Abstract
Background:
Given the influence of psychosocial factors on musculoskeletal symptoms and limitations, this study assessed if the ability of resilience (an individual's ability to adapt under stress) mediates the association of psychological adaptability with magnitude of physical limitations and pain intensity during recovery from an upper extremity injury.
Methods:
A total of 107 patients were enrolled in this prospective, longitudinal, observational cohort study. Patients completed the Patient-Reported Outcomes Measurement Information System Physical Function (PROMIS PF), an 11-point ordinal measure of pain intensity, the Brief Resilience Scale (BRS), and the Psychological Adaptation Scale (PAS). We used structural equation modeling to assess the mediation effect by resiliency and psychological adaptability on patient-reported disability and pain at initial assessment and after three months.
Results:
PAS and BRS were not independently associated with PROMIS PF or pain intensity at enrollment or after three months, so it was not possible to assess if resiliency mediated the association of psychological adaptability with physical function or pain. There were no factors independently associated with resilience.
Conclusion:
General measures of psychological adaptability and resiliency do not correlate with symptoms and limitations as well as specific measures of adaptiveness in response to nociception.
Key Words: Resilience, Brief Resilience Scale, Psychological Adaptation Scale, Structural Equation Modeling, Mediation Analysis
Introduction
Pain intensity and magnitude of limitations after upper extremity injury are related to pathophysiology (objective impairment), symptoms of depression and anxiety (psychological distress), and effectiveness of cognitive coping strategies (e.g. less catastrophic thinking and more self-efficacy) (1). Resilience refers to an individual's ability to adapt when facing adversity such as stress or trauma (2). It is considered a protective factor that can limit symptom intensity and magnitude of limitations over the short and long-term (3,4). Psychological adaptability is the dynamic and multidimensional process of coming to terms with the implications of a health threat and the outcome of that psychological process, also referred to as adjustment and acceptance (5). Because mental and social health have such a strong influence on musculoskeletal symptoms and limitations, psychological adaptability may be affected by (or effect) resilience in people recovering from injury.
This study assessed whether resilience mediates the association of psychological adaptability with magnitude of physical limitations (measured with Patient-Reported Outcomes Measurement Information System Physical Function: PROMIS PF) and pain intensity during recovery from an upper extremity injury. Second, we assessed factors independently associated with (1) resilience (measured with the Brief Resilience Scale: BRS), (2) physical limitations, and (3) pain intensity.
Methods
Study Design
After institutional review board approval, a total of 107 patients were enrolled in this prospective, longitudinal, observational cohort study. Enrollment took place intermittently over a 12-month period at five orthopaedic offices in a large urban area. All new English-speaking patients, aged 18 years old or older, with one or more traumatic injuries to the upper extremity, within two weeks of trauma, and who were able to provide informed consent were approached by research assistants after the visit with the surgeon to participate in this study. A waiver of written informed consent was granted. By completing the surveys patients indicated their informed consent. To assess the mediation effect by resiliency and psychological adaptability on the improvement effects of patient-reported outcomes after three months, a second survey was sent to participants three months after trauma by email. All questionnaires were completed using an encrypted tablet via a secure, HIPAA-compliant electronic platform: REDCap (Research Electronic Data Capture): a secure web-based application for building and managing online surveys and databases (6).
Measures
Diagnosis was recorded by the surgeon. Patients were asked to complete a set of questionnaires at enrollment (i.e. Time 1): (1) a demographic survey (including email for follow-up, age, sex, ethnicity, marital status, education, work status, presence of current psychological disorder, presence of another pain condition, use of opioids, history of orthopedic condition, and history of orthopedic surgery); (2) PROMIS PF, which is a computer adaptive test (CAT) is a measure of physical limitations (7–10). CAT uses item response theory, which customizes the subsequent question based on answers to the previous questions, resulting in a high level of precision through lesser questions (11). Higher scores reflect better physical function; (3) Pain intensity on an 11-point ordinal rating scale, with scores ranging from 0 “No pain at all” to 10 “Worst pain possible”(10); (4) BRS, which is a six-item scale to assess resilience, the ability to bounce back or recover from stress (4,10,12). A higher score represents greater resilience. The BRS consists of three positively worded statements and three negatively worded statements, with answers ranging from 1 “Strongly disagree” to 5 “Strongly agree”. It has a highly scored internal consistency, with Cronbach alpha scores ranging from 0.89-0.91; (5) and Psychological Adaptation Scale (PAS). PAS is a 20-item scale to assess adaptation to a chronic condition or disease risk (5,12). Answer possibilities range from 1 to 5 and the total score is the sum of all items. Higher scores reflect more adaptation. It is divided in four subscales assessing coping efficacy, self-esteem, social integration, and spiritual/existential well-being. After three months (i.e. Time 2) patients were asked to complete the second survey by email, consisting of PAS, PROMIS PF, and pain intensity.
