www.elsevier.com/locate/ypmed

Preventive Medicine 38 (2004) 766–776

Implementation of a cancer prevention program for working class,

multiethnic populations

Rebecca Lobb, M.P.H.,a,* Elizabeth Gonzalez Suarez, M.A.,b Martha E. Fay, M.P.H.,c

Caitlin M. Gutheil, M.S.,b Mary K. Hunt, M.P.H.,b

Robert H. Fletcher, M.D.,a,d and Karen M. Emmons, Ph.D.b,c

aDepartment of Ambulatory Care and Prevention, Harvard Pilgrim Health Care, Boston, MA 02215, USAbDana-Farber Cancer Institute, USA

cHarvard School of Public Health, Boston, MA 02115, USAdHarvard Medical School, Boston, MA 02115, USA

Available online 19 March 2004

Abstract

Background. This paper describes the implementation of the Healthy Directions-Health Centers intervention and examines the

characteristics of participants associated with completion of intervention activities. Healthy Directions-Health Centers was designed to

address social contextual factors relevant to cancer prevention interventions for working class, multi-ethnic populations.

Methods. Ten community health centers were paired and randomly assigned to intervention or control. Patients who resided in low

income, multi-ethnic neighborhoods were approached for participation. This study targeted fruit and vegetable consumption, red meat

consumption, multi-vitamin intake, and physical activity. The intervention components consisted of: (1) a brief study endorsement from a

clinician; (2) an in-person counseling session with a health advisor; (3) four follow-up telephone counseling sessions; and (4) multiple

distributions of tailored materials.

Results. Among the 1,088 intervention group participants, 978 participants (90%) completed at least five out of six intervention activities.

Participants who missed clinical appointments were less likely to complete all components of the intervention. Participant characteristics that

predicted receipt of clinician endorsement differed from characteristics that predicted completion of health advisor activities. Low

acculturation did not present a barrier to delivery of the intervention once the participant was enrolled.

Conclusions. Collection and reporting on process evaluation results can help explain variations in program implementation.

D 2004 The Institute For Cancer Prevention and Elsevier Inc. All rights reserved.

Keywords: Multiethnic populations; Cancer; Prevention

Introduction Patterns of behavioral risk factors differ by socioeconomic

Over two thirds of cancer deaths could be prevented by

changes in nutrition, physical activity, and other health

behaviors [1,2]. These same behavioral risk factors are

associated with cardiovascular disease, diabetes, and osteo-

porosis [3–7]. Yet, the prevalence of poor diet and inactivity

in the United States is widespread [3]. As a result, national

health agencies have called for population-based approaches

to prevention with emphasis on reducing socioeconomic and

racial/ethnic disparities in health [8–12].

0091-7435/$ - see front matter D 2004 The Institute For Cancer Prevention and

doi:10.1016/j.ypmed.2003.12.025

* Corresponding author. Department of Ambulatory Care and Preven-

tion, 133 Brookline Avenue, 6th floor, Harvard Pilgrim Health Care,

Boston, MA 02215. Fax: +1-617-859-8112.

E-mail address: Rebecca_hannigan@hphc.org (R. Lobb).

position and ethnicity [13–19]. Both risk factor prevalence

and cancer morbidity and mortality are higher among low-

income populations, and among some racial and ethnic

minority groups [8–11]. A nationally representative study

of adults found that lower levels of income are significantly

associated with higher prevalence of unhealthy dietary

behaviors and inactivity [14]. During 1990–1998, trends in

death rates from lung/bronchus, colon/rectum, prostate, and

female breast cancer-related deaths generally declined but the

rates remained high and increased in certain instances for

high-risk and underserved populations [11,20]. Health

behaviors do not appear in isolation, but reflect the complex

dynamic between an individual’s characteristics and societal

forces. The context in which behavior occurs includes mul-

Elsevier Inc. All rights reserved.

R. Lobb et al. / Preventive Medicine 38 (2004) 766–776 767

tiple levels of influence including individual factors (e.g.,

material circumstances, psychosocial factors), interpersonal

factors, (e.g., social ties, roles/responsibilities, social norms),

organizational factors (e.g., work organization, access to

healthcare), and neighborhood/community factors (e.g., safe-

ty, access to grocery stores) [21]. Addressing contextual

factors that influence behavior may make interventions more

meaningful to at-risk populations, thereby enhancing the

effectiveness of interventions aimed at reducing social

inequalities in risk behaviors [14,22–35].

