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. Author manuscript; available in PMC: 2013 Jun 14.
Published in final edited form as: J Behav Health Serv Res. 2009 Mar 19;37(3):322–337. doi: 10.1007/s11414-009-9169-z

Top Manager Effects on Buprenorphine Adoption in Outpatient Substance Abuse Treatment Programs

Peter D Friedmann 1, Lan Jiang 2, Jeffrey A Alexander 3
PMCID: PMC3682405  NIHMSID: NIHMS469109  PMID: 19296223

Abstract

To examine the influence of top managers’ characteristics on the adoption of buprenorphine for opioid dependence among U.S. outpatient substance abuse treatment units, this investigation analyzed a cross-sectional national study of 547 such units in the 2004–2005 wave of the Drug Abuse Treatment System Survey. Administrators reported their demographics, training, and treatment orientation, as well as features of the unit and its pattern of use of buprenorphine. Nationally, 15.8% of programs offered any buprenorphine services. Greater adoption of buprenorphine correlated with directors’ younger age, longer tenure, male gender, and weaker endorsement of abstinence as the most important treatment goal. Availability of naltrexone and medical services also correlated positively with buprenorphine adoption. The authors conclude that leaders’ characteristics are related to the adoption of innovative practices in addiction treatment programs. Future work should examine whether leadership development for community addiction programs might speed up the diffusion of buprenorphine and other innovative, evidence-based practices.

Introduction

Translation of innovative, empirically supported interventions into practice is a priority for health services researchers, clinicians, and policy-makers concerned about the quality of care in substance abuse treatment programs. Medication-assisted treatment enjoys strong empirical support for the treatment of opiate dependence.1 “Medically supervised withdrawal” by substituting and tapering a long-acting full or partial agonist at the opiate mu receptor effectively decreases opiate withdrawal symptoms and short-term craving.2 Although detoxification in this manner is a standard precursor to abstinence-based treatment for opioid dependence, subsequent relapse is extremely common.2,3 By attenuating the reinforcing effects of opioids, pharmacological maintenance therapy produces the best outcomes,4 but is less accepted than detoxification in community programs.2

Buprenorphine, an innovative pharmacotherapy for opioid dependence, was marketed in the United States in early 2003. Federal law allows physicians with special qualifications or opioid treatment programs to use buprenorphine for detoxification or maintenance treatment. Prior research has examined community substance abuse treatment programs’ early adoption of buprenorphine.5–9 For example, in a national study of 299 private and 277 public treatment centers, Knudsen and colleagues8 found that adoption of buprenorphine was positively associated with private for-profit status, accreditation, availability of physician services, use of naltrexone, detoxification services, and the percentage of opiate-dependent clients. The effectiveness and acceptability of buprenorphine for detoxification differs from its indication for maintenance,3 thus separate consideration of these indications is needed to understand fully buprenorphine’s pattern of adoption in community addiction programs.

Other work supports that treatment programs that adopt innovative pharmacotherapy tend to have more commercial sources of payment, accreditation, physician staff, detoxification services, and more services for co-occurring conditions.10–12 Although these studies have established that environmental and institutional factors influence the adoption of innovative practices in substance abuse treatment programs, limited attention has been paid to the crucial role of senior leadership in the adoption process.6,13,14

A strongly held view in the organizational literature is that organizations are profoundly influenced by top managers and the decisions they make, including promoting and sustaining innovation.15–17 The top executive is the agent ultimately responsible for action on an organization’s strategy, design, performance, and technologies. This perspective is especially compelling in relatively small community organizations, like many outpatient substance abuse treatment (OSAT) programs, where clients and staff are likely to feel the influence of top management directly and keenly.18–20 By virtue of their loose specialization of function, simple structures, and short managerial hierarchies, small organizations are very susceptible to direct managerial control.19,21–23 Idiosyncratic leadership is also common in such organizations, rendering the individual attributes of the leader synonymous with the role of the top manager.23,24 The current study thus examines the influence of senior managers’ characteristics on the adoption of buprenorphine detoxification and maintenance in a nationally representative sample survey of OSAT agencies.

Conceptual framework

Senior managers are responsible for key decisions that dictate an organization’s policies and procedures.17,25,26 Directors’ observable attributes serve as proxies for attitudes and abilities relevant to their unit’s adoption of buprenorphine. Differing norms and/or self-efficacy may lead some directors to innovate more than others.27 Superior interpersonal or managerial skills will make some directors more able to implement evidence-based practices.6,28

The above mechanisms notwithstanding, leaders might influence organizational innovation by creating environments that contribute to organizational learning and adoption of new practices, or conversely, organizations might attract, recruit, and select leaders to match their prevailing culture or strategy, thus reinforcing existing practices or behavior.29 To understand these relationships, investigations must evaluate whether observed associations between director attributes and buprenorphine adoption remain after controlling for important characteristics of the organization and its clientele. If observed associations hold while controlling for such contextual characteristics, it suggests that leadership attributes operate independently of the organizational and environmental context. On the other hand, the disappearance of such associations after controlling for contextual characteristics suggests that leaders with those attributes might self-select or are selected into OSAT programs with congruent culture, strategy, and practices. The current study posits that the characteristics of senior managers, like institutional and environmental factors, influence the adoption of innovative practices.17,25 Specifically, leaders’ characteristics like tenure at the organization, training, treatment orientation, age, and gender may influence their propensity to accept and promote new ideas.6,28

Tenure

Some work has suggested that, with longer tenure, directors gain experience maneuvering through institutional barriers to change and thus are more effective in promoting innovation.30–32 Other work suggests the converse: directors with longer tenure within the organization may be more professionally invested in the status quo and have a lower propensity to accept and promote innovation.25,33,34 Although both of these perspectives have merit, the first hypothesis examines whether:

H1: Longer director tenure at the agency will be negatively correlated with the adoption of buprenorphine.

Training

A leader’s education and training influences their likelihood of promoting medically oriented treatments and their skill in their use.35 Previous work has found that treatment program administrators with medical training are more open to pharmacological interventions.6,11 Conversely, directors with training as substance abuse counselors lack medical training and are more likely to be socialized to the primacy of abstinence-oriented counseling over pharmacotherapy.35,36

H2: Buprenorphine adoption will be negatively correlated with the directors’ licensure or certification as a substance abuse counselor.

