work is needed to refine our knowledge of age-related differences in cognitive-affective, biopsychosocial dimensions of chronic pain and to develop and test the efficacy of age-tailored interventions.

Significance:

Our cross-sectional analysis of 2,905 treatment-seeking adults with chronic pain presenting to a tertiary care center in the United Kingdom revealed distinct age differences in cognitive-affective linked to disability and depression. This study contributes to the limited knowledge on age-related variance in psychological mechanisms underlying adjustment to chronic pain. Promising avenues for future research include refining our understanding of age-related differences in cognitive-affective, biopsychosocial dimensions of chronic pain and elucidating the most salient treatment targets among different age groups.

1 |. INTRODUCTION

Chronic pain is a common condition associated with decreased physical and psychological functioning across the lifespan (Dahlhamer et al., 2018). However, there exist robust intraindividual differences in the experience and influence of pain (Fillingim, 2017). The burden of pain is not shared equally across life stages, with research demonstrating greater risk of several types of chronic pain with advancing age (e.g. musculoskeletal; Tsang et al., 2008). However, there is a paucity of research on age-related variability in the prevalence and impact of cognitive-affective factors across the lifespan, which can contribute to differential trajectories of adjustment to chronic pain. Such knowledge can lead to better incorporation of developmentally informed models of pain intervention.

Risk and resilience-focused cognitive-affective processes—including pain catastrophizing, acceptance and self-efficacy—have gained strong empirical support for their role in adjustment to chronic pain (Edwards et al., 2016; Sturgeon & Zautra, 2010). However, few studies have sought to understand whether the expression and impact of cognitive-affective processes related to pain differ according to developmental age, commonly defined by lifespan developmentalists as young adulthood (ages 18–39), middle adulthood (ages 40–64) and older adulthood (ages 65; Mehta et al., 2020; Robert & Feldman, 2019). Pain research has generally focused on the ‘average’ adult age group (i.e. middle-age), and comparatively few studies have focused on young adults and older adults. Moreover, age is often treated as a continuous or binary construct (e.g. ‘young’ versus ‘old’), with little consideration of developmental age.

Available evidence on age-related patterns in cognitive-affective processes suggests that, compared to middle age and young adults, older adults with chronic pain report lower levels of affective distress (Cook et al., 2006; Edwards, 2006) and greater ‘control over pain’ - a construct similar to self-efficacy (Lachapelle & Hadjistavropoulos, 2005). These findings align with lifespan research in general populations indicating older adults experience greater positive affect, less negative affect and stronger emotional regulation compared to their young and middle-age counterparts (Carstensen & Mikels, 2005). Moreover, to our knowledge, only one study has examined age differences in the potential effects of cognitive-affective factors; Cook and colleagues found the association between catastrophizing and depression was relatively weaker in older adults compared to middle-aged adults (Cook et al., 2006). With advanced age, other biological and psychosocial factors may become more important in explaining physical disability and depression (e.g. co-morbid health conditions), with less room for pain-related cognitive-affective factors to contribute (Oosterman et al., 2013).

The goal of this study was to determine age differences in pain-related cognitive-affective processes, including their differential associations with disability and depression. Cross-sectional data from a large treatment-seeking cohort of 2,905 adults presenting to a tertiary pain centre in the United Kingdom were analysed. We expected a pattern of lower catastrophizing, higher acceptance, and higher self-efficacy among older adults relative to young and middle-age adults. Moreover, we expected that pain catastrophizing, acceptance, and self-efficacy would be significantly associated with disability and depression across all age groups, however, associations would be comparatively weakest in the older adult age group.

