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Keeping Ourselves Well: Strategies for Promoting and Maintaining Counselor Wellness
Cummins, Paige N;Massey, Linda;Jones, Anita
Journal of Humanistic Counseling, Education and Development; Spring 2007; 46, 1; ProQuest Central
pg. 35
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A Day in the Life of an Addiction Counselor
A Day in the Life of an Addiction Counselor
Program Transcript
[MUSIC PLAYING]
FEMALE SPEAKER: Good morning. Your first client has arrived. And just to
warn you, they’ve already threatened one staff member.
FEMALE SPEAKER: Hey, can we have you sign off on this hospital release
form?
FEMALE SPEAKER: So, no, I’m fine. You need to stop asking me how I’m doing.
Have you ever done cocaine before? If not, how do you think you can help me?
MALE SPEAKER: Oh, hey. I need that report on my desk this afternoon by
3:00pm.
FEMALE SPEAKER: Hey. So you know I’ve been talking to my husband a little
bit since his mom died. And I’m worried that he’s not really dealing with it very
well. Do you have some suggestions or ideas about what he might be going
through?
FEMALE SPEAKER: OK, well I guess I’ll go first. I can remember being about six
or seven years old. And my parents had a lot of parties. And that was probably
my first introduction to alcohol.
MALE SPEAKER: I’m thinking about hurting myself. Can you fix that? [MUSIC
PLAYING]
A Day in the Life of an Addiction Counselor
Additional Content Attribution
MUSIC:
Creative Support Services
Los Angeles, CA
Dimension Sound Effects Library
Newnan, GA
Narrator Tracks Music Library
Stevens Point, WI
©2013 Laureate Education, Inc.
1
A Day in the Life of an Addiction Counselor
Signature Music, Inc
Chesterton, IN
Studio Cutz Music Library
Carrollton, TX
Special Thanks:
Fairland Center/Region One Mental Health
©2013 Laureate Education, Inc.
2
Journal of Substance Abuse Treatment 40 (2011) 323 – 335
Regular article
Burnout among the addiction counseling workforce: The differential roles
of mindfulness and values-based processes and work-site factors
Roger Vilardaga, (M.A.) a,⁎, Jason B. Luoma, (Ph.D.) b , Steven C. Hayes, (Ph.D.) a ,
Jacqueline Pistorello, (Ph.D.) a , Michael E. Levin, (M.A.) a , Mikaela J. Hildebrandt, (M.S.) a ,
Barbara Kohlenberg, (Ph.D.) c , Nancy A. Roget, (M.S.) d , Frank Bond, (Ph.D.) e
a
Department of Psychology, University of Nevada, Reno, NV 89557, USA
Portland Psychotherapy Clinic, Research, and Training Center, OR 97212, USA
c
University of Nevada School of Medicine, Reno, NV 89557, USA
d
Center for the Application of Substance Abuse Technologies, Reno, NV 89509, USA
e
Goldsmiths, University of London, London, SE14 6NW, United Kingdom
b
Received 26 April 2010; received in revised form 28 November 2010; accepted 29 November 2010
Abstract
Although work-site factors have been shown to be a consistent predictor of burnout, the importance of mindfulness and values-based
processes among addiction counselors has been little examined. In this study, we explored how strongly experiential avoidance, cognitive
fusion, and values commitment related to burnout after controlling for well-established work-site factors (job control, coworker support,
supervisor support, salary, workload, and tenure). We conducted a cross-sectional survey among 699 addiction counselors working for urban
substance abuse treatment providers in six states of the United States. Results corroborated the importance of work-site factors for burnout
reduction in this specific population, but we found that mindfulness and values-based processes had a stronger and more consistent
relationship with burnout as compared with work-site factors. We conclude that interventions that target experiential avoidance, cognitive
fusion, and values commitment may provide a possible new direction for the reduction of burnout among addiction counselors. © 2011
Elsevier Inc. All rights reserved.
Keywords: Addiction counselors; Burnout; Experiential avoidance; Values commitment; Cognitive fusion; Work-site factors
1. Introduction
Addiction counselors work under difficult conditions:
funding cuts, restrictions on the delivery of services,
changing certification and licensure standards, mandated
clients, and clients that need special care (Austad, Sherman,
Morgan, & Holstein, 1992; Carpenter, 1999; Ivey, Scheffler,
& Zazzali, 1998; Manderscheid, Henderson, Witkin, & Atay,
2000; Osborn, 2004). In addition, other situational factors
such as low salaries, staff turnover, agency upheaval, and
limited opportunities for career development create additional burdens (Ogborne, Braun, & Schmidt, 1998); not to
⁎ Corresponding author. Department of Psychology MS 298, University
of Nevada, Reno, 1664 N. Virginia St., Reno, NV 89557, USA.