Treatment orientation

The treatment orientation indicates the leaders’ view of treatments like buprenorphine. A traditional treatment orientation views abstinence as the primary goal and may view the 12-step model (whose goal is complete abstinence) as highly effective. Such an orientation is less compatible with pharmacotherapy than one grounded in the biomedical model.

H3: Buprenorphine adoption will be negatively correlated with the directors’ endorsement of complete abstinence as the most important treatment goal.

H4: Buprenorphine adoption will be negatively correlated with the directors’ high rating of the extent to which the 12-step model of treatment is effective with substance abuse clients.

Effects of age and gender are more difficult to explain as predictors of buprenorphine adoption. Conventional wisdom about age has been that people tend to become less open to new practices with time. This would imply that younger unit directors would be more favorably disposed toward adoption of new technologies or practices. General management research suggests that younger managers are more receptive to innovation, more likely to accept new ideas and risk inherent in innovation, and more flexible to adapt to new ideas and procedures.25,33,37,38. Although Young et al.25 found a negative association between administrator age and adoption of total quality management in their study of VA hospitals, another large study of US public organizations found no association.38 The literature is similarly equivocal regarding the supposition that older leaders have more influence over innovation adoption because of greater store of learning and access to information networks over time.39,40

As with age, theory and evidence are insufficient to make definitive directional hypotheses about how the director’s gender might relate to buprenorphine use. Moore et al.40 did not find differences in attitudes toward treatment between substance abuse treatment opinion leaders and other counselors by gender. A survey of nonprofit executives found that male respondents were more likely to report successful interagency collaborations, but did not predict innovation adoption.41 However, because of an interest in identifying potential, identifiable leadership attributes associated with buprenorphine use, however, both age and gender are included for exploratory purposes.

Control variables

The institutional and environmental characteristics of substance abuse treatment organizations also influence adoption of innovations.6,11,42 For the current analysis, control variables include ownership, affiliation, and prior medical and pharmacological practices.8 Privately owned units have competitive and marketing pressures that create incentives to adopt cutting-edge practices like buprenorphine treatment.43 Hospital-based programs, those with more medical staffing and a medicalized approach to addictive disorders (e.g., physical examinations, other pharmacotherapy, etc.) could adopt novel medications more readily because their experience with pharmaceutical procedures (e.g., dispensing, side effect monitoring) make them better prepared to absorb the innovation.6,44 Relatedly, units that already use pharmacological approaches will also be more likely to adopt a new pharmacological agent.11 Furthermore, on-site medical staff could facilitate prescription and delivery of pharmacotherapy or serve as opinion leaders.45,46 A unit’s commitment to quality care affects its propensity to provide evidence-based treatments.47,48 Organizations accredited by the Joint Commission on Accreditation of Health Care Organizations (JCAHO) are thus expected to be more likely to adopt buprenorphine.

Programs with uncertain or scarce resources tend to forgo innovation.49 Hence, drug treatment organizations subject to the liabilities of “newness” and “smallness” may be less likely to adopt buprenorphine.50 Conversely, larger units may be more likely to innovate because they face less uncertainty about their survival and have greater slack resources.43,51

Finally, programs adapt their practices to the needs of the population they serve.52,53 Client characteristics indicative of differential need and resources include clients’ gender, race, insurance status, heroin and injection drug use, and prescription drug use.54

Methods

Sample and data collection

This study analyzed data from the sixth wave (2004–2005) of the Drug Abuse Treatment System Survey (DATSS). The DATSS was a longitudinal study of OSAT units conducted by the Institute for Social Research, University of Michigan. In the DATSS, an OSAT unit was formally defined as a physical facility with a majority of resources (>50%) dedicated to treating individuals with substance abuse problems (including alcohol and other drugs) on an outpatient basis. Programs run by the Veteran’s Administration and by correctional facilities were excluded from the sample. DATSS was a telephone survey of 550 pairs of administrative directors and clinical supervisors at each unit, with the response rate of 88.3% and 87.5%, respectively. This analysis used only 547 pairs because of the deletion of units with incomplete data on buprenorphine adoption.

Experienced interviewing staff conducted the survey from the Survey Research Center at the University of Michigan. The survey was administered using computer-aided telephone interviewing system that promoted data reliability and validity. Two pretests with national representative samples of N=20 units each were conducted before the survey. As the data were collected, computer programs performed extensive reliability checks that notified interviewers when numbers did not sum as they should or were out of expected ranges (e.g., the percent of clients receiving various methadone dose levels should sum to 100%). Interviewers then worked with respondents to resolve inconsistencies.

Measures

Dependent variables

Adoption of buprenorphine was examined through three primary outcomes: any use of buprenorphine at all; any use for detoxification; and any use for opioid maintenance therapy. Clinical supervisors were asked the percentage of the unit’s outpatient substance abuse clients receiving buprenorphine for opiate detoxification and the percentage that received buprenorphine for opioid maintenance therapy. Units having at least one client receiving buprenorphine for the above services were coded as yes, otherwise no. In addition, indicating overall adoption of buprenorphine was coded yes if the unit had at least one client receiving buprenorphine for either of the above services, otherwise no.

In programs that reported any use of buprenorphine, secondary outcomes examined implementation as the percentage of clients that received buprenorphine for detoxification or maintenance. Implementation levels were categorized by tertile as low (1% to 1.9% of clients), moderate (2% to 5%), or high (5% or greater).

Explanatory variables

Program leadership

The characteristics assessed of administrative directors included sex, age, tenure at the agency in years, race/ethnicity, and whether he/she possessed the license/certification as a substance abuse treatment counselor. Clinical supervisor characteristics were highly correlated with respective director characteristics, so they were excluded from the analysis to avoid multicollinearity. Supervisors were asked the extent of the treatment effectiveness of the Alcoholics Anonymous or Narcotics Anonymous 12-step model. The categories were “no extent, a little extent, some extent, a great extent, and a very great extent” (reference category). Among a list of ten treatment goals for the program, the clinical supervisors rank ordered from 1, the most, to 10, the least important priorities of the program. The units’ abstinence orientation was coded as 1 when the supervisors ranked complete abstinence as the most important treatment goal and 0 otherwise; approximately 82% ranked complete abstinence as the most important treatment goal. Number of days from January 1, 2003 to the interview date approximated the time since public launch of buprenorphine in the United States and controlled for the effect of time on the individual adoption of buprenorphine.