2 |. METHODS

2.1 |. Participants

A convenience sample of 2,905 adults (18–75 years old) was recruited from a large tertiary care pain centre in Liverpool, UK. Adults were stratified into the following age groups: young adulthood (Group 1: ages 18–39; M age = 30.72, SD = 6.05, N = 854, middle adulthood (Group 2: ages 40–64; M age = 50.6, SD = 6.5, N = 1,848) and older adulthood (Group 3: ages 65–75; M age = 70.6, SD = 5.05, N = 250). We selected these age groupings based on a priori, developmental life stage considerations that have been underscored as important in recent research (Mehta et al., 2020); although there is no ‘validated’ age cutoff, the age groupings chosen in our study are generally accepted within the developmental literature as they coincide with social and psychological resource changes as well as biological changes in adult development (Robert & Feldman, 2019). Specifically, young adulthood (ages 18–39) is generally characterized by transitioning to a committed romantic partnership (and typically marriage), new parenthood, building a career while balancing multiple professional and family roles, and overall good physical health (Mehta et al., 2020; Robert & Feldman, 2019). By middle adulthood (ages 40–64), individuals often acquire career expertise and reach occupational and economic stability, launch their adult children into independence, care for their aging parents and experience gradual decrements in physical health (e.g. declines in metabolism; Lachman, 2015; Mehta et al., 2020; Robert & Feldman, 2019). As individuals reach older adulthood (ages 65+), numerous distinctive social and physical changes can occur, including retirement, grief or bereavement of loved ones, placing greater value on social connections with family and friends, and increased risk for chronic disease (e.g. heart disease, osteoporosis; Robert & Feldman, 2019).

The demographic and pain characteristics of the total sample are presented in Table 1. Participants were consecutive patients attending an assessment clinic for a multidisciplinary pain management programme (PMP) in the North West of England. Inclusion criteria were diagnosis of a chronic pain condition by a physician, age ≥ 18, and provided informed consent for entering their data into a national registry. Chronic pain was defined as pain lasting longer than three months and encompassed neuropathic, musculoskeletal and other pain conditions. Exclusion criteria were being unable to understand the study protocol and provide informed consent, being too distressed to complete assessments, and co-morbid health conditions if primary treatment for these conditions interfered with pain treatment (e.g. cancer, multiple sclerosis). As this was a convenience sample, participation rate was not calculated.

TABLE 1.

Demographic and clinical characteristics of adults with chronic pain seeking care at a pain specialty clinic (N = 2,905)

Characteristic Total sample, N = 2,905 Young adults ages 18–39, N = 854 Middle adults ages 40–64, N = 1,848 Older adults ages 65–75, N = 203
Age (mean, SD)a 46.6 (13.1) 30.7 (6.1) 50.7 (6.5) 70.6 (5.0)
Sex (% female)b 71.8% 75.6% 70.9% 65.5%
Employment statusa
 Employed (part or full-time) 28.3% 33.3% 29.1% 3.9%
 Unemployed/not currently working 54.9% 55.4% 61.0% 7.4%
 Homemaker 3.5% 4.8% 3.2% 0.4%
 Student 1.9% 5.8% 0.4% 0.0%
 Retired 11.4% 0.6% 6.2% 88.3%
Primary pain diagnosis/typea
 Musculoskeletal 37.4 35.4 38.6 35.7
  Fibromyalgia/widespread pain 26.4 25.7 27.7 18.6
  Extremities (hip/legs/arms/shoulders) 8.7 9.2 8.2 11.1
  Rheumatic conditions 2.3 0.5 2.7 6.0
 Spine 34.7 29.1 36.3 44.2
 Neuropathic 8.7 8.4 8.9 8.0
 Orofacial/head 2.9 4.3 2.4 1.5
 Visceral/pelvic/urogenital 7.0 13.0 4.5 4.5
 Other 9.4 9.7 9.5 6.0
  Chronic disease-related 1.5 1.8 1.4 0.5
  Post-surgical 2.0 1.3 2.4 1.0
  Post-stroke 0.2 0.1 0.2 0.5
  Unspecified 5.7 6.6 5.5 4.0
Pain intensity (VAS 0–10)c 7.6 (1.6) 7.5 (1.6) 7.6 (1.6) 7.8 (1.7)
Pain duration (months)a 106.8 (106.1) 80.8 (77.3) 114.1 (108.6) 143.5 (147.9)
Disability Score (RMDQ)d 17.8 (4.8) 17.4 (5.1) 18.1 (4.8) 16.9 (4.2)
Depression Score (BDI)e 28.8 (12.5) 30.20 (12.5) 29.5 (12.3) 19.2 (9.2)
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a

Significant group differences among all three age groups.

b

Significant group differences between young and older adults.

c

Significant group differences between young and middle and young and older adults.

d

Significant group differences between young adults and middle adults and middle adults and older adults.

e

Significant group differences between young and older and middle and older adults.

