Measuring joint range of motion is an important skill for many allied health professionals. While the Universal Goniometer is the most commonly utilised clinical tool for measuring joint range of motion, the evolution of smartphone technology and applications (apps) provides the clinician with more measurement options. However, the reliability and validity of these smartphones and apps is still somewhat uncertain. The aim of this study was to systematically review the literature regarding the intra- and inter-rater reliability and validity of smartphones and apps to measure joint range of motion. Eligible studies were published in English peer-reviewed journals with full text available, involving the assessment of reliability and/or validity of a non-videographic smartphone app to measure joint range of motion in participants >18 years old. An electronic search using PubMed, Medline via Ovid, EMBASE, CINAHL, and SPORTSDiscus was performed. The risk of bias was assessed using a standardised appraisal tool. Twenty-three of the eligible 25 studies exceeded the minimum 60% score to be classified as a low risk of bias, although 3 of the 13 criteria were not achieved in >50% of the studies. Most of the studies demonstrated adequate intra-rater or inter-rater reliability and/or validity for >50% of the range of motion tests across all joints assessed. However, this level of evidence appeared weaker for absolute (e.g. mean difference ± limit of agreement, minimal detectable change) than relative (e.g. intraclass correlation, correlation) measures; and for spinal rotation than spinal extension, flexion and lateral flexion. Our results provide clinicians with sufficient evidence to support the use of smartphones and apps in place of goniometers to measure joint motion. Future research should address some methodological limitations of the literature, especially including the inclusion of absolute and not just relative reliability and validity statistics.

Purpose: Prognostic models play an important clinical role in the clinical management of neck pain disorders. No study has compared the performance of modern machine learning (ML) techniques, against more traditional regression techniques, when developing prognostic models in individuals with neck pain.Methods: A total of 3001 participants suffering from neck pain were included into a clinical registry database. Three dichotomous outcomes of a clinically meaningful improvement in neck pain, arm pain, and disability at 3 months follow-up were used. There were 26 predictors included, five numeric and 21 categorical. Seven modelling techniques were used (logistic regression, least absolute shrinkage and selection operator [LASSO], gradient boosting [Xgboost], K nearest neighbours [KNN], support vector machine [SVM], random forest [RF], and artificial neural networks [ANN]). The primary measure of model performance was the area under the receiver operator curve (AUC) of the validation set.Results: The ML algorithm with the greatest AUC for predicting arm pain (AUC = 0.765), neck pain (AUC = 0.726), and disability (AUC = 0.703) was Xgboost. The improvement in classification AUC from stepwise logistic regression to the best performing machine learning algorithms was 0.081, 0.103, and 0.077 for predicting arm pain, neck pain, and disability, respectively.Conclusion: The improvement in prediction performance between ML and logistic regression methods in the present study, could be due to the potential greater nonlinearity between baseline predictors and clinical outcome. The benefit of machine learning in prognostic modelling may be dependent on factors like sample size, variable type, and disease investigated.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus is associated with psychological/emotional disturbances. This study aimed to assess internal consistency, reliability, and construct validity of the Hospital Anxiety and Depressive Scale (HADS), as a patient-reported outcome measure (PROM) for evaluating emotional consequences of SARS-CoV-2 in hospitalized COVID-19 survivors with long COVID. The LONG-COVID-EXP-CM is a multicenter cohort study including patients hospitalized by COVID-19 during the first wave of the pandemic in five hospitals in Madrid. A total of 1969 (age: 61 ± 16 years, 46.5% women) COVID-19 survivors experiencing post-COVID symptoms a mean of 8.4 ± 1.5 months after hospital discharge completed HADS. Internal consistency (Cronbach α), reliability (item-internal consistency, item-discriminant validity), construct validity (confirmatory factor analysis), and floor effect and ceiling effect were calculated. The mean time for fulfilling HADS was 65 ± 12 s. A ceiling effect ranging from 1.99% to 13.74% and a floor effect ranging from 43.05% to 77.77% was observed. Based on the item-scale correlation coefficients, the Cronbach’s alpha values reflecting the internal consistency reliability were 0.890 for the anxiety scale (HADS-A) and 0.856 for the depressive scale (HADS-D) The correlation coefficient between HADS-A and HADS-D scores was excellent (r: 0.878). The confirmatory factor analysis revealed that five out of the seven fitness indexes were excellent: CFI = 0.969, NNFI = 0.963; TLI = 0.963; AGFI = 0.951; GFI = 0.972), supporting good construct validity. In conclusion, this study indicates that both anxiety and depressive symptoms scales of HADS had overall good psychometric properties to be used for assessing psychological and emotional stress in COVID-19 survivors with long COVID.

