Higher risk industries were predicted to offer more generous EAP benefits. The study found: 1) Employers in industries with higher prevalence of behavioral health conditions (e.g. construction, manufacturing) offered more EAP sessions. 2) Non-profit employers and employers with larger workforces offered more sessions, annual session limits, and both in-person and telephone options compared to other employers. 3) Longer-running EAP contracts (10+ years) offered more sessions, but shorter contracts were more likely to offer per-incident sessions and multiple service delivery options. The findings provided mixed support for the predictions, suggesting organizational resources and experience with EAPs also influence benefit design

1. Decision-making in EAPs:
Purchaser & Client Perspectives
Bernie McCann, PhD, CEAP
EAPA Annual World Conference
Session # 1020-1b-390
Baltimore, MD, USA
October 20, 2012

2. Presentation Materials
 1 page summary available in today’s session
 PowerPoint slide show is available online:
 www.linkedin.com/in/berniemccannphd or
 www.eapassn.org/onDemand
 Both summary & slide show are available by email;
please provide business card or email request to
mccannbag@gmail.com

3. Study Rationale
 EAPs have become an important component of contemporary
behavioral healthcare for millions of working Americans and their
families (>200 million per Oss, 2011).
 Although current treatments for substance use disorders and
depression are considered highly successful, uptake rates are
low. Reasons include ineffective diagnosis, stigma, and
suboptimal behavioral health benefit coverage (SAMHSA, 2011).
 This study sought to better understand how various factors may
impact EAPs as a gateway to behavioral health treatment.

4. Theory
 Organizational studies provides the overall theoretical
basis for the study of work organizations, which can
then be investigated by their actions, processes, and by
the behavior of their members.
 Additionally, theoretical frameworks of Institutionalism,
Resource Dependency and Organizational Ecology
were utilized to provide insights about employers’ and
enrollees’ demand for EAP features and services.

5. Defining Study Terms
Demand: In economic terms, a desire to possess goods or services
EA Purchaser: Parent work organization which contracts for EAPs
Enrollees: Workers & dependents eligible for EAP services
Session allowance: Number of EAP sessions offered to enrollees
Workplace activities: On site orientations, presentations, trainings, etc.
Significant: Statistically ‘accurate’ findings (i.e., p ≥ 0.05)
Association: When found between factors, does not prove causation.
Alcohol Use Disorders: Alcohol abuse or dependence in past year
Major Depressive Episode: Episode of major depression in past year

6. Research Questions
1. What factors may influence employers’ demand
for various service features in an EAP
contract?
2. Do these same factors influence employers’
demand for EAP worksite activities?
3. Do these same factors influence enrollees’
demand for EAP counseling services?

7. Research Domains
Structural Factors*
Organizational type (For profit vs. non-profit)
Size of workforce
Industry type (by NAICS sector codes)
Age of program (Contract length in years)
Behavioral Health Conditions**
Industry prevalence of alcohol use disorders
Industry prevalence of major depressive episodes
EA Program Features*
Number of EAP sessions available (2-12)
Session configuration (Per incident or annual)
Service delivery mode (In-person, telephone, or both)
*EAP source data; **SAMSHA data

8. Factors in Demand for EAP Services
Structural & Prevalence of
Environmental Behavioral Health
Factors Conditions
Employer EAP Purchasing Decisions
Demand for Enrollee Demand
Worksite Activities for EAP services

9. Study Sample - 490 employer purchasers from a major US
EAP/managed behavioral health provider in 12 mo. period
Agriculture, Forestry, Fishing & Hunting 0.4%
Mining 1.8%
Utilities 1.0%
Construction 1.6%
Manufacturing 16.1%
Wholesale Trade 2.0%
Retail Trade 3.9%
Transportation & Warehousing 2.2%
Information 6.5%
Finance & Insurance 8.0%
Real Estate, Rental & Leasing 1.6%
Professional, Scientific & Technical Services 12.7%
Mgmt of Comp & Entr; Admin & Supp, Waste Mgmt & Remed Svcs 1.6%
Educational Services 3.7%
Health Care & Social Assistance 9.4%
Arts, Entertainment & Recreation 0.6%
Accommodations & Food Services 2.7%
Other Services 1.8%
Public Administration 22.2%

10. Study Sample – 490 Employers
Employer Type Workforce Size
37.1%
64.3% 11%
35.7%
23.7%
28.2%
Non-profit For profit 1 to 99 100 to 499 500 to 999 1000 +

11. Study Sample – 490 Employers
Session Allowance Age of Contract
19.5% 7.3%
42.4%
20.2%
28.8%
2.2% 35.9%
19.5% 25.5%
2-3 sessions 4-5 sessions 1-3 years 4-6 years
6-8 sessions 10-12 sessions 7-9 years 10-15 years
16-29 years