2.2 |. Procedure

Patients were seen for an initial assessment at a large tertiary pain centre in the United Kingdom between July 2012 and January 2018. The National Health Service (NHS) England commissioned the multidisciplinary pain management programme (PMP) to provide specialized assessment and treatment services for individuals with chronic pain. In order to facilitate referral and triage to appropriate treatment services, patients completed a demographic information form and questionnaire packet including validated measures of pain, psychological health and physical functioning as part of their clinic intake. Patients provided informed consent to enter their data into a national registry. The NHS (UK) clinic obtained ethical approval for the management of the PMP Registry. No other studies have been published from this dataset.

2.3 |. Measures

2.3.1 |. Demographic information

Participants provided basic demographic information (age, sex and employment status).

2.3.2 |. Chronic pain characteristics

Pain characteristics included pain intensity, pain duration and primary pain diagnosis. Participants rated usual pain intensity over the past week on an 11-point Numerical Rating Scale (NRS; 0 = no pain, 10 = the most intense pain imaginable). The NRS is a widely used and valid measure (Hawker et al., 2011). Participants rated pain duration as the total number of months since the onset of pain. Finally, primary pain diagnosis was extracted from medical records and classified according to organ system and anatomic structure with guidance from the ACTTION-American Pain Society Pain Taxonomy (AAPT; Dworkin et al., 2016). These categories included (a) musculoskeletal pain (with extremity, wide-spread/fibromyalgia and rheumatic condition subcategories), (b) spine pain, (c) neuropathic pain, (d) orofacial and head pain (including headache, temporomandibular disorders), (e) pelvic/urogenital and visceral pain (including abdominal pain) and (f) other pain (chronic disease-associated pain, post-stroke pain, post-surgical pain subcategories).

2.3.3 |. Disability

Participants in the current study completed a modified version of the Roland-Morris Disability Questionnaire (RMDQ), a 24-item checklist designed to measure disability associated with chronic pain. The scale was modified to apply to a broader range of chronic pain conditions (i.e. statements related to ‘my back pain’ were changed to ‘my pain’) and this version has been used in heterogeneous pain populations (Senske & Harris, 2013). Participants endorse their ability to complete daily physical activities. The overall score is a sum of positive responses, ranging from 0 to 24, with higher scores signifying greater disability. The RMDQ has been found to have excellent psychometric properties, including high levels of internal consistency and test-retest reliability (Roland & Fairbank, 2000).

2.3.4 |. Depression

Self-reported symptoms of depression were measured with the Beck Depression Inventory-II (BDI-II). The BDI-II consists of 21 items that cover the major features and symptoms of depression (e.g. mood, insomnia, loss of appetite). Participants are asked to rate each item on a scale from 0 (not present) to 3 (present) according to their experience over the past week. The BDI-II yields a total score ranging from 0 to 63, with higher scores indicating higher levels of depressive symptoms. The BDI-II has been shown to have strong psychometric properties (Arnau et al., 2001; Dozois et al., 1998).

2.3.5 |. Pain catastrophizing

Pain catastrophizing was measured using the 13-item Pain Catastrophizing Scale (PCS; (Sullivan et al., 1995). The PCS measures the degree to which individuals magnify the threat value of ongoing pain, on a 5-point scale (0 = not at all; 4 = all the time). Item responses were summed to yield a total score ranging from 0 to 52. Higher scores indicate a greater tendency to magnify the threat and significance of pain. The PCS is a widely used measure demonstrating good psychometric properties (Sullivan et al., 1995).

2.3.6 |. Pain self-efficacy

The Pain Self-Efficacy Questionnaire (PSEQ) assesses an individual’s beliefs about his or her ability to undertake and engage in daily activities despite pain. The PSEQ contains 10 items rated on a 7-point scale from 0 (not at all confident) to 6 (completely confident). Sample items include ‘I can enjoy things, despite the pain’ and ‘I can still accomplish most of my goals in life, despite the pain’. Item scores are summed to yield a total score (possible range 0–60, with higher scores indicating greater self-efficacy). Studies of the psychometric properties of the PSEQ have demonstrated its reliability and validity (Nicholas, 2007).

2.3.7 |. Pain acceptance

The 21-item Chronic Pain Acceptance Questionnaire (CPAQ) contains items designed to measure acceptance in the context of chronic pain. Participants rated items on a scale from 0 (‘never true’) to 6 (‘always true’), with higher scores indicating greater willingness to experience and accept their pain. Item responses were summed to create an overall score (possible range 0–126). Numerous studies have shown the CPAQ has strong psychometric properties (Wicksell et al., 2009).

