INS NYC 2024 Program

Poster	Poster Session 09 Program Schedule 02/16/2024 03:30 pm - 04:45 pm Room: Shubert Complex (Posters 1-60) Poster Session 09: Epilepsy \| Oncology \| MS \| Infectious Disease Final Abstract #54 Predictors of Employment Decline in People with Multiple Sclerosis Michael Jaworski III, University at Buffalo, Buffalo, United States Jacob Balconi, University at Buffalo, Buffalo, United States Omid Mirmosayyeb, University at Buffalo, Buffalo, United States Dejan Jakimovski, University at Buffalo, Buffalo, United States Niels Bergsland, University at Buffalo, Buffalo, United States Bianca Weinstock-Guttman, University at Buffalo, Buffalo, United States Ralph Benedict, University at Buffalo, Buffalo, United States Category: Multiple Sclerosis/ALS/Demyelinating Disorders Keyword 1: vocation Keyword 2: cognitive functioning Keyword 3: multiple sclerosis Objective: Multiple Sclerosis (MS) is a chronic autoimmune disease affecting the central nervous system, often challenging individuals' employment due to its unpredictable symptoms. Employment is a critical aspect of individuals' lives, providing financial stability, social independence, and a sense of purpose. Understanding predictors of job loss and work deterioration in People with MS (PwMS) is vital for developing effective interventions. Participants and Methods: Over approximately three years (2.8±2.2) we assessed 186 employed PwMS at two timepoints to investigate employment outcomes. At both visits we used the Buffalo Vocational Monitoring Survey (BVMS) to evaluate employment status and related variables, including MS-specific factors. Baseline cognitive functioning was assessed using the Brief International Cognitive Assessment for MS which includes the Symbol Digit Modalities Test (SDMT), Brief Visuospatial Memory Test-Revised (BVMT-R), and the California Verbal Learning Test-II (CVLT). We also administered the Beck Depression Inventory Fast-Screen (BDI-FS) and Fatigue Severity Scale (FSS). We employed two binary logistic regression models: one for predicting complete job loss (e.g., full-time to unemployed) and the other for work deterioration, such as a decrease in work status (e.g., full-time to part-time) or an increase in negative work events among PwMS, relative to their stable counterparts. Subsequent post-hoc analyses compared baseline employment characteristics between work-deteriorated and work-stable PwMS. Results: At follow-up, 73.1% of PwMS were classified as work-stable, 14.0% were work-deteriorated, and 12.9% fell into the work-loss category. The first model predicting complete job loss in PwMS was significant (p = .004) accounting for 46% of variance (Nagelkerke R² = 0.460). CVLT-Total (OR = 1.325, p = 0.009), CVLT-Delay (OR = 0.405, p = 0.014), BVMT-Total (OR = 0.700, p = 0.010), and BVMT-Delay (OR = 2.092, p = 0.064) were associated with higher odds of employment loss at follow-up. The second model predicting work-deterioration was significant (p = .001) and accounted for 28.4% of variance (Nagelkerke R2 = .284). Fatigue was the only significant predictor of work deterioration (OR = 2.37, p = .003) in employed PwMS. Subsequent post-hoc analyses were performed and identified differences in baseline employment characteristics between work-stable and work-deteriorated PwMS. Those in the work deterioration group experienced higher rates of absenteeism (p < .001), were more likely to use work accommodations (p < .001), and disclose their disease to employers (p = .033) compared to their work-stable counterparts. Notably, the work-deterioration group most commonly experienced verbal criticism for errors (20%), formal disciplinary actions from their employer (12%), and mandatory reduced work hours (12%). Conclusions: This study underscores the role of cognitive factors, particularly verbal and visual memory, in predicting job loss in PwMS, replicating past findings. Furthermore, we reveal a multifaceted interplay of factors, including fatigue, workplace dynamics (e.g., accommodations, disease related absenteeism, and disease disclosure), and negative work events, contributing to work deterioration and eventual job loss in PwMS. This underscores the importance of implementing early interventions to ensure employment stability. Furthermore, the BVMS stands out as a valuable tool for early detection, enabling proactive support to at risk PwMS.