12. Study Sample – 490 Employers
Session Configuration Service Delivery Type
0.6%
7.8% 8.3%
92.2% 91.1%
Telephone only Both options
Annual Limit Per-incident/issue In-person only

13. Predictions: Employer Choices in EAPs
 Regulatory, social, and environmental pressures such as
higher workplace safety risks, higher public accountability,
extent of workforce behavioral health disorders will
influence employers to provide a more generous EAP
benefit.
 If true, these variables: Employer type, Workforce size,
Industry, Length of EAP contract, and Worker prevalence
rates of behavioral health conditions by industry will be
associated with statistically significant differences in
employer choices of EA program features.

14. Methods: Employer Choices in EAP Features
Study methods were designed to test 1) the null hypothesis (no
differences) and, 2) determine differences among employers for:
1) choice of EAP session allowances (3 - 12 sessions)
2) choice of EAP session configuration (sessions per
incident/issue vs. annual session limit)
3) choice of EAP service delivery (telephone only, in-person
only, or both)
Methodologies: t-tests, ANOVA, Chi-square, Post-hoc & Regression

15. Findings: Employer Choices in EAP Features
EAP feature ANOVA Chi-Square Regression
Non-profit
employer (vs. for Session allowance +
profit) = More
generous EAP Session configuration + ̶ +
benefit
Service delivery N/S + ̶
EAP feature ANOVA Post hoc Regression
Large workforce
(vs. medium vs. Session allowance +
small) = More
generous EAP Session configuration + ̶ +
benefit
Service delivery + ̶ +
+ = As predicted; ̶ = Against predicted; N/S = Not significant

16. Discussion: Employer Choices by Org Type &
Workforce Size
 Findings indicate that differences in employer decisions
regarding EAP features were positively associated with
organizational type and workforce size, this suggests these
choices may be based on organizational resource
dependency considerations.
 The prediction that non-profit and larger employers offer a
more generous EAP benefit was largely confirmed, although
evidence regarding employer choice of service delivery
option was mixed.

17. Findings: Employer choices by Age of
EAP contract
Post hoc,
EAP feature ANOVA Chi-Square
Regression
Older EAP
contract (vs.
younger)
Session allowance +
= More Session configuration + + ̶
generous
EAP benefit Service delivery + + ̶
+ = As predicted; ̶ = Against predicted

18. Discussion: Employer choices by Age of
EAP contract
 As predicted, EAP contracts of longer ages (10 years +) were
associated with a more higher allowance of EAP sessions
chosen by employer purchasers.
 Contrary to predictions, results were mixed for session
configuration and service delivery type, as programs of 1-9
vs. 10 years were more likely to have both per-incident and
multiple delivery options. Any thoughts..?

19. Findings: Employer choices by
Industry Risk
5 High safety Post hoc,
EAP feature ANOVA
Chi-Square
Regression
risk and 3 high
public
accountability
Session allowance +
industries
(vs. 11 low risk) =
More generous
Session configuration + +/- ̶
EAP benefit
Service delivery type N/S
High safety risk = Mining, Utilities, Construction, Transportation & Manufacturing
High public accountability = Government, Education, Healthcare
+ = As predicted; ̶ = Against predicted; N/S = Not significant

20. Discussion: Industry Type & Risk
 Overall, differences in employer decisions for session
allowance were positively associated with industry sectors
(data not shown); indicating this EAP feature may be subject
to industry-specific employer needs.
 Similarly, for employer decisions of high risk/accountability vs.
low risk industries, employers with higher risks were positively
associated as offering a greater number of EAP sessions.
 Results of employers’ choice of session configuration by
industry type and high vs. low risk industries were mixed, thus
some influence of structural and environmental factors on
employer choices is likely present, but not conclusively.

21. Past Year Alcohol Use Disorders by Industry, Annual %
Agriculture, Forestry, Fishing & Hunting 9.4%
Mining 15.2%
Utilities 8.6%
Construction 15.0%
Manufacturing 9.1%
Wholesale Trade 12.4%
Retail Trade 9.6%
Transportation & Warehousing 8.2%
Information 5.9%
Finance & Insurance 9.8%
Real Estate & Rental & Leasing 10.4%
Professional, Scientific & Technical Services 9.0%
Mgmt of Comp & Entp; Admin & Sup, Waste Mgmt & Remed Svcs 12.0%
Educational Services 5.0%
Health Care & Social Assistance 5.8%
Arts, Entertainment & Recreation 12.3%
Accommodations & Food Services 15.7%
Other Services 7.8%
Public Administration 6.1%
Total, all industries 9.5%