2.4 |. Data analysis plan

We performed all analyses using IBM SPSS (Version 19 for Windows). Initial descriptive statistics were analysed to characterize the sample, including means, standard deviations and frequencies of demographic and pain characteristics by age group (young adulthood, middle adulthood, older adulthood). We also examined bivariate associations among the three cognitive-affective factors.

To address our first aim of determining overall age differences in cognitive-affective processes, we conducted one-way analyses of covariance (ANCOVA) to determine mean differences in pain catastrophizing, pain self-efficacy and pain acceptance as a function of age group. These analyses controlled for the potential effects of demographic (age, sex, occupation) and pain characteristics (pain intensity, pain duration, primary pain diagnosis). Age as a continuous variable was further added as covariate given wide age range intervals within three age groups. Primary pain diagnosis was included as a categorical variable coded according to the six main categories pain types referenced above. Post-hoc Tukey’s HSD was computed for study variables given significant omnibus differences.

To address our second aim of determining age group differences in the effects of cognitive-affective factors on disability and depression, we conducted moderation analyses using Hayes’ PROCESS macro (Hayes, 2013) with non-parametric bootstrapping with 10,000 resamples. Following Hayes & Montana’s (Hayes & Montoya, 2017) guidance for analyses of multi-categorical moderator variables in multiple regression analyses, we used indicator or dummy coding to represent the three categories of age and facilitate group comparisons. Hayes recommends creating dummy-coded variables to delineate the groups while still including all participants in the model, thereby retaining statistical power. Specifically, two sets of dummy variables were created (see Table 1). In the first set (D1 and D2), the young adult group identified as the reference group, allowing for slope comparisons between young adults versus middle-age adults (D1) and young adults versus the older adults (D2). In the second set, (D3 and D4) the middle-age group served as the reference group, allowing for slope comparisons between the middle-age and older adults (D3). D4 offered a comparison already represented by D2 (i.e. middle-aged adults and young adults). Thus, we only present and interpret regression results of D1, D2 and D3.

Regression models predicting each of the two dependent variables (disability, depression) included demographic (age, sex, occupation) and pain characteristics (pain intensity, duration, diagnosis), one of the three cognitive-affective predictor variables (i.e. pain catastrophizing, pain self-efficacy and pain acceptance), the dummy-coded age variables as the potential moderator (i.e. D1 and D2 or D3 and D4), and the product terms between the moderator and predictor variables (i.e. D1 X Pain Catastrophizing). The Hayes PROCESS macro tested interactions for each of the cognitive-affective predictors in separate models. We conducted post-hoc analyses when a 95% bias-correct confidence interval did not include zero (Hayes & Montoya, 2017). Post-hoc analyses determined the conditional effects of cognitive-affective processes in each of the three age groups in order to understand the strength and direction of effects (i.e. simple slopes) in young adults, middle-aged adults and older adults separately.

2.4.1 |. Power analysis

We performed post-hoc power analyses for one of the models using G*power. This model included a total of 8 terms (i.e. including six covariates and two dummy-coded age X predictor interaction terms). G*power indicated greater than a 0.95 power to detect small to medium effect sizes for a moderator or predictor.

3 |. RESULTS

3.1 |. Descriptive statistics

Demographic and clinical characteristics of the total sample are shown in Table 1. Collectively, the average age of adults seeking care at this pain specialty clinic was 46.6 years (SD = 13.1), with a range of 18–75. The majority of the sample were women (71.8%), and over half reported being unemployed or not currently working (54.9%). The average duration of pain in the sample was 106 months (8.8 years). Pain intensity was severe on average (M = 7.6; SD = 1.6). The most common pain diagnosis reported was back pain (33.6%), followed by fibromyalgia/widespread pain (25.5%). We note between-group differences by age group in demographic and clinical characteristics in Table 1. Briefly, older adults were more likely to be men and retired or unemployed. As expected, pain duration was highest in older adults, significantly increasing with each age group. Older participants reported significantly lower levels of depression compared to middle-age and young adults and lower physical disability compared to middle-age (but not young) adults.

Correlation analyses reflected moderate significant associations among all three cognitive affective factors in the expected directions in the total sample of participants (Pearson rs = −0.50 to 0.68, p < 0.001); for example, higher pain catastrophizing was significantly associated with lower pain acceptance (r = −0.60, p < 0.001) and higher pain acceptance was associated with higher pain self-efficacy (r = 0.68, p < 0.001).

