Longitudinal Monitoring of Pain Associated Distress With the Optimal Screening for Prediction of Referral and Outcome Yellow Flag Tool: Predicting Reduction in Pain Intensity and Disability

Validation of the Keele STarT MSK Tool for Patients With Musculoskeletal Pain in United States-based Outpatient Physical Therapy Settings

The STarT MSK tool was developed to enable risk stratification of patients with common musculoskeletal (MSK) pain conditions and help identify individuals who may require more targeted interventions or closer monitoring in primary care settings, however, its validity in U.S.-based outpatient physical therapy settings has not been investigated. The 10-item Keele STarT MSK risk stratification tool was tested for construct (convergent and discriminant) and predictive validity using a multicenter, prospective cohort study design. Participants (n = 141) receiving physical therapy for MSK pain of the back, neck, shoulder, hip, knee, or multisite regions completed intake questionnaires including the Keele STarT MSK tool, Functional Comorbidity Index (FCI), Optimal Screening for Prediction of Referral and Outcome Review-of-Systems and Optimal Screening for Prediction of Referral and Outcome Yellow Flag tools. Pain intensity, pain interference, and health-related quality of life (Medical Outcomes Study 8-item Short-Form Health Survey (SF-8) physical [PCS] and mental [MCS] component summary scores) were measured at 2- and 6-month follow-up. Participants were classified as STarT MSK tool low (44%), medium (39%), and high (17%) risk. Follow-up rates were 70.2% (2 months) and 49.6% (6 months). For convergent validity, fair relationships were observed between the STarT MSK tool and FCI and SF-8 MCS (r = .35-.37) while moderate-to-good relationships (r = .51-.72) were observed for 7 other clinical measures. For discriminant validity, STarT MSK tool risk-dependent relationships were observed for Optimal Screening for Prediction of Referral and Outcome Review-of-Systems, Optimal Screening for Prediction of Referral and Outcome Yellow Flag, pain interference, and SF-8 PCS (low < medium < high; P < .01) and FCI, pain intensity, and SF-8 MCS (low < medium-or-high; P < .01). For predictive validity, intake STarT MSK tool scores explained additional variability in pain intensity (11.2%, 20.0%), pain interference (7.5%, 14.1%), and SF-8 PCS (8.2%, 12.8%) scores at 2 and 6 months, respectively. This study contributes to the existing literature by providing additional evidence of STarT MSK tool cross-sectional construct validity and longitudinal predictive validity. PERSPECTIVE: This study presents STarT MSK risk stratification tool validity findings from a U.S. outpatient physical therapy sample. The STarT MSK tool has the potential to help physical therapists identify individuals presenting with the most common MSK pain conditions who may require more targeted interventions or closer monitoring.

General and Pain-Associated Psychological Distress Phenotypes Among Patients With Low Back Pain in the Military Health System

OBJECTIVE

The primary objective was to describe rates of general and pain-related psychological distress for individuals with low back pain (LBP) in the Military Health System (MHS). We identified common phenotypes defined by rates of general and pain-related psychological distress and compared phenotypes on their level of pain interference, physical function, anxiety, and depression.

METHODS

We created a cohort from two completed trials assessing nonpharmacological treatment for LBP in the MHS (n = 510 total). The Optimal Screening for Prediction of Referral and Outcome Yellow Flag assessment tool identified the presence of 11 different yellow flags. Latent class analysis (LCA) used yellow flag indicators to identify common psychological phenotypes. We then compared Patient-Reported Outcomes Measurement Information Systems measures of pain interference, physical function, sleep disturbance, depression, and anxiety across phenotypes.

RESULTS

LCA identified five phenotypes (percentage of the sample): low distress (32%), high distress (27%), poor pain coping and low self-efficacy (18%), low self-efficacy and acceptance (14%), and poor pain coping (10%). Highly distressed phenotypes reported higher levels of pain interference, sleep disturbance, depression, and anxiety than those with other phenotypes, whereas the low distress phenotype had significantly lower pain interference and higher physical function scores than those characterized by all other phenotypes.

