The Impact of Organizational Factors on Burnout among Rural Mental Health Staff

 

Thomas J. DeStefano, Henry Clark & Thomas Potter

 

 

ABSTRACT

 

The purpose of this study was to determine the extent to which organizational factors as measured by the Work Environment Scale predicted with burnout among professional and paraprofessional staff employed by rural mental health agencies.  Participants in this assessment included 742 staff employed in rural mental health centers.  Results indicated that specific organizational factors contribute to the experience of burnout among rural mental health professionals, and that the factors that contributes to burnout varied by occupational category.

 

 

 

INTRODUCTION

 

Mental health agencies are labor-intensive organizations and the vast majority of a mental health agency budget goes to salaries and other human resource costs (Lewis, Lewis, Packard & Souflee, 2001).  Hiring and retaining effective professionals and paraprofessionals are significant components to the success of any mental health agency and the most critical component in the delivery of mental health and substance abuse services.  The National Council for Community Behavioral Health Care reports a consistent increase in demand for behavioral health services nationwide (2002).  However the Council’s 2002 Survey of Behavioral Healthcare Providers indicates that as the demand for services increases, so too does the annual turnover rates of direct service behavioral healthcare professionals. 

 

 In many rural areas, the recruitment and retention of qualified Mental Health professionals is a challenging task (Merwin, Hinton, Dembling & Stern, 2003).  This staff resource challenge was demonstrated in a recent human resource assessment of 858 rural mental health workers (DeStefano, Petersen, Potter & Zweig, 2003). This assessment found that the majority of workers surveyed (73%) had been with a specific agency for three years or less, while only 10% have been with a specific agency for 8 years or more.

 

Though low salaries are often referenced as a factor in attrition, Balloch, Pahl, & McLean (1998) describe aspects associated with workplace stress, job dissatisfaction, lack of promotion opportunities, and conflict with supervisors and administration as contributing to workplace attrition.  Schaufeli, Maslach, & Marek (1993) found staff “burnout” also to be a major contributor to mental health counselor attrition. 

Maslach & Leiter (1997) describe burnout as the result of three factors: high states of Emotional Exhaustion, feelings of low personal accomplishment from ones work, and a sense of Depersonalization towards one’s clients.  Maslach and Leiter claim the root causes of burnout are due to work overload, organization conflict and mistrust, a perceived lack of control, and a perception of insufficient rewards for the work completed.

 

Cherniss (1980) also reports that burnout may be caused by a combination of organizational, cultural and individual factors. Johnson and Stone (1987) have defined burnout as a state of emotional, mental and physical exhaustion resulting from working with people experiencing emotionally demanding situations.

Several studies have indicated that staff employed in Rural Mental health agencies are at significant risk of burnout.  Kee, Johnson and Hunt (2002) found 65% of 513 rural mental health counselors surveyed scored at the moderate level or greater in burnout.  The study also found that a lack of social support specifically in the areas of guidance, reassurance of worth, social integration, and attachment were associated with high levels of burnout among this sample of rural mental health counselors.

 

 DeStefano et al. (2003) found 31.2% of various professional and paraprofessional staff surveyed scored in the medium range or higher for all three Maslach Burnout Inventory (MBI) sub-scales.  Comparisons of this sample to a MBI general norm group of mental health workers yielded contrasting findings.  Rural participants experienced significantly higher levels of Emotional Exhaustion than the norm group coupled with significantly higher levels of Personal Accomplishment.  There were no differences in the sub-scale Depersonalization.

 

Mental health agencies cannot afford the loss of productivity caused by workplace stress, burnout and staff attrition.  The mental health field must find the organizational factors contributing to these employee-related issues seek solutions to these problems and develop industry wide strategies to reduce burnout and staff attrition.

 

 

METHODOLOGY

 

The purpose of this study was to determine the organizational factors associated with employee burnout among professional and paraprofessional staff employed by rural mental health agencies.