The health care system plays an important role in preven-

tion because patients often consider clinicians to be credible

sources for health information [36–39]. In addition, brief

clinician endorsement partnered with counseling from allied

health professionals can be both efficacious and cost-effec-

tive [40–48]. Community health centers that serve diverse

populations can provide access to those who have the highest

prevalence of preventable cancer-risk factors [1–3,49,50].

In this paper, we describe the implementation of the

Healthy Directions-Health Centers (HC) intervention that

occurred June 2000 through February 2002 and examine the

characteristics of intervention participants associated with

completion of intervention activities. Healthy Directions-

HC is part of the Harvard Cancer Prevention Program

Project, the theme of which is to create cancer prevention

interventions that are effective with working class, multi-

ethnic populations. The Healthy Directions-HC intervention

is designed to take into account elements of social context

that are critical components of an ecological approach to

health behavior change [27,35]. A full description of the

baseline characteristics of the intervention and control

participants is provided by Emmons et al. [22].

Methods

Study design

Healthy Directions-HC was a randomized controlled trial

in which the health center was the unit of randomization and

intervention. We paired 10 health centers based on mem-

bership size, and within each pair, randomly assigned one

site to the intervention condition.

Setting

This study was conducted in collaboration with Harvard

Vanguard Medical Associates, a multi-specialty group prac-

tice composed of 14 health centers serving over 270,000

patients.

Internal Medicine departments at 10 health centers were

invited to participate in this study and all agreed to partic-

ipate. Clinician participation was high across the health

centers, averaging 83%, (range 50–100%); totaling 97

physicians, nurse practitioners, and physician assistants

(intervention n = 49; usual care n = 48). Physicians

represented the majority of participating clinicians, averag-

ing 71% (range 33–86%) across health centers. Each

internal medicine department received a financial incentive

(intervention $2,500; usual care $1,000) for participation.

Sample

Potential study participants were 18–75 years of age, had

a scheduled appointment with an enrolled clinician, and

were identified through Harvard Vanguard’s automated

central appointment system. We used geocoding to identify

patients who lived in neighborhoods that were predominate-

ly working class, impoverished, or with low levels of

education [51–54]. At the time of enrollment, we excluded

patients who did not speak English or Spanish as a primary

language, currently had cancer, were employed by one of

the participating health centers, or were participating in a

companion study focused on work sites [55]. Participants

received a 45-min telephone card for completing the base-

line survey. Details of the recruitment process and response

rates are provided elsewhere [22].

Intervention components

The Healthy Directions-HC study recommendations for

cancer prevention were: (1) eat z5 servings of fruits and

vegetables a day; (2) eat <3 servings of red meat a week; (3)

take a multi-vitamin daily; and (4) get at least 2.5 h of

moderate physical activity per week. The intervention was

delivered over 5 months and consisted of: (1) a brief in-

person clinician endorsement of the study recommendations;

(2) an initial in-person counseling session (ICS) with a health

advisor; (3) four follow-up telephone counseling sessions

with a health advisor; and (4) multiple tailored materials. The

health advisor-counseling sessions and materials were pro-

vided to participants either in Spanish or English.

Clinician endorsement

Research staff trained physicians, nurse practitioners,

and physician’s assistants to deliver the endorsement at a

1-h group orientation delivered at each of the intervention

health centers 2 weeks before the start of the study. The

goal of the orientation was to review the scientific evidence

that supports the relationship between the study outcomes

and cancer prevention, discuss the clinician endorsement

protocol, and identify factors that would assure clinicians’

comfort with following the protocol. All participating clini-

cians received the orientation. Two of the 49 clinicians who

participated in the intervention delivery could not attend the

group orientation but did receive 15-min individual orienta-

tions with the project director.

The clinician endorsement, which occurred at a routine

care visit scheduled by the participant, consisted of the

clinician giving the participant a form called ‘Prescription

for Cancer Prevention’ (see Fig. 1) and making a supportive

Fig. 1. Prescription for cancer prevention.