CONCLUSION

These phenotypes provide opportunities for clinicians and researchers to develop novel LBP treatment pathways tailored to patients with different profiles of psychological distress. Future work is needed to validate their predictive capabilities for clinical outcomes.

Discordance between self-report and performance-based outcomes: Contribution of psychosocial factors

The purpose of this study was to examine the role of psychosocial factors in the discordance between perceived and observed physical disability in patients with osteoarthritis of the hip or knee joint. This was a cross-sectional study of patients seen for consideration of joint arthroplasty surgery. Patients completed a psychosocial outcome measure, a patient self-reported functional scale, and two performance-based tests. Data of 121 patients, mean age, 67 (8), 81 (67%) females were used for analysis. The fear avoidance and positive affect domains had the strongest association with the discordance between the self-report and both performance outcome measures. Age, gender, and severity of osteoarthritis were associated with discordance in relation to walking. Fear avoidance beliefs and positive affect play important roles in perception of pain and function. Age, gender, and severity of arthritis should be taken into consideration for a more holistic approach to arthritis care.

What Are the Underlying Mental Health Constructs Associated With Level of Capability in People With Knee and Hip Osteoarthritis?

BACKGROUND

Mental health characteristics such as negative mood, fear avoidance, unhelpful thoughts regarding pain, and low self-efficacy are associated with symptom intensity and capability among patients with hip and knee osteoarthritis (OA). Knowledge gaps remain regarding the conceptual and statistical overlap of these constructs and which of these are most strongly associated with capability in people with OA. Further study of these underlying factors can inform us which mental health assessments to prioritize and how to incorporate them into whole-person, psychologically informed care.

QUESTIONS/PURPOSES

(1) What are the distinct underlying factors that can be identified using statistical grouping of responses to a multidimensional mental health survey administered to patients with OA? (2) What are the associations between these distinct underlying factors and capability in knee OA (measured using the Knee Injury and Osteoarthritis Outcome Score, Joint Replacement [KOOS JR]) and hip OA (measured using Hip Disability and Osteoarthritis Outcome Score, Joint Replacement [HOOS JR]), accounting for sociodemographic and clinical factors?

METHODS

We performed a retrospective cross-sectional analysis of adult patients who were referred to our program with a primary complaint of hip or knee pain secondary to OA between October 2017 and December 2020. Of the 2006 patients in the database, 38% (760) were excluded because they did not have a diagnosis of primary osteoarthritis, and 23% (292 of 1246) were excluded owing to missing data, leaving 954 patients available for analysis. Seventy-three percent (697) were women, with a mean age of 61 ± 10 years; 65% (623) of patients were White, and 52% (498) were insured under a commercial plan or via their employer. We analyzed demographic data, patient-reported outcome measures, and a multidimensional mental health survey (the 10-item Optimal Screening for Prediction of Referral and Outcome-Yellow Flag [OSPRO-YF] assessment tool), which are routinely collected for all patients at their baseline new-patient visit. To answer our first question about identifying underlying mental health factors, we performed an exploratory factor analysis of the OSPRO-YF score estimates. This technique helped identify statistically distinct underlying factors for the entire cohort based on extracting the maximum common variance among the variables of the OSPRO-YF. The exploratory factor analysis established how strongly different mental health characteristics were intercorrelated. A scree plot technique was then applied to reduce these factor groupings (based on Eigenvalues above 1.0) into a set of distinct factors. Predicted factor scores of these latent variables were generated and were subsequently used as explanatory variables in the multivariable analysis that identified variables associated with HOOS JR and KOOS JR scores.

RESULTS

Two underlying mental health factors were identified using exploratory factor analysis and the scree plot; we labeled them "pain coping" and "mood." For patients with knee OA, after accounting for confounders, worse mood and worse pain coping were associated with greater levels of incapability (KOOS JR) in separate models but when analyzed in a combined model, pain coping (regression coefficient -4.3 [95% confidence interval -5.4 to -3.2], partial R 2 0.076; p < 0.001) had the strongest relationship, and mood was no longer associated. Similarly, for hip OA, pain coping (regression coefficient -5.4 [95% CI -7.8 to -3.1], partial R 2 0.10; p < 0.001) had the strongest relationship, and mood was no longer associated.