3.2 |. Aim 1: Determine age differences in cognitive-affective processes

ANCOVA analyses revealed significant age differences across all cognitive-affective processes (see Table 2). After controlling for demographic and pain characteristics, post-hoc analyses revealed that adjusted mean scores for pain catastrophizing were similar in young adults compared to middle-aged and older adults, however, older adults reported lower catastrophizing compared to middle-aged adults. Moreover, adjusted mean scores were significantly higher for pain acceptance and pain self-efficacy in the older adult group compared to both middle-age and young adult age groups.

TABLE 2.

Comparison of age groups on measures of pain-related cognitive-affective processes

Sample range Young adults ages 18–39, N = 854 Middle adults ages 40–64, N = 1,848 Older adults ages 65–75, N = 250 Difference test
M SE M SE M SE F p
Pain catastrophizing 0–52 30.97 0.70 31.72 0.33 29.10 1.28 3.68 0.03a
Pain self-efficacy 0–60 17.44 0.63 15.70 0.30 23.22 1.15 34.85 <0.0001b
Pain acceptance 0–107 43.35 1.01 42.04 0.48 51.31 1.84 18.25 <0.0001b
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Note: Analyses of group differences adjusts for age, sex, occupational status, pain intensity, pain duration and primary pain diagnosis. For follow-up comparisons using least significant difference, superscripts indicate:

a

Significant group difference between middle and older adults only.

b

Significant group differences between young and older adults and middle and older adults.

3.3 |. Aim 2a: Determine whether age modifies the associations between cognitive-affective factors and pain-related disability

After adjusting for demographics and pain characteristics, results revealed significant main effects of all three cognitive-affective processes on pain-related disability in the expected directions, such that higher pain catastrophizing and lower self-efficacy and acceptance predicted lower levels of disability (p < 0.001) (Table 3, Figure 1).

TABLE 3.

Aim 2a: Age as a moderator of the effects of cognitive-affective factors on disability

Model 1, b coef. [95% CI] Model 2, b coef. [95% CI] Model 3, b coef. [95% CI]
Age group codes
 D1 (young versus middle)a 0.51 [−0.57 to 1.59] − 0.17 [−0.89 to 0.54] 0.56 [−0.46 to 1.59]
 D2 (young versus older)a −0.46 [−2.44 to 1.52] −1.83 [−3.33 to −0.33]* −2.48 [−4.81 to −0.14]*
 D3 (middle versus older)b −0.97 [−2.66 to 0.72] −1.66 [−2.92 to −0.40]** −3.04 [−5.16 to −0.92]**
Cognitive-affective factors
 Pain catastrophizing 0.12 [0.11–0.14]** – –
 Pain self-efficacy – −0.24[−0.27 to −0.22]** –
 Pain acceptance – – −0.10[−0.12 to −0.09]**
Age by cognitive-affective factors (interactions)
 D1 X catastrophizing 0.01 [−0.03 to 0.03] – –
 D2 X catastrophizing −0.03 [−0.09 to 0.02] – –
 D3 X catastrophizing −0.04 [−0.09 to 0.01] – –
 D1 X self-efficacy – 0.03 [0.01–0.06]* –
 D2 X self-efficacy – 0.08 [0.03–0.13]** –
 D3 X self-efficacy – 0.05[0.01–0.10]* –
 D1 X acceptance – – −0.01 [−0.02 to 0.02]
 D2 X acceptance – – 0.03 [−0.01 to 0.07]
 D3 X acceptance – – 0.03 [−0.01 to 0.07]
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Note: All models adjust for age, sex, occupational status, pain duration, pain intensity, primary pain diagnosis.

a

Young adult group is the reference group.

b

Middle age group is the reference group.

**

p < 0.01;

*

p < 0.05.

FIGURE 1.

FIGURE 1

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Age differences in the associations between pain self-efficacy and disability

Moderation analyses found that age did not significantly modify the association between catastrophizing and disability or the association between acceptance and disability. However, these analyses revealed significant age differences in the association between self-efficacy and disability. Specifically, significant interactions emerged for D1 X Self-efficacy, D2 X Self-efficacy and D3 X Self-efficacy (i.e. all three age group codes X predictor interactions). This pattern of results, along with post-hoc analyses of conditional/simple slope effects, indicates that greater levels of pain self-efficacy predicted lower levels of disability, particularly for young adults (simple slope B = −0.24, p < 0.001) relative to both middle-aged (simple slope B = −0.21, p < 0.001) and older adults (simple slope B = −0.16, p < 0.001). A significant D3 X Self-efficacy interaction indicates that the magnitude of this association was stronger for middle-aged adults compared to older adults. Overall, the association between self-efficacy and disability attenuated with each subsequently older age group (see Figure 1).