R. Lobb et al. / Preventive Medicine 38 (2004) 766–776768

comment about the behavioral recommendations on the

prescription and participation in the study. The health advisor

prepared the prescription for cancer prevention and a phys-

ical activity clearance form for the clinician before the

patient’s visit. Clinicians authorized clearance for physical

activity counseling by checking off the appropriate level of

activity (moderate or limited) on the physical activity clear-

ance form. The clinicians referred participants to the health

advisor for counseling on diet and physical activity.

Health advisor counseling

The study health advisors were located at the health

centers to facilitate delivery of the clinician endorsement

and to deliver the initial counseling session to participants

after the clinician appointment. Health advisors had previ-

ous experience providing health education to individuals

either in a clinical setting or through research interventions.

Two health advisors were bilingual, which allowed them to

deliver the intervention to participants in either English or

Spanish.

The health advisors received a minimum of 16 h of

training that included background on the scientific basis for

risk factors included in the intervention, instruction in

motivational interviewing, and implementation of interven-

tion protocols. In addition, they received 8 h of social–

cultural training, which included strategies for identifying

social contextual elements, and ways in which social con-

textual factors influence individuals’ attitudes, decisions,

and behaviors. Strategies included use of open-ended ques-

R. Lobb et al. / Preventive Med

tions, self-assessments with feedback, and asking partici-

pants to reflect on what a typical day was like for them.

The project director provided on-going training, supervi-

sion, and quality assurance for the health advisor activities

through weekly staff meetings and review of monitoring

reports from the computerized process tracking system. In

addition, health advisors tape-recorded 10% of the coun-

seling sessions and completed a self-assessment of key

components of the patient/health advisor interactions. The

self-assessment had a 5-point scale ranging from ‘‘needs

improvement’’ to ‘‘completely achieved’’ to rate the health

advisor’s performance with: building rapport; identifying

participant’s living arrangement/context; assessing partici-

pant’s view of health; defining potential barriers, facilitators,

and supports to assist with health behavior change; assessing

readiness to change; discussing health habits; praising

accomplishments; reviewing materials; encouraging use of

materials; summarizing session; closing call; asking open

ended questions; and, use of reflective listening. A certified

motivational counseling trainer reviewed the tape-recorded

sessions and self-assessments with the health advisors to

assure compliance with motivational interviewing style and

adherence to the counseling protocols. Self-assessment forms

are available from the corresponding author on request.

Health advisors used motivational interviewing to elicit

motivation to change and to enhance understanding of the

factors that influence a patient’s ability to change. The

motivational interviewing techniques are well suited to

explore social context of participants’ lives because the

non-confrontational and supportive dialogue can facilitate

an open discussion of the participant’s views of health,

needs, experiences, barriers, supports, and readiness to

change. Motivational interviewing techniques include the

use of reflective listening, rolling with resistance, agenda

setting, eliciting self-motivational statements, and change

talk [56–58].

Tailored materials

The Healthy Directions-HC materials were tailored to the

participant’s risk factor-related behavioral status, gender, and

self-efficacy, as well as social contextual factors such as

social supports, barriers to change, family constellation,

health center, and clinician affiliation. Participants received

tailored materials in either English or Spanish. Each partic-

ipant received one baseline tailored feedback report at the

ICS and five mailed tailored ‘‘Step-by-Step’’ guides, a guide

was mailed after each contact with the participant. Each

tailored report addressed multiple levels of influence based

on the social ecological model. For example, we addressed

intrapersonal influences through providing feedback on

participants’ personal risk factor profiles, interpersonal influ-

ences by incorporating information on social supports such

as ways to involve family and friends, and we addressed

environmental influences through promotion of community

resources related to nutrition and physical activity.

Process tracking

We captured data on dose of the intervention delivered by

the study team, as well as dose received by the participants.