Program characteristics

Ownership was dummy-coded as private for-profit or private not-for-profit, with public ownership as the referent. Similarly, affiliation was dummy-coded as hospital, mental health center, or other organization, with freestanding as the referent. Methadone availability was generated from clinical supervisors’ reports of whether their program provided methadone treatment. The availability of detoxification services and the use of naltrexone treatment were included in addition to methadone availability. JCAHO accreditation was a dummy variable; no accreditation served as the referent. Program age, measured as years from the year when the unit began to provide OSAT services until the year of the interview (2004), was included. Program size, measured as the number of clients per year reported by the director, was also considered. To determine the breadth of medical services available, the number of routine medical services the clinic offered was summed. The seven possible services included physical examinations, routine medical care, HIV testing, HIV/AIDS acute treatment, tuberculosis screening, sexually transmitted disease testing, and hepatitis screening.

One program measure assessed medical staffing; it was coded 1 if the program had at least one staff physician or registered nurse and zero if there was no medical staff. Another staffing measure was the percentage of recovering alcoholic staffs in the unit. Due to skewness of the data, the variable was categorized into four levels: 0–5% recovering alcoholic staff among permanent staff, 6–20%, 21–40%, and 41–100% (reference category).

Measures of program treatment characteristics were also included. The routine use of the American Society of Addition Medicine (ASAM) criteria was dummy-coded, with no as the referent. Whether the program conducted physical assessments for all clients at intake was also dummy-coded, with no as the referent. In addition, a measure of urine testing was coded as 1 if all clients were monitored through urine testing, otherwise 0.

Client characteristics

To assess resources and needs of the population served in these programs, explanatory variables included mean client age, as well as the percentage of clients in the past fiscal year who were: female; Hispanic/Latino; African American; uninsured and unable to pay for treatment; insured by Medicaid; heroin users; injection drug users; and over-the-counter or prescription drug users.

Data analysis

Analyses weighted to adjust for sample selection probability evaluated the characteristics of programs adoption of buprenorphine at all, adoption for opiate detoxification, and adoption for opioid maintenance therapy. In a process of manual backward selection, bivariate correlates of the three outcomes at the P<0.2 level of significancce [not shown] entered multivariate logistic regression models, respectively; final models retain explanatory variables with P<0.05. Similar procedures were used in two exploratory ordinal logistic regression models for detoxification and maintenance, respectively, that assess the independent correlates of low (1% to 1.9%), moderate (2% to 5%), or high (5% or greater) implementation levels. All significancce tests were two-tailed.

Results

Descriptive results

Of the 547 OSAT units, 28 adopted buprenorphine for opioid detoxification only, 19 adopted buprenorphine for opioid maintenance only, and 36 adopted buprenorphine for both. Table 1 presents the characteristics of the 83 programs that had any buprenorphine services, the 64 that offered any opioid detoxification, and the 55 with any opioid maintenance therapy, weighted to be nationally representative. Buprenorphine was available at 24 (15.8%) of the 152 programs that had methadone available, compared to 59 (14.9%) of the 395 nonmethadone programs. Of the 326 programs with medical staff, 19.9% had buprenorphine available, compared with 7% among programs without medical staff.

Table 1.

National estimates of clinic and client characteristics of facilities associated with buprenorphine treatment