Study Population
The survey was completed by 107 patients and after three months the follow-up survey by email was completed by 39 patients (36%). The mean age of patients was 46 16 years and 52 (49%) were men [Table 1]. The most frequent reported diagnoses were distal radius fractures (12%), metacarpal fractures (12%), and finger fractures (11%) [Appendix 1]. Responders differed from non-responders on bivariate analysis [Table 2]. Multivariable analysis for variables with P <0.10 on bivariate analysis showed that a marital status of divorced/widowed (odds ratio [OR] 0.19; 95% CI 0.04 to 0.97; P=0.045) and a better PROMIS PF score (OR 0.95; 95% CI 0.91 to 1.0; P=0.041) were independently associated with loss to follow-up after three months [Appendix 2].
Table 1.
Patient and clinical characteristics and comparison between available and lost to follow-up
| Variables | TotalN=107 | Lost to follow-upN=68 | Available for follow-upN=39 | P value |
|---|---|---|---|---|
| Time 1 | ||||
| Age in years | 46 ± 16 (20-83) | 44 ± 15 (20-83) | 51 ± 15 (23-78) | 0.024 |
| Men | 52 (49) | 37 (54) | 15 (38) | 0.159 |
| Race/Ethnicity | ||||
| White | 85 (79) | 51 (75) | 34 (87) | 0.213 |
| Other | 22 (21) | 17 (25) | 5 (13) | |
| Marital status | ||||
| Married/Unmarried couple | 59 (55) | 31 (46) | 28 (72) | 0.034 |
| Single | 33 (31) | 26 (38) | 7 (18) | |
| Divorced/Widowed | 15 (14) | 11 (16) | 4 (10) | |
| Level of education | ||||
| High school or less | 24 (22) | 18 (26) | 6 (15) | 0.528 |
| 2-year college | 21 (20) | 14 (21) | 7 (18) | |
| 4-year college | 37 (35) | 21 (31) | 16 (41) | |
| Post-college graduate degree | 25 (23) | 15 (22) | 10 (26) | |
| Work status | ||||
| Employed | 77 (72) | 52 (77) | 25 (64) | 0,253 |
| Retired | 15 (14) | 7 (10) | 8 (21) | |
| Other (unemployed, homemaker, etc.) | 15 (14) | 9 (13) | 6 (15) | |
| BRS | 3.8 ± 0.75 (1.7-5) | 3.9 ± 0.76 (2.2-5) | 3.6 ± 0.71 (1.7-5) | 0.126 |
| PAS | 56 ± 22 (20-100) | 57 ± 23 (20-100) | 53 ± 20 (20-88) | 0.300 |
| Pain | 4.3 ± 2.4 (0-9) | 4.2 ± 2.3 (0-9) | 4.6 ± 2.5 (0-9) | 0.474 |
| PROMIS PF | 46 ± 10 (24-73) | 47 ± 11 (25-73) | 43 ± 9.6 (24-61) | 0.047 |
| Current psychological disorder | 19 (18) | 11 (16) | 8 (21) | 0.606 |
| N = 99 | N = 64 | N = 35 | ||
| Current other pain condition | 14 (14) | 5 (7.8) | 9 (26) | 0.031 |
| Current use of opioids | 11 (11) | 8 (13) | 3 (8.6) | 0.742 |
| Previous orthopaedic condition | 40 (40) | 21 (33) | 19 (54) | 0.054 |
| Previous orthopaedic surgery | 38 (38) | 23 (36) | 15 (43) | 0.523 |
| Time 2 | N = 33 | |||
| PAS | 50 ± 21 (20-100) | - | - | - |
| N = 39 | ||||
| Pain | 2.0 ± 2.0 (0-8) | - | - | - |
| PROMIS PF | 52 ± 9.7 (28-73) | - | - | - |
Bold indicates statistically significant difference; Continuous variables as mean ± standard deviation (range); Discrete variables as number (percentage); BRS=Brief Resilience Scale; PAS=Psychological Adaptation Scale; PROMIS PF=Patient-Reported Outcomes Measurement Information System Physical Function.