For dose of the intervention delivered, the health advisor

recorded the length and completion of the intervention

activity in a portable laptop computer at the conclusion of

each activity. Health advisors followed protocols to deter-

mine when an intervention activity was completed. The

clinician endorsement was complete when a participant

displayed the Prescription for Cancer Prevention to the health

advisor after the clinician appointment. Physical activity

clearance was complete when the health advisor received

the physical activity clearance form from the clinician, either

via the patient during the ICS or via the clinician. The ICS

was complete if the health advisor: (1) established rapport by

exploring the participant’s living arrangements (e.g., family

constellation, sources of support, social norms) and view of

health (attitudes and cultural and religious health beliefs); (2)

reviewed the tailored feedback report recommendations for

cancer prevention (i.e., multivitamin use, physical activity,

and diet) in relation to the participant’s health behaviors; and

(3) asked the participant to comment on the discrepancies

between personal health behaviors and the study recommen-

dations. Calls 1–4 were complete if the health advisor: (1)

assessed the participant’s readiness to change; (2) discussed

goal setting; (3) explored existing social supports; and (4)

reviewed barriers and facilitators to change. In Call 4, the

health advisor also needed to discuss ways to draw on

existing social supports and community resources beyond

the end of the intervention. The baseline-tailored feedback

report was documented as complete if the participant re-

ceived the report by the time of the ICS. Mailed Step-by-Step

guides were considered delivered if the guides were prepared

and sent to the mailroom by a study research assistant.

For data on dose received by participants, we used the 8-

month follow-up survey to measure patients’ receipt of

tailored materials. We asked participants, ‘Did you receive

any materials from Healthy Directions, such as the personal

health profile and step by Step-by-Step guides?’. Response

options were No, Yes, or Don’t Recall. Participants who

responded ‘‘no’’ to this question were instructed to ‘Skip to

question 2 on the next page’. Those who responded ‘‘yes’’

were asked to respond to two additional questions, ‘How

much of these materials would you say that you read?’

(Most or all, A little or some, None) and ‘How helpful were

the materials in helping you to set personal goals for

changing your health habits?’ (Very helpful, Neither helpful

nor unhelpful, Very unhelpful).

Measures of baseline characteristics

This paper describes the baseline health behaviors and a

subset of sociodemographic characteristics for participants

in the intervention group. A full description of the study and

baseline survey including social contextual variables is

icine 38 (2004) 766–776 769

R. Lobb et al. / Preventive Medicine 38 (2004) 766–776770

found elsewhere [22]. The survey instrument is available

from the corresponding author on request.

Sociodemographic characteristics

We asked respondents to report their date of birth,

gender, racial and ethnic groups, first or native language,

level of education completed, immigration status, proportion

of life lived in the US, and household income. We calculated

income relative to the federal poverty guidelines [59] (below

the poverty guideline, between the poverty guideline and

185% of the guideline, or above 185% poverty guideline).

As an additional measure of financial status, we asked

participants to indicate whether they had run out of money

to buy food at any time in the last 12 months [60].

Health behaviors

We assessed servings of fruit and vegetables consumed

per day using a screener developed for the National Cancer

Institute’s 5-a Day for Better Health research projects [61].

We computed a dichotomous measure: five or more servings

per day; or less than five servings per day.

We assessed servings of red meat using an abbreviated

form of the semi-quantitative food frequency questionnaire

[61]. We coded responses to equivalent servings per week

and summed, excluding poultry and fish, to obtain the total

servings of red meat per week. We dichotomized the totals

to three or fewer servings; or more than three servings per

week.

We based our physical activity assessment on the ques-

tionnaire used in the Nurses Health Study [62] by adapting

the items to include specific activities that are more common

in our target population. For physical activity, we asked how

often in the last 4 weeks respondents engaged in each of

eight moderate or vigorous activities, on average (e.g.,

walking for exercise jogging; running; bicycling; aerobics

or aerobic dancing; playing soccer, rugby, basketball, or

lacrosse; playing baseball, football, or lifting weights). We

coded responses to equivalent minutes per week and

summed for total minutes of physical activity per week.

We dichotomized the totals 150 min (2.5 h) or greater per

week; or fewer than 150 min per week.

We asked respondents on average how many days per

week they took a multi-vitamin. Responses were coded as

daily if participants reported taking one multi-vitamin at least

6 days per week. We asked respondents whether they had

ever smoked at least 100 cigarettes and whether they had

smoked even a puff in the last 7 days. Based on responses,

participants were categorized as not current smokers or

current smokers (smoked a puff in the last 7 days).