 

Participants

 

Participants in this study included 742 paraprofessional and professional staff including 221 Therapists and Social Workers, 121 Case Managers, 242 Behavioral Health Technicians and paraprofessionals, 17 psychiatrists, 37 Nurses and 104 program directors and administrators. This sample consisted of 214 males (28.8%), 510 females (68.7%), with 18 not reporting sex (2.5%). The age ranged between 21 and 72 years of age with an average age of 42.5 years.  This sample was comprised of 517 Caucasians (69.67), 21 African Americans (2.8%), 75 Hispanic Americans (10.1%), 22 Native Americans (2.9%), 4 Asian/Pacific Islanders (.5%), 16 participants self-identified as being multicultural (2.1%), 12 reported other (1.6%) and 75 participants did not identify there ethnicity (10.1%).  All participants were employees of Arizona rural mental health agencies.  All participation was voluntary and participants were required to sign a consent form prior to their Involvement with the project.  The assessment of organizational factors on burnout was conducted as part of a larger project which also explored areas of job satisfaction, employee retention and other human resource issues (DeStefano et al., 2003) 

 

Measures

 

Demographic Questionnaire

 

A demographic questionnaire was designed to collect relevant background information on position title, agency, sex, ethnicity, and age of participants.

 

The Maslach Burnout Inventory (MBI)

 

The MBI developed by Maslach and Jackson, & Leiter (1996) is a 22 item standardized instrument that measures three aspects of an individual’s experience of the burnout syndrome: Emotional Exhaustion, Depersonalization, and lack of personal accomplishment.  The MBI determines the degree of burnout on a continuum ranging from low, average to high.  Participants are asked to respond to each of the 22 items through a six-point Likert scale. High degree of burnout is considered if sub-scores are in the upper third of the normative distribution.

 

Reliability was determined by Cronbach’s alpha coefficient (n = 1316) to be .90 for Emotional Exhaustion, .79 for Depersonalization, and .71 for personal accomplishment. Test-retest reliability was assessed with social welfare professionals and administrators (n = 53) over two to four week periods.   Reliability coefficients were found to be .82 for Emotional Exhaustion, .60 for Depersonalization and .80 for Personal Accomplishment. Test-Rest reliabilities for three, six, and eight months were between .59-.74 for Emotional Exhaustion, .50-.72 for Depersonalization, and .62-.65 for Personal Accomplishment.

 

Maslach and Jackson & Leiter (1996) found that high levels of burnout lead to employee absenteeism, attrition, poor morale, and deterioration of client care. Convergent validity was established by correlating the Maslach scores of the individual with ratings by a judge who knew the individual well.  Scores for the inventory were correlated with the presence of job characteristics and other outcomes related to burnout.

 

Discriminate Validity was demonstrated by the low correlation between the MBI and other job satisfaction scales.

 

The Work Environment Scales

 

The Real Form (WES).  The WES, developed by Moos (1994), is a 90 item instrument designed to measure an employee’s perception of their current work environment.  All 90 items are answered as true or false. The WES measures three dimensions: Relationship, Personal Growth, and System Maintenance and Change, and ten sub-scales; Involvement, Coworker Cohesion, Supervisor Support, Autonomy, Task Orientation, Work Pressure, Clarity, Managerial Control, Innovation, and Physical Comfort.

 

Test-retest reliability was determined with 75 workers in four work groups. The range of reliabilities was .69 for clarity to .83 for Involvement. Stability was measured by re-testing from 1 to 10 years. The 1-year coefficients ranged from .55 to .64. The 10-year range is .32 to .56. The 10 sub-scales inter-correlate but also measure distinct aspects of work environment.  Inter-correlations were shown to account for less than 10% of the sub-scale variance. The internal consistencies of the sub-scales varied from .66 to .84 for Nurses and from .60 to .84 for teachers.

 

 

RESULTS

 

Results for Emotional Exhaustion

 

Data were analyzed using stepwise multiple regression analyses with Emotional Exhaustion as the criterion variable and the ten subscales of the WES as predictor variables for each of the six occupational groups.