Table 4.
Mediation analyses of resiliency in the relationship between psychological adaptibility and PROMIS PF and pain at baseline and 3 months
| Dependentvariable | Sample size | Mediator variable | Independent variable | Confounding variables | Effect | Regression coefficient [β] (95% Confidence interval) | Standard error | P value | Proportion total effect mediated |
|---|---|---|---|---|---|---|---|---|---|
| PROMIS PFat baseline | 99 | BRS | PAS | Current psychological disorderCurrent use of opioids | Total effect PAS | -0.02 (-0.11 to 0.07) | 0.05 | 0,656 | 0.89 |
| Total effect psychological disorder | -9.1 (-15 to -2.9) | 3.2 | 0.004 | ||||||
| Total effect use of opioids | -8.3 (-14 to -2.2) | 3.2 | 0.008 | ||||||
| Direct effect PAS | -0.00 (-0.09 to 0.09) | 0.05 | 0.962 | ||||||
| Indirect effect through BRS | -0.02 (-0.04 to 0.01) | 0.01 | 0.172 | ||||||
| PROMIS PFafter 3 months | 39 | BRS | PAS | - | Total effect PAS | 0.03 (-0.12 to 0.18) | 0.08 | 0.690 | 0.03 |
| Direct effect PAS | 0.03 (-12 to 0.18) | 0.08 | 0.703 | ||||||
| Indirect effect through BRS | 0.00 (-0.02 to 0.02) | 0.01 | 0.931 | ||||||
| Painat baseline | 107 | BRS | PAS | MenWhite race | Total effect PAS | 0.01 (-0.01 to 0.03) | 0.01 | 0,549 | 0.37 |
| Total effect men | -0.90 (-1.8 to -0.04) | 0.44 | 0.041 | ||||||
| Total effect white race | -1.2 (-2.3 to -0.10) | 0.56 | 0.033 | ||||||
| Direct effect PAS | 0.00 (-0.02 to 0.02) | 0.01 | 0.704 | ||||||
| Indirect effect through BRS | 0.00 (-0.00 to 0.01) | 0.00 | 0.284 | ||||||
| Painafter 3 months | 39 | BRS | PAS | White race | Total effect PAS | 0.02 (-0.01 to 0.05) | 0.01 | 0.165 | 0.14 |
| Total effect white race | -2.4 (-4.0 to -0.74) | 0.83 | 0.004 | ||||||
| Direct effect PAS | 0.02 (-0.01 to 0.04) | 0.01 | 0.234 | ||||||
| Indirect effect through BRS | 0.00 (-0.00 to 0.01) | 0.00 | 0.449 |
Bold indicates statistically significant difference; BRS=Brief Resilience Scale; PAS=Psychological Adaptation Scale; PROMIS PF=Patient-Reported Outcomes Measurement Information System Physical Function.
Appendix A.
Diagnoses and frequencies
| Diagnoses, N=107 | Frequency |
| Distal Radius Fracture | 13 (12) |
| Metacarpal fracture | 13 (12) |
| Finger fracture | 12 (11) |
| Finger Sprain | 5 (4.7) |
| Nonspecific arm pain | 4 (3.8) |
| Wrist fracture | 4 (3.8) |
| Finger Laceration | 3 (2.8) |
| Finger Osteoarthritis | 3 (2.8) |
| Mallet Finger | 3 (2.8) |
| Wrist Sprain | 3 (2.8) |
| Elbow fracture | 2 (1.9) |
| Finger Tendon Tear | 2 (1.9) |
| Hand Sprain | 2 (1.9) |
| Proximal radius fracture | 2 (1.9) |
| Trigger Finger | 2 (1.9) |
| Wrist Pain | 2 (1.9) |
| Arm pain | 2 (1.9) |
| Biceps tendon tear | 2 (1.9) |
| Biceps tendinitis | 1 (0.93) |
| Bursitis and infection olecranon | 1 (0.93) |
| Carpal Tunnel Syndrome | 1 (0.93) |
| Carpal Tunnel Syndrome and Ganglion Cyst | 1 (0.93) |
| Clavicle fracture | 1 (0.93) |
| De Quervain Tenosynovitis | 1 (0.93) |
| Distal Phalanx Fracture | 1 (0.93) |
| Elbow dislocation | 1 (0.93) |
| Elbow Sprain | 1 (0.93) |
| Finger flexon tendon rupture | 1 (0.93) |
| Finger injury unspecified | 1 (0.93) |
| Finger nailbed tear | 1 (0.93) |
| Fracture unspecified | 1 (0.93) |
| Gamekeepers thumb | 1 (0.93) |
| Hand laceration | 1 (0.93) |
| Humerus fracture | 1 (0.93) |
| Mallet Finger and Trigger Thumb | 1 (0.93) |
| Medial Epicondylitis | 1 (0.93) |
| Medial Epicondylitis and Cubital Tunnel Syndrome | 1 (0.93) |
| Pectoral muscle tear | 1 (0.93) |
| Proximal phalanx fracture | 1 (0.93) |
| Proximal ulnar fracture | 1 (0.93) |
| Radius fracture | 1 (0.93) |
| Rotator Cuff Injury | 1 (0.93) |
| Scapholunate ligament injury | 1 (0.93) |
| Shoulder dislocation | 1 (0.93) |
| Ulnar Fracture | 1 (0.93) |
| Wrist sprain and Finger Fracture | 1 (0.93) |
| Discrete variables as number (percentage). | |
Statistical Analysis
Continuous data were reported with mean, standard deviation (SD), and ranges.