Measures of implementation

We assessed three measures of implementation: (1)

reach; (2) extent of implementation; and (3) fidelity to

intervention protocol. To determine the reach of interven-

tion, we computed the number of participants who received

the clinician endorsement, completed the initial counseling

session (ICS), completed counseling calls, were mailed

tailored materials, and received tailored materials. We mea-

sured extent of implementation by calculating the average

number of intervention activities per participant, average

number of telephone calls completed, and average number

of tailored materials mailed. Fidelity to intervention protocol

was measured by the proportion of participants who re-

ceived key intervention components as planned, the ICS on

the same day as the clinician visit, physical activity clear-

ance on the same day as the ICS, and ICS at the health

center. We also examined the mean length of the initial

counseling session, telephone sessions, and the proportion

of call attempts that resulted in completed calls.

In addition, we created a multi-item index of protocol

completion to summarize the overall reach of intervention.

For each person-to-person intervention activity, we scored a

‘1’ if completed or a ‘0’ if not completed. The scores for

each participant were added to determine the index of

protocol completion for person-to-person activities. An

index of six indicates that all person-to-person intervention

activities (one clinician endorsement, one ICS, and four

follow-up telephone calls) were completed by the partici-

pant; an index of five indicates that one activity was missed.

Data analyses

Using SAS (SAS Institute, Cary, NC, v.8), we exam-

ined the distribution of participants according to measures

of sociodemographic characteristics, social context, and

levels of target health behaviors. We then examined the

measures of intervention activity and the bivariate associ-

ations between baseline participant characteristics and

intervention activities. To control for the clustering of

participants within health centers, we calculated a chi-

square statistic for each bivariate association using the

SAS GLIMMIX macro with health center as a random

effect. Because having the ICS and clinician visit on the

same day strongly predicted a successful outcome on all

three measures, the bivariate analyses were repeated after

exclusion of participants who did not see the clinician on the

same day as the health advisor. All reported P values were

two-tailed and P values of 0.05 or less were considered

statistically significant.

We performed multivariate analysis for the index of

protocol completion, receipt of clinician endorsement, and

completion of health advisor calls using linear logistic

regression controlling for health center as a random effect.

Predictor variables that were significantly associated (P V0.05) with the outcomes in bivariate analysis or sub-group

analysis were included in the logistic regression multivariate

model. Variables related to the outcome, but presented in the

bivariate analyses, were excluded (clinician same day visit

as ICS and clinician endorsement).

Table 2

Implementation measures

Intervention activities % Participants

(n = 1088)

Clinician visit and ICS on same day 79

Clinician endorsement received 77

Physical activity clearance completed 94

Initial counseling session completed 96

No. of calls completed

0 4

1 1

2 3

3 11

4 81

No. of tailored materials mailed

0 2

1 0

R. Lobb et al. / Preventive Medicine 38 (2004) 766–776 771

Results

Participant characteristics

The majority of the sample consisted of older people and

women (see Table 1). Almost one-third were racial/ethnic

minorities and 40% were first or second-generation immi-

grants. Slightly more that one third of participants had a 4-

year degree or higher education. Six percent of participants

received the intervention in Spanish and 15% were living at

or below 185% of the poverty guideline. The majority of

participants had low fruit and vegetable intake, low multi-

vitamin use, or high red meat intake as risk factors. About

one third of the sample had inadequate physical activity as a

risk factor.

Table 1

Baseline characteristics of intervention participants

Sociodemographic N = 1088

Mean age 52 years

Female 61%

Education

High school or less 30%

Some post high school 33%

4-year degree or higher 37%

Race/ethnicity

White 72%

Black 17%

Hispanic 6%

Mixed 3%

Asian 1%

American-Indian <1%

Place of birth

Participant born outside USA 19%

Participant born in USA, parents born outside 21%

Participant and both parents born in USA 60%

Proportion of life in USA

100% 82%

50–99% 10%

<50% 8%

First language

English 87%

Spanish 6%

Other 7%

Yearly income

<$20,000 10%

$20,000–50,000 38%

z$50,000 52%

Poverty index

Above 185% of poverty 85%

Between poverty and 185% 10%

Below poverty line 5%

Food ran out in last 12 months 9%

Health behaviors N = 1088

Fruits and vegetables: <5 servings/day 86%

Red meat: >3 servings/week 51%

Multivitamin: <6 days/week 61%

Physical activity: <2.5 h/week 29%

Current smoker 15%

2 0

3 0

4 0

5 98

Index of protocol completion

0 4

1 0

2 0

3 2

4 4

5 23

6 67

Note. % have been rounded to nearest whole number.