E-mail address: roger.vilardaga@gmail.com (R. Vilardaga).
0740-5472/10/$ – see front matter © 2011 Elsevier Inc. All rights reserved.
doi:10.1016/j.jsat.2010.11.015
mention, the well-known difficulty of working with clients
who have high relapse rates (Festinger, Rubenstein,
Marlowe, & Platt, 2001; Hubbard, Flynn, Craddock, &
Fletcher, 2001) and high rates of psychiatric comorbidity
(McGovern, Xie, Segal, Siembab, & Drake, 2006).
Under those circumstances, burnout has been reported as
a prevalent problem among addiction counselors and other
providers of mental health care (Balogun, Titiloye, Balogun,
Oyeyemi, & Katz, 2002; Maslach, Schaufeli, & Leiter, 2001;
Osborn, 2004; Sarata, 1983), especially among those
rendering direct services to their recipients (Peterson,
1990). Burnout is associated with job turnover (Ducharme,
Knudsen, & Roman, 2008; Knudsen, Ducharme, & Roman,
2006; Knudsen, Ducharme, & Roman, 2009; Schaufeli &
Bakker, 2004), which exacerbates the chaos within agencies
that often are already unstable, underfunded, and struggling.
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R. Vilardaga et al. / Journal of Substance Abuse Treatment 40 (2011) 323–335
Burnout also impacts other aspects of the counselors’
functioning, including the counselor–client therapeutic
relationship (Garner, 2006), the counselors’ morale (Cushway & Tyler, 1996), and counselors’ job efficacy and
commitment (Maslach et al., 2001). Data from research on
both addiction counselors and other health professionals
show that work-site factors of job control, coworker social
support, supervisor support, workload, and tenure are linked
to burnout (e.g., Alotaibi, 2003; Ducharme et al., 2008; Frese
& Zapf, 1994; Hackman & Lawler, 1971; Knudsen,
Ducharme, & Roman, 2008; Maslach et al., 2001; Ogborne
et al., 1998; Terry & Jimmieson, 1999). Although organizational interventions such as reducing workload or
increasing job control are helpful in reducing burnout, this
pathway can be difficult to implement in agencies that treat
substance use disorders due to inadequate funding and
unstable organizational environments. Furthermore, targeting organizational factors alone may not adequately address
the problem of burnout. Although task control relates to job
satisfaction, other job control factors, such as the degree of
involvement in organizational decisions and control over
work scheduling, do not seem to increase it (Sargent &
Terry, 1998), and some reports indicate that social support
does not relate significantly to some aspects of burnout,
including depersonalization and sense of accomplishment
(van Dierendonck, Schaufeli, & Buunk, 1998).
A second pathway to burnout prevention and remediation
might be interventions aimed at altering the psychological
factors that contribute to burnout, such as mindfulness and
values-based approaches (e.g., Hayes, Follette, & Linehan,
2004). Mindfulness processes have shown some promise,
having been found to reduce therapists’ stress (Shapiro,
Brown, & Biegel, 2007) and to increase well-being (Brown
& Ryan, 2003; Epstein, 1999). Acceptance and commitment
therapy (ACT; Hayes, Strosahl, & Wialson, 1999) incorporates mindfulness and acceptance into a larger context of
commitment and behavior change processes linked to
values. A number of studies based on this model have
shown that ACT is relevant to issues faced by addiction
counselors. For example, ACT interventions have been
shown to reduce substance abuse among those with an
addiction (Gifford et al., 2004; Hayes, Wilson, et al., 2004),
reduce self-stigma in addiction patients (Luoma, Kohlenberg, Hayes, Bunting, & Rye, 2008), increase adoption of
evidence-based practices among addiction counselors
(Luoma et al., 2007; Varra, Hayes, Roget, & Fisher,
2008), and reduce work-site stress (Bond & Bunce, 2001,
2003; McCracken & Yang, 2008).