Categorical data are presented as frequencies and percentages. Using structural equation modeling (SEM), we created four mediation models to assess the mediation effect by resiliency and psychological adaptability on patient reported disability and pain at initial assessment and after three months [Figure 1]. These models reveal a total -, direct -, and indirect effect of mediator (and other independent) variables on the dependent variable. To select confounding variables for our final mediation model, we first selected confounding variables with P <0.10 on bivariate analysis [Table 2] in a multivariable model. Consecutively, we selected confounding variables with P <0.05 on multivariable analysis [Table 3] in our mediation model [Table 4]. Adjusted R2 indicates how much variability in the outcome variable the model accounts for. The proportion total effect mediated in the mediation table shows the proportion of the total effect (resiliency and adaptability combined) that is mediated through resilience. We considered P <0.05 significant.
Figure1.
Indirect effect (mediation)=path A x path B (mediation model hypothesis). Total effect=direct effect (path C)+indirect effect
| Variables | PROMIS PFBaseline | P value | PROMIS PF 3 months | P value | PainBaseline | P value | Pain3 months | P value | BRSBaseline | P value |
| Age (r) | -0.15 | 0.127 | -0.28 | 0.088 | -0.14 | 0.149 | 0.06 | 0.740 | 0.12 | 0.231 |
| Sex | ||||||||||
| Women | 45 ± 10 | 0.423 | 49 ± 9.7 | 0.037 | 4.8 ± 2.5 | 0.061 | 2.2 ± 1.8 | 0.358 | 3.8 ± 0.78 | 0.997 |
| Men | 47 ± 11 | 56 ± 8.3 | 3.9 ± 2.2 | 1.6 ± 2.3 | 3.8 ± 0.72 | |||||
| Race/Ethnicity | ||||||||||
| White | 46 ± 11 | 0.801 | 52 ± 9.8 | 0.170 | 4.1 ± 2.2 | 0.031 | 1.6 ± 1.6 | 0.005 | 3.8 ± 0.73 | 0.042 |
| Other | 45 ± 8.9 | 46 ± 7.4 | 5.3 ± 2.7 | 4.2 ± 2.9 | 3.5 ± 0.77 | |||||
| Marital status | ||||||||||
| Married/Unmarried couple | 47 ± 10 | 0.576 | 52 ± 9.1 | 0.575 | 4.4 ± 2.4 | 0.873 | 2.3 ± 2.0 | 0.217 | 3.9 ± 0.69 | 0.212 |
| Single | 45 ± 10 | 54 ± 12 | 4.5 ± 2.4 | 1.0 ± 1.8 | 3.6 ± 0.78 | |||||
| Divorced/Widowed | 45 ± 13 | 47 ± 10 | 4.1 ± 2.5 | 1.3 ± 1.5 | 3.7 ± 0.87 | |||||
| Level of education | ||||||||||
| High school | 44 ± 10 | 0.781 | 52 ± 5.0 | 0.235 | 4.5 ± 2.5 | 0.179 | 2.5 ± 2.2 | 0.834 | 3.7 ± 0.81 | 0.376 |
| 2-year college | 47 ± 8.7 | 53 ± 7.4 | 4.0 ± 3.1 | 1.9 ± 1.9 | 3.6 ± 0.91 | |||||
