Abstract
Background and aims:
Chronic pain affects an estimated 1 in 10 adults globally regardless of age, gender, ethnicity, income or geography. Chronic pain, a multifactorial problem requires multiple interventions. One intervention which demonstrates promising results to patient reported outcomes is pain education. However, patient perspective on pain education and its impact remains fairly unknown. A cross-sectional study involving individuals with chronic pain examined their perspectives on pain education; did it change their understanding about their pain and self-management and did it have any impact on their perceived pain intensity and recovery.
Methods:
The study complied with CHERRIES guidelines and the protocol was locked prior to data collection. Primary outcomes were pain intensity and participants’ expectation of recovery. Univariate and multiple logistic regressions were used to analyze the data.
Results:
Five hundred and seventy three people participated; full data sets were available for 465. Participants who observed changes in their pain cognition and self-management following pain education reported lower pain intensity and greater expectation of recovery than participants who did not observe changes to cognition and management.
Conclusions:
The results suggest that individuals who observed changes to pain cognition and self-management on receiving pain education reported lower pain intensity and higher expectations of recovery than their counterparts who did not perceive any changes to pain cognition and self-management.
Implications:
Pain intensity and expectations about recovery are primary considerations for people in pain. What influences these factors is not fully understood, but education about pain is potentially important. The results suggest that individuals who observed changes to pain cognition and self-management on receiving pain education reported lower pain intensity and higher expectations of recovery than their counterparts who did not perceive any changes to pain cognition and self-management. The results from this study highlight the importance of effective pain education focused on reconceptualization of pain and its management.
1 Introduction
Persistent pain is a major global health problem [1], ranked as one of the leading causes for medical visits [2], [3], [4]. Defined as pain on most days for more than 3 months [5], persistent pain affects people regardless of age, gender, ethnicity, income or geography. Present understanding of pain stipulates that it is a complex, multi-factorial condition usually triggered by tissue injury. However, nociception – the detection and transmission of a rapid change in tissue state – is neither sufficient nor necessary for pain [6]. Contemporary concepts emphasize biopsychosocial principles [6] for better understanding, assessment, prevention and management of persistent pain.
Progress in our understanding of pain has led to a fundamental shift in management approaches. Pain biology education which emerged about 15 years ago [7] is now recognized as part of best practice [8]. Pain education aims to give patients an overview of the underlying physiological mechanisms and adaptive processes which support persistent pain, such that pain becomes ‘over-protective’ [9], [10]. Reconceptualization of pain in this fashion shows clinically important improvements [11] with increased participation from patients in active biopsychosocial based rehabilitation [12]. Explaining pain seems to have similar positive effects across painful conditions, for example fibromyalgia [13], [14], neck pain [15], chronic fatigue syndrome [16], and chronic low back pain [17], [18].
However, one issue that remains to be investigated is the patients’ perspective on the impact of pain education. Although empirical data shows that learning about pain biology improves pain and enhances the likelihood of recovery from persistent pain [12], whether or not patients see value in pain education, and whether or not perceiving that value is associated with pain and expectations of recovery, remains unknown. It is an important question because it is the patient’s perspective that will best inform their future responses to painful events and the advice they give to others – an important method of knowledge transfer [19].
The current study investigated these issues using an online cross-sectional design. We aimed to determine if participants believed that pain education had changed their views on their pain (hereafter referred to as pain cognition) and had changed the way they managed their pain (hereafter referred to as self-management of pain), and whether or not these perceptions were associated with their expectations of recovery and their current usual pain intensity.
2 Methods
2.1 Design and participants
A cross sectional online survey design was used to collect data on two critical aspects of chronic pain, use of supplement intake [20] and pain education. The survey questionnaire was developed according to a review of the literature and was built in accordance with the Checklist for Reporting Results of Internet E-Surveys (CHERRIES) [21]. The study protocol and questionnaire was published in The Journal of Pain Research [22], prior to data collection. Consistent with guidelines for transparency in research [23], any deviations from the published protocol are noted. In addition to demographic data, the survey investigated participants’ daily pain management strategies, their expectation of recovery and their perspectives on the value of pain education, if they had received it. All participants provided digital consent prior to prior to participating in the survey. The study was approved by the Human Research Ethics Committees of the University of Adelaide and the University of South Australia.