CONCLUSION

This study simplifies the multitude of mental health assessments into two underlying factors: cognition (pain coping) and feelings (mood). When considered together, the association between capability and pain coping was dominant, signaling the importance of a mental health assessment in orthopaedic care to go beyond focusing on unhelpful feelings and mood (assessment of depression and anxiety) alone to include measures of pain coping, such as the Pain Catastrophizing Scale or Tampa Scale for Kinesiophobia, both of which have been used extensively in patients with musculoskeletal conditions.

LEVEL OF EVIDENCE

Level III, prognostic study.

The relationships between pain-associated psychological distress, pain intensity, patient expectations, and physical function in individuals with musculoskeletal pain: A retrospective cohort study

INTRODUCTION

The presence of pain-associated psychological distress (PAPD) in musculoskeletal disorders, including negative mood, fear-avoidance, and lack of positive affect/coping, is associated with prolonged disability. The importance of considering psychological influence on pain is well known, but practical ways of addressing it are not as straightforward. Identifying relationships between PAPD and pain intensity, patient expectations, and physical function may guide the development of future studies that assess causality and inform clinical practice.

OBJECTIVE

To assess the relationship between PAPD measured by the Optimal Screening for Prediction of Referral and Outcome-Yellow Flag tool, and baseline pain intensity, expectations of treatment effectiveness, and self-reported physical function at discharge.

DESIGN

Retrospective cohort study.

SETTING

Hospital-based outpatient physical therapy.

PARTICIPANTS

Patients 18 to 90 years old with spinal pain or lower extremity osteoarthritis.

MAIN OUTCOME MEASURES

Pain intensity and patient expectations of treatment effectiveness at intake, and self-reported physical function at discharge.

RESULTS

A total of 534 patients, 56.2% female, median (interquartile range [IQR]) age 61 (21) years with an episode of care between November 2019 and January 2021 were included. A multiple linear regression showed a significant association between PAPD and pain intensity with 6.4% (p < .001) of the variance explained. PAPD explained 3.3% (p < .001) of the variance in patient expectations. One additional yellow flag present resulted in a 0.17-point increase in pain intensity and 1.3% decrease in patient expectations. PAPD was also associated with physical function with 3.2% (p < .001) of the variance explained. PAPD explained 9.1% (p < .001) of the variance in physical function at discharge in the low back pain cohort only when assessed independently by body region.

CONCLUSION

These findings support the theory that the pain experience is complex and multiple factors should be considered when evaluating a patient with musculoskeletal pain. Clinicians who have identified PAPD may consider these relationships when planning or modifying interventions and pursuing multidisciplinary collaboration.

The influence of pain-related comorbidities on pain intensity and pain-related psychological distress in patients presenting with musculoskeletal pain

BACKGROUND

Musculoskeletal pain (MSP) is the largest contributor to chronic pain and frequently occurs alongside other medical comorbidities.

OBJECTIVE

Explore the relationships between the presence of pain-related comorbidities, pain intensity, and pain-related psychological distress in patients with MSP.

METHODS

A longitudinal assessment of individuals 18-90 years old in the Midwestern United States beginning a new episode of physical therapy for MSP. Electronic medical records were assessed the full year prior for care-seeking of diagnoses for pain-related comorbidities (anxiety, metabolic disorder, chronic pain, depression, nicotine dependence, post-traumatic stress disorder, sleep apnea, and sleep insomnia). Pain intensity and pain-related psychological distress (Optimal Screening for Prediction of Referral and Outcome - Yellow Flags tool) were captured during the physical therapy evaluation. Generalized linear models were used to assess the association between pain intensity, psychological distress, and pain-related co-morbidities. Models were adjusted for variables shown in the literature to influence pain.