Most directly relevant to this article is preliminary
efficacy data showing that an intervention based on an
ACT model reduced burnout in addictions counselors with
effects at least partially mediated through these processes
(Hayes, Bissett, et al., 2004). Although preliminary efficacy
data are promising, it is not yet known if the processes ACT
targets are generally important in burnout among addiction
counselors. Three such processes are examined in this study
and further described below: experiential avoidance, cognitive fusion, and values commitment.
Experiential avoidance is “a verbal process that involves
the unwillingness to remain in contact with particular
thoughts, feelings, memories, bodily sensations or behavioral
predispositions and the direct and deliberate attempts to alter
the form and frequency of those events or the context in
which they appear” (Hayes, Wilson, Gifford, & Follette,
1996, p.1154), which is argued to lead to insensitivity to the
environment and to rigid and ineffective patterns of behavior.
Experiential avoidance is associated with higher levels of
depression, anxiety, and low quality of life (Hayes, Strosahl,
et al., 2004) and a wide variety of other negative outcomes,
such as sexual victimization and distress (Polusny,
Rosenthal, Aban, & Follette, 2004), posttraumatic stress
disorder (Marx & Sloan, 2005; Plumb, Orsillo, & Luterek,
2004), self-harm behaviors (Chapman, Gratz, & Brown,
2006), and parental distress and adjustment difficulties
(Greco et al., 2005). Changes in experiential avoidance
have also been found to mediate the impact of ACT on
clinical outcomes in several randomized controlled trials
(Hayes, Luoma, Bond, Masuda, & Lillis, 2006; Ost, 2008;
Powers, Vording, & Emmelkamp, 2009).
Cognitive fusion, another important process in ACT, is a
broad construct that refers to the domination of thinking in
behavioral regulation over other available processes (Hayes
et al., 1999; Masuda, Hayes, Sackett, & Twohig, 2004). Fusion
can be reduced by mindfully seeing thoughts as an ongoing
cognitive process rather than merely interacting with the world
as if it was structured by these thoughts (Hayes & Melancon,
1989). Changes in cognitive fusion, or the ability to see
thoughts as “just thoughts,” have also been shown to mediate
the outcomes of ACT interventions in several controlled trials
(e.g., Hayes, Bissett, et al., 2004; Zettle & Hayes, 1986). Since
cognitive fusion can take many forms, and stigma toward
substance abusers has been found to be a prevalent problem in
this subset of health care providers (Crisp, Gelder, Rix,
Meltzer, & Rowlands, 2000), previous ACT studies have
looked at fusion with stigmatizing thoughts, feelings, and
attitudes toward substance abusers as a specific and problematic manifestation of cognitive fusion among addiction
counselors (Hayes, Bissett, et al., 2004).
A third process in ACT, values commitment, refers to
engagement in patterns of behavior consistent with values.
Values are further defined as “verbally constructed, globally
desired life directions” (Wilson, Hayes, Gregg, & Zettle,
2001, p.235; see also Plumb, Stewart, Dahl, & Lundgren
2009 for a more extended review on values from an ACT
perspective). Values are known to be a key feature of the
motivation to sustain healthy behaviors over time (Cohen,
Garcia, Purdie-Vaughns, Apfel, & Brzustoski, 2009; Elliot &
Harackiewicz, 1996; Sheldon & Elliot, 1999), and from an
ACT perspective, burnout may be increased due to a
disconnect between one’s values and one’s day-to-day
actions. Therefore, a target process in ACT becomes
commitment to values.
R. Vilardaga et al. / Journal of Substance Abuse Treatment 40 (2011) 323–335
Although there are several studies examining processes
predicting burnout among addiction counselors (e.g.,
Broome, Knight, Edwards, & Flynn, 2009; Ducharme et
al., 2008; Knudsen et al., 2008, 2009; Ogborne et al., 1998;
Peterson, 1990), and mindfulness treatments have received
increasing attention in the substance abuse treatment field
(e.g., Bowen et al., 2006; Carrico, Gifford, & Moos, 2007;
Leigh, Bowen, & Marlatt, 2005; Ostafin & Marlatt, 2008),
to our knowledge, no large study has yet examined the
relationship between mindfulness and values-based processes (such as those proposed by ACT) and burnout
among addiction counselors. In this study, we examined the
role of ACT processes on burnout as compared to
traditional work-site factors, including job control, salary,
social support, workload, and tenure in a sample of
addiction counselors. We hypothesized that both sets of
factors play a role, but that ACT processes will have a
relationship with burnout even after accounting for worksite factors. If this proves to be the case, it supports the
argument that these processes would be important targets
for burnout reduction interventions.