All participants were individuals who could read and understand English, were aged 18 years and above, and at the time of participation, had experienced pain on most days for more than three consecutive months. There was no limitation on gender, ethnicity or country of residence.
2.2 Measures
2.2.1 Dependent variables
The primary outcomes used in this study were; patient-perceived pain intensity and patient-perceived time to recovery. Information on pain intensity was collected from the participants using the question, “what is the average severity of your pain in the last 2 days?” Participants were asked to complete a numerical rating scale (NRS), anchored at left with “0 – no pain” and at right with “10 – worst pain”. Participants were also asked, “how long do you think it will take for you to recover from your current pain problem?” where recovery was outlined as reduction in pain severity and improved daily functioning. The possible responses were “3–6 months”, “up to 1 year”, “more than 1 year” and “never”. In order to fulfill the requirements of logistic regression, and because we were primarily interested in whether perspectives on the impact of pain education would be associated with expecting recovery rather than not expecting recovery, we analyzed recovery as a dichotomous variable: those who responded with “never” and those who chose one of the other responses. Similarly, we dichotomized pain intensity over the last 2 days either side of the predicted median: ≤5 and ≥6. The survey only allowed selection of whole numbers.
2.2.2 Independent variables
The independent/explanatory variables were: observed change in views on their pain (referred to as pain cognition) following pain education, observed change in self-management of pain following pain education, and demographic characteristics determined a priori to be likely confounders: age, gender, education level, employment status, and marital status.
Pain education was defined as, information patients had received from their health care providers explaining their pain and potential triggers such as lack of sleep, inactivity, stress which may aggravate their pain and symptoms. Participants were asked if they had received pain education. If the response to this question was “yes”, they were directed to these questions – “Did this education change the way you think about your pain?” and “Did this education change the way you manage your pain?” Responses to both these questions were collected using simple “yes”, “no” dichotomization.
2.3 Data collection and analysis
Univariate and multiple logistic regression was computed to estimate the odds of expected recovery among patients who had reported observed change in pain cognition and self-management of pain following pain education. The likelihood ratio test was used to find the best predictors of these relations. To compare the regression models and maintain uniformity of sample size, “not applicable” cases from all the covariates were removed. If change in pain cognition and change in self-management demonstrated collinearity, then separate regressions were undertaken, as per protocol.
Basic univariate descriptive statistics was used to characterize the sample for the proportion of the entire cohort who had received pain education, those who had observed change in pain cognition and change in self-management of pain as a result of pain education, pain intensity and expected recovery. Cross-tabulation was used to describe pain intensity and expected recovery in groups that were defined by age, gender, education level, employment status, marital status, pain education, change in pain cognition and change in self-management of pain. All analysis was performed in STATA.14.1.
3 Results
There were no deviations from the published protocol [22]. Responses were received from 573 participants. Full data sets were available from 465, of which 412 participants (91%) had participated in pain education (Table 1), which meant statistical comparison based on this variable was not possible. The mean (SD) pain intensity for the entire cohort was 5.8 (2). Two hundred and eighty-seven of participants reported that pain education had led to a change in the way they think about their pain. Two hundred and seventy-nine reported that pain education had led to a change in the way they manage their pain. In the logistic/simple linear regression, the effect estimates of the outcome confounder relation were adjusted for age, gender, education level, employment status and marital status.