Offer any buprenorphine
Offer buprenorphine detoxification
Offer buprenorphine maintenance
No Yes No Yes No Yes
Overall national estimates (%) 84.2 15.8 85.9 14.1 91.0 9.0
Program leadership
 Director age, mean years (SD) 50.8 (30.0) 44.2 (27.9)**** 50.8 (30.0) 43.7 (30.1)**** 50.0 (31.7) 46.9 (19.5)**
 Director tenure at agency (per 10 years) 10.7 (28.1) 9.4 (23.7) 10.6 (27.7) 9.5 (25.6) 10.6 (28.1) 8.5 (19.9)*
 Director sex
  Male 82.0 18.0**** 84.0 16.0**** 87.7 12.3****
  Female 87.9 12.1**** 89.0 11.0**** 96.1 3.9****
 Director race
  White 82.4 17.6**** 84.2 15.8**** 89.8 10.2****
  Black 95.9 4.1**** 97.1 2.9**** 97.6 2.4****
  Other 94.7 5.3**** 95.0 5.0**** 97.8 2.2****
 Director ethnicity
  Hispanic 94.7 5.3**** 95.2 4.8**** 97.3 2.7****
  Non-Hispanic 83.8 16.2**** 85.5 14.5**** 90.6 9.4****
 Director licensed or certified as substance abuse counselor
  Yes 86.7 13.3**** 88.2 11.8**** 2.0 8.0***
  No 79.5 20.5**** 81.5 18.5**** 89.0 11.0***
 Complete abstinence as most important treatment goal
  Yes 84.7 15.3* 86.3 13.7* 92.9 7.1****
  No 82.3 17.7* 84.1 15.9* 83.9 16.1****
 Extent that 12-step model of treatment effective with substance abuse clients
  No extent 96.0 4.0**** 100.0 0.0**** 96.0 4.0****
  A little extent 53.5 46.5**** 53.5 46.5**** 54.5 45.5****
  Some extent 86.8 13.2**** 89.0 11.0**** 95.3 4.7****
  A great extent 92.5 7.5**** 94.0 6.0**** 95.3 4.7****
  A very great extent 72.2 27.8**** 73.7 26.3**** 84.9 15.1****
Program characteristics
 Ownership (%)
  Private for-profit 90.8 9.2**** 93.2 6.8**** 93.1 6.9****
  Private not-for-profit 76.6 23.4**** 77.5 22.5**** 87.7 12.3****
  Public 95.7 4.3**** 97.9 2.1**** 96.7 3.3****
 Affiliation (%)
  Hospital 65.2 34.8**** 69.4 30.6**** 89.5 10.5****
  Mental health 98.0 2.0**** 98.2 1.8**** 99.2 0.8****
  Other organization 80.0 20.0**** 81.8 18.2**** 86.8 13.2****
  Freestanding 91.6 8.4**** 92.7 7.3**** 94.1 5.9****
 Methadone available
  Yes 87.0 13.0* 92.4 7.6**** 91.5 8.5
  No 83.8 16.2* 84.8 15.2**** 90.9 9.1
 Offers detoxification services
  Yes 66.0 34.0**** 71.2 28.8**** 71.0 29.0****
  No 86.9 13.1**** 88.0 12.0**** 93.8 6.2****
 Offers naltrexone treatment
  Yes 57.8 42.2**** 64.8 35.2**** 80.3 19.7****
  No 88.8 11.2**** 89.4 10.6**** 92.7 7.3****
 JCAHO accredited
  Yes 77.2 22.8**** 80.6 19.4**** 92.1 7.9
  No 86.1 13.9**** 87.3 12.7**** 90.8 9.2
 Breadth of medical services provided, mean (SD) 3.5 (8.2) 4.5 (7.3)*** 3.5 (8.1) 4.3 (8.0)** 3.4 (8.1) 5.5 (5.2)****
 Has medical staff
  Yes 76.7 23.3**** 80.5 19.5**** 90.9 9.1
  No 90.3 9.7**** 90.3 9.7**** 91.2 8.8
Percentage of recovering staff
  0–5 94.4 5.6**** 96.3 3.7**** 96.6 3.4****
  6–20 72.8 27.2**** 74.7 25.3**** 84.8 15.2****
  21–40 78.4 21.6**** 79.1 20.9**** 94.4 5.6****
  41–100 87.3 12.7**** 88.8 11.2**** 88.6 11.4****
 Program age, mean years (SD) 16.4 (36.3) 20.5 (41.0)** 16.6 (36.1) 20.2 (44.8)* 17.2 (37.5) 15.6 (35.4)
 Program size, mean no. clients per year (SD) 505 (3246) 1823 (11077)*** 510 (3208) 1920 (12486)** 712 (5336) 779 (6680)
 Routinely use ASAM criteria
  Yes 86.5 13.5**** 88.5 11.5**** 90.2 9.8
  No 80.7 19.3**** 82.0 18.0**** 91.4 8.6
 Conduct physical assessment at intake
  Yes 83.2 16.8**** 84.8 15.2* 90.3 9.7
  No 85.1 14.9**** 86.8 13.2* 91.5 8.5
 All clients’ progress monitored through urine testing
  Yes 76.2 23.8**** 77.9 22.1**** 89.6 10.4**
  No 90.2 9.8**** 91.8 8.2**** 91.9 8.1**
Client characteristics
 Weighted client mean age, mean years (SD) 35.6 (17.6) 36.3 (17.6) 35.6 (17.6) 36.0 (17.5) 35.6 (17.5) 36.0 (18.4)
 Percent female, mean (SD) 33.0 (63.2) 43.5 (56.4)**** 32.9 (62.4) 45.3 (58.4)**** 33.8 (63.7) 41.5 (55.7)**
 Percent Hispanic/Latino, mean (SD) 16.4 (67.1) 20.3 (47.9)* 16.3 (66.6) 21.0 (46.8)* 16.7 (66.3) 20.3 (47.2)
 Percent African American, mean (SD) 24.0 (95.1) 20.5 (68.6) 23.9 (93.9) 20.6 (73.2) 23.5 (93.5) 22.9 (73.0)
 Uninsured clients admitted
  Yes 84.1 15.9**** 85.6 4.4**** 9.8 10.2****
  No 91.7 8.3**** 93.3 6.7**** 94.1 5.9****
 Medicaid clients admitted
  Yes 80.7 19.3**** 83.0 17.0**** 88.9 11.1****
  No 90.3 9.7**** 91.5 8.5**** 92.2 7.8****
 Percent clients use heroin, mean (SD) 16.6 (94.7) 23.4 (72.4)* 16.9 (93.9) 22.9 (75.4)* 17.2 (94.2) 22.6 (69.2)
 Percent clients use drug involved injection with needles, mean (SD) 16.1 (79.9) 21.6 (59.4)* 16.2 (78.8) 21.7 (64.8)* 16.3 (79.0) 24.5 (58.1)**
 Percent clients use over-the-counter or prescription drugs, mean (SD) 8.4 (50.0) 16.7 (59.4)**** 8.7 (50.7) 16.0 (58.2)*** 9.2 (51.4) 15.4 (57.2)*
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Proportions, means, and standard deviations were based on a stratified sample of 547 units weighted to be representative of 6,339 units nationally

*

P<0.05;

**

P<0.01;

***

P<0.001;

****

P<0.0001

In multivariate analyses (Table 2, data column 1), programs with older and female directors were less likely to adopt buprenorphine at all. Programs whose directors ranked complete abstinence as the most important treatment goal were also less likely to adopt buprenorphine, as were programs affiliated with mental health centers compared to freestanding units. Regarding breadth of available medical services, every additional medical service was associated with an estimated 20% increase in buprenorphine services. Programs with medical staff were almost three times more likely to adopt buprenorphine and programs that use naltrexone were six times more likely. However, programs that provided physical assessments for all patients appeared to be half as likely to adopt buprenorphine. Time since public launch of buprenorphine in the United States showed no effect on the adoption of buprenorphine at all; the effect is insignificanct (P=0.89).

Table 2.

Multivariate correlates of buprenorphine use in outpatient substance abuse treatment programs

Odds ratio estimate (95%CI)
Offer any buprenorphine Offer buprenorphine detoxification Offer buprenorphine maintenance
Program leadership
 Director tenure at agency (per 10 years) – 1.5 (1.0, 2.3)*
 Complete abstinence as most important treatment goal 0.4 (0.2, 0.9)* – 0.5 (0.2, 0.9)*
 Director age (per 10 years) 0.6 (0.4, 0.9)** 0.6 (0.4, 0.8)** 0.6 (0.4, 0.9)*
 Male director 1.8 (1.0, 3.3)* 2.0 (1.1, 3.8)* 2.1 (1.1, 4.0)*
Program characteristics
 Affiliation – –
  Hospital 1.2 (0.5, 2.7) – –
  Mental health 0.2 (0.1, 0.7)* – –
  Other organization 0.8 (0.4, 1.5) – –
  Freestanding Referent – –
 Offers naltrexone 6.0 (3.3, 11.0)**** 7.0 (3.7, 13.3)**** 6.1 (3.2, 11.4)****
 Breadth of medical services provided 1.2 (1.1, 1.4)** – 1.2 (1.0, 1.4)*
 Has medical staff 2.8 (1.4, 5.7)** – –
 Physical exams for all clients 0.5 (0.3, 0.9)* – –
Client characteristics
 Percent female clients (per 10%) – 1.3 (1.1, 1.5)** –
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From multivariate logistic models

*

P<0.05;

**

P<0.01;

***

P<0.001;

****

P<0.0001

Adoption of buprenorphine for detoxification

Director age and gender had a similar effect on buprenorphine adoption for detoxification (Table 2, data column 2) as for any adoption of buprenorphine. Longer director tenure at the agency, naltrexone use, and serving more female clients was associated with increased adoption of buprenorphine for detoxification. Program affiliation, breadth of medical services, or provision of physical assessments for all clients did not influence the adoption of buprenorphine for detoxification.