RESULTS

532 participants were included in the cohort (56.4% female; median age of 59 years, Interquartile Range [IQR]:47, 69). Comorbid depression (beta coefficient (β) = 0.7; 95%CI: 0.2, 1.2), spine versus lower extremity pain ((β = 0.6; 95%CI: 0.1, 1.1), and prior surgery (β = 0.8, 95%CI: 0.3, 1.4) were associated with higher pain intensity scores. No pain-related comorbidities were associated with pain-related psychological distress (yellow flag count or number of domains). Female sex was associated with less pain-related psychological distress (β = -0.2, 95%CI: -0.3, -0.02).

CONCLUSIONS

Depression was associated with greater pain intensity. No comorbidities were able to account for the extent of pain-related psychological distress.

Heterogeneity of pain-related psychological distress in patients seeking care for shoulder pathology

BACKGROUND

Psychological distress is associated with disability and quality of life for patients with shoulder pain. However, uncertainty around heterogeneity of psychological distress has limited the adoption of shoulder care models that address psychological characteristics. In a cohort of patients with shoulder pain, our study sought to (1) describe the prevalence of various subtypes of psychological distress; (2) evaluate associations between psychological distress and self-reported shoulder pain, disability, and function; and (3) determine differences in psychological distress profiles between patients receiving nonoperative vs. operative treatment.

METHODS

The sample included 277 patients who were evaluated in clinic by a shoulder surgeon and completed the Optimal Screening for Prediction of Referral and Outcome Yellow Flag Assessment Tool (OSPRO-YF) from 2019 to 2021. This tool categorizes maladaptive and adaptive psychological traits, and the number of yellow flags (YFs) ranges from 0 to 11, with higher YF counts indicating higher pain-related psychological distress. Operative and nonoperative cohorts were compared using χ² test and Student t test. Linear regression was used to evaluate the association between pain, disability, and YFs, whereas Poisson regression evaluated the association between operative treatment and psychological distress. K-means cluster analysis was performed to propose potential psychological distress phenotypes.

RESULTS

Two hundred fifty-one patients (91%) had at least 1 YF on the OSPRO-YF tool, with a mean number of 6 ± 3.5 YFs. YFs in unhelpful coping (85%) and helpful coping domains (78%) were most prevalent. The number of YFs was significantly associated with baseline shoulder pain (P < .001), Single Assessment Numeric Evaluation (P < .001), and American Shoulder and Elbow Surgeons Standardized Shoulder Assessment Form (P < .001) scores. Comparing operative and nonoperative cohorts, the operative cohort had a significantly higher mean number of YFs (6.5 vs. 5.6, P = .035), presence of any YF (94.3% vs. 85.7%, P = .015), and presence of YFs within the unhelpful coping domain (91.8% vs. 75.6%, P < .001). Three phenotypes were described, corresponding to low, moderate, and severe psychological distress (P < .001), with females (P = .037) and smokers (P = .018) associated with higher psychological distress phenotypes.

CONCLUSIONS

YFs, particularly within the unhelpful coping and helpful coping domains, were highly prevalent in a cohort of patients presenting to a shoulder surgeon's clinic. Additionally, operative patients were found to have a significantly higher rate of YFs across multiple dimensions of psychological distress. These findings stress the importance of routine attentiveness to multiple dimensions of pain-related psychological distress in shoulder populations, which can provide an opportunity to reinforce healthy interpretation of pain while minimizing distress in appropriately identified patients.

Injury-related psychological distress and the association with perceived running ability in injured runners

OBJECTIVE

Examine injury-related psychological distress and association with perceived running ability in injured runners.

DESIGN

Prospective longitudinal study.

PARTICIPANTS

Forty-three patients with a running-related injury.

MAIN OUTCOME MEASURES

Data collection at initial physical therapy visit and 12-16 weeks later included Optimal Screening for Prediction of Referral and Outcome - Yellow Flag (OSPRO-YF) and Athlete Fear Avoidance Questionnaire (AFAQ) for injury-related psychological distress, and University of Wisconsin Running and Recovery Index (UWRI) for perceived running ability. OSPRO-YF composite score, total yellow flags, and yellow flags in each domain (negative mood, fear-avoidance, positive affect/coping) were calculated.