3.4 |. Aim 2b: Determine whether age modifies the associations between cognitive-affective factors and depression

After adjusting for covariates, results of regression analyses revealed significant main effects of all three cognitive-affective processes on depression, such that greater levels of pain catastrophizing and lower levels of self-efficacy and acceptance predicted higher levels of depression (p < 0.001) (Table 4, Figures 2–4).

TABLE 4.

Aim 2b: Age as a moderator of the effects of cognitive-affective factors on depression

Model 1, b coef. Model 2, b coef. Model 3, b coef.
Age group codes
 D1 (young versus middle)a 4.81 [2.29–7.33]* 1.11 [−0.84 to 3.06] 0.29 [−2.18 to 2.77]
 D2 (young versus older)a 4.40 [−0.23 to 9.02] −8.45 [−12.51 to −4.38]** −11.29 [−16.93 to 5.64]**
 D3 (middle versus older)b −0.41 [−4.38 to 3.56] −9.55 [−12.96 to −6.14]** −11.58 [−16.71 to −6.46]**
Cognitive-affective factors
 Pain catastrophizing 0.62 [0.56–0.68]** – –
 Pain self-efficacy – −0.61 [−0.68 to −0.54]** –
 Pain acceptance – – −0.42 [−0.46 to −0.38]**
Age by cognitive-affective factors (interactions)
 D1 X catastrophizing −0.06 [−0.13 to 0.01] – –
 D2 X catastrophizing −0.27 [−0.40 to −0.15]** – –
 D3 X catastrophizing −0.21 [−0.33 to −0.09]* – –
 D1 X self-efficacy – 0.07 [0.01–0.15]* –
 D2 X self-efficacy – 0.35 [0.21–0.48]** –
 D3 X self-efficacy – 0.27 [0.15–0.40]* –
 D1 X acceptance – – 0.06 [0.01–0.10]*
 D2 X acceptance – – 0.20 [0.10–0.29]**
 D3 X acceptance – – 0.14 [0.05–0.23]**
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Note: All models adjust for age, sex, employment status, pain duration, pain intensity, primary pain diagnosis.

a

Young adult group is the reference group.

b

Middle age group is the reference group.

**

p < 0.01;

*

p < 0.05.

FIGURE 2.

FIGURE 2

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Age differences in the associations between pain catastrophizing and depression

FIGURE 4.

FIGURE 4

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FAge differences in the associations between pain acceptance and depression

In testing age as a moderator, we found significant age differences in all three cognitive-affective processes predicting depression. Specifically, significant interactions emerged for D2 X Catastrophizing and D3 X Catastrophizing. See Table 4. Together with post-hoc analyses examining simple slopes of each age group, this pattern of results indicates that, relative to older adults, the predictive value of pain catastrophizing on depression was stronger for young adults (simple slope Bs = 2.69 and 0.62 respectively; p < 0.001) and middle-aged adults (simple slope Bs = 2.81 and 0.56, respectively; p < 0.001). The strength of the association for older adults was significant (simple slope Bs = 1.32 and 0.35, respectively, p < 0.01), but relatively weaker compared to young and middle-aged groups. As indicated by a non-significant D1 X Catastrophizing interaction, the strength of associations was similar across young and middle-aged adult groups (see Figures 2 and 3).

FIGURE 3.

FIGURE 3

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Age differences in the associations between pain self-efficacy and depression

Finally, moderation analyses revealed age differences in the relationships of both resilience factors (self-efficacy, acceptance) with depression. Specifically, results revealed significant interactions between all three age code groups (i.e. D1, D2, D3) and resilience predictors. See Table 4. This pattern of results indicates that greater pain self-efficacy and acceptance predicted lower levels of depression, particularly for young adults (simple slope Bs = −0.61 and −0.42, respectively, p < 0.001) relative to both middle-aged (simple slope Bs = −0.53 and −0.36, respectively, p < 0.001) and older adults (simple slope Bs = −0.26 and −0.23, respectively, p < 0.001). Further, the significant D3 X Self-efficacy D3 X Acceptance interactions indicate that these relationships were also relatively stronger for middle-aged adults compared to older adults. In other words, the association between resilience-based factors and depression attenuated with increasing age (see Figure 2c,d).