Adoption of buprenorphine for maintenance

Older director age, female gender, and endorsement of abstinence as the most important treatment goal were associated with a lower likelihood of adopting buprenorphine for opioid maintenance (Table 2, data column 3). Naltrexone use and breadth of medical services were again associated with greater adoption of buprenorphine for opioid maintenance. No other variables emerged as correlates of the adoption of buprenorphine for maintenance therapy services.

Implementation of buprenorphine

Very few patients received buprenorphine in these programs. For example, in the 83 units that adopted buprenorphine at all, a mean of 6.3±13.6% [median, 2%; range 0–85%] of clients received it for opioid detoxification and 6.6±16.3% [median, 2%; range 0–100%] of clients received it for maintenance. In ordinal logistic regression models, only JCAHO accreditation (OR=7.0; 95%CI=2.2 to 22; P<0.001), offering naltrexone (OR=2.6; 95%CI=0.9 to 7.1; P<0.07), and serving more female clients (OR=1.0 per 10% increase; 95%CI=1.0 to 1.1; P< 0.08) were associated with increased implementation of buprenorphine detoxification. No correlates were detected of implementation of buprenorphine for maintenance therapy.

Discussion

Although directional hypotheses regarding age and gender were not specified, this nationally representative sample survey of OSAT programs found that programs most likely to have adopted buprenorphine in 2004 had younger and male administrators whose orientation was least orthodox regarding complete abstinence, even controlling for other leadership characteristics, institutional variables, and client variables. One potential explanation is that greater age and female gender might be associated with more risk-averse attitudes toward innovation. For example, conventional wisdom has been that people tend to become more risk-averse with time. This would imply that, in general, older unit directors would be less favorably disposed toward novel practices. There may also be a historical effect, such that individuals who were trained a long time ago will be less open to treatment practices that differ philosophically from their accustomed models for appropriate substance abuse treatment. Indeed, a traditional, abstinence-only treatment orientation is a well-documented factor in the acceptability and use of medications, especially agonist or partial agonist substitution therapy, to treat addictive disorders.55 Recent initiatives in training and staff development thus might make younger leaders more accepting of pharmacotherapies and innovative approaches.56

Controlling for age, however, administrators with longer tenure might have the experience and bonafides to successfully change the organization’s policies and procedures. Directors with more experience in their units are also likely to understand the staff, clients, and context better than less experienced directors, and thus, have stronger implementation skills. In addition, long-tenured directors should have developed influence with supervisors and staff over time, further enhancing the likelihood of successful adoption. An awareness of these assets should make adoption as well as implementation more likely, given greater optimism about success,27 though the evidence to date has been mixed. Indeed, a recent meta-analysis found a positive overall association between leader tenure and organizational innovation.57

It is uncertain why the current study detected no effect of private ownership, accreditation, or percentage of opiate-dependent patients. The reasons for the finding regarding female leaders are equally obscure. The literature suggests that gender effects may differ somewhat in health care compared to other sectors. For example, although women in nonhealth care organizations tend to rate their own leadership qualities and effectiveness less highly than men, this difference is attenuated in health care organizations.58 Similarly, the “glass ceiling” phenomenon within senior management teams is thought to be less pronounced in health care than in other industries.59,60 Thus, the finding that units led by women directors are less likely to be adopters should be considered exploratory.

Like a recent analysis of the National Treatment Center Study,8 medical services and staffing and current use of naltrexone correlated with adoption of buprenorphine. These findings are consistent with the notion that a medical-oriented cultural consensus within the program facilitates adoption of innovative pharmacological treatments.61

Several limitations warrant mention. Because of its cross-sectional design, this study cannot determine causal direction, although many of the explanatory variables were relatively fixed structural characteristics. Only a limited number of measures of the organizational environment could be examined—other influential factors undoubtedly exist. Furthermore, although organizational-level reports in DATSS have been compared against client-level responses for some measures,62 reports of buprenorphine adoption have not been specifically validated. The possibility remains that an affirmative response regarding buprenorphine availability could have been the result of availability from outside sources rather than true adoption within the program. Organizational scholars have also criticized studies that use observable attributes such as education and tenure in place of the social–psychological factors they are believed to represent, assuming that these attributes affect organizational outcomes through unmeasured and, thus, untestable mediators and yielding only prediction without explanation about why such patterns might exist.63 Given the very early stage of leadership research in substance abuse treatment, however, it is appropriate to begin with tests of association between observable attributes, leaving future research to probe how and why identified patterns emerged.

Implications for Behavioral Health

Adoption of evidence-based medication-assisted therapies is important as community addiction treatment programs address the problem of early attrition of opioid-dependent patients.64 Despite buprenorphine’s safety and efficacy, its adoption has been relatively delayed compared to many innovations in health care. Leadership appears key to the adoption of buprenorphine in addiction treatment programs. That said, leaders in behavioral health care often face inconsistent or conflicting demands.65 Many of these demands stem from strong, but fragmented, institutional and market forces.66 Leaders feel pressure to improve both quality and access to services but, at the same time, reduce costs. This situation makes the decision as to what technologies to adopt a critical leadership issue.

Another challenge derives from uncertainty surrounding the work of behavioral health care organizations. As a human service, behavioral health care entails great variability in the nature of the “inputs” and uncertain means–ends causal relationships in production, which, in turn, creates problems in defining and measuring organizational outcomes.67 Despite this uncertainty, OSAT leaders must decide the optimal mix of services, treatment practices, and staffing that they think will result in the best outcomes for their clients

Finally, leaders in the behavioral health sector must deal with a mix of professional and nonprofessional providers who continue to dominate day-to-day work in substance abuse treatment care organizations. Providers of all types have ambivalent relationships with organizations and may resist practices that are not consistent with established norms or experience. For example, the substance abuse field and its largely recovering workforce still struggle with the normative legacy of the 12-step movement’s insistence on abstinence and suspicion of medication-assisted treatment. Although the articulation of standards for competent practice will help,56,68 the challenge of influencing norms within these organizations is a primary task for effective local leadership.

