Abstract
The following portfolio is a compilation of proposals and applied projects that utilize SIOP competencies expected of I/O practitioners. The current competencies covered in this portfolio primarily touch upon the concepts of Diversity, Equity, Inclusion, & Accessibility (DEIA), Statistical Analysis & Data Analysis, Training & Development, and Job Analysis & Competency Modeling.
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The DEIA competency is fulfilled with a qualitative analysis that thematically coded 14 interviewees to examine the underlying shared experiences of caretakers of children with autism. The resulting project gives insights on the ways in which organizations may not consider accommodations for their employees who come from marginalized populations. Future research done on the topic may examine the all-female sampleset that was gathered despite no conditions barring caretaker identities and examining the ways in which caretaking responsibilities over a child with autism differs from other special-needs children.
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The statistical analysis competency is fulfilled with a quantitative analysis done on the Shortened Dark Triad that goes through the item development process by running a factor analysis, SEM, and CTT and IRT analyses to flag problematic items that warrant some further investigation if the scale were to be developed further. The resulting project demonstrates my ability to work with a large dataset, filter the dataset to increase the trustworthiness of subsequent analyses, and make recommendations of scale items based on the various analyses conducted.
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This training and development competency is fulfilled through a training proposal focused on identifying and retaining individuals who serve as central nodes toward an organization's social network through usage of Big Data gathered from an organization's knowledge management system. The proposal goes into the theoretical basis of the social network analysis perspective to note key centrality characteristics, how those characteristics may be detected within a virtual environment, and the outcome of training managers to identify these individuals. The hope of this training proposal is to identify individuals for future professional development while highlighting the importance of supporting a diverse workforce.
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The job analysis competency is fulfilled by a report that details a job analysis on nurses. For this analysis, preliminary research was conducted through sourcing data from the Department of Labor and O*NET. From the data gathered there, interview questions were formulated and an interview was conducted with a subject matter expert (SME). After the interview was conducted, the results of the interview were used to develop a Qualtrics survey that was distributed to 7 SMEs total. The report breaks down the KSAs and Duty Areas identified through interview and survey data to define the roles and responsibilities expected of nurses and the required characteristics to succeed in patient care.
From these products, I hope to demonstrate my comprehensive ability to utilize various psychometrically rigorous techniques while also working toward creating equitable conditions for those most marginalized.
Introduction
When reflecting upon the progression of DEI throughout the late 2010's up until today, research has still much to learn to more consistently facilitate the successful integration of diverse workforces.
This portfolio reviews various SIOP competencies with the overall intention to demonstrate my abilities to integrate both quantitative and qualitative data to inform proposals and applied projects that are aimed toward improving outcomes for marginalized populations within an organization.
SIOP Competencies
Caretakers Study
Dark Triad Analysis
Training Proposal
Nurse Job Analysis
Diversity, Equity, Inclusion & Accessibility
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X
Occupational Health, Safety, & Well-Being
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Statistical Analysis & Data Analysis
X
Training & Development
X
Technology Integration & Workplace Evolution
X
Career Development
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X
Job Analysis & Competency Modeling
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Personnel Recruitment, Selection, and Placement
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Experiences of Caretakers of Children with Autism
Summary
As a co-lead to this qualitative study, I involved myself throughout the various processes of thematic coding. These processes were the verifying interview transcripts for accuracy, establishing the thematic codebook utilized in NVivo qualitative coding, coding half of the study’s interviews according to the research question, scheduling and holding interrater reviews to ensure quality of codes identified, guiding the establishment of themes, subthemes, and outcomes observed throughout the various caretakers interviewed, and the presentation of research findings at research conferences such as SIOP 2026. This project relates to the DEIA SIOP competency as it explores the experience of marginalized populations whose insights may potentially expand beyond to other special-needs caretakers while also seeking to expand understanding on the exact challenges organizations should address if they wish to create a more inclusive and equitable workplace.
16 90-minute interviews were collected from participants responding to a recruitment flyer for caretakers of children with autism. As interviews were done, transcriptions were generated through OtterAI and were reviewed for accuracy, making adjustments to the transcription text as necessary. After the transcriptions were compiled, a thematic codebook was established referencing literature related to work-life conflict literature due to the research question exploring the impacts of autistic childcare on the caretaker’s career. This thematic codebook was intended to be loose, as the study intended to use an inductive, latent level approach. All interviews were then thematically coded, with individual codes being cross-referenced with at least one other coder through interrater reviews. Once all interviews underwent coding and interrater reviews, the identified texts were compiled into a document to form themes, subthemes, and outcomes based on the shared experiences noted by various caretakers. For the themes, subthemes, and outcomes, quotes were reviewed to capture the sentiments in a research poster presentation.