4 |. DISCUSSION

This is the first study to examine age differences in several key, modifiable cognitive-affective processes linked to disability and depression in a large, treatment-seeking cohort of adults with chronic pain. Our cross-sectional analysis of 2,905 adults presenting to a tertiary care centre in the UK extends the paucity of data on age differences in cognitive-affective factors known to play a key role in adjustment to chronic pain. First, after controlling for several demographic and pain characteristics, the relationship between pain catastrophizing and depression was relatively stronger for young and middle-aged adults compared to older adults. Moreover, the relationships of pain self-efficacy and acceptance with depression, as well as the relationship between pain self-efficacy and disability, were strongest among young adults and weakest among older adults with chronic pain. Overall, the present study adds to the limited evidence on age differences in cognitive-affective processes in the context of chronic pain, highlighting several promising avenues for future research and clinical care.

Pain catastrophizing, pain-self efficacy and pain acceptance are strongly associated with disability and depression in chronic pain populations (Edwards et al., 2011; Mankovsky et al., 2012; Sullivan et al., 2005). Despite clinical importance, only a handful of studies have examined age differences in patterns of cognitive-affective processes similar to those investigated in our study. Past research has demonstrated lower levels of pain-related affective distress and higher ‘perceived control over pain’ in older adults versus middle-age and young adults (Cook et al., 2006; Edwards, 2006; Lachapelle & Hadjistavropoulos, 2005). Consistent with this research, we found that older adults reported lower levels of pain catastrophizing compared to middle-age adults and higher levels of pain acceptance and pain self-efficacy compared to middle-age and young adults.

There may be several reasons for this pattern of findings. Overall, our results dovetail with lifespan research on aging and emotional health in the general population. There is consistent evidence to indicate that older adults demonstrate considerable psychological resilience, such that emotional regulation and mood management improve with advancing age (Gooding et al., 2012; Ong et al., 2009). For example, compared to their young and middle-age counterparts, older adults experience greater positive affect, less negative affect and ruminate less about negative experiences (Carstensen & Mikels, 2005; Kessler & Staudinger, 2009). In the context of chronic pain, older adults may also perceive painful symptoms as a natural and unavoidable part of aging, thereby experiencing greater acceptance and fewer negative emotions related to pain (Edwards, 2006; Riley et al., 2000). Moreover, investigators have theorized that older adults may be more accepting of pain and possess stronger beliefs in their ability to cope with disability related to pain because they experience fewer work and family stressors (Lachapelle & Hadjistavropoulos, 2005). In contrast, young and middle-age adults may experience greater distress and less acceptance due to the salient impact of pain on school, employment and family responsibilities.

Our findings indicate that pain catastrophizing is not only higher, but also is more closely associated with depression in young and middle-age adults compared to older adults. To our knowledge, only one other study has examined the differential impact of pain catastrophizing on depression according to age: using a cohort of 469 treatment-seeking adults with chronic pain, Cook and colleagues (Cook et al., 2006) found the link between pain catastrophizing and depression to be stronger for middle-aged adults (defined as ages 41–54) compared to older adults (ages 55+). Moreover, catastrophizing has been found to have robust correlations with depression in studies that investigate these age groups separately (Buenaver et al., 2008; López-López et al., 2008). We extend this research through comparing the relative strength of these associations across age groups, finding that catastrophizing may be a relevant target for improving depression for all ages, but particularly for young and middle-aged adults.

Finally, as hypothesized, despite older adults indicating higher levels of pain self-efficacy and acceptance, the associations of these two cognitive-affective processes with depression and disability were comparatively weakest in this age group (and strongest in young adults). There are several potential explanations for these findings. First, with advanced age, other factors including pain intensity, health status and social-contextual factors that were not measured in this study may be more important in explaining disability and depression (Suso-Ribera et al., 2017). Potential relevant factors that this study did not measure include perceived loneliness (Cacioppo et al., 2010), low social support (Vanderhorst & McLaren, 2005) and the presence of multiple medical conditions (Mills, 2001) or symptoms (e.g. sleep, fatigue; Patel et al., 2019) that have been found to predict depression and disability in community samples of older adults. Results may also reflect a ceiling effect, such that older adults tended to be less distressed and experience higher levels of adaptation overall. Moreover, there may be differences in content validity of these measures across the lifespan reflecting differences in perceptions and perceived relevance. Overall, these results highlight the need to take a more nuanced approach to understand how individuals of different age groups adjust to their pain. Research including age-relevant biopsychosocial factors in addition to specific pain-related cognitive-affective processes can elucidate the most salient treatment targets among different age groups.

