Audio file
File
J. Lalata1, J.J. Amparo1, J.B. Mabansag1, A.A. Pascual1, E.j. Petil1, D. Sotto1, A.D. Caoili2
1Manila Central University, College of Physical Therapy, Caloocan, Philippines, 2Manila Central University, College of Physical therapy, Caloocan city, Philippines
Background: Proper posture indicates efficacy of musculoskeletal balance involving a properly distributed amount of stress or strain to the muscles and ligaments of the body. Static posture is where the body segments are aligned and maintained in a constant position, In Physical Therapy practice, Postural Analysis (PA)is a screening tool in examining different postures, identifying deformity which can lead to various musculoskeletal problems. Postural Analysis Application Technology(PAAT) is a Photogrammetric method that can be consider as an alternative way in more objective assessment of static postural assessment.
Purpose: The purpose of this study were to determine the instrument reliability of Postural Analysis Application Technology (PAAT) in objective analysis of static posture. It also to utilized photogrammetric method in Philippine setting as an alternative tools in taking PA with objective findings.
Methods: This study is quantitative experimental research, a convenience sampling technique was utilized. Slovin’s formula was used to determine the sample size. The researcher utilized the SPSS version 24 in analyzing the reliability of the tool. A Cronbach’s Alpha was used to assess the internal consistency of the tool with the following value of High 0.70- 1.00, Medium 0.50-0.69, Low 0.30-0.49, Poor 0.1-0.29 and Intraclass Correlation Coefficient (ICC) by Cicchetti & Sparrow for Interrater reliability of measurements or rating. Poor <0.40, Fair 0.40-60, Good 0.60-0.75,Excellent 0.75-1.00 Participants are screened in standing upright position in Anterior and Lateral view three times with 5 minutes interval per trial using PAAT. Three Registered Physical therapy served as independent raters.
Results: In Frontal view; The Cronbach Alpha on Head and neck- 0.75, High reliability , Shoulder -0.84,High reliability , Arms- 0.82, High reliability, Pelvis- 0.75, High reliability, Knees- 0.57 Medium reliability and Ankle – 0.82, high reliability and with an average of 0.76High reliability. And on the Lateral View, Head tilt-0.80 High reliability, torso- 0.87 and leg- 0.83 High reliability. And an average of 0.83 – High reliability
For inter rater reliability on Frontal view the Intraclass Correlation Coefficient (ICC) Head and Neck-0.75, Excellent Reliability, Shoulder- 0.85, Excellent reliability, Arms- 0.80 Excellent reliability, pelvis-0.75 Excellent reliability, knees – 0.70 Good reliability, ankle -0.82 Excellent reliability. On Lateral view; Head tilt 0.81 excellent reliability, Torso- 0.87, Excellent reliability leg 0.82 Excellent reliability. And an average of 0.83. Excellent reliability.
For inter rater reliability on Frontal view the Intraclass Correlation Coefficient (ICC) Head and Neck-0.75, Excellent Reliability, Shoulder- 0.85, Excellent reliability, Arms- 0.80 Excellent reliability, pelvis-0.75 Excellent reliability, knees – 0.70 Good reliability, ankle -0.82 Excellent reliability. On Lateral view; Head tilt 0.81 excellent reliability, Torso- 0.87, Excellent reliability leg 0.82 Excellent reliability. And an average of 0.83. Excellent reliability.
Conclusion(s): The study indicate that PAAT showed excellent reliability results from three rater and High reliability in internal consistency.
Implications: The utilization of PAAT can be suggested as Photogrammetric tool in objective analysis of static posture. Clinician may improve their skills in Postural analysis with good documentation evidence based assessment. Academically, PT faculty can present other options of Postural analysis via photogrammetric method. And PT students will able to widen their knowledge and skills in postural evaluation.
Funding, acknowledgements: No funding
Keywords: Static Posture, Photogrammetric, Postural Analysis Application Technology
Topic: Innovative technology: information management, big data and artificial intelligence
Did this work require ethics approval? Yes
Institution: MCU
Committee: MCU RDC ERB
Ethics number: 2020-20
All authors, affiliations and abstracts have been published as submitted.
