Thanks so much for your help O and P Lists!
Gerald Stark
Description
Collection
Title:
Thanks so much for your help O and P Lists!
Creator:
Gerald Stark
Date:
12/17/2016
Text:
Hey O and P List!
I want to thank everyone so much for their participation in my many surveys. My most recent one was for my doctoral dissertation “The relationship of the attributional dimensions of emotional differentiation on the attributional dimensions of technology readiness for orthotic and prosthetic clinicians.” I just realized I had never given the group a summary of the results like I promised.
The 50-question survey was posted for 14 days and had 230 respondents with 148 fully completing the survey and 23 additional comments. 78% were male and 22% were female with the mean number of years of experience at 20.9 years. When assessing their own skill 44% indicated they were “experts,” 32% said they were “specialists,” 23% were “intermediates,” and only one indicated themselves as a “novice.” In terms of demographics 56% were from private clinics, 22% were from corporate-owned offices, 11% were from hospital/rehabilitation centers, and 1.4% from institutional settings with 9.5% indicating they were from other settings. In terms of certification the largest groups were 47% were CPO’s, 26% were CP’s, and 22% CO’s.
The study used statistical correlation, regression, t-test, ANOVA with the Workplace Differentiation Inventory (WDI) and Technology Readiness index (TRI-2.0) with eight additional demographic factors such as gender, experience, technology self-assessent, high tech use, and office affiliation. Originally the WDI was the independent predictor variable and the TRI-2.0 was the dependent outcome variable, but this was checked by reversing the relationships.
There were several key findings. One was that there was a strong predictive relationship between emotional reactivity and emotional cutoff on technology optimism. This means that if individuals have frequent emotionally charged conflicts or stop talking, then the group is less likely to look at new innovation in a favorable light. This could impact the very survival of a small office to integrate not only new components, but new office management and reimbursement software.
The second was that technology optimism and innovation had a very strong predictive relationship on on emotional reactivity. This means that there was an even stronger relationship with technology use and the ability of the group to tolerate disharmony. A leader could use this by consistently introducing new technology and in time the group will learn to deal with it better and seek out their own innovations. The leader who challenges their group makes it healthier. This was even more important that attempting to get them to “get along” better in the previous finding.
A demographic key finding was there there was no significant relationships between gender, certification level, technology self-assessment, office affiliation, and years of experience with respect to technology readiness. This means that there were no difference in how innovative you are no matter your gender, how old you are, where you work, or even if you consider yourself innovative—it makes no difference. Your level of innovativeness depends on you!
Finally there were some slight differences with respect to Workplace Differentiation and office affiliation and years of experience. This indicates that people who work in larger facilities such as a hospital/rehab center recognize that they must attempt to harmonize with others and that there is a decline in positive attitude with experience, however there is an uptick to half of that initial positive attitude from 50 onward—so there is hope!
Once again thank you so much for your participation! The entire dissertation is at this link if you are interested: <URL Redacted>
Best regards,
Dr. Gerald Stark (still getting used to it!)
Gerald Stark, PhD, MSEM, CPO/L, FAAOP
(612) 270-7363 cell
<Email Address Redacted>
I want to thank everyone so much for their participation in my many surveys. My most recent one was for my doctoral dissertation “The relationship of the attributional dimensions of emotional differentiation on the attributional dimensions of technology readiness for orthotic and prosthetic clinicians.” I just realized I had never given the group a summary of the results like I promised.
The 50-question survey was posted for 14 days and had 230 respondents with 148 fully completing the survey and 23 additional comments. 78% were male and 22% were female with the mean number of years of experience at 20.9 years. When assessing their own skill 44% indicated they were “experts,” 32% said they were “specialists,” 23% were “intermediates,” and only one indicated themselves as a “novice.” In terms of demographics 56% were from private clinics, 22% were from corporate-owned offices, 11% were from hospital/rehabilitation centers, and 1.4% from institutional settings with 9.5% indicating they were from other settings. In terms of certification the largest groups were 47% were CPO’s, 26% were CP’s, and 22% CO’s.
The study used statistical correlation, regression, t-test, ANOVA with the Workplace Differentiation Inventory (WDI) and Technology Readiness index (TRI-2.0) with eight additional demographic factors such as gender, experience, technology self-assessent, high tech use, and office affiliation. Originally the WDI was the independent predictor variable and the TRI-2.0 was the dependent outcome variable, but this was checked by reversing the relationships.
There were several key findings. One was that there was a strong predictive relationship between emotional reactivity and emotional cutoff on technology optimism. This means that if individuals have frequent emotionally charged conflicts or stop talking, then the group is less likely to look at new innovation in a favorable light. This could impact the very survival of a small office to integrate not only new components, but new office management and reimbursement software.
The second was that technology optimism and innovation had a very strong predictive relationship on on emotional reactivity. This means that there was an even stronger relationship with technology use and the ability of the group to tolerate disharmony. A leader could use this by consistently introducing new technology and in time the group will learn to deal with it better and seek out their own innovations. The leader who challenges their group makes it healthier. This was even more important that attempting to get them to “get along” better in the previous finding.
A demographic key finding was there there was no significant relationships between gender, certification level, technology self-assessment, office affiliation, and years of experience with respect to technology readiness. This means that there were no difference in how innovative you are no matter your gender, how old you are, where you work, or even if you consider yourself innovative—it makes no difference. Your level of innovativeness depends on you!
Finally there were some slight differences with respect to Workplace Differentiation and office affiliation and years of experience. This indicates that people who work in larger facilities such as a hospital/rehab center recognize that they must attempt to harmonize with others and that there is a decline in positive attitude with experience, however there is an uptick to half of that initial positive attitude from 50 onward—so there is hope!
Once again thank you so much for your participation! The entire dissertation is at this link if you are interested: <URL Redacted>
Best regards,
Dr. Gerald Stark (still getting used to it!)
Gerald Stark, PhD, MSEM, CPO/L, FAAOP
(612) 270-7363 cell
<Email Address Redacted>
Citation
Gerald Stark, “Thanks so much for your help O and P Lists!,” Digital Resource Foundation for Orthotics and Prosthetics, accessed November 2, 2024, https://library.drfop.org/items/show/242688.