Our findings have several clinical implications. Due to age disparities in research, the multidisciplinary treatment of chronic pain has generally been developed to target middle-aged adults (i.e. the ‘average’ adult age group), and surprisingly little research attention has been directed towards understanding the unique treatment needs of young adult and older adult age groups. Because the majority of significant interactions testing age as a moderator were found for depression, it is possible that age-tailored interventions targeting co-morbid depression may be particularly relevant. Qualitative studies have revealed that young adults with chronic pain present with unique treatment needs; for example, young adults have indicated the need to incorporate content related to the impact of chronic pain on emotional health and transition to college or full-time work (Stinson et al., 2013; Twiddy et al., 2017). However, there has been limited testing of treatments tailored to this age group. Applying skills drawn from cognitive-behavioural therapy, Acceptance and Commitment Therapy and dialectical behavioural therapy (DBT) approaches to target pain catastrophizing, acceptance, self-efficacy could improve co-morbid depression outcomes and enhance treatment benefit in young adults with chronic pain.

Moreover, despite the complexity and unique characteristics of older adults and their increased prevalence of chronic pain conditions, surprisingly little research attention has been directed towards tailoring psychological treatment to this age group. There is a small but growing evidence base for the efficacy of CBT in older adults (e.g. Ehde et al., 2014) and recent emergence of ACT and other mindfulness-based therapies for these individuals have found promising benefits (for a review see Keefe et al., 2013). However, given our findings on weaker associations among cognitive-affective processes and depression in older adults and recent meta-analytic reviews indicating that CBT may be less effective for older adults compared to other age groups (Gurung et al., 2015), future research could examine combined approaches incorporating pharmacological, physical and psychological therapies to understand the best treatment approach for ameliorating depression in older patients with chronic pain.

These results should be interpreted in the context of several limitations. First, we utilized a cross-sectional rather than longitudinal design. We were therefore unable to rule out cohort effects or determine how the prevalence and impact of cognitive-affective processes fluctuate over the course of an individual’s lifespan. Consequently, we present the current findings as a topology of relationships, and cannot specifically state that the cognitive-affective variables are causal determinants of depression and disability. Second, we did not collect data on demographic and clinical variables that would be important to include in future work, including ethnicity and presence of a full range of co-morbid chronic medical conditions. Third, to our knowledge, research has not yet tested age-related invariance in measures of cognitive-affective processes (e.g. pain acceptance) among young, middle-age and older adults with chronic pain; this will be an important area to address in future work. Finally, older adults over 75 were relatively underrepresented in our sample, which is both reflective of other outpatient pain clinic samples (Nicholas et al., 2008; Sturgeon et al., 2015) and of an unfortunate trend of underrepresentation of older adult populations in chronic pain (e.g. Paeck et al., 2014). Despite limitations, our study possesses a number of strengths, including analysis of several common cognitive-affective constructs in a large treatment-seeking cohort of adults aged 18–75 years with chronic pain presenting to tertiary care. Although there were unequal sample sizes across the three age cohorts, our sample size was large and allowed for greater power to detect effects.

This study contributes to the burgeoning evidence base on pain and aging. Our findings suggest that the impact of cognitive-affective processes on depression and disability is not uniform across the lifespan. The presence of age-related differences in psychological mechanisms that influence pain present unique challenges and opportunities for scientists and clinicians to improve our understanding and treatment of pain across the lifespan. To continue to move the field forward, it will be critical to refine our understanding of age-related differences in cognitive-affective and other biopsychosocial dimensions of chronic pain, to examine mechanisms for age-related patterns, and to develop and test the efficacy of age-tailored interventions.

ACKNOWLEDGEMENTS

Special acknowledgement is due to all the staff and patients at The Walton Centre NHS Foundation Trust Pain Management Programme service for their support and contributions to the data collection.

Funding information

The research reported in this publication was supported by the National Institutes of Health under Award Number F32 HD097807 (PI: Caitlin Murray). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Footnotes

CONFLICTS OF INTEREST

The authors have no conflict of interest to declare.

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