Do Maladaptive Imaging Beliefs Predict Self-Reported Pain Interference and Physical Function in Patients With Musculoskeletal Disorders?

OBJECTIVE: To determine if maladaptive imaging beliefs correlated with, and predicted pain interference and physical function outcomes in people with musculoskeletal pain disorders. DESIGN: A prospective cohort study of patients with musculoskeletal disorders receiving outpatient physical therapy from April 2022 to August 2023. METHODS: Four questions about imaging were asked to assess maladaptive beliefs, the need to rule out serious conditions, guide treatment, determine diagnosis, and validate symptoms. Correlations with beliefs and outcomes were assessed using Kendall's tau rank and Spearman's rho correlation coefficients. Generalized linear models determined if these beliefs predicted outcomes at baseline and 6 weeks. RESULTS: The cohort included 152 participants (mean [standard deviation] age: 56.13 [15.13]; 32.2% male). Maladaptive imaging beliefs correlated positively with pain interference and negatively with physical function. The need to rule out serious conditions and validate symptoms correlated with pain interference (range: τb = 0.17, 0.20; P = .003, .0121) and physical function (range: ρ = -0.22, -0.22; P = .006, .008). All but 1 belief correlated with pain interference (range: τb = 0.19, 0.24; P<.001, .004) and physical function (range: ρ = -0.26, -0.21; P = .001, .009) at 6 weeks. Each additional belief slightly increased pain interference at 6 weeks (ß = 0.01; 95% CI: 0.001, 0.03; P = .04) and lowered physical function at both baseline (ß = -0.97; 95% CI: -1.66, -0.28; P = .01) and 6 weeks (ß = -0.76; 95% CI: -1.37, -0.15; P = .02). CONCLUSION: Maladaptive imaging beliefs were significantly (albeit weakly) correlated with pain and physical function. Each additional maladaptive imaging belief increased pain interference at 6 weeks and lowered physical function at baseline and 6 weeks. Beliefs about the necessity of imaging to properly manage musculoskeletal disorders may influence outcomes. J Orthop Sports Phys Ther 2024;54(9):1-10. Epub 5 July 2024. doi:10.2519/jospt.2024.12625.

Reproducibility of Exercise Interventions in Randomized Controlled Trials for the Treatment of Rotator Cuff-Related Shoulder Pain: A Systematic Review.

OBJECTIVE: To determine the reproducibility of exercise therapy interventions in randomized controlled trials for rotator cuff-related shoulder pain (RCRSP). DATA SOURCES: Data sources included Medline, Cumulative Index to Nursing and Allied Health Literature, Cochrane Central Register of Controlled Trials, and SPORTDiscus from studies published from database inception to April 23, 2022. STUDY SELECTION: Randomized controlled trials studying the use of exercise therapy for RCRSP. DATA EXTRACTION: Two reviewers extracted exercise reporting details from all studies using the Template for Intervention Description and Replication (TIDieR) and the modified Consensus on Exercise Reporting Template (CERT). The same 2 reviewers assessed risk of bias of all studies using Cochrane Risk of Bias Tool version 2.0. DATA SYNTHESIS: For 104 studies meeting inclusion criteria, the average number of items reported on the TIDieR was 5.27 (SD 2.50, range 1-12 out of 12) and 5.09 (SD 4.01, range 0-16 out of 16) on the CERT. Improved reporting over time was seen on both the TIDieR and CERT dating back to 1993 and through April 23, 2022. When comparing groups of studies published before and after the TIDieR (2014) and CERT (2016) were established, a statistically significant increase in median scores was noted on the TIDieR (P=.02) but not the CERT (P=.31). Quality of exercise therapy reporting was highest in studies with "low risk" of bias, and lowest in studies with "high risk" of bias on the RoB-2. CONCLUSION: Overall exercise reporting in trials for RCRSP is incomplete despite the development of the TIDieR and CERT checklists. This has implications for translating evidence into practice.

The effectiveness of post-professional physical therapist training in the treatment of chronic low back pain using a propensity score approach with machine learning.

RATIONALE: Low back pain (LBP) is a leading cause of disability in the United States creating substantial hardships through negative social, financial, and health effects. Chronic low back pain (CLBP) accounted for above half of patients treated in physical therapy (PT) clinics for LBP. However, research shows small benefit from PT in CLBP treatment. Preliminary evidence suggests clinician-level training variables may affect outcomes, but requires further investigation to determine whether patients with CLBP benefit from treatment by providers with post-professional training. This study examined the relationship between clinician training levels and patient-reported outcomes in CLBP treatment. METHODS: Physical therapies were surveyed using a large patient outcome assessment system to determine and categorise them by level of post-professional education. To account for the possibility that clinicians with higher levels of training are referred more-complex patients, a machine learning approach was used to identify predictive variables for clinician group, then to construct propensity scores to account for differences between groups. Differences in functional status score change among pooled data were analysed using linear models adjusted for propensity scores. RESULTS: There were no clinically meaningful differences in patient outcomes when comparing clinician post-professional training level. The propensity score method proved to be a valuable way to account for differences at baseline between groups. CONCLUSION: Post-professional training does not appear to contribute to improved patient outcomes in the treatment of CLBP. This study demonstrates that propensity score analysis can be used to ensure that differences observed are true and not due to differences at baseline.

Integrating Physical Therapists Into Primary Care Within A Large Health Care System.

BACKGROUND: Bellin Health in Wisconsin has pioneered the colocation and integration of physical therapists into primary care pods. METHODS: This is an observational study based on one in-person visit and several interviews. RESULTS: For patients with musculoskeletal complaints, providers make warm handoffs to the physical therapist, who is a few steps away. The physical therapist performs most of the visit, providing diagnosis, treatment, and patient education. Research studies show that-compared with physician management-appropriate patients managed by physical therapists have better outcomes, lower costs, and higher patient satisfaction. In a fee-for-service environment, the business case for this innovation requires an increased number of follow-up referrals to the physical therapy department. In the Coronavirus disease 2019 (COVID-19) era, physical therapists can provide video visits with equal quality compared with in-person visits. CONCLUSION: The Bellin Health program is a blueprint for other primary care practices to integrate physical therapists into primary care teams.