| 4-year college | 46 ± 10 | 54 ± 8.1 | 4.9 ± 2.2 | 1.7 ± 1.5 | 3.8 ± 0.72 | |||||
| Post-college graduate degree | 46 ± 13 | 46 ± 14 | 3.6 ± 1.7 | 2.2 ± 2.7 | 4.0 ± 0.55 | |||||
| Work status | ||||||||||
| Employed | 47 ± 10 | 0,153 | 52 ± 9.6 | 0,605 | 4.5 ± 2.2 | 0,364 | 2.2 ± 2.2 | 0,393 | 3.7 ± 0.74 | 0,712 |
| Retired | 41 ± 10 | 49 ± 6.3 | 3.5 ± 2.8 | 1.1 ± 1.1 | 3.9 ± 0.75 | |||||
| Other (unemployed, homemaker, etc.) | 45 ± 11 | 54 ± 14 | 4.5 ± 2.6 | 2.0 ± 2.0 | 3.7 ± 0.85 | |||||
| Current psychological disorder | ||||||||||
| No | 47 ± 10 | 0.038 | 52 ± 9.4 | 0.271 | 4.3 ± 2.4 | 0.797 | 2.3 ± 2.1 | 0.078 | 3.8 ± 0.70 | 0.172 |
| Yes | 41 ± 9.5 | 48 ± 10 | 4.5 ± 2.5 | 0.88 ± 0.83 | 3.6 ± 0.93 | |||||
| Current other pain condition | ||||||||||
| No | 47 ± 10 | 0.058 | 53 ± 10 | 0.086 | 4.4 ± 2.4 | 0.940 | 2.2 ± 2.2 | 0.809 | 3.8 ± 0.72 | 0.812 |
| Yes | 41 ± 11 | 46 ± 7.3 | 4.4 ± 2.6 | 2.0 ± 1.5 | 3.8 ± 0.85 | |||||
| Current use of opioids | ||||||||||
| No | 47 ± 9.5 | 0.007 | 51 ± 9.0 | 0.919 | 4.3 ± 2.3 | 0.243 | 2.3 ± 2.0 | 0.312 | 3.8 ± 0.74 | 0.841 |
| Yes | 38 ± 15 | 50 ± 21 | 5.2 ± 3.0 | 1.0 ± 1.7 | 3.8 ± 0.67 | |||||
| Previous orthopaedic condtion | ||||||||||
| No | 46 ± 11 | 0.662 | 51 ± 9.3 | 0.983 | 4.3 ± 2.3 | 0.572 | 1.5 ± 1.2 | 0.083 | 3.8 ± 0.77 | 0.513 |
| Yes | 45 ± 10 | 51 ± 11 | 4.6 ± 2.5 | 2.7 ± 2.4 | 3.9 ± 0.67 | |||||
| Previous orthopaedic surgery | ||||||||||
| No | 46 ± 10 | 0.918 | 50 ± 11 | 0.682 | 4.5 ± 2.4 | 0.572 | 1.9 ± 1.6 | 0.419 | 3.7 ± 0.77 | 0.466 |
| Yes | 46 ± 11 | 52 ± 8.9 | 4.2 ± 2.5 | 2.5 ± 2.5 | 3.9 ± 0.68 | |||||
| BRS Time 1 ( r ) | 0.14 | 0.155 | -0.02 | 0.888 | -0.19 | 0.043 | -0.05 | 0.775 | - | - |
| PAS Time 1 ( r ) | -0.02 | 0.809 | 0.06 | 0.700 | 0.13 | 0.198 | 0.26 | 0.109 | -0.18 | 0.062 |
| Pain Time 1 ( r ) | -0.33 | 0.001 | -0.08 | 0.615 | - | - | 0.52 | 0.001 | -0.20 | 0.043 |
| PROMIS PF Time 1 ( r ) | - | - | 0.65 | <0.001 | -0.33 | 0.001 | -0.22 | 0.185 | 0.14 | 0.155 |
Bold indicates statistically significant difference; Pearson correlation indicated by r; Continuous variables as mean ± standard deviation (range), unless otherwise indicated; Discrete variables as number (percentage); ¹=Only 1 value; BRS=Brief Resilience Scale; PAS=Psychological Adaptation Scale; PROMIS PF=Patient-Reported Outcomes Measurement Information System Physical Function.