Implementation measures

Healthy Directions reached the majority of participants.

Among the 1,088 intervention group participants, 842

participants (77%) received the clinician endorsement (see

Table 2). Health advisors delivered the initial counseling

session to 96% of participants, and all four telephone-

counseling sessions to 81% of participants. A total of 967

(89%) intervention participants responded to the follow-up

survey; of those, 876 (91%) reported that they received

tailored materials from Healthy Directions-HC. Seventy-six

percent reported reading most or all of the materials. The

extent of implementation for telephone calls was 3.7 (0–4

calls) and for tailored materials was 4.9 (0–5 materials).

Analysis of fidelity indicated that 79% of participants

received the clinician endorsement on the same day as the

ICS, 79% of participants received physical activity clear-

ance on the same day as the ICS, and 86% of the ICSs were

completed at the health center, per study protocol. The

mean length of the ICS was 25 min (range 5–50 min). The

mean length of telephone calls 1 through 4 was 9.7, 9.2,

8.9, 8.5 min, respectively. There was little variation in ICS

or call length among the health advisors. The overall

implementation score was 5.4 (0–6 activities). A total of

726 participants (67%) had an index of 6 for protocol

completion, indicating that the majority of participants

completed all intervention activities; 90% had an index of

5 or greater.

Table 3

Bivariate associations between participant characteristics and intervention

activities

Controlled for

Health Center Health Center

and same day visit

Protocol Completion Index = 6

Clinician visit same day as ICS P < 0.0001 NA

Non-smoker P = 0.0097 NS

Male P = 0.0005 P = 0.0035

American-Indian, Asian/Pacific

islander, or white

P = 0.0280 NS

Income z$50 K per year P = 0.0130 NS

Food did not run out P = 0.0210 NS

Older age P < 0.0001 P = 0.0011

Endorsement = Yes

Clinician visit same day as ICS P < 0.0001 NA

Red meat: >3 servings per week P = 0.0410 P = 0.0370

Male P = 0.0110 NS

American Indian, Asian/Pacific

islander, or white

P = 0.0011 P = 0.0017

z50% of life in USA P = 0.0190 NS

First language other than Spanish P = 0.0190 NS

Income z$50 K per year P = 0.0013 NS

Food did not run out P = 0.0360 NS

Older age P = 0.0002 NS

Calls = 41Clinician visit same day as ICS P < 0.0001 NA

Multivitamin: z6 days per week P = 0.0120 NS

Non-smoker P = 0.0002 P = 0.0390

Male NS P = 0.0300

<50% of life in USA P = 0.0430 P = 0.1100

Food did not run out P = 0.0110 P = 0.1900

Older age P = 0.0110 P = 0.0013

Endorsement P < 0.0001 NA

ICS was also completed.

NA = not applicable.

NS = P > 0.05.

Table 4

Multivariate analysis

Odds ratio P-value

Protocol Completion Index = 6

Non-smoker 1.41 NS

Male 1.43 0.0150

American-Indian, Asian/Pacific islander, or white 1.30 NS

Income z$50 K per year 1.45 0.0110

Food did not run out 1.26 NS

Age 1.03 0.0001

Endorsement = Yes

Red meat: >3 servings per week 1.42 0.0270

Male 1.25 NS

American-Indian, Asian/Pacific islander, or white 1.38 NS

z50% of life in USA 1.06 NS

First language other than Spanish 1.36 NS

Income z$50 K per year 1.60 0.0048

Food did not run out 1.21 NS

Age 1.03 0.0001

Calls = 41Multivitamin: z6 days per week 1.38 NS

Non-smoker 1.92 0.0018

Male 1.24 NS

<50% of life in USA 2.05 0.0310

Food did not run out 1.67 0.0410

Age 1.01 0.0500

ICS was also completed.

NS = P > 0.05.

