Abstract: Mental Health, Substance Dependence, and Occupational Fit: Challenges and Opportunities for Social Work in the Workplace (Society for Social Work and Research 14th Annual Conference: Social Work Research: A WORLD OF POSSIBILITIES)

13507 Mental Health, Substance Dependence, and Occupational Fit: Challenges and Opportunities for Social Work in the Workplace

Schedule:
Saturday, January 16, 2010: 9:00 AM
Marina (Hyatt Regency)
* noted as presenting author
Karen Ann Rolf, PhD , University of Nebraska, Omaha, Assistant Professor, Omaha, NE
Rachel E. Roiblatt, PhD , University of Nebraska, Omaha, Assistant Professor, Omaha, NE
Background and Purpose:

Research has shown that sustained employment is particularly beneficial for individuals with behavioral health conditions because it enhances creation of identity through meaningful activities, socialization, and development of routines (Hvalsoe & Josephsson, 2003). Studies suggest the need for systematic interventions to promote success in the workplace, such as environmental modifications and maximizing control at work sites (Wilhelm, Kovess, Rios-Seidel, & Finch, 2004).

Social workers are uniquely equipped to design modifications for individuals with disabilities in work settings due to their understanding of the relationships between persons and their environments. Social workers thus bring a special perspective to the creation of accommodations that minimize the disability and maximize the ability of the individual. This perspective is particularly useful when working with individuals with mental illness.

At the same time, recent attention has been given to the notion that some mental health conditions may bring advantages in some workplaces. These specific conditions include Attention Deficit Disorder (ADD) (Honos-Webb, 2005), Attention Deficit Hyperactivity Disorder (ADHD) (Hollowell & Ratey, 1995), and Bipolar Disorder (Hershman & Lieb, 1998; Jamieson, 1996). Where these conditions can be matched to specific employment characteristics and interventions, it may be possible to maximize the successful employment of individuals who have mental illness (Krupa, 2007).

Methods:

The National Co-morbidity Survey Replication(2002) provides information on the patterns, predictors, and treatment of mental health disorders for 10,000 individuals. It provides DSM-IV-TR diagnoses, childhood and adult correlates of those disorders, health information and treatment information, and information on occupations.

Research questions:

1) What is the relationship between the identified mental health conditions (social phobia, depression, ADHD, and obsessive-compulsive disorder), work setting, and tenure?

2) What is the relationship between treatment for a mental health condition and occupational performance?

3) What is the relationship between occupational performance, mental health condition, and co-occurring substance dependence?

Multinomial Logistic Regression analyses were used to predict the relationship between mental health conditions, substance dependence disorders, occupation, and work histories controlling for childhood and adult demographic characteristics at each time period.

Results:

The results of this study showed a significant relationship between severity of mental health condition, substance dependence, and occupational instability. Treatment (counseling and psychopharmacological) mediated these effects. The clustering of occupation by mental health condition was also found.

Conclusions and Implications:

These findings suggest that individuals with mental illness cluster into occupations or are sorted into occupations by their characteristics. Therefore, social work interventions that maximize the “fit” of individuals with specific occupations and workplaces may be useful. An important question is whether individuals have sorted themselves into positions or whether they have been assigned to those positions based upon their presenting characteristics. Future research will examine the job trajectories of individuals with specific disabilities using these data.