Effect of an Exercise Program That Includes Deadlifts on Low Back Pain.

Clinical Scenario: Low back pain is a common condition for the general population with 29% of adults having low back pain within the last 3 months. A deadlift is described as a free weight exercise in which a barbell is lifted from the floor in a continuous motion by extending the knees and hips. For those without low back pain, the deadlift was found to have the highest muscle activation of paraspinal musculature compared with other exercises. There are a limited number of studies that investigate the usefulness of incorporating deadlifts as part of a rehabilitation program for low back pain. Clinical Question: For those who live with low back pain, is an exercise routine that includes a deadlift a viable treatment option to improve pain and/or function? Summary of Key Findings: The literature search yielded 3 total studies meeting the inclusion and exclusion criteria: 1 randomized control trial, 1 secondary analysis of a randomized control trial, and 1 cohort study. Exercise programs that include deadlifts can yield improvements in both pain and function for those living with low back pain but were not found to be more beneficial than low load motor control exercises. Those with lower pain levels and higher baseline lumbar extension strength may be most appropriate to participate in an exercise program that includes deadlifts. Further research is needed to compare exercise programs that include deadlifts to other interventions for those living with low back pain. Clinical Bottom Line: There is minimal evidence that exercise programs that included deadlifts are a clinically effective option for the treatment of low back pain for both pain scores and functional outcome measures. Strength of Recommendation: Level B evidence exists that exercise programs that include deadlifts are a clinically effective option for the treatment of low back pain for both pain scores and functional outcome measures.

Interrater reliability of the modified prone instability test for lumbar segmental instability in individuals with mechanical low back pain.

OBJECTIVE: The purpose of this study was to establish the interrater reliability of measures obtained with a novel Modified Prone Instability Test (mPIT), which, like the original Prone Instability Test (PIT), is proposed to identify lumbar segmental instability. The mPIT has clinical feasibility advantages to the PIT, but its psychometric properties are yet to be determined. DESIGN: Repeated measures (test-retest) design, methods study. METHODS: The mPIT was administered by two blinded testers, an orthopedic physical therapy resident with < 1 year experience and board-certified orthopedic specialist physical therapist with >25 years' experience. Procedures were administered at an outpatient physical therapy clinic of a tertiary Medical Center. Participants included 50 adults (≥18 years old) with mechanical low back pain and no radicular (below the knee) symptoms (mean age 50.7 years, 66% female, 76% reported previous episodes of low back pain). Interrater reliability was measured via Fleiss' kappa coefficient. RESULTS: Assessments of the mPIT had moderate interrater agreement (κ = .579 [95% CI = .302 to .856], p < .001.). CONCLUSION: Measures obtained using the mPIT demonstrated moderate interrater reliability between a new graduate and an experienced clinician, which aligns with several studies examining interrater reliability of the original PIT. Further study examining comparative validation of the mPIT with other lumbar instability measures is warranted.

Detecting Artificial Intelligence-Generated Personal Statements in Professional Physical Therapist Education Program Applications: A Lexical Analysis.

OBJECTIVE: The objective of this study was to compare the lexical sophistication of personal statements submitted by professional physical therapist education program applicants with those generated by OpenAI's Chat Generative Pretrained Transformer (ChatGPT). METHODS: Personal statements from 152 applicants and 20 generated by ChatGPT were collected, all in response to a standardized prompt. These statements were coded numerically, then analyzed with recurrence quantification analyses (RQAs). RQA indices including recurrence, determinism, max line, mean line, and entropy were compared with t-tests. A receiver operating characteristic curve analysis was used to examine discriminative validity of RQA indices to distinguish between ChatGPT and human-generated personal statements. RESULTS: ChatGPT-generated personal statements exhibited higher recurrence, determinism, mean line, and entropy values than did human-generated personal statements. The strongest discriminator was a 13.04% determinism rate, which differentiated ChatGPT from human-generated writing samples with 70% sensitivity and 91.4% specificity (positive likelihood ratio = 8.14). Personal statements with determinism rates exceeding 13% were 8 times more likely to have been ChatGPT than human generated. CONCLUSION: Although RQA can distinguish artificial intelligence (AI)-generated text from human-generated text, it is not absolute. Thus, AI introduces additional challenges to the authenticity and utility of personal statements. Admissions committees along with organizations providing guidelines in professional physical therapist education program admissions should reevaluate the role of personal statements in applications. IMPACT: As AI-driven chatbots like ChatGPT complicate the evaluation of personal statements, RQA emerges as a potential tool for admissions committees to detect AI-generated statements.