Table 3.
Multivariable linear regression of factors associated with PROMIS PF and Pain at baseline and 3 months, and with BRS at baseline
| Dependentvariables | Retained variables | Regression coefficient [β](95% Confidence interval) | Standarderror | P value | SemipartialR-squared (R²) | Adjusted R² |
|---|---|---|---|---|---|---|
| PROMIS PFTime 1 | Current psychological disorder | -7.8 (-14 to -1.4) | 3.2 | 0.018 | 0.05 | 0.14 |
| Current other pain condition | -2.7 (-8.7 to 3.2) | 3.0 | 0.364 | |||
| Current use of opioids | -7.8 (-14 to -1.4) | 3,2 | 0.017 | 0.05 | ||
| BRS | 2.3 (-0.38 to 5.0) | 1.4 | 0.091 | |||
| PROMIS PFTime 2 | Age | -0.09 (-0.32 to 0.15) | 0.12 | 0.455 | 0.10 | |
| Men | 5.3 (-2.0 to 13) | 3.6 | 0.150 | |||
| Current other pain condition | -5.9 (-13 to 1.7) | 3.7 | 0.123 | |||
| BRS | 0.20 (-4.4 to 1.8) | 2,3 | 0.932 | |||
| PainTime 1 | Men | -0.91 (-1.8 to -0.04) | 0.44 | 0.041 | 0.04 | 0.08 |
| White race | -1.1 (-2.2 to -0.00) | 0,56 | 0.049 | 0.03 | ||
| BRS | -0.50 (-1.1 to 0.09) | 0.30 | 0.098 | |||
| PainTime 2 | White race | -2.7 (-4.6 to -0.77) | 0,95 | 0.008 | 0.19 | 0.20 |
| Current psychological disorder | -1.1 (-3.3 to 1.1) | 1.1 | 0.304 | |||
| Previous orthopaedic condtion | 0.57 (-0.84 to 2.0) | 0,69 | 0.416 | |||
| BRS | -0.68 (-1.6 to 0.24) | 0,45 | 0.142 | |||
| BRSTime 1 | White race | 0.30 (-0.07 to 0.66) | 0.18 | 0.107 | 0.04 | |
| PAS | -0.00 (-0.01 to 0.00) | 0.00 | 0.165 |
Bold indicates statistically significant difference; Only the semipartial R² of significant variables is displayed; BRS=Brief Resilience Scale; PAS=Psychological Adaptation Scale; PROMIS PF=Patient-Reported Outcomes Measurement Information System Physical Function.
Based on the Fritz and Mackinnon’s sample size stimulation study a minimum sample size of 71 was necessary to detect a medium effect size (0.13) with 0.80 power for inferring an indirect effect through mediation analysis (13). We enrolled 50% more patients (total of 107), to cover for measurement error inherent in psychosocial measures and loss to follow-up (14).
Results
PROMIS PF Mediation
PAS and BRS were not independently associated with PROMIS PF at enrollment or after three months [Table 2] so we did not perform mediation analysis.
Pain Intensity Mediation
PAS and BRS were not independently associated with pain intensity at enrollment or after three months [Table 2], so we did not perform mediation analysis.
Factors Associated with Resilience
Using multivariable linear regression, there were no factors independently associated with resilience (BRS)[Table 3].
Factors Associated with PROMIS PF
Patients with a diagnosed psychological disorder ( -7.8; 95% CI -14 to -1.4; P=0.018) and patients with current use of opioids ( -7.8; 95% CI -14 to -1.4; P=0.017) had worse physical function (lower PROMIS PF scores) at baseline, accounting for potential confounding using multivariable regression analysis [Table 3]. No factors were independently associated with PROMIS PF 3 months after enrollment.
Factors Associated with Pain Intensity
At baseline, men ( -0.91; 95% CI -1.8 to -0.04; P=0.041) and patients that self-described as white race ( -1.1; 95% CI -2.2 to 0.00; P=0.049), had lower pain intensity [Table 3]. White race was still independently associated after 3 months ( -2.7; 95% CI -4.6 to -0.77; P=0.008).
Discussion
Symptom intensity and physical limitations are affected by psychological distress and effectiveness of cognitive coping strategies in patients recovering from trauma (15). Resilience is the ability to adapt to stressful adverse events (16). The purpose of this study was to assess if greater resilience mediates the association of psychological adaptation with disability and pain. We found that resiliency, measured using the BRS, does not correlate with magnitude of limitations, and pain intensity in people with upper extremity injury, which made it impossible to study mediation.