Process Overview
Special acknowledgements: Elan Martin, Chris Trudeaux, Susan Saephan, David Medina Zepeda, Jocelyn Muñoz Lozano, Ciobha McKeown, & Catherine Warren
Item Analysis on the Shortened Dark Triad
This project utilizes data pulled from an open-source psychometrics site, allowing for larger-scale analyses to be run. In this video demo, I go over the general screening processes I take when processing raw datasets and utilizing that filtered dataset to run factor analyses, an SEM analysis, and a CTT and IRT perspective on the items. This project relates to the statistical methods and data analysis SIOP competency as I reviewed scale items, ran analyses to determine the appropriate number of factors and explored model fit, and ran CTT and IRT analyses that identify weaker items within the scale that would be replaced for stronger items within organizational assessment contexts. This project also utilizes a large, archival data set that would be more typically found in organizational settings.
Process Overview
Summary
Data from the Shortened Dark Triad scale was pulled from open-source psychometrics projects online (n = ). From this dataset, I ran screening using the R careless package based on missing responses and longstring answers, determining screening points based on the larger dataset and the maximum reasonable longstring based on the scale’s formatting. A factor analysis and SEM was conducted, in line with the original Jones & Paulhus (2013) study to determine factors and model fit. I discuss the model fit and potential explanations comparing the original study’s model fit and the results of this analysis. Additional CTT and IRT analyses were run to identify items that discriminate individuals scores the most and an item-by-item overview of test items to determine low information items. A few example flagged items are discussed to talk about the item’s curve characteristics and suggested courses of action.
Training Proposal for Social Network Centrality Identification
Summary
This training proposal focused on the selection of individuals for future career development based on a DEI and social networks analysis perspective.The proposal incorporates a DEI perspective, as it discusses communication transfer between nodes within an organizational network, and notes the possible clustering of nodes based on marginalized identities connected with similar nodes. The proposal then reviews the types of social network connection models, centrality characteristics of interest, and how organizations may utilize Big Data sources to select employees for further development in decentralized work contexts. The proposal hypothesizes that the incorporation of data from communities of practice present within organizational knowledge management systems may allow for organizations to get more from the diversity within the organization through acknowledging their presence within their communities and providing meaningful career development opportunities.
The proposal begins by discussing the issue faced by multinational organizations–its decentralized nature may not make it clear which employees are good candidates for future organizational development through career development opportunities. Utilizing a social networks perspective, the proposal discusses the expected type of model and clustering that may be expected for people within marginalized communities within an organization. We then discuss centrality characteristics and what we may expect based on the model identified in the previous step. The proposal then links these centrality characteristics to possible markers within an organization’s knowledge management system and communities of practice that managers may use to identify individuals who seem centralized within a cluster of an organization’s social network.Organizations may then use that data to decide the ways in which they can provide more opportunities to develop the skillsets of their diversified workforce to reaffirm their commitment toward DEIA within the workplace.
Process Overview
Summary
This project was a job analysis based on data collected from nurses at Dignity Health in Woodland, CA. Utilizing data gathered from O*NET and the Department of Labor, interview questions were formulated and an interview was conducted with a subject matter expert (SME). Based on information from databases and this interview, a Qualtrics survey was created detailing knowledge, skills, and abilities (KSAs) and tasks related to the profession of nurses. The report concludes by discussing KSAs universal for the position of nurse and linking competencies identified to duty area success.
Process Overview
Data regarding the KSAs and tasks expected of nurses was gathered through searching the term “registered nurse” on the O*NET and in the U.S. Department of Labor’s website. Interview questions were then created with the intention of identifying additional KSAs and defining the duty areas of nurses. Once the SME interview was completed, KSAs and duty areas, along with their associated tasks, were listed in a Qualtrics survey that asked participants to rate items based on frequency, importance, and necessity upon entry for KSAs and duty areas. Participants additionally had the option to identify additional KSAs they believed were relevant to the profession of nursing, with items being added after verifying with the initially-interviewed SME. The data collected led to the identification of KSAs into competencies, which were filtered alongside duty areas based on criticality scores detailed in the report. A subsequent Qualtrics survey was sent out asking participants to rate individual KSAs across the competencies with duty areas to create Task-KSA linkages between characteristics of nurses and the ability to perform necessary job duties.