2. Materials and methods
2.1. Sample and procedure
Participants were 699 alcohol and drug abuse counselors
recruited to participate in a National Institute of Drug Abusefunded trial that tested workshop-based interventions for
burnout during years 2006–2007. Participants were told that
the study was aimed to help them “overcome barriers to
effectiveness with difficult and different clients.” In return
for participation, participants were provided with free tuition,
continuing education credits, a $25 gift certificate to a
department store for completion of the prerassessment, a $25
gift certificate for postassessment, and a $50 gift certificate
for the 3-month follow-up assessment. The data analyzed in
this study were drawn from the preintervention assessment
of this larger study. We do not report details of the
intervention or post and follow-up assessments in this
article, as they are not relevant to this analysis, which focuses
on baseline scores.
Participants were recruited through as many outreach
formats as possible, by primarily using the master lists of
licensed/certified alcohol and drug abuse counselors provided by Addiction Technology Transfer Centers, a national
network of regional training and technical assistance centers
that design and implement activities to strengthen and
improve the substance abuse treatment workforce, funded by
the Center for Substance Abuse Treatment under the
Substance Abuse Mental Health Services Administration
(SAMHSA). We sent out e-mails and letters to individual
counselors as well as substance abuse treatment agencies in
states that were in the vicinity of the training venue and
encouraged recipients of the e-mails to forward them to other
325
substance abuse counselors who might be interested. In
addition, we announced the event in specialized listservs that
could have reached addiction counselors in that venue. The
training events were also advertised on the national
Addiction and Technology Transfer Center (ATTC) Network Web site. In an effort to maximize the sample’s
representativeness, we established training venues across the
nation: Las Vegas, NV; Sacramento, CA; Los Angeles, CA;
Phoenix, AZ; Vancouver, WA; Orlando, FL; and Chicago,
IL. It is not possible to calculate the response rate per se due
to the digital nature of the outreach and inability to know
how many individuals received or read the study announcements. Table 1 compares our sample to the addiction
workforce nationally. On various demographic variables
such as age, gender, education, current licensure/certification, and salary compensation, the sample is similar to
national norms (ATTC National Office, 2009). The study
was approved by the Institutional Review Board of the
University of Nevada, Reno, and informed consent was
obtained from all addiction counselors at the training site.
Participants completed the baseline self-report measures that
were used in the analyses reported in this article in a paperand-pencil format.
Criteria for inclusion in our final sample were being an
addiction counselor or trainee working toward licensure or
certification, being employed by an organization that
provides substance abuse treatment services, being supervised, agreement to participate in the full course of the 2-day
workshop-based interventions to reduce burnout, and
agreement to complete assessment packets at pre, post, 3month, and 12-month follow-ups. Participants also had to be
fluent in English. Participants agreed ahead of time to
undergo the consent process on site before the workshop and
provided their name and contact information so we had a
priori knowledge of individuals who would be present at a
particular date and site: fewer than five individuals agreed to
come and then no-showed or canceled; one individual
declined to participate after reading the consent form.
Our participants (60.8% female, 39.2% male, N = 697)
had an average age of 49.7 years (SD = 10.6, N = 681). Their
education levels were as follows: 0.58% never attended high
school, 3.35% had a high school degree, 18.63% reported at
least some college education, 11.21% had an associate’s
degree, 27.22% had a Bachelor’s degree, 34.06% had a
master’s degree, 3.20% had a PhD, and 1.75% indicated
“other” (n = 687). The average number of years in their
current job was 5.2 years (SD = 5.3, N = 692). Self-reports
indicated that our sample was 58.5% White, 27% African
American, 3.6% American Indian, 2% Asian, 1.3% Pacific
Islander, and 7.6% reporting “other” (n = 644), with 9.2%
missing data. For ethnicity, 12.7% identified as Latino(a)/
Hispanic. Fifty-one percent of the participants described
their job responsibilities as line staff (counseling), 26.5% as
supervisors, 11.7% as administrators, and 10.7% as trainers
or educators (n = 618). Changes in our demographic forms
during the course of our study resulted in a missing rate of
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R. Vilardaga et al. / Journal of Substance Abuse Treatment 40 (2011) 323–335
Table 1
Demographic comparison with U.S. national data from 2009 ATTC workforce summary
Variable
Study sample
Workforce summary
Age
Gender
Race
Education
M = 49.7
60.8% female
58.5% White
64.5% with BA or more
Certification
Salary
76.2% currently certified/licensed in substance abuse treatment
73.1% made between $20,000 and $50,000
M = 45–50 a
50%–70% female b
70%–90% White c
Several studies 80% with BA or more d
Two studies reported 60% with BA e
45%–75% certified across various studies f
Counselors’ average salary = 30,000
Directors’ = between $40,000 and $75,000 g
Note. BA = bachelor of arts.