Patient-reported pain intensity by participants aged 18 years and above.
| Variable | Age 18–40 years |
Total | Age 41+years |
Total | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Pain intensity ≥6 |
Pain intensity ≤5 |
Pain intensity ≥6 |
Pain intensity ≤5 |
|||||||
| No | % | No | % | No | % | No | % | |||
| Sexa | ||||||||||
| Female | 100 | 59 | 70 | 41 | 170 | 149 | 64 | 84 | 36 | 233 |
| Male | 12 | 46 | 14 | 54 | 26 | 18 | 51 | 17 | 49 | 35 |
| Education levela | ||||||||||
| Primary | 26 | 60 | 17 | 40 | 43 | 32 | 64 | 18 | 36 | 50 |
| Others | 86 | 56 | 67 | 44 | 153 | 134 | 62 | 83 | 38 | 217 |
| Employment statusa | ||||||||||
| Full time employed | 36 | 58 | 26 | 42 | 62 | 47 | 64 | 27 | 36 | 74 |
| Unemployed/on leave because of pain | 37 | 82 | 8 | 18 | 45 | 58 | 72 | 23 | 28 | 81 |
| Part time employed | 15 | 39 | 23 | 61 | 38 | 27 | 49 | 28 | 51 | 55 |
| Home duties | 5 | 63 | 3 | 38 | 8 | 22 | 58 | 16 | 42 | 38 |
| Student | 17 | 43 | 23 | 58 | 40 | 7 | 54 | 6 | 46 | 13 |
| Marital statusa | ||||||||||
| Married | 34 | 52 | 31 | 48 | 65 | 88 | 58 | 63 | 42 | 151 |
| Single/unmarried | 47 | 63 | 28 | 37 | 75 | 56 | 69 | 25 | 31 | 81 |
| Partnered | 31 | 56 | 24 | 44 | 55 | 21 | 64 | 12 | 36 | 33 |
| Pain education | ||||||||||
| No | 9 | 47 | 10 | 53 | 19 | 24 | 71 | 10 | 29 | 34 |
| Yes | 103 | 58 | 74 | 42 | 177 | 144 | 61 | 91 | 39 | 235 |
| Duration of pain | ||||||||||
| <1 year | 7 | 50 | 7 | 50 | 14 | 8 | 42 | 11 | 58 | 19 |
| >1 year | 105 | 58 | 77 | 42 | 182 | 160 | 64 | 90 | 36 | 250 |
| Change in self-management of pain | ||||||||||
| No | 41 | 56 | 32 | 44 | 73 | 84 | 74 | 29 | 26 | 113 |
| Yes | 71 | 58 | 52 | 42 | 123 | 84 | 54 | 72 | 46 | 156 |
| Change in pain cognition | ||||||||||
| No | 46 | 59 | 32 | 41 | 78 | 72 | 72 | 28 | 28 | 100 |
| Yes | 66 | 56 | 52 | 44 | 118 | 96 | 57 | 73 | 43 | 169 |
3.1 Patient expected recovery
Table 2a shows the unadjusted and adjusted ORs obtained from univariate and multinomial logistic regression analysis stratified into two age groups, including the best predictors of expected recovery. Those who observed a change in pain cognition as a result of pain education were more likely to expect to recover than those who reported no change in pain cognitions as a result (unadjusted OR=2.06; 95% CI=1.34–3.16). Males were more likely than females to expect to recover (unadjusted OR=2.04; 95% CI=1.21–3.66). Adjusted ORs were similar (Table 2a).
Unadjusted and adjusted odds ratios for patient reported recovery among individuals who observed changes to pain cognition following pain education.