This study’s findings suggest that leaders less ideologically grounded in the “abstinence-only” approach are more likely to promote innovative practices like buprenorphine. Other characteristics of leaders, such as age, also influence adoption. Consistent with previous findings,8 an established medical culture, including on-site medical services, staffing, and current use of other medications for addictive disorders, also facilitate adoption of buprenorphine. Further study is needed to determine whether initiatives in leadership development for community addiction programs might speed up the diffusion of buprenorphine and other innovative, evidence-based practices.

Acknowledgments

Grant R01-DA32727 from the National Institute on Drug Abuse (NIDA) supported this research. Dr. Friedmann directs the Program to Integrate Psychosocial and Health Services, a Targeted Research Enhancement Program (TRP 04-179) supported by the Department of Veterans Affairs Health Services Research & Development Service at the Providence Veterans Affairs Medical Center (Rhode Island). The views expressed in this article are the authors’ and not necessarily those of the National Institute on Drug Abuse or Department of Veterans Affairs.

Contributor Information

Peter D. Friedmann, Center on Systems, Outcomes & Quality in Chronic Disease & Rehabilitation (SOQCR), Research Service, Providence Veterans Affairs Medical Center and Alpert Medical School of Brown University, Providence, RI, USA.

Lan Jiang, Email: Lan.Jiang@va.gov, Center on Systems, Outcomes & Quality in Chronic Disease & Rehabilitation, Research Service, Providence Veterans Affairs Medical Center, Providence, RI, USA. Phone: +1-401-2737100; Fax: +1-401-4573311.

Jeffrey A. Alexander, Email: jalexand@umich.edu, Department of Health Management and Policy, School of Public Health, University of Michigan, Ann Arbor, MI, USA. Phone: +1-734-9361194; Fax: +1-734-7644338;.

