Mitogen-activated protein kinases (MAPKs) are expressed in postmitotic neuronal cells of adult mammalian brain and are involved in the regulation of various cellular activities, including inducible gene expression. Recent data from this laboratory show that selective stimulation of metabotropic glutamate receptor 5 (mGluR5) activates a major subclass of MAPKs, extracellular signal-regulated protein kinase ( ERK), in striatal neurons. The activation of ERK was mediated partially through the mGluR5-associated signaling pathway, i. e., inositol-1,4,5-triphosphate (IP3 )-mediated Ca2+ release. More importantly, the member of Homer family, Homer1b/c, forms a central signaling pathway linking mGluR5 to ERK in a Ca2+ -independent manner. In addition, a major serine/threonine phosphatase, protein phosphatase 2A (PP2A), is also involved in the mGluR5 regulation of ERK phosphorylation. As an information superhighway between the surface membrane and the nucleus, ERK when co-activated by both IP3/Ca2+- and Homer1 b/c-dependent pathways showed the ability to phosphorylate two transcription factors, Elk-1 and cAMP response element-binding protein (CREB),and thereby facilitated c-Fos expression. Together, available data obtained from this laboratory and others indicate that mGluR5 possesses the ability to activate the ERK pathway in striatal neurons. A sophisticated signaling apparatus involving coordinated interactions between protein kinases and protein phosphatases mediates the mGluR5-ERK coupling imperative for the transcriptional regulation.

Purpose: The primary aim of this study is to validate the Blended Learning Usability Evaluation–Questionnaire (BLUE-Q) for use in the field of health professions education through a Bayesian approach. As Bayesian questionnaire validation remains elusive, a secondary aim of this article is to serve as a simplified tutorial for engaging in such validation practices in health professions education. Methods: A total of 10 health education-based experts in blended learning were recruited to participate in a 30-minute interviewer-administered survey. On a 5-point Likert scale, experts rated how well they perceived each item of the BLUE-Q to reflect its underlying usability domain (i.e., effectiveness, efficiency, satisfaction, accessibility, organization, and learner experience). Ratings were descriptively analyzed and converted into beta prior distributions. Participants were also given the option to provide qualitative comments for each item. Results: After reviewing the computed expert prior distributions, 31 quantitative items were identified as having a probability of “low endorsement” and were thus removed from the questionnaire. Additionally, qualitative comments were used to revise the phrasing and order of items to ensure clarity and logical flow. The BLUE-Q’s final version comprises 23 Likert-scale items and 6 open-ended items. Conclusion Questionnaire validation can generally be a complex, time-consuming, and costly process, inhibiting many from engaging in proper validation practices. In this study, we demonstrate that a Bayesian questionnaire validation approach can be a simple, resource-efficient, yet rigorous solution to validating a tool for content and item-domain correlation through the elicitation of domain expert endorsement ratings.

Purpose: To generate Cronbach’s alpha and further mixed methods construct validity evidence for the Blended Learning Usability Evaluation–Questionnaire (BLUE-Q). Methods: Forty interprofessional clinicians completed the BLUE-Q after finishing a 3-month long blended learning professional development program in Ontario, Canada. Reliability was assessed with Cronbach’s α for each of the 3 sections of the BLUE-Q and for all quantitative items together. Construct validity was evaluated through the Grand-Guillaume-Perrenoud et al. framework, which consists of 3 elements: congruence, convergence, and credibility. To compare quantitative and qualitative results, descriptive statistics, including means and standard deviations for each Likert scale item of the BLUE-Q were calculated. Results: Cronbach’s α was 0.95 for the pedagogical usability section, 0.85 for the synchronous modality section, 0.93 for the asynchronous modality section, and 0.96 for all quantitative items together. Mean ratings (with standard deviations) were 4.77 (0.506) for pedagogy, 4.64 (0.654) for synchronous learning, and 4.75 (0.536) for asynchronous learning. Of the 239 qualitative comments received, 178 were identified as substantive, of which 88% were considered congruent and 79% were considered convergent with the high means. Among all congruent responses, 69% were considered confirming statements and 31% were considered clarifying statements, suggesting appropriate credibility. Analysis of the clarifying statements assisted in identifying 5 categories of suggestions for program improvement. Conclusion The BLUE-Q demonstrates high reliability and appropriate construct validity in the context of a blended learning program with interprofessional clinicians, making it a valuable tool for comprehensive program evaluation, quality improvement, and evaluative research in health professions education.

Purpose: The primary aim of this study is to validate the Blended Learning Usability Evaluation–Questionnaire (BLUE-Q) for use in the field of health professions education through a Bayesian approach. As Bayesian questionnaire validation remains elusive, a secondary aim of this article is to serve as a simplified tutorial for engaging in such validation practices in health professions education. Methods: A total of 10 health education-based experts in blended learning were recruited to participate in a 30-minute interviewer-administered survey. On a 5-point Likert scale, experts rated how well they perceived each item of the BLUE-Q to reflect its underlying usability domain (i.e., effectiveness, efficiency, satisfaction, accessibility, organization, and learner experience). Ratings were descriptively analyzed and converted into beta prior distributions. Participants were also given the option to provide qualitative comments for each item. Results: After reviewing the computed expert prior distributions, 31 quantitative items were identified as having a probability of “low endorsement” and were thus removed from the questionnaire. Additionally, qualitative comments were used to revise the phrasing and order of items to ensure clarity and logical flow. The BLUE-Q’s final version comprises 23 Likert-scale items and 6 open-ended items. Conclusion Questionnaire validation can generally be a complex, time-consuming, and costly process, inhibiting many from engaging in proper validation practices. In this study, we demonstrate that a Bayesian questionnaire validation approach can be a simple, resource-efficient, yet rigorous solution to validating a tool for content and item-domain correlation through the elicitation of domain expert endorsement ratings.

