https://www.technology.eurekajournals.com/index.php/GJADSIT <p style="text-align: justify;">Global&nbsp;Journal on Application of Data Science and Internet of Things (GJADSIT) is Scholarly open access, high citation leading scientific journal. Now a days, it is seen that operations of today’s world become knowledge intensive and reliability of system became the top criterion for selection of particular system, therefore there is increase in demand for High quality novel research. Also, from industrial point of view, Continuity of&nbsp;Data Science and Internet of Things is the major factor for increases industrial production of finished goods. Therefore, the objective is to spread research work to mitigate problems of&nbsp;Data Science and Internet of Things arise during day to day operations around the world. The journal focused on fast peer review process of submitted paper to ensure accuracy, relevance of article and originality of paper.</p> <p style="text-align: justify;">Our journals are indexed in&nbsp;Google Scholar, International Institute of Organized Research (I2OR), Academic Keys,IIJIF,Cosmos Impact Factor, J-Gate.</p> en-US admin@eurekajournals.com (Eureka Journals) Fri, 23 Oct 2026 08:55:30 +0000 OJS 3.0.0.0 http://blogs.law.harvard.edu/tech/rss 60 https://www.technology.eurekajournals.com/index.php/GJADSIT/article/view/916 <p><strong>Background</strong>: Reliable measurement of physical functioning is important for understanding health and well-being among organisational and community leaders. Although Cronbach's alpha is widely used to assess internal consistency, high reliability does not necessarily establish unidimensionality.</p> <p><strong>Objective</strong>: This study examined the internal consistency and exploratory component structure of the ten physical-functioning indicators of the SF-36 Health Survey within a Jamaican leadership dataset.</p> <p>&nbsp;<strong>Methods</strong>: A quantitative secondary analysis examined existing SPSS reliability and Principal Component Analysis (PCA) output. Of 270 observations, 234 (86.7%) were retained following listwise deletion. The indicators corresponded in numbering to SF-36 questions 3-12, covering physical activities, stair climbing, walking and self-care.</p> <p><strong>Results</strong>: Cronbach's alpha was 0.903, while standardised alpha was 0.906. The Kaiser-Meyer-Olkin statistic was 0.880, and Bartlett's test was significant, ?²(45) = 1331.491, p &lt;0.001. Two components explained 64.967% of total variance, with a component correlation of 0.621. Physical4 exhibited cross-loading, while Physical12 displayed a complex pattern coefficient.</p> <p><strong>Discussion</strong>: The findings demonstrate strong internal consistency within an established physical-functioning domain, although the exploratory two-component solution suggests possible differences in how activity limitations are represented.</p> <p><strong>Conclusion</strong>: Further verification of coding, parallel analysis and common-factor modelling remain necessary before interpreting the two components as separate dimensions.</p> Paul Andrew Bourne, PhD, DrPH, Shelli-Gaye Bignall MSc, Maxine Cowan, MBA https://www.technology.eurekajournals.com/index.php/GJADSIT/article/view/916