RESULTS

UWRI score and OSPRO-YF composite score and yellow flags significantly improved over time, while AFAQ score and yellow flags in OSPRO-YF negative mood domain did not. AFAQ scores were significantly correlated with UWRI score at baseline, follow-up and change over time, while OSPRO-YF composite score and yellow flags were not. Baseline OSPRO-YF composite score and AFAQ score were not correlated with follow-up UWRI score.

CONCLUSIONS

Injury-related psychological distress is elevated when injured runners start rehabilitation, and generally improves; however, negative mood and athletic fear-avoidance may persist. Higher athletic fear-avoidance is associated with lower perceived running ability at the same time point or interval.

Efficient Screening for Fear of Movement in Outpatient Settings: Short Form and Computer Adaptive Tests for Fear Avoidance and Negative Pain Coping

OBJECTIVE

The purpose of this study was to develop screening measures using item response theory (IRT) for 2 factors highly relevant to fear of movement (FoM): fear avoidance and negative pain coping.

METHODS

A total of 431 patients with neck (n = 93), shoulder (n = 108), low back (n = 119), or knee (n = 111) conditions seeking physical therapy completed 8 validated psychological questionnaires measuring fear avoidance and negative pain coping, resulting in 97 candidate items for IRT analysis. Unidimensionality and local independence were assessed using exploratory factor analyses followed by confirmatory factor analyses. Items were assessed for model fit to the graded response model for ordinal items. Using the final item bank, a computer adaptive test (CAT) administration mode was constructed, and reduced item sets were selected to create short forms (SFs), including items with highest information (reliability) at the different levels of the trait being measured while also considering clinical content.

RESULTS

The results supported a 28-item bank for fear avoidance and 16-item bank for negative pain coping. A 10-item and 8-item SF were developed for fear avoidance and negative pain coping, respectively. Additionally, 4-item form versions were created to provide options with lower administrative burden. CAT administration used a mean (median) of 7.7 (8) and 7.0 (7) items for fear avoidance and negative pain coping, respectively. All factors demonstrated construct validity by discriminating patient groups in expected clinical patterns.

CONCLUSION

These newly derived SFs and CAT administration modes provide reliable, valid, and efficient options to screen for fear avoidance and negative pain coping in populations with musculoskeletal pain.

IMPACT

These tools, collectively referred to as the Screening for Pain Vulnerability and Resilience tools, address a critical need for standard FoM screening processes that aid in clinical decision-making to identify who might benefit from psychologically informed approaches.

Screening for Yellow Flags in Orthopaedic Physical Therapy: A Clinical Framework

BACKGROUND

Psychological factors influence or are associated with physical function, pain, and health care costs among individuals with musculoskeletal pain conditions. Recent clinical practice guidelines recommend screening for psychological factors (also referred to as "yellow flags") in physical therapy practice to help understand prognosis and inform shared decision making for treatment.

CLINICAL QUESTION

Despite the urgings of clinical practice guidelines and evidence of the influence of psychological factors on clinical outcomes, screening for yellow flags is uncommon in clinical practice. Clinicians may feel uncertain about how to integrate screening tools into clinical practice, and how screening results might inform decision making and care coordination.

KEY RESULTS

We outline a 3-step framework for routine yellow flag screening in physical therapy practice: (1) establish a standard first-line screening instrument and process, (2) interpret the results to inform shared decision making, and (3) monitor treatment progress. Four case examples illustrate how yellow flag screening can help clinicians and patients decide whether the patient might benefit most from standard physical therapy, psychologically informed physical therapy, psychologically informed physical therapy with referral to another health care provider, or immediate referral.

CLINICAL APPLICATION

Consider incorporating a standard yellow flag screening process into usual musculoskeletal health care. We present a framework to guide yellow flag screening in practice (1) to help inform treatment pathway selection and (2) to enhance interdisciplinary communication. J Orthop Sports Phys Ther 2021;51(9):459-469. doi:10.2519/jospt.2021.10570.