22. Past Year Major Depressive Episode by Industry, Annual %
Agriculture, Forestry, Fishing & Hunting 6.2%
Mining 4.4%
Utilities 2.5%
Construction 5.2%
Manufacturing 6.1%
Wholesale Trade 4.9%
Retail Trade 8.2%
Transportation & Warehousing 5.9%
Information 8.7%
Finance & Insurance 8.2%
Real Estate & Rental & Leasing 6.8%
Professional, Scientific & Technical Services 6.7%
Mgmt of Comp & Entp; Admin & Sup, Waste Mgmt & Remed Svcs 9.6%
Educational Services 7.6%
Health Care & Social Assistance 9.4%
Arts, Entertainment & Recreation 8.6%
Accommodations & Food Services 9.6%
Other Services 7.5%
Public Administration 7.0%
Total, all industries 7.4%

23. Findings: Employer choices by Behavioral
Health Conditions
Post hoc,
High (vs. low) EAP feature ANOVA Regression
Chi-Square
industry worker
prevalence rate Session allowance N/S ̶
of AUDs = More
generous EAP Session configuration + ̶
benefit Service delivery N/S
Post hoc,
High (vs. low) EAP feature ANOVA Chi-Square
Regression
industry worker
prevalence rate Session allowance + N/S
of MDEs = More
generous EAP Session configuration N/S
benefit Service delivery N/S
+ = As predicted; - = Against predicted; N/S = Not significant

24. Discussion: Employer choices by
Behavioral Health Conditions
 Alcohol use disorders (AUD) – Results indicate higher industry
rates of AUDs are associated with a tendency to offer a per incident
sessions, however regression (OLS) results of session allowance
indicate that for every increase of 1 in the AUD prevalence rate, the
number of EAP sessions drops by .073. Any thoughts..?
 Major depressive episodes (MDE) – Results of employer
decisions regarding session allowance and industry rates of MDEs
are mixed, indicating slight evidence for the prediction that
purchasers in these industries may choose a higher number of
sessions.

25. Employer Demand for EAP Worksite Activities
Of the 490 employers in the sample, Demand for Worksite
286 reported EAP worksite activities. Activities
Again using same six variables, e.g.,
• Organizational type
• Workforce size
• Industry type 41.7% 58.3%
• Length of EAP contract
• Behavioral health conditions
We now ask: Are there differences in
demand for EAP worksite activities
among employers? YES NO

26. Findings: Demand for Worksite Activities
Odds ratios for significant variables (all others N/S; n = 286)
For Profit Ref: Non-profit (p= .01*)
Wkforce1-99
Ref: Wkforce1000+ (p= <.0005***)
Wkforce100-999
Prog Age3-9 Ref: Prog age10+ (p= .009**)
Manufacturing Ref: Government (p= .01*)
0 0.2 0.4 0.6 0.8 1

27. Discussion: Demand for EAP Worksite Activity
 As predicted, non-profit employers’ demand for EAP worksite
activities was nearly double that of for profits’. Also as
predicted, employers with longer EAP contracts showed
greater demand for EAP worksite activities.
 Contrary to predictions, larger (1000+) employers’ demand for
worksite activities was substantially greater than smaller (1-99)
and medium-sized (99-999) workforces. Any thoughts..?
 Non-significant findings regarding high risk vs. low risk
industries and for behavioral health conditions preclude any
conclusions about these factors.

28. Predictions: Enrollee Demand for EAP
Clinical Services
 Enrollees in non-profits, smaller workforces, with EAPs of
longer contract length, and higher prevalence rates of
behavioral health conditions will demonstrate higher
demand for EAP clinical services.
 For industries with higher risks for workplace safety and
more public accountability - this effect will “trickle down”
through the workplace environment and demonstrate
higher enrollee demand for EAP clinical services.

29. Study Sample: Enrollees
 The total number of eligible employees represented in the sample
was 687,958 with median of 139 employees per employer.
 The total number of eligible members (employees, spouses and
dependents) represented in the sample was 961,122 with a
median of 178 members per employer EAP benefit population.
 The following equations were used to create measures for
employee and member demand:
Aggregated number of employee EAP clinical authorizations/employer
Aggregated number of employees/employer
Aggregated number of member EAP clinical authorizations/employer
Aggregated number of members/employer

30. Methods: Enrollee Demand for EAP
Clinical Services
 To determine differences among aggregated employer enrollee
population for EAP clinical authorizations (Number of
authorizations/Employer enrollee population), I used the same
six variables, e.g.,
• Organizational type
• Workforce size
• Industry type
• Length of EAP contract
• Behavioral health conditions
 Methodologies: t-tests, ANOVA, Post-hoc & Regression (OLS)