R. Lobb et al. / Preventive Medicine 38 (2004) 766–776772

Bivariate associations

We performed two sets of bivariate analyses to examine

the relationships between participant characteristics and

intervention activities (see Table 3). The first bivariate

analysis controlled for health center on the full sample

and the second bivariate analysis controlled for health center

on the sub-group of participants who received the clinician

endorsement and ICS on the same day. A clinician endorse-

ment on a day other than the ICS indicates that the

participant either did not show or cancelled the original

appointment with the clinician or health advisor. Partici-

pants were less likely than their counterparts to have same-

day appointments if they had the following characteristics:

current smoker, female gender, younger age, black, Hispan-

ic, or of mixed heritage race, spent less than 50% of their

life in the US, Spanish as a native language, yearly income

less than $50,000, or reported that food ran out.

When we controlled for health center on the full sample,

we found that having the clinician endorsement on the same

day as the ICS was the strongest predictor for completing all

intervention activities. In addition, both older age and not

having food run out were associated with completion of all

intervention activities. Non-smoking status was associated

with receipt of health advisor calls but not clinician en-

dorsement. Male gender, American-Indian, Asian/Pacific

Islander, or white race, native language other than Spanish,

intake of greater than three servings of red meat per week,

and income greater than $50,000/year were associated with

receipt of clinician endorsement but not with completion of

health advisor calls. Spending greater than 50% of life in US

was associated with clinician endorsement, whereas spend-

ing less than 50% of one’s life in the US was associated with

completion of health advisor calls. Taking multivitamins 6

or more days per week and receipt of clinician endorsement

were related to completion of all health advisor calls only.

Controlling for health center on the sub-group of partic-

ipants who had their clinician endorsement and ICS on the

same day, we found that the following variables were no

longer significantly associated with any of the outcome

variables: income, food running out, percent of life in

USA, and taking a multivitamin 6 or more days per week.

Multivariate analysis

In the multivariate analyses (Table 4), male gender (OR =

1.43, P = 0.015), older age (OR = 1.03, P = 0.0001), and

income >$50,000 (OR = 1.45, P = 0.011) predicted com-

pletion of all intervention activities. Consuming more than

R. Lobb et al. / Preventive Medicine 38 (2004) 766–776 773

three servings of red meat per week (OR = 1.42, P = 0.027),

and income >$50,000 (OR = 1.60, P = 0.0048) were

significantly associated with receipt of endorsement. The

characteristics that predicted completion of all health advi-

sor calls were non-smoker (OR = 1.92, P = 0.0018), food

not running out (OR = 1.67, P = 0.041), and percent of life

in USA less than 50% (OR = 2.05, P = 0.031).

Discussion

We examined the implementation of the overall inter-

vention and identified associations between participant

characteristics and individual components of the interven-

tion. Implementation measures of reach, extent of imple-

mentation, and fidelity to protocol indicated high levels of

participation in Healthy Directions-HC compared to similar

studies [42,46,56,63–66]. The combination of clinician

endorsement, use of motivational interviewing techniques,

and strategies to incorporate social context in the interven-

tion through counseling and tailored materials may account

for the higher rates of completed counseling calls in the

Healthy Directions-HC study. Several studies have evaluat-

ed the effect of these individual techniques or combinations

of these techniques with success but we are not aware of any

studies that have used all of these techniques simultaneously

in an intervention. Reasons why participants did not com-

plete all study activities included missed appointments with

the clinician, missed appointments with the health advisor,

and lack of time to complete the activity during an interac-

tion with the participant.

Three findings from our analyses are especially relevant

to cancer prevention programs delivered in health centers.

First, patient characteristics associated with a missed ap-

pointment, either with the clinician or health advisor for the

ICS, were consistently associated with low levels of inter-

vention completion. Missed appointment rates in general

medical settings range from 5% to 30%, so it is not surprising

that our implementation was affected by ‘no-shows’ [67].

However, relatively little consideration has been given to the

impact of missed appointments within health-care-based

prevention research. Characteristics of participants who

missed appointments in our study are consistent with previ-

ous reports or positive correlations between missed appoint-

ments and characteristics of younger age, non-white race,

current smoker, lower income status, and lower acculturation

[67–69]. Missed appointments within these groups may be

due to fewer resources or more complex lives. Researchers

who design interventions for health care settings should

anticipate this barrier to intervention delivery and partner

with the health care system to provide facilitators to encour-

age patients with these characteristics to keep appointments.