 

Therapists and Social WorkersThree workplace variables entered the equation as significant predictors of Emotional Exhaustion accounting for 30.7% of the variance (F (3, 219) = 32.338, p<.001).   The first variable to enter was Work Pressure which accounted for 23.2% of the variation in Emotional Exhaustion (F (1, 221) = 66.69, p<.001).  Task Orientation entered on the second step and accounted for an additional 6.2% of the variance (F (1, 220) = 19.248, p<.001).   This was followed by Involvement accounting for 1.3% of the variance (F (1, 219) = 4.218, p<.05).

 

Case Managers: Three workplace variables entered the equation as significant predictors of Emotional Exhaustion accounting for 34.9% of the variance (F (3, 119) = 21.289, p<.001).   The first variable to enter was Work Pressure which accounted for 20.7% of the variation in Emotional Exhaustion (F (3, 119) = 21.289, p<.001).  Task Orientation entered on the second step and accounted for an additional 10.5% of the variance (F (1, 120) = 18.368, p<.001).   This was followed by Involvement accounting for 3.7% of the variance (F (1, 119) = 6.809, p<.01).

 

Behavioral Health Technicians and other Paraprofessionals: Five workplace variables entered the equation as significant predictors of Emotional Exhaustion accounting for 37.9%of the variance (F (5, 238) = 29.024, p<.001).   The first variable to enter was Work Pressure which accounted for 20.7% of the variation in Emotional Exhaustion (F (1, 242) = 89.579, p<.001).  Clarity entered on the second step and accounted for an additional 6.7% of the variance (F (1, 241) = 24.374 p<.001).   This was followed by Control accounting for 1.7% of the variance (F (1, 240) = 6.277, p<.05), Comfort accounting for 1.4% of the variance in EE (F (1, 239) = 5.223, p=.05), and Supervisor Support accounting for 1.1% of the variance (F (1, 238) = 4.171, p<.05).

 

Psychiatrists: Two workplace variables entered the equation as significant predictors of Emotional Exhaustion accounting for 60% of the variance (F (2, 16) = 12.014, p<.001).   The first variable to enter was Innovation which accounted for 34.3% of the variation in Emotional Exhaustion (F (1, 17) = 8.860, p<.001).  Work Pressure entered on the second step and accounted for an additional 25.7% of the variance (F (1, 16) = 10.313, p<.001).

 

Nurses: Two workplace variables entered the equation as significant predictors of Emotional Exhaustion accounting for 36.6%of the variance (F (2, 36) = 10.410, p<.001.   The first variable to enter was Work Pressure which accounted for 21.8% of the variation in Emotional Exhaustion (F (1, 37) = 10.301, p<.001).  Involvement entered on the second step and accounted for an additional 14.9% of the variance (F (1, 36) = 8.466, p<.01).

 

Program Directors and Administrators: Two workplace variables entered the equation as significant predictors of Emotional Exhaustion accounting for 34.4%of the variance (F (2, 103) = 26.995, p<.001).  The first variable to enter was Work Pressure which accounted for 28% of the variation in Emotional Exhaustion (F (1, 104) = 40.412, p<.001).  Clarity entered on the second step and accounted for an additional 6.4% of the variance (F (1, 103) =10.058 p<.001). 

 

A summary table for multiple regressions for Emotional Exhaustion is presented in Table 1.

 

Table 1

Stepwise Regression

WES scales & Emotional Exhaustion

Occupation Group

Variance

Total

Step 1

Step 2

Step 3

Step 4

Step 5

 

Therapists  Social Workers

R2

 

.307

F 3/219=

32.338***

Work Pressure

.232

F 1/221=

66.69***

Task Orientation

.062

F 1/220=

19.248****

 

Involvement

.013

F 1/119=

4.218*

                

 

Case Managers

R2

.349

F 3/119=

21.289****

 

Work Pressure

.207

F 1/121=

31.53****

Task Orientation

.105

F 1/120

18.368****

Comfort

.037

F 1/119=

6.809**

 

 

Behavioral Health Technicians

R2

.379

F 5/238=

29.995****

 

Work Pressure

.270

F 1/242=

89.579****

Clarity

 

.067

F 1/241=

24.374****

Control

 

.017

F 1/240=

6.277*

Comfort

 

.014

F 1/239=

4.171*

Supervisor

Support

.011

F 1/238=

4.171*

Psychiatrists

 

R2

.600

F 2/16=

12.014****

 

Innovation

.343

F 1/17=

8.860***

Work Pressure

.257

F 1/16=

10.313***

 

 

 

Nurses

R2

.366

F 2/36=

10.410****

 

Work Pressure

.218

F 1/37=

10.301****

Involvement

.149

F 1/36=

.466**

 

 

 

Program Directors & Admin.

