Institutional factors contributing to counselor turnover in substance abuse treatment centers

Counselor Turnover in Substance Abuse Centers

This article examines a study of institutional and ecological factors contributing to turnover rates among counselors in substance abuse treatment centers. The researchers wanted to investigate correlations among four groups of factors, counselor-management relations, center characteristics, workforce composition, and counselor-client relations. The purpose of the study was to identify factors that were under the control of organizations and thus inform management decisions as they relate to employee retention. Reducing counselor turnover would help organizations control the direct costs associated with the recruitment, hiring, and training of new staff.

Introduction

The rate of employee turnover in substance abuse treatment centers, both hospital-based and for-profit centers, is worthy of study. McNulty, Oser, Johnson, Knudsen and Roman, 2007) found that in the female-dominated profession of substance abuse counselors, the turnover rate is higher than that found in teaching and nursing, two other female-dominated professions that are traditionally considered to experience high turnover (p. 166). Although McNulty et al. considered the role of gender in turnover rates, it was not the main focus of their study and was considered in only one of their hypotheses. McNulty et al. formulated ten hypotheses about turnover rates; their study was an attempt to examine external factors at the centers to determine causes for counselor dissatisfaction. Gender was considered only in that the pay structure and slow mobility tend to characterize female-dominated professions, one of which is substance abuse counseling. Traditionally, women move in and out of the workforce for family reasons, and that needed to be considered as well.

The study did not explore reasons why women are drawn to the profession, nor did it attempt to look at any personal characteristics of counselors in order to determine common themes in worker dissatisfaction leading to turnover. McNulty et al. were interested in factors associated with management practices and workplace climate and culture as contributors to turnover. The rationale for studying turnover emphasizes the costs incurred by organizations when employees leave (Hom and Griffeth, 1995, cited in McNulty et al., p. 166). Additionally, high turnover can negatively impact the conduct of work within centers. Inefficient channels of communication, increased workloads, and a demoralized workforce can all result from high turnover (McNulty et al., p. 167) and be detrimental to the mission of providing high-quality care.

An understanding of the factors that contribute to turnover may help organizations address those that are under their control in an effort to attract and retain quality workers.

The purpose of this paper is to examine the work of McNulty et al. And discuss the reliability and validity of their study of turnover among substance abuse counselors. The results of the study, provided external validity can be determined, may be used to inform management practices by treatment centers in an attempt to address the problem of turnover.

Model

For their investigation, McNulty et al. (2007) created a model of voluntary counselor turnover using multivariate blocks as categorized above. They used panel data from 1997 -- 1998 (Wave 2) and 2000 -- 2001 (Wave 3) National Treatment Center Study (NCTS), conducted by the University of Georgia and the Georgia Institute of Technology. They used a sample of 217 privately funded substance abuse treatment centers in the United States, matched with survey data on counselors employed at participating centers (p. 168). They were particularly interested in the role played by counselors' organizational commitment. In all, 269 centers provided data for collection. Administrators and clinical directors reported a response rate of 95% with on-site interviews in facilities that were open and eligible for participation. McNulty et al. used variables from Wave 2 to predict turnover in Wave 3, taking advantage of the longitudinal nature of the NTCS (p. 176).

Measures

The dependent variable in the study was the number of counselors who elected to leave voluntarily (McNulty et al., p. 176). Indicators for counselor-management relations were derived from a seven-question survey in which respondents could assign ratings over a seven-point range from strongly agree to strongly disagree. Also included was a four-question survey on organizational commitment, again rates by respondents according to a seven-point response set, ranging from strongly agree to strongly disagree.

McNulty et al. derived two binary indicators of treatment center characteristics, hospital-based and freestanding centers, and for-profit and not-for-profit centers (p. 176). Additionally they derived indicators of center capacity (inpatient and outpatient) and a scale from one to eight for service diversity, measuring levels of care regularly provided. Mean counselor salary is the average annual salary, measured in thousands. McNulty et al. measured prior turnover as the percentage of counselors that left voluntarily in the preceding year (p. 176).

All measures of workforce composition were represented by percentages. There were five characteristics of counselors that were measured: (1) percentage of female counselors; (2) percentage represented by minority groups; (3) percentage with master's degrees; (4) percentage with certification; and (5) percentage in recovery.

McNulty et al. derived four indicators of client characteristics relevant to counselor-client relations, also measured as percentages: (1) percentage of clients in treatment who have relapsed following initial recovery; (2) percentage of court-mandated clients; (3) percentage of Medicaid clients; and (4) percentage of managed care clients.