The aim of this systematic review was to evaluate the impact of bilaterally symmetrical backpack systems borne on the posterior trunk on walking biomechanics, as backpacks represent the most prevalent method of load carriage in the military and civilian population. A search of electronic databases was performed for studies that only investigated posteriorly-borne backpack carriage during level-grade walking (treadmill and over ground). Methodology of studies was assessed, and both meta-analysis and qualitative synthesis were completed. Fifty-four studies were included in this review. In summary, the available literature showed that backpack carriage in walking was associated with an increased trunk flexion angle, increased hip and ankle range of motion, increased vertical and horizontal ground reaction force, increased cadence, and reduced stride length. Several variations in backpack carriage protocols could explain between-study variations in results, including: walking speed, backpack carriage skill level, the use of a hip belt, and posterior displacement of the load away from the trunk. The findings of this systematic review will inform backpack carriage practices in the area of injury risk assessment and physical performance enhancement.

Background and Objective: Numerous studies have examined the influence of pain on spinal reflex excitability, motor unit behaviour and corticospinal excitability. Nevertheless, there are inconsistencies in the conclusions made. This systematic review sought to understand the effect of pain on spinal and supraspinal projections to motoneurons and motor unit properties by examining the influence of clinical or experimental pain on the following three domains: H‐reflex, corticospinal excitability and motor unit properties.Databases and Data Treatment: MeSH terms and preselected keywords relating to the H‐reflex, motor evoked potentials and motor unit decomposition in chronic and experimental pain were used to perform a systematic literature search using Cumulative Index of Nursing and Allied Health Literature (CINAHL), Excerpta Medica dataBASE (EMBASE), Web of Science, Medline, Google Scholar and Scopus databases. Two independent reviewers screened papers for inclusion and assessed the methodological quality using a modified Downs and Black risk of bias tool; a narrative synthesis and three meta‐analyses were performed.Results: Sixty‐one studies were included, and 17 different outcome variables were assessed across the three domains. Both experimental and clinical pain have no major influence on measures of the H‐reflex, whereas experimental and clinical pain appeared to have differing effects on corticospinal excitability. Experimental pain consistently reduced motor unit discharge rate, a finding which was not consistent with data obtained from patients. The results indicate that when in tonic pain, induced via experimental pain models, inhibitory effects on motoneuron behaviour were evident. However, in chronic clinical pain populations, more varied responses were evident likely reflecting individual adaptations to chronic symptoms.Significance: This is a comprehensive systematic review and meta‐analysis which synthesizes evidence on the influence of pain on spinal and supraspinal projections to motoneurons and motor unit properties considering measures of the H‐reflex, corticospinal excitability and motor unit behaviour. The H‐reflex is largely not influenced by the presence of either clinical or experimental pain. Whilst inhibitory effects on corticospinal excitability and motor unit behaviour were evident under experimental pain conditions, more variable responses were observed for people with painful musculoskeletal disorders.

Musculoskeletal (MSK) pain disorders represent a group of highly prevalent and often disabling conditions. Investigating the structure of motor variability in response to pain may reveal novel motor impairment mechanisms that may lead to enhanced management of motor dysfunction associated with MSK pain disorders. This review aims to systematically synthesize the evidence on the influence of MSK pain disorders on muscle synergies. Nine electronic databases were searched using Medical Subject Headings and keywords describing pain, electromyography and synergies. Relevant characteristics of included studies were extracted and assessed for generalizability and risk of bias. Due to the significant heterogeneity, a qualitative synthesis of the results was performed. The search resulted in a total of 1312 hits, of which seven articles were deemed eligible. There was unclear consistency that pain reduced the number of muscle synergies. There were low consistencies of evidence that the synergy vector (W weights) and activation coefficient (C weights) differed in painful compared to asymptomatic conditions. There was a high consistency that muscle synergies were dissimilar between painful and asymptomatic conditions. MSK pain alters the structure of variability in muscle control, although its specific nature remains unclear. Greater consistency in muscle synergy analysis may be achieved with appropriate selection of muscles assessed and ensuring consistent achievement of motor task outcomes. Synergy analysis is a promising method to reveal novel understandings of altered motor control, which may facilitate the assessment and treatment of MSK pain disorders.