Purpose: To generate Cronbach’s alpha and further mixed methods construct validity evidence for the Blended Learning Usability Evaluation–Questionnaire (BLUE-Q). Methods: Forty interprofessional clinicians completed the BLUE-Q after finishing a 3-month long blended learning professional development program in Ontario, Canada. Reliability was assessed with Cronbach’s α for each of the 3 sections of the BLUE-Q and for all quantitative items together. Construct validity was evaluated through the Grand-Guillaume-Perrenoud et al. framework, which consists of 3 elements: congruence, convergence, and credibility. To compare quantitative and qualitative results, descriptive statistics, including means and standard deviations for each Likert scale item of the BLUE-Q were calculated. Results: Cronbach’s α was 0.95 for the pedagogical usability section, 0.85 for the synchronous modality section, 0.93 for the asynchronous modality section, and 0.96 for all quantitative items together. Mean ratings (with standard deviations) were 4.77 (0.506) for pedagogy, 4.64 (0.654) for synchronous learning, and 4.75 (0.536) for asynchronous learning. Of the 239 qualitative comments received, 178 were identified as substantive, of which 88% were considered congruent and 79% were considered convergent with the high means. Among all congruent responses, 69% were considered confirming statements and 31% were considered clarifying statements, suggesting appropriate credibility. Analysis of the clarifying statements assisted in identifying 5 categories of suggestions for program improvement. Conclusion The BLUE-Q demonstrates high reliability and appropriate construct validity in the context of a blended learning program with interprofessional clinicians, making it a valuable tool for comprehensive program evaluation, quality improvement, and evaluative research in health professions education.

Purpose: The primary aim of this study is to validate the Blended Learning Usability Evaluation–Questionnaire (BLUE-Q) for use in the field of health professions education through a Bayesian approach. As Bayesian questionnaire validation remains elusive, a secondary aim of this article is to serve as a simplified tutorial for engaging in such validation practices in health professions education. Methods: A total of 10 health education-based experts in blended learning were recruited to participate in a 30-minute interviewer-administered survey. On a 5-point Likert scale, experts rated how well they perceived each item of the BLUE-Q to reflect its underlying usability domain (i.e., effectiveness, efficiency, satisfaction, accessibility, organization, and learner experience). Ratings were descriptively analyzed and converted into beta prior distributions. Participants were also given the option to provide qualitative comments for each item. Results: After reviewing the computed expert prior distributions, 31 quantitative items were identified as having a probability of “low endorsement” and were thus removed from the questionnaire. Additionally, qualitative comments were used to revise the phrasing and order of items to ensure clarity and logical flow. The BLUE-Q’s final version comprises 23 Likert-scale items and 6 open-ended items. Conclusion Questionnaire validation can generally be a complex, time-consuming, and costly process, inhibiting many from engaging in proper validation practices. In this study, we demonstrate that a Bayesian questionnaire validation approach can be a simple, resource-efficient, yet rigorous solution to validating a tool for content and item-domain correlation through the elicitation of domain expert endorsement ratings.

Purpose: To generate Cronbach’s alpha and further mixed methods construct validity evidence for the Blended Learning Usability Evaluation–Questionnaire (BLUE-Q). Methods: Forty interprofessional clinicians completed the BLUE-Q after finishing a 3-month long blended learning professional development program in Ontario, Canada. Reliability was assessed with Cronbach’s α for each of the 3 sections of the BLUE-Q and for all quantitative items together. Construct validity was evaluated through the Grand-Guillaume-Perrenoud et al. framework, which consists of 3 elements: congruence, convergence, and credibility. To compare quantitative and qualitative results, descriptive statistics, including means and standard deviations for each Likert scale item of the BLUE-Q were calculated. Results: Cronbach’s α was 0.95 for the pedagogical usability section, 0.85 for the synchronous modality section, 0.93 for the asynchronous modality section, and 0.96 for all quantitative items together. Mean ratings (with standard deviations) were 4.77 (0.506) for pedagogy, 4.64 (0.654) for synchronous learning, and 4.75 (0.536) for asynchronous learning. Of the 239 qualitative comments received, 178 were identified as substantive, of which 88% were considered congruent and 79% were considered convergent with the high means. Among all congruent responses, 69% were considered confirming statements and 31% were considered clarifying statements, suggesting appropriate credibility. Analysis of the clarifying statements assisted in identifying 5 categories of suggestions for program improvement. Conclusion The BLUE-Q demonstrates high reliability and appropriate construct validity in the context of a blended learning program with interprofessional clinicians, making it a valuable tool for comprehensive program evaluation, quality improvement, and evaluative research in health professions education.