31. Findings: Demand for EA Clinical Services
Non-profit workforce Enrollee group ANOVA Regression
(vs. for profit) = More
demand for EA
Employees + +
clinical services Members + +
Smaller workforce Enrollee group ANOVA Post hoc Regression
(vs. med. vs. larger) =
More demand for EA
Employees + + +
clinical services Members + + +
Older (vs. younger) Enrollee group ANOVA Post hoc Regression
program = More
demand for EA
Employees + + ̶
clinical services Members + + ̶
+ = As predicted; - = Against predicted

32. Discussion: Enrollee Demand for EA
Clinical Services by Employer Type,
Workforce Size, and EAP Contract Length
 As predicted, greater demand for EAP clinical services was
positively associated with enrollees in non-profit workforces,
small and mid-size workforces than in larger-sized workforces.
 Contrary to prediction, greater enrollee demand was present in
workforces with shorter EAP contract rather than longer contract
lengths. Any thoughts..?

33. Findings: Enrollee Demand for Clinical
Services by Industry Type and Risk
Enrollee group ANOVA Post hoc
Demand for EAP
clinical services by
industry type
Employees + +
Members + +
Post hoc,
High risk (vs. low Enrollee group ANOVA Chi-Square
Regression
risk) industries =
More demand for Employees + + +
clinical services
Members + + +

34. Discussion: Enrollee EAP Clinical Service
Demand by Industry Type
 ANOVA and Post-hoc tests reveal significant differences in rates
of enrollee demand for EAP sessions in eight industries with high
workplace safety and public accountability risk vs. those eleven
with lower risk.
 As predicted, enrollee demand for EAP sessions increased in
workplaces in industries with either a high risk for workplace
safety or high risk of public accountability vs. enrollees in those
with lower risks.
High safety risk = Mining, Utilities, Construction, Transportation & Manufacturing
High public accountability = Government, Education, Healthcare

35. Findings: Enrollee Demand for Clinical
Services by Behavioral Health Condition
High (vs. low) Enrollee group ANOVA Post hoc Regression
Industry AUD
prevalence rate
Employees + + ̶
Members + + ̶
Enrollee group ANOVA Post hoc Regression
High (vs. low)
Industry MDE
Employees N/S
prevalence rate
Members N/S
+ = As predicted; - = Against predicted; N/S = Not significant

36. Discussion: Enrollee Demand for Clinical
Services by Behavioral Health Condition
 Alcohol use disorders (AUD) – Rates of enrollee demand for EAP
sessions showed significant findings of differences between employers
industries above the 9.0 median AUD prevalence rate vs. those below
median. However, regression results are negative, indicating as industry
AUD prevalence rates rise, enrollee demand authorization rates for EAP
clinical services fall; specifically, -.063 for employees and -.071 for
members with each 1 point rise in AUD rate.
 Major depressive episodes (MDE) – Tests for differences in enrollee
demand between employers in industries above the 7.5 median MDE
prevalence rate vs. vs. those below median were not significant, as were
regression results, thus no conclusions can be drawn for this condition.

37. EAP Practice Implications
 One clear finding is that significant and predictable differences exist among
employers regarding: 1) choices about the nature of EAP benefits offered to
enrollees; 2) in demand for EAP-provided worksite activities; and, 3) that
significant and predictable differences exist in enrollee demand for EAP
clinical services.
 These findings advise that the employer market for EAPs is quite diverse,
and that a bona-fide organizational analysis combined with purchaser/client
education regarding any findings is a good practice when proposing an EAP
for a particular work organization.
 Cautions in applying “cookie cutter” approaches to providing EAP services
for diverse work populations. Potential risks may be low/poor utilization
rates by enrollees, and a subsequent premature cancellation or disinterest
in EA services by a work organization.

38. Behavioral Healthcare Policy Implications
 Findings suggest that the diversity of purchasers in the marketplace
is reflected in differing choices of EAP service features and enrollee
demand for EAP counseling. Thus, these influences should be
considered when benefits consultants, human resource staff and
MBHOs design and implement behavioral health care coverage.
 A primary motivation for including prevalence rates of alcohol use
disorders and depression as dependent variables is the well-
documented need for increasing identification of and access to
treatment for these conditions. While the results for these two
variables were less than conclusive -- it appears the variance in
prevalence rates among enrollee populations is worthy of
consideration when designing and implementing behavioral health
care coverage.

39. Study Limitations
1. Cross Sectional Research Design
2. Data Issues
• Convenience Sample Population (not randomized)
• Ecological Fallacy of NSDUH Prevalence Rates
• Regression to the Mean
3. Effect of Unexamined Variables – Any thoughts…?
4. Combined Effect of Contextual Factors

40. Questions or Comments..?
Thank you for your attention