a
Kaplan, 2003; NAADAC, 2003; RMC, 2003a, 2003b; NTIES 2001; Harwood, 2002.
Mulvey, Hubbard, & Hayashi, 2003; RMC, 2003a, 2003b; Knudsen & Gabriel, 2003; NAADAC, 2003; Harwood, 2002; NEDs 2001, Johnson, Knudsen,
& Roman, 2002.
c
RMC, 2003a, 2003b; Harwood, 2002; Knudsen & Gabriel, 2003; Landis, Earp, & Libretto, 2002; Mulvey et al., 2003.
d
Johnson et al, 2002; Knudsen & Gabriel, 2003; RMC, 2003b.
e
RMC, 2003a; Gallon, Gabriel, & Knudsen, 2003.
f
SAMHSA 2003; Harwood, 2002; RMC, 2003a.
g
Kaplan, 2003.
b
11.6% on this variable. Finally, 73.1% of the sample had
income between $20,000 and $50,000 per year (n = 671).
2.2. Measurement
2.2.1. ACT processes
Our measures of ACT processes included assessments of
experiential avoidance, cognitive fusion, and values
commitment.
The Acceptance and Action Questionnaire (AAQ; Hayes,
Strosahl, et al., 2004) in its most recent version, the AAQ-II,
measures the experiential avoidance component of ACT.
The AAQ-II contains 10 items rated on a 7-point Likert scale
that ranges from 1 (never true) to 7 (always true). Item 1, for
example, reads “It’s OK if I remember something unpleasant.” Because of a square root transformation to normalize
scores for analyses, high scores on this scale indicate high
levels of experiential avoidance. This scale typically obtains
Cronbach’s alpha coefficients in the range of .76 to .87
(Bond et al., n.d.). This study obtained an adequate
Cronbach’s alpha of .73.
The Stigmatizing Attitudes—Believability Scale (SAB,
20 items; Hayes, Bissett, et al., 2004) is a measure of
cognitive fusion (or cognitive believability) with common
negative attitudes of treatment providers toward substance
abusers. The measure asks participants to rate the believability of 20 items referring to negative thoughts or attitudes
about substance abusers on a 7-point Likert scale ranging
from 1 (not at all believable) to 7 (completely believable). An
example item is “one can never really overcome their history
of substance abuse.” This measure is relatively new. In
previous studies, this measure was found to have a
Cronbach’s alpha of .78 (Hayes, Bissett, et al., 2004). This
study obtained a moderate Cronbach’s alpha of .81. Previous
research has successfully shown the mediational effect of
cognitive fusion measures in other settings (Bach & Hayes,
2002; Zettle & Hayes, 1986), and in a previous study, this
specific measure partially mediated the effects of ACT on
burnout outcomes (Hayes, Bissett, et al., 2004). The SAB
does not measure the content or presence of particular
negative attitudes or the level of emotion attached to it, but
the degree in which the counselor believes them. Higher
scores on this scale indicate higher cognitive fusion with
negative attitudes toward substance abusers.
The Work Values Questionnaire is a relatively new
measure that constitutes a shortened version of the Personal
Values Questionnaire, an unpublished measured developed
by Blackledge, Spencer, and Ciarrochi (May, 2007)
grounded in previous work by Sheldon, Kasser, Smith, and
Share (2002). In this measure, participants were asked to
write in a few sentences about their work values and rate nine
items in relation to this values statement. Examples of
participant’s values were the following: “I want to be
personally successful, and in that process, successful in
helping others” or “[to be] an effective worker and team
player.” Only the final item of this scale was used in this
study because it refers to how successful participants were in
the accomplishment of their value in the past month, with
response options ranging from 1 (0%–20% successful), to 5
(81%–100% successful). This percentage of success served
us as our index of commitment to work-related values, with
scores transformed using a square root transformation.