References

  • 1.Kakko J, Gronbladh L, Svanborg KD, et al. A stepped care strategy using buprenorphine and methadone versus conventional methadone maintenance in heroin dependence: a randomized controlled trial. American Journal of Psychiatry. 2007;164(5):797–803. doi: 10.1176/appi.ajp.164.5.797. [DOI] [PubMed] [Google Scholar]
  • 2.Kleber HD. Pharmacologic treatments for opioid dependence: detoxification and maintenance options. Dialogues in Clinical Neuroscience. 2007;9(4):455–470. doi: 10.31887/DCNS.2007.9.2/hkleber. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Stein MD, Friedmann PD. Optimizing opioid detoxification: rearranging deck chairs on the Titanic. Journal of Addictive Diseases. 2007;26(2):1–2. doi: 10.1300/J069v26n02_01. [DOI] [PubMed] [Google Scholar]
  • 4.Mattick RP, Breen C, Kimber J, Davoli M. Methadone maintenance therapy versus no opioid replacement therapy for opioid dependence. Cochrane Database of Systematic Reviews. 2002;(4):CD002209. doi: 10.1002/14651858.CD002209. [DOI] [PubMed] [Google Scholar]
  • 5.Heinrich CJ, Lynn LE., Jr Improving the organization, management, and outcomes of substance abuse treatment programs. American Journal of Drug and Alcohol Abuse. 2002;28(4):601–622. doi: 10.1081/ADA-120015871. [DOI] [PubMed] [Google Scholar]
  • 6.Roman PM, Johnson JA. Adoption and implementation of new technologies in substance abuse treatment. Journal of Substance Abuse Treatment. 2002;22(4):211–218. doi: 10.1016/S0740-5472(02)00241-6. [DOI] [PubMed] [Google Scholar]
  • 7.Simpson DD. A conceptual framework for transferring research to practice. Journal of Substance Abuse Treatment. 2002;22(4):171–182. doi: 10.1016/S0740-5472(02)00231-3. [DOI] [PubMed] [Google Scholar]
  • 8.Knudsen HK, Ducharme LJ, Roman PM. Early adoption of buprenorphine in substance abuse treatment centers: data from the private and public sectors. Journal of Substance Abuse Treatment. 2006;30(4):363–373. doi: 10.1016/j.jsat.2006.03.013. [DOI] [PubMed] [Google Scholar]
  • 9.D’Aunno T. The role of organization and management in substance abuse treatment: review and roadmap. Journal of Substance Abuse Treatment. 2006;31(3):221–233. doi: 10.1016/j.jsat.2006.06.016. [DOI] [PubMed] [Google Scholar]
  • 10.Ducharme LJ, Knudsen HK, Roman PM, et al. Innovation adoption in substance abuse treatment: exposure, trialability, and the Clinical Trials Network. Journal of Substance Abuse Treatment. 2007;32(4):321–329. doi: 10.1016/j.jsat.2006.05.021. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Knudsen HK, Ducharme LJ, Roman PM. The adoption of medications in substance abuse treatment: associations with organizational characteristics and technology clusters. Drug and Alcohol Dependence. 2007;87(2–3):164–174. doi: 10.1016/j.drugalcdep.2006.08.013. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Ducharme LJ, Knudsen HK, Roman PM. Trends in the adoption of medications for alcohol dependence. Journal of Clinical Psychopharmacology. 2006;26(Suppl 1):S13–S19. doi: 10.1097/01.jcp.0000246209.18777.14. [DOI] [PubMed] [Google Scholar]
  • 13.Bradley EH, Schlesinger M, Webster TR, et al. Translating research into clinical practice: making change happen. Journal of the American Geriatric Society. 2004;52(11):1875–1882. doi: 10.1111/j.1532-5415.2004.52510.x. [DOI] [PubMed] [Google Scholar]
  • 14.Bradley EH, Webster TR, Baker D, et al. After adoption: sustaining the innovation. A case study of disseminating the hospital elder life program. Journal of the American Geriatric Society. 2005;53(9):1455–1461. doi: 10.1111/j.1532-5415.2005.53451.x. [DOI] [PubMed] [Google Scholar]
  • 15.Chagantim R, Sambharya S. Strategic orientation and characteristics of upper management. Strategic Management Journal. 1987;8:393–401. doi: 10.1002/smj.4250080409. [DOI] [Google Scholar]
  • 16.Miller D, Kets De Vries M, Toulouse J. Top executive’s locus of control and its relation to strategy making, structure and environment. Academy of Management Journal. 1982;25:237–253. doi: 10.2307/255988. [DOI] [Google Scholar]
  • 17.Hambrick DC, Mason PA. Upper echelons: the organization as a reflection of its top managers. Academy of Management Review. 1984;9:193–206. doi: 10.2307/258434. [DOI] [Google Scholar]
  • 18.Carroll G. Dynamics of publisher succession in newspaper organizations. Administrative Science Quarterly. 1984;59:93–113. doi: 10.2307/2393082. [DOI] [Google Scholar]
  • 19.Levinthal DA. Organizational adaptation, environmental selections and random walks. In: Singh JV, editor. Organizational Evolutions: New Directions. Newbury Park, CA: Sage; 1990. pp. 201–223. [Google Scholar]
  • 20.Miller D, Droge C. The relative determinants of structures in small firms. Administrative Science Quarterly. 1986;31:539–560. doi: 10.2307/2392963. [DOI] [Google Scholar]
  • 21.Haveman H. Ghosts of managers past: managerial succession and organization mortality. Academy of Management Journal. 1993;36:864–881. doi: 10.2307/256762. [DOI] [Google Scholar]
  • 22.Mintzberg H. The Structuring of Organizations: A Synthesis of the Research. Englewood Cliffs, NJ: Prentice Hall; 1979. [Google Scholar]
  • 23.Preisendoerfer P, Voss T. Organizational mortality of small firms: the effects of entrepreneurial age and human capital. Organizational Studies. 1990;11:107–129. doi: 10.1177/017084069001100109. [DOI] [Google Scholar]
  • 24.Kanter RM. Men and Women of the Corporation. New York: Basic Books; 1977. [Google Scholar]
  • 25.Young GJ, Charns MP, Shortell SM. Top manager and network effects on the adoption of innovative management practices: a study of TQM in a public hospital system. Strategic Management Journal. 2001;22:935–951. doi: 10.1002/smj.194. [DOI] [Google Scholar]
  • 26.Bradley EH, Webster TR, Baker D, et al. Translating research into practice: speeding the adoption of innovative health care programs. Commonwealth Fund Issue Brief. 2004;724:1–12. [PubMed] [Google Scholar]
  • 27.Bandura A. Personal and collective efficacy in human adaptation and change. In: Adair JG, Belanger D, Dion KL, editors. Advances in Psychological Science: Social, Personal and Cultural Aspects. Montreal: Psychology Press; 1996. [Google Scholar]
  • 28.Wells R, Lemak CH, D’Aunno TA. Insights from a national survey into why substance abuse treatment units add prevention and outreach services. Substance Abuse Treatment, Prevention and Policy. 2006;1(1):21. doi: 10.1186/1747-597X-1-21. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Kraatz MA, Moore JH. Executive migration and institutional change. Academy of Management Journal. 2002;45:120–145. doi: 10.2307/3069288. [DOI] [Google Scholar]
  • 30.Kimberly JR, Evanisko MJ. Organizational innovation: the influence of individual, organizational and contextual factors on hospital adoption of technological and administrative innovations. Academy of Management Journal. 1981;24(4):689–713. doi: 10.2307/256170. [DOI] [PubMed] [Google Scholar]
  • 31.Meyer AD, Goes JB. Organizational assimilation of innovations: a multilevel contextual analysis. Academy of Management Journal. 1988;31(4):897–923. doi: 10.2307/256344. [DOI] [Google Scholar]
  • 32.Arndt M, Bigelow B. The adoption of corporate restructuring by hospitals. Hospital and Health Services Administration. 1995;40 (3):332–347. [PubMed] [Google Scholar]
  • 33.Grimm CM, Smith KG. Management and organizational change: a note on the railroad industry. Strategic Management Journal. 1991;12:557–562. doi: 10.1002/smj.4250120708. [DOI] [Google Scholar]
  • 34.Boeker W. Strategic change: the influence of managerial characteristics and organizational growth. Academy of Management Journal. 1997;40:152–170. doi: 10.2307/257024. [DOI] [Google Scholar]