The following limitations should be considered when interpreting our results. First, the sample size for the longitudinal part of the study is limited due to low participation rate 3 months after enrollment. Married patients, older patients, and patients with less physical limitations were more likely to participate at 3 months. Performing the second evaluation by phone instead of by email might have improved participation (17). Second, this study was conducted with English-fluent traumatic upper extremity trauma patients in one large urban area, limiting the external validity of this study, as well as the racial and socioeconomic diversity. Third, 19 patients (8.9%) did not answer questions about having another pain condition, previous orthopaedic surgery, a previous orthopaedic condition, or use of opioids. We used complete case analyses for our main study as these variables were not of main interest to the study. Additionally, we used mean imputation for the missing data and reran our multivariable models [Appendix 3]. The only difference we found was that having a current psychological disorder was not independently associated with PROMIS PF at baseline anymore. No further differences were found. Fourth, 10 patients (9.3%) were included because they presented with acute pain they believed was related to trauma, but were eventually diagnosed with a non-traumatic disease (misperception of etiology).
Appendix B.
Multivariable logistic regression analysis of factors associated with completing a follow-up assessment
| Dependent variable | Retained variables | Odds Ratio(95% Confidence interval) | Standarderror | P value | C statistic¹ |
|---|---|---|---|---|---|
| Completing follow-up assessment | Age in years | 1.0 (0.97 to 1.0) | 0.02 | 0.759 | 0,75 |
| Marital status | |||||
| Married/Unmarried couple | Reference value | ||||
| Single | 0.40 (0.11 to 1.4) | 0.26 | 0.156 | ||
| Divorced/Widowed | 0.19 (0.04 to 0.97) | 0.16 | 0.045 | ||
| PROMIS PF | 0.95 (0.91 to 1.0) | 0.02 | 0.041 | ||
| Current other pain condition | 3.2 (0.79 to 13) | 2.2 | 0.102 | ||
| Previous orthopaedic condition | 1.9 (0.71 to 5.1) | 0.95 | 0.205 | ||
Bold indicates statistically significant difference; ¹ The C statistic is a measure of model fit and is the area under the receiver operating characteristics curve.
We found that neither resilience nor psychological adaptability correlated with physical limitations or pain intensity in patients recovering from upper extremity trauma. This was an unexpected finding given the consistent association of measures of stress, distress, and less effective cognitive coping strategies with symptoms intensity and magnitude of limitations. For instance, greater self-efficacy is associated with less physical limitations in patients with elbow fractures and proximal humerus fractures (18,19). Our findings replicate those from a separate study, where neither measures of resilience nor psychological adaptability correlated with physical limitations nor pain intensity among people with non-traumatic upper extremity illness (20). The questions used to assess resilience ask about things such as recovering from stressful events or set-backs in life (12). People may have a tendency to identify with these statements, perhaps in an aspirational way, or thinking of themselves at their best (21). Consistent with the findings of the current study, Esteve et al. found that resilience was not associated with pain-related disability over time (22). In contrast, some studies have shown that resilience may be a protective factor for chronic pain (22–24). There are several measurements for resilience, for example the Connor-Davidson Resilience Scale (CD-RISC) or the Resilience Scale for Adults (RSA) (25,26). Neither the CD-RISC nor the RSA seem to assess the ability to adapt to painful disease. Using a scale that focuses on cognitions in response to nociception (e.g. catastrophic thinking, kinesiophobia, self-efficacy), may be preferred as it may get at one’s inner voice in the moment and better measures important resiliency factors specific to the illness.
We found that a concurrent, diagnosed mental health disorder is associated with less resilience. Resilient individuals often use emotion regulation strategies, replacing less adaptive thoughts with more adaptive thoughts (27). A person with greater symptoms of depression or anxiety may have difficulty replacing less adaptive thoughts. More limited symptoms of anxiety is associated with greater resiliency (28). We did not measure symptoms of depression or anxiety, which are likely to have a stronger association than a diagnosed mental disorder, which can be well-treated or even misapplied.
The finding that a concurrent mental health disorder and current use of opioids were associated with greater physical limitations at enrollment further supports the link between mental health and physical health. A study by Uddin et al. suggested the fear-avoidance model, where pain-related outcomes as physical limitations are determined by psychological factors such as catastrophic thinking in response to nociception and pain-related fear (29). Greater pain intensity and greater use of opioids are also associated with less effective cognitive coping strategies and greater psychological distress (30–35).