Because of this data transformation, high scores on this
item indicate low commitment to work-related values.
Because this was a single-item measure, no reliability
analyses were conducted.
2.2.2. Work-site factors
Traditional predictors of burnout have been work-site
factors. In particular, levels of job control and social support
have shown to be reliable predictors of burnout (Ganster,
Fusilier, & Mayes, 1986; Perrewe & Ganster, 1989).
Job control was measured using a shortened version
(Smith, Tisak, Hahn, & Schmieder, 1997) of the longer 21-
R. Vilardaga et al. / Journal of Substance Abuse Treatment 40 (2011) 323–335
item Job Control Scale (Lee & Ashforth, 1996) that has been
shown to have adequate psychometric properties. Participants rated nine items from 1 (very little) to 5 (very much)
that attempt to measure participants’ perceived control over
their work environment. For example, Item 3 reads: “How
much control do you have over when you take vacation or
days off?” This study obtained a moderate Cronbach’s alpha
of .82.
Social support at work was measured using two subscales
of the Job Content Questionnaire, a widely used measure of
workplace characteristics (Karasek et al., 1998). One of
them, the coworker support subscale has six items (“People I
work with are friendly”), with high scores indicating high
levels of coworker support. In our sample, this subscale
obtained a moderate Cronbach’s alpha of .85. The
Supervisor Support Subscale contains six items (“my
supervisor is concerned about the welfare of those under
him/her”), with high scores indicating high supervisor
support. In our sample, this subscale obtained a moderate
Cronbach’s alpha of .89.
The variable salary was obtained with a single item that
asked “What is your approximate income.” Each response
option (1 through 6) provided the participant with a salary
range ($0–$20,000/year; $20,000–$35,000/year; $35,000–
$50,000/year; $50,000–$65,000/year; $65,000–$80,000/
year; $80,000 and up/year, respectively) and an additional
opt-out answer (“I’d rather not say”).
Tenure and workload were measured with three open
questions. For tenure, participants were asked to write down
“years of experience in addictions” and the number of
months, if applicable. High scores on tenure indicate more
experience in the addictions field. For workload, participants
were first asked if they performed addiction counselingrelated duties, and then, they were asked: “If yes about how
many hours per week?” Higher scores on this variable
indicate higher workload. Because salary, workload, and
tenure were single item measures, no reliability analyses
were conducted.
2.2.3. Criterion variables
The Maslach Burnout Inventory (MBI; Maslach, Jackson,
& Leiter, 1996) is a measure of burnout containing 22 items
that can be scored from 0 (never) to 6 (every day). This
questionnaire has three subscales that can be interpreted
independently (Maslach et al., 1996): exhaustion, which
measures the depletion of emotional energy and is different
in nature than physical debilitation or mental tiredness (e.g.,
Item 20 is “I feel like I’m at the end of my rope”);
depersonalization, which measures personal sensitivity to
service recipients (e.g., Item 10 is “I’ve become more callous
toward people since I took this job”); and personal
accomplishment, which measures effectiveness and success
in having a positive impact on recipients of care (e.g., Item
19 is “I have accomplished many worthwhile things in this
job”). For the sake of consistency of interpretation, direction
of scores was set so that higher scores on these three
327
subscales indicated higher levels of exhaustion, depersonalization, and low accomplishment. In our sample, we found
alpha levels of .91 for exhaustion, .69 for depersonalization,
and .75 for accomplishment, whereas previous reports have
established alpha levels of .90, .79, and .71, respectively
(Maslach et al., 1996).
2.3. Data analytic strategy
Data were double entered using the SPSS Data Entry
Builder module (version 4.0). We evaluated accuracy of data
entry, missing values, outliers and fit with assumptions by
examining frequencies and histograms and calculating
skewness, kurtosis, and z scores. Workload, tenure, and salary
had 9.9%, 3.7%, and 4% of missing values, respectively.
Accomplishment had one missing value; experiential avoidance, two; values commitment, eight; and supervisor support,
one. In addition, 18 did not report their age, and 2 their gender.
None of the other predictor and predicted variables had
missing values. Finally, 27 counselors did not have a
supervisor and were excluded from our final analyses because
the model we were testing was not relevant to them. The only
dichotomous variable, gender, had an appropriate split (61%–
39%), so we retained it in our analyses. Based on the z scores
and the observations of histograms and box plots, we identified
several outliers before data transformation. Square root and
logarithmic transformations produced near-normal distributions and eliminated outliers.