| Patient-reported recovery (category “recovery”) |
||||
|---|---|---|---|---|
| Unadjusted |
Adjusted |
|||
| OR (95% CI) | p-Value | OR (95% CI) | p-Value | |
| Age | ||||
| 18–40 years | 1 | 1 | ||
| +41 years | 0.66 (0.47–1.04) | 0.08 | 0.65 (0.42–1.03) | 0.06 |
| Gender | ||||
| Female | 1 | 1 | ||
| Male | 2.04 (1.21–3.66) | 0.00 | 2.04 (1.15–3.62) | 0.01 |
| Marital status | ||||
| Single/unmarried | 0.74 (0.47–1.16) | 0.20 | 0.72 (0.44–1.16) | 0.18 |
| Partnered | 0.92 (0.54–1.56) | 0.76 | 0.85 (0.48–1.51) | 0.59 |
| Education level | ||||
| Primary | 1 | 1 | ||
| Others | 1.22 (0.73–2.03) | 0.43 | 1.21 (0.71–2.05) | 0.47 |
| Employment status | ||||
| Full time employed | 1 | 1 | ||
| Unemployed/leave because of pain | 0.99 (0.59–1.67) | 0.99 | 0.99 (0.57–1.71) | 0.99 |
| Part time employed | 0.98 (0.56–1.74) | 0.97 | 0.92 (0.51–1.66) | 0.79 |
| Home duties | 0.83 (0.39–1.73) | 0.62 | 0.99 (0.45–2.17) | 0.98 |
| Student | 1.27 (0.65–2.48) | 0.46 | 1.30 (0.65–2.61) | 0.45 |
| Change in pain cognition | ||||
| Yes | 2.06 (1.34–3.16) | 0.00 | 2.11 (1.35–3.29) | 0.00 |
Ninety-seven percent (97%) of those who had participated in pain education reported observing a change in their self-management strategies as a result. Those who observed a change in self-management strategies were more likely to expect to recover than those who did not observe a change (unadjusted OR=2.06; 95% CI, 1.34–3.16) (Table 2b).
Unadjusted and adjusted odds ratios for patient reported recovery among individuals who observed changes to self-management of pain following pain education.
| Patient-reported recovery (“recover”) |
||||
|---|---|---|---|---|
| Unadjusted |
Adjusted |
|||
| OR (95% CI) | p-Value | OR (95% CI) | p-Value | |
| Age | ||||
| 18–40 years | 1 | 1 | ||
| +41 years | 0.70 (0.47–1.04) | 0.08 | 0.69 (0.45–1.08) | 0.10 |
| Gender | ||||
| Female | 1 | 1 | ||
| Male | 2.11 (1.21–3.66) | 0.00 | 2.24 (1.26–3.99) | 0.00 |
| Marital status | ||||
| Single/unmarried | 0.74 (0.47–1.16) | 0.20 | 0.71 (0.44–1.15) | 0.17 |
| Partnered | 0.92 (0.54–1.56) | 0.76 | 0.84 (0.47–1.48) | 0.56 |
| Education level | ||||
| Primary | 1 | 1 | ||
| Others | 1.22 (0.73–2.03) | 0.43 | 1.21 (0.71–2.05) | 0.47 |
| Employment status | ||||
| Full time employed | 1 | 1 | ||
| Unemployed/leave because of pain | 0.99 (0.59–1.67) | 0.99 | 1.05 (0.61–1.80) | 0.85 |
| Part time employed | 0.98 (0.56–1.74) | 0.97 | 1.03 (0.57–1.84) | 0.91 |
| Home duties | 0.83 (0.39–1.73) | 0.62 | 0.94 (0.43–2.06) | 0.88 |
| Student | 1.27 (0.65–2.48) | 0.46 | 1.33 (0.66–2.67) | 0.41 |
| Change in self-management of pain | ||||
| Yes | 2.06 (1.34–3.16) | 0.00 | 2.00 (1.30–3.08) | 0.00 |
Table 3 shows a more comprehensive account of the univariate logistic regression analysis stratified by age (18–40 years; 41+ years). Younger participants were more likely to expect recovery (~37%=72/196) than older participants (~30%=80/269). Being married, or having attained a higher level of formal education, were associated with expecting to recover.
Patient-reported recovery according to age among participants with chronic pain aged 18 years and above.