R2

.344

F 2/103=

26.995****

 

Work Pressure

.280

F 1/104=

40.4312****

Clarity

 

.064

F 1/103=

10.058***

 

 

 

 

 

 

Results for Depersonalization

 

Data were analyzed using a stepwise multiple regression with Depersonalization as the criterion variable and the ten subscales of the WES as predictor variables for each of the six occupational groups.

 

Therapists and Social Workers: Only one workplace variable, Innovation, entered the equation as significant predictor of Depersonalization accounting for 9.9% of the variance (F (1, 221) = 24.307, p<.001).  

               

Case Managers: Three workplace variables entered the equation as significant predictors of Depersonalization accounting for 21.4%of the variance (F (3, 118) = 10.725, p<.001).   The first variable to enter was Clarity which accounted for 13.9.7% of the variation in Depersonalization (F (1, 120) = 19.421, p<.001).  Innovation entered on the second step and accounted for an additional 4.7% of the variance (F (1, 119) = 6.903, p<.05).   This was followed by Involvement accounting for 3.6% of the variance (F (1, 241) = 10.118, p<.001).

 

Behavioral Health Technicians and other Paraprofessionals: Two workplace variables entered the equation as significant predictors of Depersonalization accounting for 15.3%of the variance (F (2, 241) = 21.728, p<.001).   The first variable to enter was Clarity which accounted for 11.7% of the variation in Depersonalization (F (2, 241) = 32.128, p<.001).  Innovation entered on the second step and accounted for an additional 3.6% of the variance (F (1, 241) = 10.118, p<.001).

 

Psychiatrist: Two workplace variables entered the equation as significant predictors of Depersonalization accounting for 43.6% of the variance (F (2, 16) = 6.174, p<.01).   The first variable to enter was Work Pressure which accounted for 25.5% of the variation in Depersonalization (F (1, 17) = 8.860, p<.001).  Innovation entered on the second step and accounted for an additional 18.1% of the variance (F (1, 16) = 5.127, p<.05).

 

Nurses: Two workplace variables entered the equation as significant predictors of Depersonalization accounting for 37.1% of the variance (F (2, 36) = 10.638, p<.001.   The first variable to enter was Clarity which accounted for 22.3% of the variation in Depersonalization (F (1, 37) = 10.597, p<.001).  Comfort entered on the second step and accounted for an additional 14.9 of the variance (F (1, 36) = .8.524, p<.01). 

 

Program Directors and Administrators: One workplace variable entered the equation as a significant predictor of Depersonalization. Work Pressure accounted for 12.6 % of the variance (F (1, 104) = 15.047, p<.001).  

 

A summary table for the multiple regressions for Depersonalization is presented in Table 2.

 

Table 2

Stepwise Regression

WES scales & Depersonalization

Occupation Group

Variance

Total

Step 1

Step 2

Step 3

 

Therapists & Social Workers

R2

.099

F 1/221=

24.307****

Involvement

.099

F 1/221=

24.307****

 

 

Case Managers

R2

.214

F 3/118=

10.725****

 

Clarity

.139

F 1/120=

19.421****

Innovation

.047

F 1/119

6.903**

Control

.028

F 1/118=

4.168*

 

Behavioral Health Technicians

R2

.379

F 5/238=

29.995****

 

Clarity

.117

F 1/242=

32.128****

Involvement

.036

F 1/241=

10.118***

 

Psychiatrists

 

R2

.436

F 2/16=

6.174**

 

Work

Pressure

.255

F 1/17=

5.811*

Innovation

.181

F 1/16=

5.127*

 

Nurses

R2

.371

F 2/36=

10.638****

 

Clarity

.223

F 1 /37=

10.597***

Comfort

.149

F 1/36=

8.524

 

Program Directors & Admin.

