Testing the Relationship of Burnout to Job Satisfaction for Psychiatric Rehabilitation Practitioners beyond Controlled-for Background Variables

Gary Blau

doi:10.5539/jedp.v10n2p52

Abstract

A Psychiatric Rehabilitation Practitioner (PRP) is a less-often studied rehabilitation counselor who works specifically with mental health patients. An on-line survey was filled out by 1,635 PRPs who provided background, burnout and job satisfaction data. Full data was available for 819 PRPs. Background data collected included: gender, race, age, highest education level, length of service, and salary. The study hypothesis that burnout would be negatively related to job satisfaction beyond the controlled-for background variables was supported. Although only a limited amount of job satisfaction variance was explained, the study results support continued study of burnout and job satisfaction for PRPs and other mental health professionals.

Highlights

A Psychiatric Rehabilitation Practitioner (PRP) is a type of rehabilitation counselor who works with mental health patients (Blankertz & Robinson, 1996)
The goal of this study was to test for the relationship of burnout to the job satisfaction of PRPs beyond controlled for background variables
In the Fall, 2012 PRPs filled out an online survey, including a section asking about backgrounds, burnout and job satisfaction

Summary

Introduction

A Psychiatric Rehabilitation Practitioner (PRP) is a type of rehabilitation counselor who works with mental health patients (Blankertz & Robinson, 1996). In a prior study of PRPs, Blankertz and Robinson (1996) found that burnout was negatively related to job satisfaction. The goal of this study was to test for the relationship of burnout to the job satisfaction of PRPs beyond controlled for background variables. Gender, race, age, education level, length of service and salary. Race/Ethnicity: Hispanic (3%), African American (11%), Caucasian (81%), Asian/Pacific Islander (3%), and other (2%) This was background information was recoded into Caucasian (81%), non-Caucasian (19%) for regression data analyses. Salary was indicated by most recent yearly salary in thousands (K) using the following categories: less than $20K (8%), 20K– 29,999 (14%), 30K–39,999 (21%), 40K–49,999 (16%), 50K–59,999 (13%), 60K–69,999 (9%), 70K–79,999 (6%), 80K–89,999 (5%), and over 90K (8%)

Objectives

Methods

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Discussion

Conclusion