  • 35.D’Aunno T, Pollack HA. Changes in methadone treatment practices: results from a national panel study, 1988–2000. Journal of the American Medical Assocation. 2002;288(7):850–856. doi: 10.1001/jama.288.7.850. [DOI] [PubMed] [Google Scholar]
  • 36.Kerwin ME, Walker-Smith K, Kirby KC. Comparative analysis of state requirements for the training of substance abuse and mental health counselors. Journal of Substance Abuse Treatment. 2006;30(3):173–181. doi: 10.1016/j.jsat.2005.11.004. [DOI] [PubMed] [Google Scholar]
  • 37.Carlson R, Karlsson K. Age, cohorts and the generation of generations. American Sociological Review. 1970;35:710–718. doi: 10.2307/2093946. [DOI] [Google Scholar]
  • 38.Damanpour F, Schneider M. Phases of the adoption of innovation in organizations: effects of environment, organization and top managers. British Journal of Management. 2006;17:215–236. doi: 10.1111/j.1467-8551.2006.00498.x. [DOI] [Google Scholar]
  • 39.Berger J, Zelditch M, editors. Status, Rewards, and Influence. How Expectations Organize Behavior. Washington, DC: Jossey-Bass; 1985. [Google Scholar]
  • 40.Moore KA, Peters RH, Hills HA, et al. Characteristics of opinion leaders in substance abuse treatment agencies. American Journal of Drug and Alcohol Abuse. 2004;30(1):187–203. doi: 10.1081/ADA-120029873. [DOI] [PubMed] [Google Scholar]
  • 41.Goldman S, Kahnweiler WM. A collaborator profile for executives of nonprofit organizations. Nonprofit Management and Leadership. 2000;10(4):435–450. doi: 10.1002/nml.10406. [DOI] [Google Scholar]
  • 42.Friedmann PD, Lemon SC, Durkin EM, et al. Trends in comprehensive service availability in outpatient drug abuse treatment. Journal of Substance Abuse Treatment. 2003;24(1):81–88. doi: 10.1016/S0740-5472(02)00323-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Damanpour F. Organizational innovation: a meta-analysis of effects of determinants and moderators. Academy of Management Journal. 1991;34:555–590. doi: 10.2307/256406. [DOI] [Google Scholar]
  • 44.Fiol CM. Squeezing harder doesn’t always work: continuing the search for consistency in innovation research. Academy of Management Review. 1996;21(4):1012–1021. [Google Scholar]
  • 45.Friedmann PD, Alexander JA, D’Aunno TA. Organizational correlates of access to primary care and mental health services in drug abuse treatment units. Journal of Substance Abuse Treatment. 1999;16(1):71–80. doi: 10.1016/S0740-5472(98)00018-X. [DOI] [PubMed] [Google Scholar]
  • 46.Fitzgerald L, Ferlie E, Wood M, Hawkins C. Interlocking interactions, the diffusion of innovations in health care. Human Relations. 2002;55:1429–1449. doi: 10.1177/001872602128782213. [DOI] [Google Scholar]
  • 47.McCaughrin WC, Price RH. Effective outpatient drug treatment organizations: program features and selection effects. International Journal of the Addictions. 1992;27:1335–1358. doi: 10.3109/10826089209047355. [DOI] [PubMed] [Google Scholar]
  • 48.D’Aunno TA. Linking substance abuse treatment and primary health care. In: Egertson JA, Fox DM, Leshner AI, editors. Treating Drug Abusers Effectively. Malden, MA: Blackwell Publishers; 1997. pp. 311–351. [Google Scholar]
  • 49.Thompson J. Organizations in Action. New York: McGraw-Hill; 1967. [Google Scholar]
  • 50.Wells R, Lemak CH, D’Aunno TA. Organizational survival in the outpatient substance abuse treatment sector, 1988–2000. Medical Care Research and Review. 2005;62(6):697–719. doi: 10.1177/1077558705281062. [DOI] [PubMed] [Google Scholar]
  • 51.Moch MK, Morse EV. Size, centralization and organizational adoption of innovations. American Sociological Review. 1977;42:716–725. doi: 10.2307/2094861. [DOI] [Google Scholar]
  • 52.D’Aunno T, Vaughn TE, McElroy P. An institutional analysis of HIV prevention efforts by the nation’s outpatient drug abuse treatment units. Journal of Health and Social Behavior. 1999;40(2):175–192. doi: 10.2307/2676372. [DOI] [PubMed] [Google Scholar]
  • 53.Pollack HA, D’Aunno T, Lamar B. Outpatient substance abuse treatment and HIV prevention: an update. Journal of Substance Abuse Treatment. 2006;30(1):39–47. doi: 10.1016/j.jsat.2005.09.002. [DOI] [PubMed] [Google Scholar]
  • 54.D’Aunno T, Vaughn TE. An organizational analysis of service patterns in outpatient drug abuse treatment units. Journal of Substance Abuse. 1995;7(1):27–42. doi: 10.1016/0899-3289(95)90304-6. [DOI] [PubMed] [Google Scholar]
  • 55.Knudsen HK, Ducharme LJ, Roman PM, et al. Buprenorphine diffusion: the attitudes of substance abuse treatment counselors. Journal of Substance Abuse Treatment. 2005;29(2):95–106. doi: 10.1016/j.jsat.2005.05.002. [DOI] [PubMed] [Google Scholar]
  • 56.Center for Substance Abuse Treatment. Changing the Conversation: Improving Substance Abuse Treatment: The National Treatment Plan Initiative. Rockville, MD: US Department of Health and Human Services, Substance Abuse and Mental Health Services Administration; 2000. [Google Scholar]
  • 57.Camison-Zornoza C, Boronat-Navarro M, Segarra-Cipres M. A meta-analysis of organizational innovation: moderator effects and internal and market variables. In: Saee J, editor. Contemporary Corporate Strategy. London: Global Perspectives; 2007. [Google Scholar]
  • 58.Ostroff C, Atwater LE, Feinberg BJ. Understanding self-other agreement: a look at rater and rates characteristics, context and outcomes. Personnel Psychology. 2004;57:333–375. doi: 10.1111/j.1744-6570.2004.tb02494.x. [DOI] [Google Scholar]
  • 59.Weil P, Kimball P. Gender and compensation in health care management. Health Care Management Review. 1996;21(3):19–33. [PubMed] [Google Scholar]
  • 60.Foundation of the American College of Healthcare Executives. A Comparison of Career Attainments of Men and Women Healthcare Executives. [Accessed 4 November 2008.];Findings of a National Survey of Health Care Executives. 2006 http://www.ache.org/PUBS/research/gender_study_full_report.pdf.
  • 61.Jaskyte K. Transformational leadership, organizational culture and innovativeness in nonprofit organizations. Nonprofit Management & Leadership. 2004;15:153–167. doi: 10.1002/nml.59. [DOI] [Google Scholar]
  • 62.Batten HL, Horgan CH, Prottas JM, et al. Drug Services Research Survey. Phase I Final Report: Non-Correctional Facilities. Waltham, MA: Brandeis University Institute for Health Policy; 1993. [Google Scholar]
  • 63.Lawrence BS. The black box of organizational demography. Organization Science. 1997;8(1):1–22. [Google Scholar]
  • 64.Amass L, Ling W, Freese TE, et al. Bringing buprenorphine–naloxone detoxification to community treatment providers: the NIDA Clinical Trials Network field experience. American Journal of Addiction. 2004;13(Suppl 1):S42–S66. doi: 10.1080/10550490490440807. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 65.D’Aunno TA, Sutton RI, Price RH. Isomorphism and external support in conflicting institutional environments: a study of drug abuse treatment units. Academy of Management Journal. 1991;34:636–661. doi: 10.2307/256409. [DOI] [PubMed] [Google Scholar]
  • 66.D’Aunno TA, Alexander JA, Succi M. The role of institutional and market factors in divergent organizational change. Administrative Science Quarterly. 2000;45(4):679–703. doi: 10.2307/2667016. [DOI] [Google Scholar]
  • 67.Hasenfeld Y. Human Service Organizations. Englewood Cliffs, NJ: Prentice Hall; 1983. [Google Scholar]
  • 68.Hoge MA, Morris JA, Daniels AS, et al. Report of recommendations: the Annapolis Coalition Conference on Behavioral Health Work Force Competencies. Administration and Policy in Mental Health. 2005;32(5–6):651–663. doi: 10.1007/s10488-005-3267-x. [DOI] [PubMed] [Google Scholar]

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