Cloud-Biebl, Beth A

Reaching is a common daily activity requiring a range of humeral elevation that contributes to rotator cuff compression. The purpose of this study was to estimate supraspinatus and infraspinatus tendon compression risk relative to the acromion and coracoacromial ligament during reaching by manual wheelchair users with spinal cord injury. A cross-sectional design was used to evaluate 8 participants (7 males, median [range] age 36 y [23–61]). Electromagnetic motion capture recorded shoulder kinematics while participants reached for a can at 2 heights: low (0.91 m) and high (1.37 m). Using 1 set of computed tomographic-based bone models and individual glenohumeral kinematics, compression risk was evaluated as the percentage of the reach activity and number of seconds that tendon insertions were less than 5 mm from scapular landmarks. Reach conditions were compared using a Wilcoxon signed-rank test (α = .05). Although not statistically significant, the supraspinatus and infraspinatus relative to the acromion had approximately 40% of the activity duration or 0.8 seconds more time under 5 mm in low versus high reach, indicating increased risk of compression. Compression risk estimates were consistent with prior publications on planar arm movements. Estimating the risk of tendon compression using absolute time may help with understanding cumulative exposure during day-to-day activity.

Abstract 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.

Arm use in manual wheelchair (MWC) users is characterized by a combination of overuse and a sedentary lifestyle. This study aimed to describe the percentage of daily time MWC users and able-bodied individuals spend in each arm use intensity level utilizing accelerometers. Arm use intensity levels of the upper arms were defined as stationary, low, mid, and high from the signal magnitude area (SMA) of the segment accelerations based on in-lab MWC activities performed by eight MWC users. Accelerometry data were collected in the free-living environments from forty MWC users and 40 sex- and age-matched able-bodied individuals. The SMA intensity levels were applied to the free-living data and the percentage of time spent in each level was calculated. The SMA intensity levels were defined as, stationary: ≤0.67 g, low: 0.671–3.27 g, mid: 3.27–5.87 g, and high: >5.871 g. The dominant arm of both MWC users and able-bodied individuals was stationary for most of the day and less than one percent of the day was spent in high intensity arm activities. Increased MWC user age correlated with increased stationary arm time (R = 0.368, p = 0.019). Five and eight days of data are needed from MWC users and able-bodied individuals, respectively, to achieve reliable representation of their daily arm use intensities.