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

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 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.

The Effect of Mobile Care Delivery on Clinically Meaningful Outcomes, Satisfaction, and Engagement Among Physical Therapy Patients: Observational Retrospective Study

Background

Musculoskeletal care is now delivered via mobile apps as a health care benefit. Although preliminary evidence shows that the clinical outcomes of mobile musculoskeletal care are comparable with those of in-person care, no research has examined the features of app-based care that secure these outcomes.

Objective

Drawing on the literature around in-person physical therapy, this study examines how patient-provider relationships and program engagement in app-based physical therapy affect clinically meaningful improvements in pain, function, and patient satisfaction. It then evaluates the effects of patient-provider relationships forged through in-app messages or video visits and timely, direct access to care on patients’ engagement in their recovery.

Methods

We conducted an observational, retrospective study of 814 pre- and postsurveyed participants enrolled in a mobile app physical therapy program where physical therapists prescribed workouts, education, and therapeutic activities after a video evaluation from February 2019 to December 2020. We estimated generalized linear models with logit functions to evaluate the effect of program engagement on clinical outcomes, minimal clinically important differences (MCIDs) in pain (ΔVisual Analogue Scale ≤−1.5) and function (ΔPatient Specific Functional Scale ≥1.3), and the effects of patient-provider relationships and clinical outcomes on patient satisfaction—participant reported likelihood to recommend the program (Net Promoter Scores of 9-10). We estimated Poisson generalized linear models to evaluate the effects of stronger patient-provider relationships and timely access to physical therapy within 24 hours on engagement including the number of weekly workouts and weeks in the program.

Results

The odds that participants (N=814) had a pain MCID increased by 13% (odds ratio [OR] 1.13, 95% CI 1.04-1.23; P=.003) with each weekly workout and the odds of a function MCID by 4% (OR 1.04, 95% CI 1.00-1.08; P=.03) with each week in the program. Participants with MCIDs in function and large changes in pain (Δ Visual Analogue Scale ≤−3.5) were 1.85 (95% CI 1.17-2.93; P=.01) and 2.84 times (95% CI 1.68-4.78; P<.001) more satisfied, respectively. Those with video follow-up visits were 2 to 3 times (P=.01) more satisfied. Each physical therapist’s message increased weekly workouts by 11% (OR 1.11, 95% CI 1.07-1.16; P<.001). Video follow-up visits increased weekly workouts by at least 16% (OR 1.16, 95% CI 1.04-1.29; P=.01) and weeks in the program at least 8% (OR 1.08, 95% CI 1.01-1.14; P=.02). Access was associated with a 14% increase (OR 1.14, 95% CI 1.05-1.24; P=.003) in weekly workouts.

Conclusions

Similar to in-person care, program engagement positively affects clinical outcomes, and strong patient-provider relationships positively affect satisfaction. In app-based physical therapy, clinical outcomes positively affect patient satisfaction. Timely access to care and strong patient-provider relationships, particularly those forged through video visits, affect engagement.

Can Physical Therapy Deliver Clinically Meaningful Improvements in Pain and Function through a Mobile App?: An Observational Retrospective Study

Objective

To examine the effect of digital physical therapy (PT) delivered by mobile application (app) on reducing pain and improving function for people with a variety of musculoskeletal conditions.

Design

An observational, longitudinal, retrospective study using survey data collected pre- and postdigital PT to estimate multilevel models with random intercepts for patient episodes.

Setting

Privately insured employees participating in app-based PT as an employer health care benefit.

Participants

The study sample included 814 participants (N=814) 18 years or older who completed their digital PT program with reported final clinical outcomes between February 2019 (program launch) through December 2020. Mean age of the sample at baseline was 40.9±11.89 years, 47.5% were female, 21% sought care for lower back pain, 16% for shoulders, 15% for knees, and 13% for neck.

Interventions

Digital PT consisted of a synchronous video evaluation with a physical therapist followed by a course of PT delivered through a mobile app.

Main Outcome Measures

Pain was measured by the visual analog scale from 0 “no pain” to 10 “worst pain imaginable” and physical function by the Patient-Specific Functional Scale on a scale from 0 “completely unable to perform” to 10 “able to perform normally.”

Results

After controlling for significant demographics, comorbid conditions, adverse symptoms, chronicity, and severity, the results from multilevel random intercept models showed decreased pain (−2.69 points; 95% CI, −2.86 to −2.53; P<.001) and increased physical function (+2.67 points; 95% CI, 2.45-2.89; P<.001) after treatment.

Conclusions

Digital PT was associated with clinically meaningful improvements in pain and function among a diverse set of participants. These early data are an encouraging indicator of the clinical benefit of digital PT.