Assessment of Gender Differences in Letters of Recommendation for Physical Therapy Residency Applications.

INTRODUCTION: Letters of recommendation (LOR) are an integral component of physical therapy residency applications. Identifying the influence of applicant and writer gender in LOR will help identify whether potential implicit gender bias exists in physical therapy residency application processes. REVIEW OF LITERATURE: Several medical and surgical residency education programs have reported positive, neutral, or negative LOR female gender bias among applicants and writers. Little research exists on gender differences in LOR to physical therapy education programs or physical therapy residency programs. SUBJECTS: Seven hundred sixty-eight LOR were analyzed from 256 applications to 3 physical therapy residency programs (neurologic, orthopaedic, sports) at one institution from 2014 to 2020. METHODS: Thematic categories were developed to identify themes in a sample of LOR. Associations between writer and applicant gender were analyzed using summary statistics, word counts, thematic and psycholinguistic extraction, and rule-based and deep learning Natural Language Processing . RESULTS: No significant difference in LOR word counts were found based on writer or applicant gender. Increased word counts were seen in sports residency LOR compared with the orthopaedic residency. Thematic analysis showed LOR gender differences with male applicants receiving more positive generalized recommendations and female applicants receiving more comments regarding interpersonal relationship skills. No thematic or psycholinguistic gender differences were seen by LOR writer. Male applicants were 1.9 times more likely to select all male LOR writers, whereas female applicants were 2.1 times more likely to choose all female LOR writers. DISCUSSION AND CONCLUSION: Gender differences in LORs for physical therapy residencies were found using a comprehensive Natural Language Processing approach that identified both a positive recommendation male applicant gender bias and a positive interpersonal relationship skill female applicant gender bias. Applicants were not harmed nor helped by selecting LOR writers of the opposite gender. Admissions committees and LOR writers should be mindful of potential implicit gender biases in LOR submitted to physical therapy residency programs.

Gender-based Language Differences in Letters of Recommendation.

Gender stereotyping is the practice of assigning or ascribing specific characteristics, differences, or identities to a person solely based on their gender. Biased conceptions of gender can create barriers to equality and need to be proactively identified and addressed. In biomedical education, letters of recommendation (LOR) are considered an important source for evaluating candidates' past performance. Because LOR is subjective and has no standard formatting requirements for the writer, potential language bias can be introduced. Natural language processing (NLP) offers a promising solution to detect language bias in LOR through automatic extraction of sensitive language and identification of letters with strong biases. In our study, we developed, evaluated, and deployed four NLP different methods (sublanguage analysis, dictionary-based approach, rule-based approach, and deep learning approach) for the extraction of psycholinguistics and thematic characteristics in LORs from three different physical therapy residency programs (Neurologic, Orthopaedic, and Sport) at Mayo Clinic. The evaluation statistics suggest that both MedTaggerIE model and Bidirectional Encoder Representations from Transformers model achieved moderate-high performance across eight different thematic categories. Through the pilot demonstration study, we learned that male writers were more likely to use the words 'intelligence', 'exceptional', and 'pursue' and male applicants were more likely to have the words 'strength', 'interpersonal skills', 'conversations', and 'pursue' in their letters of recommendation. Thematic analysis suggested that male and female writers have significant differences in expressing doubt, motivation, and recommendation. Findings derived from the study needed to be carefully interpreted based on the context of the study setting, residency programs, and data. A follow-up demonstration study is needed to further evaluate and interpret the findings.

Recurrence Quantification Analysis of Personal Statements from Applicants to a Physical Therapy Doctoral Program: A Cross-Sectional Analysis.