| Variable | Age 18–40 years |
Total | Age 41+years |
Total | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| PRR (no) |
PRR (yes) |
PPR (no) |
PRR (yes) |
|||||||
| No | % | No | % | No | % | No | % | |||
| Sexa | ||||||||||
| Female | 110 | 65 | 60 | 35 | 170 | 170 | 73 | 63 | 27 | 233 |
| Male | 14 | 54 | 12 | 46 | 26 | 18 | 51 | 17 | 49 | 35 |
| Educationa | ||||||||||
| Primary | 25 | 58 | 18 | 42 | 43 | 41 | 82 | 9 | 18 | 50 |
| Others | 99 | 65 | 54 | 35 | 153 | 147 | 68 | 70 | 32 | 217 |
| Employment statusa | ||||||||||
| Full time employed | 44 | 71 | 18 | 29 | 62 | 47 | 64 | 27 | 36 | 74 |
| Unemployed/on leave because of pain | 25 | 56 | 20 | 44 | 45 | 60 | 74 | 21 | 26 | 81 |
| Part time employed | 21 | 55 | 17 | 45 | 38 | 41 | 75 | 14 | 25 | 54 |
| Home duties | 6 | 75 | 2 | 25 | 8 | 26 | 68 | 12 | 32 | 38 |
| Student/unemployed | 25 | 63 | 15 | 38 | 40 | 8 | 62 | 5 | 38 | 13 |
| Marital statusa | ||||||||||
| Married | 39 | 60 | 26 | 40 | 65 | 100 | 66 | 51 | 34 | 151 |
| Single/unmarried | 47 | 63 | 28 | 37 | 75 | 65 | 80 | 16 | 20 | 81 |
| Partnered | 37 | 67 | 18 | 33 | 55 | 22 | 67 | 11 | 33 | 33 |
| Pain education | ||||||||||
| No | 14 | 74 | 5 | 26 | 19 | 22 | 65 | 12 | 35 | 34 |
| Yes | 110 | 62 | 67 | 38 | 177 | 167 | 71 | 68 | 29 | 235 |
| Patient-provider relationship | ||||||||||
| Not good | 48 | 64 | 27 | 36 | 75 | 76 | 71 | 31 | 29 | 107 |
| Good | 76 | 63 | 45 | 37 | 121 | 113 | 65 | 49 | 35 | 162 |
| Duration of pain | ||||||||||
| <1 year | 4 | 29 | 10 | 71 | 14 | 2 | 11 | 17 | 89 | 19 |
| >1 year | 120 | 66 | 62 | 34 | 182 | 187 | 75 | 63 | 25 | 250 |
| Change in pain management | ||||||||||
| No | 54 | 74 | 19 | 26 | 73 | 86 | 76 | 27 | 24 | 113 |
| Yes | 70 | 57 | 53 | 43 | 123 | 103 | 66 | 53 | 34 | 156 |
| Change in pain cognition | ||||||||||
| No | 58 | 74 | 20 | 26 | 78 | 78 | 78 | 22 | 22 | 100 |
| Yes | 66 | 56 | 52 | 44 | 118 | 111 | 66 | 58 | 34 | 169 |
-
aUnknown category totals not shown based on ≤5 cases; PRR=patient-provider relationship.
3.2 Primary outcome: current pain intensity
Table 4a shows the unadjusted and adjusted ORs obtained from univariate and multinomial logistic regression analysis stratified into two age groups, including the best predictors of perceived pain intensity. Subgroup analysis of participants who observed change in pain cognition as a result of pain education showed lower pain intensity scores 5.7 (2) than those who reported no change.
Unadjusted and adjusted odds ratios for pain intensity among individuals who observed changes to pain cognition following pain education.