R2

.344

F 2/103=

26.995****

 

Work

Pressure

.126

F 1/104=

15.047****

 

 

 

 

 

Results for Personal Accomplishment

 

Data were analyzed using a stepwise multiple regression with Personal Accomplishment as the criterion variable and the ten subscales of the WES as predictor variables for each of the six occupational groups.

 

Therapists and Social Workers: Only one workplace variable entered the equation as significant predictor of Personal Accomplishment, Involvement accounted for 4.1%of the variance (F (1, 221) = 9.370, p<.001).  

 

Case Managers: One workplace variable, Innovation, entered the equation as significant predictor of Personal Accomplishment, Autonomy accounted for 10.1%of the variance (F (1, 120) = 13.486, p<.001

               

Behavioral Health Technicians and other Paraprofessionals: Only one workplace variable entered the equation as significant predictor of Personal Accomplishment, Involvement accounted for 5.7% of the variance (F (1, 242) = 14.579, p<.001).  

 

Psychiatrists: One workplace variable, entered the equation as significant predictor of Personal Accomplishment, Innovation accounted for 25.6% of the variance (F (1, 17) = 5.864, p<.05

 

Nurses: No variables were significant predictors for Personal Accomplishment for this group.

               

Program Directors and Administrators: One workplace variable entered the equation as significant predictor of Personal Accomplishment, Innovation accounted for 5.8 % of the variance (F (1, 104) = 6.419, p<.001).  

 

A summary table for the multiple regressions for Personal Accomplishment is presented in Table 3.

 

Table 3

Stepwise Regression

WES scales & Personal Accomplishment

Occupation Group

Variance

Total

Step 1

Step 2

Step 3

 

Therapists & Social Workers

R2

.041

F 1/221=

9.370***

Involvement

.041

F 1/221=

9.370***

 

 

Case Managers

R2

.101

F 1/120=

13.486****

 

Autonomy

.101

F 1/120=

13.486****

 

 

 

Behavioral Health Technicians

R2

.057

F 1/242=

14.579****

 

Involvement

.057

F 1/242=

14.579****

 

 

Psychiatrists

 

R2

.256

F 1/17=

5.864*

 

Innovation

.256

F 1/17=

5.864*

 

 

 

Nurses

No Variables were significant predictors

 

 

 

Program Directors & Admin.

R2

.058

F 1/104=

6.419*

 

Innovation

.058

F 1/104=

6.419*

 

 

 

 

 

 

DISCUSSION

 

Results of these analyses indicated that workplace and organizational factors contribute to the experience of burnout among rural mental health professionals and paraprofessionals.  Overall work environment factors accounted for greater levels of variance for Emotional Exhaustion and Depersonalization than for Personal Accomplishment. 

               

Emotional Exhaustion

 

In regards to Emotional Exhaustion, the analyses indicate that for all categories of rural mental health workers, Work Pressure is a significant factor contributing to feelings of Emotional Exhaustion.  Participants who perceived a higher degree of work demand and time pressure to do their work also experienced greater feelings of Emotional Exhaustion.  The variance in Emotional Exhaustion attributed to Work Pressure varied from 20.7% for Case Managers to 28% for administrators and program directors.  Work Pressure was also the primary predictor of Emotional Exhaustion for all groups with the exception of psychiatrists for whom Innovation was the primary predictor.  However, for psychiatrists Work Pressure still accounted for 25.7% of the variance in Emotional Exhaustion. This consistently high level of variance accounted for by Work Pressure suggests that work demands and time pressures dominate the work setting regardless of occupational group.

