Reliability and Validity of Observational Methods for Postural Load Assessment: An Updated Systematic Review

Context: Defined by several physiological and anatomical contributors, posture is essentially an accurate indicator of health status that is most frequently highlighted by affecting the configuration and operations of internal systems and organs. Quantifying body position has always been highlighted in clinical, academic, and industrial contexts, and various posture analysis approaches have been developed throughout the years. Objectives: This study aims to establish the reliability and validity of several novel observational approaches to postural load assessment and provide an overall view of related trends. Methods: This review was designed and conducted following (PRISMA) guidelines and five databases were surveyed, namely PubMed, Science Direct, CINAHL, Ergonomic Abstracts, and EMBASE, utilizing both generic and specific search terms modified for each database. Articles introducing a novel approach to observational postural load analysis and concepts of reliability and validity of the introduced method were included. Cross-sectional, case-control, experimental, and controlled trial designs were considered. Studies were excluded if they were exclusively based on subjective approaches. The methodological quality of the studies was evaluated using the MacDermid checklist. Similarly, reliability, measurement error, content validity, and criterion validity were assessed using COSMIN (Consensus-based Standards for selecting health Measurement Instruments) boxes B, C, D, and H, respectively. Results: Twenty-five articles were selected for the final review. The studies mainly reported ICC for reliability and r and r2 for validity. The results on the MacDermid quality evaluation tool varied from 38 to 80%, with a mean of 61.60 ± 11.54%. Regarding the COSMIN checklists, the scores were 61.40 ± 10.39%, 59.16 ± 11.35%, 64 ± 16.07%, and 57.12 ± 15.19% for boxes B, C, D, and H, respectively. Some studies did not obtain high scores for specified inclusion and exclusion criteria and appropriate sample size, leading to a moderate quality rating in checklists. Conclusions: Drawing comprehensive conclusions by directly comparing and contrasting observational techniques can be challenging due to their unique strengths, limitations, and inconsistencies. Such variations may arise from the methods’ characteristics, such as the fields, settings, populations, and the evaluated risk factors.