| Pain intensity |
||||
|---|---|---|---|---|
| Unadjusted |
Adjusted |
|||
| OR (95% CI) | p-Value | OR (95% CI) | p-Value | |
| Age | ||||
| 18–40 years | 1 | 1 | ||
| +41 years | 0.84 (0.57–1.23) | 0.38 | 0.90 (0.58–1.38) | 0.63 |
| Gender | ||||
| Male | 1.69 (0.98–2.92) | 0.05 | 2.02 (1.12–3.61) | 0.01 |
| Female | 1 | 1 | ||
| Marital status | ||||
| Married | 1 | 1 | ||
| Single/unmarried | 0.68 (0.44–1.05) | 0.08 | 0.73 (0.46–1.17) | 0.19 |
| Partnered | 0.87 (0.52–1.44) | 0.59 | 0.84 (0.48–1.46) | 0.55 |
| Education level | ||||
| Primary | 1 | 1 | ||
| Others | 1.09 (0.67–1.76) | 0.70 | 0.93 (0.56–1.55) | 0.80 |
| Employment status | ||||
| Full time employment | 1 | 1 | ||
| Unemployed/leave because of pain | 0.50 (0.29–0.85) | 0.01 | 0.47 (0.27–0.82) | 0.00 |
| Part time employed | 1.81 (1.06–3.11) | 0.02 | 1.78 (1.02–3.10) | 0.04 |
| Home duties | 1.11 (0.56–2.21) | 0.75 | 1.17 (0.56–2.41) | 0.67 |
| Student | 1.78 (0.93–3.40) | 0.07 | 1.95 (0.99–3.81) | 0.05 |
| Change in pain cognition | ||||
| Yes | 1.53 (1.03–2.27) | 0.03 | 1.53 (1.01–2.33) | 0.04 |
Individuals who reported observing a change in self-management strategies as a result of pain education (subgroup analysis) reported less pain intensity 5.6 (2) than/as those who reported no change. Adjusted OR for participants who observed change in their pain cognition as a result of pain education was 1.53 (95% CI, 1.01–2.33) (Table 4a). The adjusted association between pain intensity and observed change in self-management of pain increased (adjusted OR, 1.69; CI, 1.12–2.56), suggesting that participants who observed change in self-management of pain following pain education were more likely to report less pain than participants who observed no change in their self-management of pain. Pain intensity was also affected by sex, age, duration of pain, employment status especially home duties, which may be attributed to higher female participation. The full regression data shown in Table 4b.
Unadjusted and adjusted odds ratios for pain intensity among individuals who observed changes to self-management of pain following pain education.
| Pain intensity |
||||
|---|---|---|---|---|
| Unadjusted |
Adjusted |
|||
| OR (95% CI) | p-Value | OR (95% CI) | p-Value | |
| Age | ||||
| 18–40 years | 1 | 1 | ||
| +41 years | 0.84 (0.57–1.23) | 0.38 | 0.93 (0.60–1.43) | 0.74 |
| Gender | ||||
| Male | 1.69 (0.98–2.92) | 0.05 | 2.17 (1.21–3.89) | 0.00 |
| Female | 1 | 1 | ||
| Marital status | ||||
| Married | 1 | 1 | ||
| Single/unmarried | 0.68 (0.44–1.05) | 0.08 | 0.73 (0.45–1.16) | 0.18 |
| Partnered | 0.87 (0.52–1.44) | 0.59 | 0.83 (0.48–1.45) | 0.53 |
| Education level | ||||
| Primary | 1 | 1 | ||
| Others | 1.09 (0.67–1.76) | 0.70 | 0.93 (0.55–1.55) | 0.79 |
| Employment status | ||||
| Full time employment | 1 | 1 | ||
| Unemployed/leave because of pain | 0.50 (0.29–0.85) | 0.01 | 0.48 (0.28–0.84) | 0.01 |
| Part time employed | 1.81 (1.06–3.11) | 0.02 | 1.89 (1.09–3.28) | 0.02 |
| Home duties | 1.11 (0.56–2.21) | 0.75 | 1.13 (0.54–2.34) | 0.73 |
| Student | 1.78 (0.93–3.40) | 0.07 | 2.00 (1.02–3.92) | 0.04 |
| Change in self-management of pain | ||||
| Yes | 1.53 (1.03–2.27) | 0.03 | 1.69 (1.12–2.56) | 0.01 |
4 Discussion
The aim of this study was to determine if participants believed that pain education had changed their views on their pain (pain cognition) and had changed the way they self-managed their pain. We also wanted to determine whether or not these perceptions were associated with their expectations of recovery and their perceived pain intensity. Our main finding is that those who report a shift in their pain cognition or self-management strategies after participating in pain education have lower perceived pain and higher expectations of recovery than those who do not observe these shifts. Pain intensity and expected recovery are also affected by a range of demographic and other variables, but accounting for those variables in the statistical model does not conceal the effect.
Expectations about recovery are often investigated in acute or subacute pain populations [24], [25], and in pre-surgical groups [26], [27], but not in chronic pain patients. Our findings are consistent with available literature insofar as younger participants have higher expectations of recovery than older ones. This may be because older people are more likely to suffer from multiple chronic conditions [28] and, arguably, may have lower self-efficacy when it comes to exercise and movement-based rehabilitation. In addition, home duties affected changes in self-management of pain, which may also contribute to the male/female differences.