 

Other work environment factors were also significant predictors of Emotional Exhaustion.  As indicated above, the primary predictor of Emotional Exhaustion among Psychiatrists was innovation.  This was an inverse relationship with low scores on Innovation associated with higher levels of Emotional Exhaustion. For Psychiatrists, perceptions of the work environment as structured, rigid and lacking in innovation lead to higher levels of Emotional Exhaustion.  Low scores on Involvement also were significant predictors for Emotional Exhaustion among the Therapists and Social Workers group and the Nurses group.  Lower levels of commitment and concern for one’s job among these groups also appear to be predictors of higher levels of Emotional Exhaustion.  Lower scores on Task Orientation, indicating the perception of the work environment as not promoting optimal planning and efficiency, was a secondary predictor of higher levels of Emotional Exhaustion for Therapists and Social Workers as well as Case Managers

               

Clarity was a secondary predictor of Emotional Exhaustion for Behavioral Health Technicians.  As workplace expectations become vaguer and Behavioral Health Technicians become unsure as what to expect of their daily routine then Emotional Exhaustion increases.  Comfort, the extent that one’s physical surroundings are perceived as unpleasant was also a significant predictor of Emotional Exhaustion for Case Managers and Behavioral Health Technicians

               

Finally, Control (the extent that employees feel controlled by their employers) and low Supervisor support were secondary predictors of higher levels of Emotional Exhaustion for Behavioral Health Technicians

               

Overall, work environment factors accounted for a fairly substantial and consistent amount of variance in Emotional Exhaustion.  For five of the six position categories, the total accounted for ranged from 30.7% to 37.9%.  The exception was Psychiatrists, for whom work environment factors accounted for 60% of the total variance in Emotional Exhaustion.  This suggests that work environment factors are critical elements in understanding and predicting burnout.        

 

Depersonalization

 

 While Work Pressure appeared consistently as a major predictor of Emotional Exhaustion among all job categories, the picture with Depersonalization is more varied.  The analyses indicated that Work Pressure is a significant factor contributing to feelings of Depersonalization for Psychiatrists and Administrators, but did not show up as a significant predictor for other groups.  For Psychiatrists and Administrators, higher Work Pressure predicts a higher degree of detachment and reduced empathy.  Clarity was the primary predictor of Depersonalization for Nurses, Case Managers and Behavioral Health Technicians.  In all three cases the relationship was inverse with lower levels of clarity associated with greater feelings of Depersonalization.  Low scores on Involvement appear to be the primary predictor for Depersonalization for Therapists and Social Workers and is a secondary predictor for Behavioral Health Technicians.   Low levels of commitment and concern for one’s job among these groups predict Depersonalization.

               

Innovation was also a significant predictor of Depersonalization among psychiatrists and Case Managers with low scores on Innovation associated with higher scores on Depersonalization.  For these groups, perceptions of the work environment as structured, rigid, and lacking in innovation lead to higher levels of Depersonalization.

 

Comfort appears to be a secondary predictor of Depersonalization for Nurses.  Lower Comfort scores resulted in higher Depersonalization.  Finally, Control appears to be a tertiary predictor of higher levels of Depersonalization for Case Managers.

 

               

Overall, work environment factors accounted for a fairly substantial amount of variance in Depersonalization for Behavioral Health Technicians, Psychiatrists, Nurses and Administrators, with total explained variance ranging from .344 to .436.  Work Environment factors were less predictive of Depersonalization for Case Managers, Therapists and Social Workers.

 

Personal Accomplishment

 

Work environment factors were less useful predictors for Personal Accomplishment then for either Emotional Exhaustion or Depersonalization.  Only for psychiatrists did the total accounted for variance exceed 10%.  However several factors were found to be statistically significant, Innovation was the single significant predictor of personal accomplishment for psychiatrists and administrators.  It appears that those Psychiatrist and administrators who felt more able to implement variety and new approaches to their work tasks reported a greater sense of Personal Accomplishment. For Psychiatrists this relationship was appreciable of Personal Accomplishment, however given the relatively small number of psychiatrists (N=16) this should be interpreted with caution.  Involvement was the single significant predictor of Personal Accomplishment for Therapists and Social Workers and Behavioral Health Technicians.  Again those Therapists and Social Workers and Behavioral Health Technicians who felt more committed to their work reported higher feelings of Personal Accomplishment.  Autonomy was the single significant predictor of Personal Accomplishment for Case Managers.  As a Case manager’s sense of autonomy increases so to does a sense of Personal Accomplishment.  It is important to note that there were no significant work environment predictors of Personal Accomplishment for Nurses.