Reminder phone calls, flexible scheduling, assistance with

transportation, or incentives for keeping an appointment may

serve as a means for assuring higher show rates in groups

that have difficulty keeping appointments.

Second, participants who spent less than 50% of their life

in the US were more than twice as likely to receive all four

calls from health advisors compared to those who spent 50%

or more of their life in the US. This finding indicates that

although participants with lower acculturation may be asso-

ciated with high rates of missed appointments, they can also

be highly compliant with intervention protocols. Our inter-

vention materials and health advisor counseling addressed

social contextual factors that may have made our interven-

tion more salient to participants with lower acculturation

than traditional interventions based solely on health behav-

iors [23,36,70,71]. In particular, the emphasis placed on the

individual’s view of health and social supports during the

health advisor counseling sessions may have helped partic-

ipants with lower acculturation overcome barriers to com-

pleting intervention activities [34,72–75]. It is noteworthy

that we found higher levels of intervention participation

among more recent immigrants, as utilization of preventive

services are generally lower for minority patients.

Third, participant characteristics associated with receipt

of the clinician endorsement differed from characteristics

that predicted completion of the health advisor activities.

Previous studies on utilization of health care services indi-

cate that clinicians sometimes differentially manage patients

based on gender, race, acculturation, or socioeconomic

position [48,68,76–80]. In addition, there is evidence that

rates of clinician advice delivered during usual care to reduce

chronic disease-risk factors is low; 20–57% for dietary

advice, 15–69% for physical activity [50,81]. When clini-

cians do provide advice it tends to be directive and less open

to the patient’s agenda due to time constraints and counseling

style [80]. In our pairing of the clinician and health advisor to

deliver the Healthy Directions-HC activities, we may have

created a safety net for those patients who would have

received lower doses of the intervention had only the

clinician or the health advisor been used in the study. The

patient-centered, contextually based counseling used by the

health advisors in our study contrasts with the behavior-

based recommendations provided by clinicians, yet may

create a synergy that appeals to a broader audience of

patients. Interventions delivered in health centers that rely

on clinician as well as auxiliary supports should examine the

relationships between the care provider’s characteristics and

participant’s characteristics so we may gain further insight

into the dynamics of patient and provider interactions.

Our analysis of predictors of intervention activities was

limited to participant characteristics reported on the baseline

survey and the data collected in the automated process

tracking system. It is possible that other factors, such as

clinician characteristics or co-morbid conditions may have

influenced the implementation of the Healthy Directions-

HC intervention. In addition, we did not control for health

advisor in our analysis because the health advisors rarely

worked with participants outside of their primary health

center. It could be that the data are confounded by a health

advisor effect independent of the health center effect, but

R. Lobb et al. / Preventive Medicine 38 (2004) 766–776774

our small numbers of health advisors and health centers

prevent us from analyzing this possibility. Finally, sub-

analysis like the type we describe can be difficult to interpret

when nearly all participants complete most of the desired

number of intervention activities. There may be some

associations between participant characteristics and inter-

vention activities where the strength of clinical significance

is not supported by statistical significance or statistical

significance is achieved but clinical significance is not

relevant. This manuscript reports baseline data and explores

predictors of participation. In a future paper, we will explore

possible relationships between process data and outcomes.

The data reported here provide health care professionals

and researchers with a description of the implementation of

a cancer prevention intervention for working class, multi-

ethnic populations. Participation in Healthy Directions-HC

was highly successful, particularly with participants of

lower acculturation, a group that has traditionally been

difficult to reach because of missed appointments or low

compliance with treatment regimens. Consideration of so-

cial contextual factors in addition to health behaviors in the

counseling and tailored materials may have resulted in our

success with reaching our target population. This paper

demonstrates the contributions that process evaluation can

make to understanding the implementation of intervention

studies.

Acknowledgments

This research was supported by grant # 5 PO1 CA 75308

from the National Institutes of Health and support to Dana-

Farber Cancer Institute by Liberty Mutual and National Grid.

The authors would like to thank the numerous staff

members contributing to this study, including Elizabeth

Alvarez, Jamie Baron, Simone Pinheiro, Kathleen Scafidi,

Tracy Liwen, and Tatyana Pinchuk. In addition, this work

could not have been done without the participation of the

internal medicine departments of Harvard Vanguard Medical

Associates.

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