Descriptive Statistics

The analysis of data showed that the average annual turnover rate among counselors is approximately 16%, which represents a three percent increase over previously collected data. As a caveat, it must be noted that the measures of turnover varied across centers. Representing 62% of the treatments centers, hospitals overwhelmingly constituted the largest group, with only 31% of centers classified as for-profit. Centers of both types averaged approximately 115 clients each, ranging, on average, over four or five levels of care. The demographic composition of the couselor workforce was 57% female, 13% minority group members, 50% with graduate degrees, 56% certified, and 37% in recovery. Counselors' salaries averaged $30,134, with a range of $15,000 -- $62,640. With respect to the client population, an average of 54% had experienced a relapse. Twenty-nine percent will in a program due to a court mandate. Twenty-six percent of clients were covered by Medicaid and 18% were covered by managed care.

Discussion

McNulty et al. tested ten hypotheses in four conceptual blocks of variables. Their "key hypotheses" (p. 173) concerned the role of management practices. They were careful, in formulating hypotheses, not to assume causal relationships between management practices and center and workforce characteristics. They did note, however "the model considers center characteristics first because…workforce and client composition are perhaps shaped in part by the structural/operation features of treatment centers (p. 173). Factors under study in their hypotheses are not independent of one another, as the tabulation of multivariate sustainability indicates.

In discussing reliability of the study, there are several points that are worthy of consideration. The first is with respect to the nature of the factors considered in forming the hypotheses and then subsequently measured and studied. Examination of the factors shows that they are objective measures and, in some instances, binary. The nature of the facility, for example, is binary; it is either for-profit or hospital-based. Factors such as counselor-client ratio, size of the facility, classification of facility (inpatient, outpatient, or both), salary ranges, and opportunities for mobility are generally stable but can, dependent upon circumstances, be changeable to an extent. Factors such as education levels and attainment of certification may also be relatively stable in that facilities may have established mandates for hiring. Factors such as gender composition of the workforce, racial and ethnic composition, and recovery status among members of the workforce has the most potential for change within and across institutions; as with education and certification attainment, however, organizations may have mandated quotas to meet in hiring practices.

The subjective factors in the study are the scaled-response survey questions completed by counselors in the facilities studied. The study by McNulty et al. does not have any way of controlling or accounting for the emotional states of counselors or personal or professional experiences they may have had that will influence their responses.

Survey questions cannot control for individuals who, as a matter of practice, never select the strongest response in a set. Responses to questions about participatory management will be influenced by each employee's experiences. For example is the statement "The center's management makes sure that employee concerns are heard before decisions are made" (p. 188). Responses could be affected by an employee's own experience, the experience or a colleague, hearsay, or an employee's perception of a typical management response. There is no provision for factoring in an employee's length of service and whether dissatisfaction, as expressed in this response or others, reflects a single incident or what the employee perceives as a pattern of behavior by management.

There are four survey questions designed to collect data on individuals' organizational commitment. As above, responses are subjective and depend, to a small extent, on individual's customary response habits (e.g., choosing to avoid strongest responses or tending to select "middle-of-the-road" responses). To a greater extent, responses may be skewed depending upon whether respondents answer based on overall feelings or in reaction to a specific incident. For example, the first item in the category of organization commitment states "As soon as I can find a better job, I will leave this center" (p. 188). An individual's response may be affected by a negative encounter with another staff member or client; if the staff member or client left the facility, the individual's response might be different. An individual's response might be a reflection or management behavior or practice, or a personal agenda which management may not be aware of and over which it has no control.

Results from the study by McNulty et al. were based on a large sample population in two waves, so it is reasonable to conclude that the questions raised about the subjectivity of certain responses would not invalidate the findings. McNulty et al. used WLS regression equations to account for the roles of participatory management and organizational commitment in counselor turnover and controlled separately for each additional block of variables.

The methodology of the study is solid. McNulty et al. carefully evaluated a number of factors that could affect turnover. The model used a dependent variable and examined factors categorized in four blocks. Analysis of the data revealed "significant heteroscedasticity in the models" (p. 177); the researchers compensated for this variance in statistical measures by weighting scores, since it was determined that prediction errors were tended to be greater with smaller centers that employed fewer workers.

Careful methodology and statistical analysis resulted in a valid study, the ramifications of which are important to substance abuse treatment centers that are faced with high turnover rates as well as for centers who endeavor to take a proactive approach in developing and executing management practices that support counselor retention. The study could easily be replicated for any group of centers, provided that a sufficiently large sample was studied. Important considerations in addition to the large sample size would be inclusion of hospital-based and for-profit centers and composition of client base (inpatient, outpatient, Medicaid, and managed care).

McNulty et al. noted that their analysis had some limitations and made recommendations for future research. Key would be studies that "would help to sort out causal processes and establish the nature of direct and indirect effects of predictors on turnover rates" (p. 187). As has been shown, the study by McNulty et al. And future studies could be used to inform management decisions. Another application of the studies, those which have been undertaken as well as those suggested for the future, is to inform educational programs and professional development opportunities within the fields of social work, psychology, and administration as they pertain to substance abuse treatment centers. Awareness of potential factors influencing turnover could be a first step in creating not only effective policies but also effective programs to build and maintain a supportive culture in which counselors can work to provide the best possible treatment environment for their clients.