 

               

Generally, given the small explained variance for five of the six groups, it appears that Personal Accomplishment is not strongly related to external and work environment factors. It might be more useful to look for personal or individual variables as contributory factors for the sense of high personal accomplishment from one’s work

               

Limitations of this Assessment

 

Important limitations are inherent in an assessment of this kind. First, because the survey instruments utilized in this assessment were self-report measures, information presented by participants is based upon their subjective perceptions.  Although participants were assured confidentiality, it is possible that they either over- or under-reported their level of burnout on the MBI, and their perceptions of the environment on the WES.  Second, even with the high level of participation in this assessment the possibility exists that individuals choosing not to participate in the assessment may have differed in some manner from those staff members who did in fact participate.

               

Conclusions and Recommendations

 

These analyses demonstrated the value of organizational factors as significant contributors to the experience of burnout among rural mental health professionals and paraprofessionals.  Overall work environment factors accounted for greater levels of variance on Emotional Exhaustion and Depersonalization then on Personal Accomplishment.  The variance associated to Emotional Exhaustion from organizational factors by occupational categories ranged from 30.7% to 60%, for Depersonalization the variance ranged from 9.9% to 43.6% and for Personal Accomplishment the variance ranged between 4.1% and 25.6%.  For all occupational categories of rural mental health workers, Work Pressure was found to be the greatest contributor to Burnout.  Other workplace factors contributing to burnout factors included low scores on Innovation, Involvement, Task Orientation, Clarity, Supervisor Support, Autonomy, and high scores on supervisor control.

 

Results of this study have several important implications for providers of rural mental health services.  This information may be useful to the Administrator, Human Resource Director and Clinical Supervisor who must make decisions regarding staff retention strategies.  In addition the Work Environment Scale appears to be a useful measure of work environment factors contributing to Burnout.  Administration of this instrument along with the Maslach Burnout Inventory may offer early detection of potential, developing or actual problems, thereby providing an opportunity for appropriate workplace interventions.

 

 

REFERENCES

 

Balloch, S., Pahl, J., & McLean, J. (1998). Working in the social services: Job

    Satisfaction, Stress and Violence. British Journal of Social Work, 28, 32-350.

 

Cherniss, C. (1980).  Professional burnout in human service organizations. 

    New York: Praeger.

 

DeStefano, T. J., Petersen, J., Potter, T., & Zweig, B. (2003, July). A Preliminary

    assessment of the rural Arizona behavioral health human resource assessment

    project. Paper presented at the Rural Arizona Health Conference, Tucson, AZ.

 

Johnson, M., & Stone, G.L. (1987).  Social Workers and Burnout: A Psychological

    Description.  Journal of Social Science Research, 10(1), 67-80.

 

Kee, J., Johnson, D. & Hunt, P. (2002) Burnout and Social Support in Rural Mental

    Health.  Journal of Rural Community Psychology, E5 (1).

 

Lewis, J., Lewis, M., Packard, T., Souflee, F. (2001). Management of Human Service

    Programs. 3rd Ed.  Wadsworth/Thomson Learning, Belmont, CA.

 

Maslach, C., Jackson, S., & Leiter, P. (1996). Maslach Burnout Inventory Manual 3rd Ed.

    Consulting Psychologists Press, Inc.  Palo Alto CA.

 

Maslach, C., & Leiter, M. (1997). The truth about burnout: How organizations cause

    personal stress and how to get out of it.  San Francisco: Josey-Bass.

 

Merwin, E., Hinton, I., Dembling, B. & Stern, S (2003). Shortages of rural mental health

     Professionals.  Rural Mental Health, 17, 42-51.

 

Moos, R. (1994) Work Environment Scale Manual.  Consulting Psychologist Press. 

    Palo Alto, CA. 

 

National Council of Community Behavioral Healthcare, (2002). Survey of

    Behavioral Healthcare Providers.  Rockville, MD.

 

Scaufeli, W., Maslach, C., & Marek T. (Eds.) (1993). Professional Burnout: Recent

    Developments in Theory and Research.  Taylor & Francis.  Washington, DC.