Developing an Instrument to Measure Personal Keyboarding Style
Developing an Instrument to Measure Personal Keyboarding Style
This study will develop and refine an observational assessment tool called the Personal Computer Keyboard Style (PeCKS). When completed this assessment tool will provide researchers and clinicians with a valid and reliable method to describe computer keyboarding postures and kinematics.
The proposed study will be divided into two phases. Phase I will be devoted to developing and refining an instrument, the Pre-PeCKS, into a valid and reliable data gathering observational tool. In Phase II the Pre-PeCKS will be used to develop a predictive model that can discriminate between those with and without MSD-UE. The model developed will be used to select the construction and weighting of the subscales of the final instrument, the PeCKS.
Phase I - PeCKS psychometrics - reliability and validity Specific Aim 1: To evaluate inter- and intra-rater reliability and the concurrent criterion-related validity of the Pre-PeCKS.
H.1.1 The Pre-PeCKS will demonstrate acceptable reliability for the following tests:
H.1.1a. Intra-rater reliability (stability within one rater) H.1.1b. Inter-rater reliability (stability across raters) H.1.1c. Test of internal consistency (Cronbach's alpha) (stability across items)
H.1.2 The Pre-PeCKS will demonstrate good concurrent criterion-related validity - Parameters selected by raters using the Pre-PeCKS will significantly correlate with biomechanical measures (VICON™ motion recording and analysis system and force plate):
H.1.2.a. Angles and displacements identified by raters using the Pre-PeCKS will correlate with angles and displacements measured by the VICON™ motion recording and analysis system; H.1.2.b. Number of times spent performing actions as specified by raters using the Pre-PeCKS will correlate with number of times measured by a VICON™ motion recording and analysis system; H.1.2.c. Level of forceful keying as specified by raters using the Pre-PeCKS will correlate with levels of forceful keying measured with a force plate under the keyboard.
Phase II - PeCKS psychometrics - diagnostic tool development
Specific Aim 2: To use information gathered using the Pre-PeCKS to develop a diagnostic instrument that can identify those with and without MSD-UE. The major hypothesis related to Specific Aim 2 is:
H.2.1. Using information gathered with the Pre-PeCKS and knowing the disease outcome of the subjects, predictive models can be developed that discriminate between those who do and do not have MSD-UE.
This three-year study will be divided into two phases. Phase I will be devoted to developing and refining an instrument, the Pre-PeCKS, into a valid and reliable data gathering observational tool. In Phase II the Pre-PeCKS will be used to develop a predictive model that can discriminate between those with and without MSD-UE. The model developed will be used to select the construction and weighting of the subscales of the final instrument, the PeCKS. The specific aim of Phase I is to evaluate the inter- and intra- rater reliability and the concurrent criterion-related validity of the Pre-PeCKS; the specific aim of Phase II is to use information gathered using the Pre-PeCKS to develop a diagnostic instrument that can identify those with and without MSD-UE. In Phase I, 50 subjects will be digitally recorded while typing while at the same time the kinematics of their hands will be recorded using a VICON™ motion analysis system and a keyboard force plate. The video of the typing performance will be rated by independent raters using the Pre-PeCKS and reliability statistics will be calculated. Concurrent validity will be obtained by comparing the results of the VICON™ with the results of the Pre-PeCKS. In Phase II, 20 typists with MSD-UE and 20 typists without MSD-UE will be rated using the Pre-PeCKS. Variables from the Pre-PeCKS along with other variables of interest will be used to build models that can discriminate between those with and without MSD-UE. The best model will be used to assign weights to Pre-PeCKS parameters and to develop how subscores will be combined to best identify those with MSD-UE. This information will be integrated into the final tool, the PeCKS. The PeCKS can then be used to identify an individual who have keyboarding styles that have been associated with MSD-UE.
Inclusion Criteria:
Exclusion Criteria: - BMI greater than 30