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Original

Effectiveness of Vocational Problem-Solving Skills on Motivation and Job-Seeking Action Steps

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Pages 2309-2324 | Published online: 03 Jul 2009
 

Abstract

Most research on employment interventions focuses on job acquisition as the sole outcome measure, despite the fact that there are many intermediate steps to obtaining work. This article examines the impact of a vocational problem solving skills (VPSS) intervention to increase motivation and action step activities that lead to employment. Over a 1-year period between 1995 and 1996, a sample of 109 methadone maintained treatment clients were randomly assigned to either a 10-session vocational problem solving intervention (N = 62) or a time and attention control condition (N = 47). The Addiction Severity Index (ASI) and a Vocational Motivational Assessment Checklist (VMAC) were administered upon enrollment in the study and at 6 months postbaseline. The VMAC was completed on a biweekly basis over the 12-week intervention period. The VMAC measures both the behavioral actions to obtain employment (e.g., reading want ads, completing job applications) and client perceived motivation to obtain a job. There were no differences by condition in the level of motivation to secure employment and the number of job seeking activities during the intervention period. However, motivation to work and number of action steps did predict obtaining employment for the sample as a whole at the 6-month follow-up. Although the intervention did not increase motivation and job seeking activities, information regarding reasonable outcomes for this population of chronically unemployed persons was identified. Also, practical and methodological implications are discussed.

Additional information

Notes on contributors

Donna M. Coviello

Dr. Donna M. Coviello, Ph.D. is an Assistant Research Professor at the Center for Studies of Addiction at the University of Pennsylvania. She is currently the Principal Investigator on a NIDA-funded study that will develop, implement, and evaluate a manual-based intervention that integrates drug counseling with an employment intervention in a community-based Methadone Maintenance Treatment Program. She was the project director on a NIDA-funded study that assessed the impact of providing case management to methadone patients following discharge from treatment. Recent publications include the efficacy of different intensities of psychosocial treatment for cocaine addiction and employment interventions for methadone patients. Dr. Coviello has also been involved in HIV and family planning program evaluation, computerization of stage-based multi-risk behavioral interventions, smoking prevention/cessation programs, and other research related to the health of women and adolescents.

David A. Zanis

Dr. David A. Zanis, Ph.D. is a research associate professor in the graduate school of social work at the University of Maryland. He is also an adjunct assistant research professor of social welfare in the department of psychiatry, school of medicine, University of Pennsylvania. His professional interests focus on addictive disorders and the effectiveness of programs to provide treatment and prevention services. Currently, he is also the co-principal investigator of a 3-year, NIDA-funded grant to develop a cognitive, problem-solving theoretical model that simultaneously addresses addiction in relation to employment functioning. Dr. Zanis is founder and CEO of Clinical Outcomes Group, a health and social service management group for community services.

Kevin Lynch

Dr. Kevin G. Lynch, Ph.D. is Assistant Professor of Biostatistics in Psychiatry at the University of Pennsylvania Medical Center, where he is the Director of the Informatics Core of the Treatment Research Center. His methodology research is in the area of latent variable models, specifically, mixture models and diagnostics for mixture structure, models for zero-inflation, and latent class models for longitudinal data. His collaborative research is concerned with applications of statistical methods in psychiatry, particularly the use of latent variable models in diagnosis, and longitudinal studies of treatment and continuing care.

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