The finding that men and white race were independently associated with lower pain intensity at enrollment likely reflects social standing and social health. More research is likely to identify that differences according to social constructions such as race and ethnicity are explained by psychological and social confounders rather than inherent racial characteristics or genetics (24,36–40).
The evidence that psychological adaptability and effective cognitive coping strategies limit pain intensity and magnitude of activity intolerance can be considered to reflect the cognitive aspects of resiliency. Our findings suggest that general measures of resilience (in other words, measures that are not specific to physical symptoms, pain in particular) are less well correlated with pain intensity and magnitude of activity intolerance. It seems that resilience in the context of musculoskeletal health may be quite specific to health thoughts (effective cognitive coping strategies) in response to nociception (pathophysiology of actual or potential tissue damage) - a concept for future studies.
Appendix C.
Multivariable linear regression of factors associated with PROMIS PF and Pain at baseline and 3 months, and with BRS at baseline after mean imputation
| Dependentvariables | Retained variables | Regression coefficient [β](95% Confidence interval) | Standarderror | P value | SemipartialR-squared (R²) | Adjusted R² |
|---|---|---|---|---|---|---|
| PROMIS PFTime 1 | Current psychological disorder | -4.6 (-9.7 to 0.43) | 2.5 | 0.072 | 0.10 | |
| Current other pain condition | -3.7 (-9.5 to 2.2) | 2.9 | 0.217 | |||
| Current use of opioids | -8.2 (-15 to -1.8) | 3.2 | 0.013 | 0.05 | ||
| BRS | 1.8 (-0.80 to 4.4) | 1.3 | 0.173 | |||
| PROMIS PFTime 2 | Age | -0.09 (-0.30 to 0.13) | 0.1 | 0.411 | 0,12 | |
| Men | 5.1 (-1.5 to 12) | 3.5 | 0.125 | |||
| Current other pain condition | -6.4 (-13 to 0.61) | 3.5 | 0.072 | |||
| BRS | -0.14 (-4.3 to 4.0) | 2.1 | 0.946 | |||
| PainTime 1 | Men | -0.91 (-1.8 to -0.04) | 0.44 | 0.041 | 0.04 | 0.08 |
| White race | -1.1 (-2.2 to -0.00) | 0.56 | 0.049 | 0.03 | ||
| BRS | -0.50 (-1.1 to 0.09) | 0.30 | 0.098 | |||
| PainTime 2 | White race | -2.7 (-4.5 to -0.85) | 0.89 | 0.005 | 0.18 | 0.25 |
| Current psychological disorder | -1.1 (-2.8 to 0.48) | 0.80 | 0.163 | |||
| Previous orthopaedic condtion | 0.58 (-0.76 to 1.9) | 0.66 | 0.388 | |||
| BRS | -0.57 (-1.4 to 0.26) | 0.41 | 0.169 | |||
| BRSTime 1 | White race | 0.30 (-0.07 to 0.66) | 0.18 | 0.107 | 0.04 | |
| PAS | -0.00 (-0.01 to 0.00) | 0.00 | 0.165 |
Bold indicates statistically significant difference; Only the semipartial R² of significant variables is displayed; BRS=Brief Resilience Scale; PAS=Psychological Adaptation Scale; PROMIS PF=Patient-Reported Outcomes Measurement Information System Physical Function.
Conflict of Interest Statement:
No benefits in any form have been received or will be received related directly or indirectly to the subject of this article. The authors report no conflict of interest concerning the materials or methods used in this study or the findings specified in this paper
CN, JK, AG, TC, GV, and LR certify that they have no commercial associations (e.g. consultancies, stock ownership, equity interest, patent/licensing arrangements, etc.) that might pose a conflict of interest in connection with the submitted article.
DR has or may receive payment or benefits from Skeletal Dynamics, Wright Medical for elbow implants, Deputy Editor for Clinical Orthopaedics and Related Research, Universities and Hospitals, Lawyers outside the submitted work.
Ethical Committee Approval
This study received approval from the Institutional Review Board of the University of Texas at Austin. This study has been performed in accordance with the ethical standards in the 1964 Declaration of Helsinki. This study has been carried out in accordance with relevant regulations of the US Health Insurance Portability and Accountability Act (HIPAA).
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