Poster

02/16/2024
03:30 pm - 04:45 pm
Room: Shubert Complex (Posters 1-60)

Poster Session 09: Epilepsy | Oncology | MS | Infectious Disease

Final Abstract #54

Predictors of Employment Decline in People with Multiple Sclerosis

Michael Jaworski III, University at Buffalo, Buffalo, United States
Jacob Balconi, University at Buffalo, Buffalo, United States
Omid Mirmosayyeb, University at Buffalo, Buffalo, United States
Dejan Jakimovski, University at Buffalo, Buffalo, United States
Niels Bergsland, University at Buffalo, Buffalo, United States
Bianca Weinstock-Guttman, University at Buffalo, Buffalo, United States
Ralph Benedict, University at Buffalo, Buffalo, United States

Category: Multiple Sclerosis/ALS/Demyelinating Disorders

Keyword 1: vocation
Keyword 2: cognitive functioning
Keyword 3: multiple sclerosis

Objective:

Multiple Sclerosis (MS) is a chronic autoimmune disease affecting the central nervous system, often challenging individuals' employment due to its unpredictable symptoms. Employment is a critical aspect of individuals' lives, providing financial stability, social independence, and a sense of purpose. Understanding predictors of job loss and work deterioration in People with MS (PwMS) is vital for developing effective interventions.

Participants and Methods:

Over approximately three years (2.8±2.2) we assessed 186 employed PwMS at two timepoints to investigate employment outcomes. At both visits we used the Buffalo Vocational Monitoring Survey (BVMS) to evaluate employment status and related variables, including MS-specific factors. Baseline cognitive functioning was assessed using the Brief International Cognitive Assessment for MS which includes the Symbol Digit Modalities Test (SDMT), Brief Visuospatial Memory Test-Revised (BVMT-R), and the California Verbal Learning Test-II (CVLT). We also administered the Beck Depression Inventory Fast-Screen (BDI-FS) and Fatigue Severity Scale (FSS). We employed two binary logistic regression models: one for predicting complete job loss (e.g., full-time to unemployed) and the other for work deterioration, such as a decrease in work status (e.g., full-time to part-time) or an increase in negative work events among PwMS, relative to their stable counterparts. Subsequent post-hoc analyses compared baseline employment characteristics between work-deteriorated and work-stable PwMS.

Results:

At follow-up, 73.1% of PwMS were classified as work-stable, 14.0% were work-deteriorated, and 12.9% fell into the work-loss category. The first model predicting complete job loss in PwMS was significant (p = .004) accounting for 46% of variance (Nagelkerke R² = 0.460). CVLT-Total (OR = 1.325, p = 0.009), CVLT-Delay (OR = 0.405, p = 0.014), BVMT-Total (OR = 0.700, p = 0.010), and BVMT-Delay (OR = 2.092, p = 0.064) were associated with higher odds of employment loss at follow-up. The second model predicting work-deterioration was significant (p = .001) and accounted for 28.4% of variance (Nagelkerke R2 = .284). Fatigue was the only significant predictor of work deterioration (OR = 2.37, p = .003) in employed PwMS. Subsequent post-hoc analyses were performed and identified differences in baseline employment characteristics between work-stable and work-deteriorated PwMS. Those in the work deterioration group experienced higher rates of absenteeism (p < .001), were more likely to use work accommodations (p < .001), and disclose their disease to employers (p = .033) compared to their work-stable counterparts. Notably, the work-deterioration group most commonly experienced verbal criticism for errors (20%), formal disciplinary actions from their employer (12%), and mandatory reduced work hours (12%).

Conclusions:

This study underscores the role of cognitive factors, particularly verbal and visual memory, in predicting job loss in PwMS, replicating past findings. Furthermore, we reveal a multifaceted interplay of factors, including fatigue, workplace dynamics (e.g., accommodations, disease related absenteeism, and disease disclosure), and negative work events, contributing to work deterioration and eventual job loss in PwMS. This underscores the importance of implementing early interventions to ensure employment stability. Furthermore, the BVMS stands out as a valuable tool for early detection, enabling proactive support to at risk PwMS.