It is notable that 40% of those who had participated in pain education reported that it did not change their pain cognition or self-management strategies. This rather concerning failure rate might reflect, in part, patients who already have a contemporary understanding of pain when they present for care, although the available data would suggest otherwise [11]. It might also be more likely to reflect the lack of information on variables that can influence any educational intervention, for example the message, the context and number of sessions, which were not collected.
Of the confounding variables, we identified a priori and entered into the statistical models, marital status, education level and employment status showed no association with “recovery”. This is in line with the literature, which shows similar findings [29].
4.1 Limitations
This was a pragmatic study, in which data were collected from individuals experiencing chronic pain in the real-world, designed to answer specific questions; we did not seek to fully characterize the subtle relationships between different variables and we did not seek to determine the impact of other important variables – for example the number, type and context of education sessions, type of diagnosis, comorbidities and treatments received. To investigate these issues would have required a much larger sample and would have exerted a participant burden that pilot testing taught us would be unacceptable. Any online survey is associated with a lack of control over who participates and how they participate. People self-select and we have no way of verifying the authenticity of responses, clarifying their responses, or preventing individuals completing the survey twice on different devices. Our approach will also have excluded potential participants who have no internet access. Our recruitment strategy depended on circulation of the survey link via consumer organizations and clinician followers of professional development websites. This means that we would not have recruited those patients not involved with such organizations or with clinicians who are engaged with the professional development websites we used. Considering that many people with persistent pain do not fully engage with the community, the reader must consider the limited extent to which our sample was representative of the persistent pain population. Our design does not allow causal conclusions about effects of one variable on another, nor the time course of effects. The current study also had strengths. For example, our survey design was consistent with recommended protocols; we published the full survey protocol prior to data collection; we identified important potential confounders a priori and controlled for them in our analysis; we calculated required sample size prior to commencement and our sample exceeded the required sample size; the distribution of our independent and confounder variables was broadly reflective of the wider population, reducing the risk of selection bias on these variables.
5 Conclusions
Findings, from this patient-reported, internet survey suggest that pain education induced change in pain cognition and self-management of pain can influence pain intensity and recovery in chronic pain patients. These findings are important as several studies [30], [31], [32] have documented that although pain education helps to alter patients’ knowledge about pain this effect can be lost over time, producing no long-term benefits [33] and repetition of pain education session [34] may allow consolidation of the information. Our study findings show that patients reporting change in both their pain cognition and self-management of pain on receiving pain education were more likely to report not only lower pain intensity scores but were also more likely to have an optimistic view about recovery. These findings are pertinent for future practice and research, as they give a new direction for employing pain education. Future strategies should be directed towards enhancing cognizance and management of pain at an individual level. One limitation of this study is the responses are patient-perceived hence could be affected by measurement/misclassification error which is not taken into consideration for the analysis, it is for this reason the results must be interpreted cautiously.
Acknowledgements
The authors would like to thank all the individuals who participated in our study and the organizations and societies who promoted our survey on their websites.
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Authors’ statements
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Research funding: M. N. Mittinty is funded by John Lynch’s NHMRC Australian Fellow funding (ID 478115). G. L. Moseley has received support from Pfizer, Kaiser Permanente, USA; Workers’ Compensation Boards in Australia, North America, and Europe; Agile Physiotherapy, USA; Results Physiotherapy, USA; the International Olympic Committee and the Port Adelaide Football Club, Australia. G. L. Moseley is supported by a Principal Research Fellowship from the National Health and Medical Research Council of Australia.
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Conflict of interest: G. L. Moseley receives royalties for books on pain and rehabilitation, including two books that are cited in this article. He receives speaker fees for lectures on pain and rehabilitation. All the authors declare that they have no conflict of interest.
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Informed consent: Informed consent was required and collected digitally from all participants.
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Ethical approval: The study was approved by the Human Research Ethics Committee, The University of Adelaide, and University of South Australia, Australia.
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