To preserve our sample power and reduce undue bias as a
result of missing values, we used a multiple-imputation
technique. Multiple imputation is one of the best techniques
for dealing with missing data, allowing less stringent assumptions on its latent causes (Croy & Novins, 2005; Graham, 2009;
Rubin, 1987; Schafer, 1999). After transforming the variables
and adjusting them to a multivariate normal distribution, we
used AMOS (version 18.0) to perform 10 stochastic regression
imputations that included 14 auxiliary variables that were part
of our model. Using simulations, Rubin (1987) has shown that
3 to10 imputations can achieve almost equivalent efficiencies;
thus, based on this standard, we opted for a conservative
approach and decided to perform 10 imputations. Each imputed
data set was exported to a data file in PASW (version 18.0),
where our final analyses were conducted. Parameter estimates,
standard errors, t statistics, and degrees of freedom were
calculated in Microsoft Excel following the steps described by
Schafer (1999) and Rubin (1987). This procedure allowed us to
collapse each scalar into a single coefficient of determination
for each variable in the entire group of imputed data sets. The
statistical significance of each coefficient was determined
comparing the t statistic to the Student’s t distribution.
To test our theoretical rationale, we produced three
sequential multiple regressions with the aim of parsing out
the effect of work-site factors on burnout from the effect of
the ACT processes. One regression was run for each burnout
subscale: exhaustion, depersonalization, and accomplishment. In each of these regressions, we controlled for
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R. Vilardaga et al. / Journal of Substance Abuse Treatment 40 (2011) 323–335
Table 2
Zero-order correlations (n = 699) of variables entered in our regression analysis
Variable
1
1.Exhaustion
2. Depersonalization
3. Low accomplishment
4. Experiential avoidance
5. Low values commitment
6. Cognitive fusion
7. Job control
8. Coworker support
9. Supervisor support
10. Salary
11. Age
12. Gender
13. Education
14. Tenure
15. Workload
1
.52 ⁎⁎
.29 ⁎⁎
.34 ⁎⁎
.28 ⁎⁎
.15 ⁎⁎
−.29 ⁎⁎
−.26 ⁎⁎
−.21 ⁎⁎
.05
−.12 ⁎
.05
.09 ⁎
−.07
.07
8. Coworker support
9. Supervisor support
10. Salary
11. Age
12. Gender
13. Education
14. Tenure
15. Workload
2
3
4
5
6
7
1
.26 ⁎⁎
.26 ⁎⁎
.21 ⁎⁎
−.11 ⁎
−.19 ⁎⁎
−.04
−.06
−.16 ⁎⁎
.01
−.12 ⁎
−.05
−.04
1
.27 ⁎⁎
.19 ⁎⁎
−.14 ⁎⁎
−.11 ⁎
−.01
−.03
−.02
−.05
−.02
−.05
.05
1
.10 ⁎
−.21 ⁎⁎
−.19 ⁎⁎
−.09 ⁎
−.04
−.08 ⁎
0
−.05
−.07
.03
1
−.06
−.05
−.04
−.10 ⁎
−.03
−.05
−.12 ⁎
−.13 ⁎⁎
.03
1
.39 ⁎⁎
.37 ⁎⁎
.24 ⁎⁎
.03
−.04
.08 ⁎
.20 ⁎⁎
−.12 ⁎⁎
1
.28 ⁎⁎
.31 ⁎⁎
.24 ⁎⁎
.15 ⁎⁎
−.13 ⁎⁎
−.15 ⁎⁎
−.08 ⁎
.08 ⁎
−.10 ⁎
−.03
.04
−.06
.01
8
9
10
11
12
13
14
1
.50 ⁎⁎
−.01
−.05
0
−.01
−.03
−.01
1
−.00
−.06
−.02
−.02
−.05
−.12 ⁎⁎
1
.15 ⁎⁎
−.06
.35 ⁎⁎
.32 ⁎⁎
−.09 ⁎
1
−.20 ⁎⁎
−.01
.54 ⁎⁎
−.03
1
.10 ⁎
−.13 ⁎⁎
−.04
1
.09 ⁎
−.13 ⁎⁎
1
−.06
⁎ p b .05.
⁎⁎ p b .01.
demographic variables (age, gender, and education) by
entering them as the first step. Since work-site factors have a
stronger support in the literature and are arguably a primary
source of influence in addi