Patient-centered outcomes: Domain importance predicts health care use following physical therapy

INTRODUCTION

Identifying patients with musculoskeletal pain who are at risk for additional health care use is important for improving the value of physical therapists' services. We previously identified three subgroups based on the importance attached by patients to improvements in outcome domains including a (1) Pain and Function Outcomes Important subgroup; (2) Pain Important subgroup; and (3) Multiple Outcome Domains Important subgroup.

OBJECTIVE

The primary aim was to determine whether subgroups based on patient-determined outcomes of importance predicted any additional pain-related health care use after an episode of physical therapy. A secondary aim was to determine if subgroup membership predicted use of specific services.

DESIGN

Secondary analysis of a longitudinal cohort.

SETTING

Ambulatory outpatient physical therapy clinics.

PATIENTS

Two hundred forty-six patients seeking physical therapy recruited from the Optimal Screening for Prediction of Referral and Outcome (OSPRO) cohort study.

INTERVENTIONS

Patients completed a demographic and health history questionnaire, numeric pain rating scale, region-specific disability measure, and Charlson Comorbidity Index. Subgroup membership was determined based on responses to the Patient Centered Outcome Questionnaire. At 1 year, patients reported use of health care since discharge from physical therapy. Separate logistic regression models determined whether subgroup membership predicted additional health care use.

RESULTS

Compared to the Pain and Function Outcomes Important subgroup, the Pain Important subgroup had higher adjusted odds (95% confidence interval [CI]) for the primary outcome of any additional health care use (adjusted odds ratio [aOR] 2.47, 95% CI 1.01-6.00) and secondary outcomes of opioid use (aOR 9.45, 95% CI 2.87-31.17), injection (aOR 4.09, 95% CI 1.25-13.41), and surgery (aOR 5.10, 95% CI 1.15-22.67). There were no significant differences in health care utilization between the Pain and Function Outcomes Important and Multiple Outcome Domains Important subgroups.

CONCLUSION

In this cohort, patients with a singular focus on pain improvements were at higher risk for additional health care, including opioid use, injection, and surgery. These findings are exploratory and need to be confirmed in other cohorts.

Derivation of a Risk Assessment Tool for Prediction of Long-Term Pain Intensity Reduction After Physical Therapy

Rationale

Risk assessment tools can improve clinical decision-making for individuals with musculoskeletal pain, but do not currently exist for predicting reduction of pain intensity as an outcome from physical therapy.

Aims and Objective

The objective of this study was to develop a tool that predicts failure to achieve a 50% pain intensity reduction by 1) determining the appropriate statistical model to inform the tool and 2) select the model that considers the tradeoff between clinical feasibility and statistical accuracy.

Methods

This was a retrospective, secondary data analysis of the Optimal Screening for Prediction of Referral and Outcome (OSPRO) cohort. Two hundred and seventy-nine individuals seeking physical therapy for neck, shoulder, back, or knee pain who completed 12-month follow-up were included. Two modeling approaches were taken: a longitudinal model included demographics, presence of previous episodes of pain, and regions of pain in addition to baseline and change in OSPRO Yellow Flag scores to 12 months; two comparison models included the same predictors but assessed only baseline and early change (4 weeks) scores. The primary outcome was failure to achieve a 50% reduction in pain intensity score at 12 months. We compared the area under the curve (AUC) to assess the performance of each candidate model and to determine which to inform the Personalized Pain Prediction (P3) risk assessment tool.

Results

The baseline only and early change models demonstrated lower accuracy (AUC=0.68 and 0.71, respectively) than the longitudinal model (0.79) but were within an acceptable predictive range. Therefore, both baseline and early change models were used to inform the P3 risk assessment tool.

Conclusion

The P3 tool provides physical therapists with a data-driven approach to identify patients who may be at risk for not achieving improvements in pain intensity following physical therapy.