PURPOSE: We examined lexical sophistication of written personal statements from physical therapy applicants to determine whether recurrence quantification analysis (RQA) indices distinguish higher- versus lower-scored candidates and correlate with other admissions variables. METHODS: Written personal statements were extracted from 152 applications, coded numerically, and analyzed with RQA. Along with other RQA indices, determinism-representing predictability of words and phrases-was quantified. A receiver operating characteristic (ROC) curve analysis was used to examine discriminative validity of RQA indices to distinguish between top-10 and bottom-10 candidates. Correlation coefficients between RQA indices and other admissions variables (grade point averages, standardized exam, behavioral interview, and cumulative admissions scores) were also examined. RESULTS: Determinism in personal statements was lower in top-scored (mean 7.38%) than bottom-scored candidates (mean 11.29%, p = 0.015), differentiated between them with 70% sensitivity (95% CI 34.8%-93.3%) and 100% specificity (95% CI 69.2%-100%), and correlated negatively with candidates' behavioral interview scores (r = -0.168, p = 0.039). DISCUSSION: The greater expressive lexical sophistication characterized by lower determinism in personal statements provides information about candidates' writing proficiency as a component of their communication abilities that may not otherwise be assessed in traditional admissions variables.

Identifying patient fear-avoidance beliefs by physical therapists managing patients with low back pain.

STUDY DESIGN: Cross-sectional. OBJECTIVES: To evaluate the accuracy with which physical therapists identify fear-avoidance beliefs in patients with low back pain by comparing therapist ratings of perceived patient fear-avoidance to the Fear-Avoidance Beliefs Questionnaire (FABQ), Tampa Scale of Kinesiophobia 11-item (TSK-11), and Pain Catastrophizing Scale (PCS). To compare the concurrent validity of therapist ratings of perceived patient fear-avoidance and a 2-item questionnaire on fear of physical activity and harm, with clinical measures of fear-avoidance (FABQ, TSK-11, PCS), pain intensity as assessed with a numeric pain rating scale (NPRS), and disability as assessed with the Oswestry Disability Questionnaire (ODQ). BACKGROUND: The need to consider psychosocial factors for identifying patients at risk for disability and chronic low back pain has been well documented. Yet the ability of physical therapists to identify fear-avoidance beliefs using direct observation has not been studied. METHODS: Eight physical therapists and 80 patients with low back pain from 3 physical therapy clinics participated in the study. Patients completed the FABQ, TSK-11, PCS, ODQ, NPRS, and a dichotomous 2-item fear-avoidance screening questionnaire. Following the initial evaluation, physical therapists rated perceived patient fear-avoidance on a 0-to-10 scale and recorded 2 influences on their ratings. Spearman correlation and independent t tests determined the level of association of therapist 0-to-10 ratings and 2-item screening with fear-avoidance and clinical measures. RESULTS: Therapist ratings of perceived patient fear-avoidance had fair to moderate interrater reliability (ICC2,1 = 0.663). Therapist ratings did not strongly correlate with FABQ or TSK-11 scores. Instead, they unexpectedly had stronger associations with ODQ and PCS scores. Both 2-item screening questions were associated with FABQ-physical activity scores, while the fear of physical activity question was also associated with FABQ-work, TSK-11, PCS, and ODQ scores. CONCLUSION: Therapists' ratings of perceived patient fear-avoidance were not associated with self-reported fear-avoidance scores, showing a potential disconnect between therapist judgments and commonly used fear-avoidance measures. Instead, therapist ratings had small but statistically significant correlations with pain catastrophizing and disability, findings that may support therapists' inability to discriminate fear-avoidance from these other factors. The 2-item screening questions based on fear of physical activity and harm showed potential to identify elevated FABQ physical activity scores. LEVEL OF EVIDENCE: Differential diagnosis, level 2b.

Collaborative model of clinical education in physical and occupational therapy at the Mayo Clinic.

Clinical education experiences, a significant portion of entry-level professional education programs in physical therapy (PT) and occupational therapy (OT), commonly use a one student to one clinical instructor (1:1) model. Recently, though, the collaborative model of clinical education has received more attention in the professional literature and in clinical education experiences. The collaborative model--where two or more students complete a clinical education experience within a specific clinical area while supervised and educated by one primary clinical instructor (2:1 or 3:1)--has been used historically within the Mayo Clinic's Department of Physical Medicine and Rehabilitation in PT and now OT. Clinical instructors, referred to as clinical education coordinators, supervise and educate students as a primary job responsibility. Students also teach and learn from each other. This article describes the collaborative clinical education model used at the Mayo Clinic. Benefits and challenges of the model, feedback from students who have participated in the model, and the productivity implications of using the model are included.