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This is to certify that the

thesis entitled

MOTHERS OFFERING MOTHERS SUPPORT: THE
DIFFUSION OF A PREVENTIVE PRENATAL INNOVATION

presented by

Marcy Elisabeth Meyer

has been accepted towards fulfillment
of the requirements for

 

Master of Arts degree in Communication

Major professor

 

Date August 2, 1993

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MOTHERS OFFERING MOTHERS SUPPORT:
THE DIFFUSION OF A PREVENTIVE PRENATAL INNOVATION

By
Marcy Elisabeth Meyer

A THESIS

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

MASTER OF ARTS

Department of Communication
and Urban Affairs Program

1993

ABSTRACT

MOTHERS OFFERING MOTHERS SUPPORT:
THE DIFFUSION OF A PREVENTIVE PRENATAL INNOVATION

By
Marcy Elisabeth Meyer

The Mothers Offering Mothers Support (MOMS) Program.is an
innovative parent-to-parent prenatal support intervention
that seeks to reduce the number of low birthweight infants
born to at-risk women in Michigan. The MEMO for MOMS is a
questionnaire that attempts to measure the level of perceived
change agent success in MOMS program participants. This
scale was mailed to clients in the MOMS program (n=72).
Respondents (n=23) were 69% white, 19% African American, 6%
Asian, and 6% Hispanic, with a mean age of 21.8, 11 years of
education, and 76.5% Medicaid status. Although no
significant correlation was found between client score on the
MEMO for MOMS and level of preventive health behavior (PHB),
certain items in the MEMO for MOMS scale were moderately
associated with P338. This preliminary investigation is a
descriptive study that calls for future research in the

diffusion of prenatal support programs.

ACKNOWLEDGEMENTS

I would like to thank Dr. Lee Anne Roman, Dr. Charles Atkin,
Dr. John Schweitzer, Dr. Jim Dearing, Dr. Richard Lerner, Dr.
Al Shoemaker, Sharon Richardson, Christy Deeds, and all of
the participants in the Mothers Offering Mothers Support

Program.who were generous enough to share their ideas with

iii

TABLE OF CONTENTS

 

 

 

 

 

 

 

 

 

 

List of Tables vi
Introduction 1
Significance 1
National Data 4
Review of the Literature 10
Community-based Health Promotion 10
Social Support 14
Diffusion Theory 19
Rationale 22
Methods OIZQ
Psychometric Theory 25
Elements of Instrument Design 25
Reliability and Validity of MEMO for MOMS 28
Hypotheses 29
Method of Administration 31
Results 33
Follow-up 33
Participants 34
Mean and Standard Deviation of Perceived Change Agent

Success and P88 35
Part-Whole Comparison 36
Influence of Perceived Change Agent Success on P33 40

iv

 

 

 

 

 

 

 

 

 

 

 

Discussion 1;
Limitations of the Study 43
Examining Relationships in a kart-Whole Coeparisonp 45
Inter-Item.Analysis of Perceived Change Agent Success

end PHB 47
Conclusions 50
Appendix A: Study Explanation 53
Appendix B: Informed Consent 54
Appendix C: MEMO for MOMS 55
Appendix D: Human Subjects Approval 59
Appendix E: Item Fregpencies 61
List of References 67

 

8.
9.

LIST OF TABLES

U.S.Infant Mortality Rates, 1960-1980

Infant Mortality Rates by Race, 1960-1987

Causes of Infant Mortality by Race

Percent of Infants Born at Low Birth weight by Race
Incidence of LBW Infants in Michigan

Means and Standard Deviations of Perceived Change
Agent Success Variables

Part-Whole Comparison of MEMO for MOMS
Correlations Between Scale Items and Client PHB

The Relationship Between Tobacco Use and Health
Habit

vi

GUI

\l

10

36
38

40

42

INTRODUCTION

Significance

In the United States, our infant mortality rate (IMR) is
higher than many other industrialized countries. The United
States ranks 22nd in infant mortality among industrialized
nations with a rate 10.6, in spite of the fact that we spend
more per capita for prenatal care than does any other country
in the world (USDHHS, 1991). A body of literature exists
that seeks to explain the etiology of infant deaths. Many
studies focus on factors that may contribute the growing gap
between the IMR for black and white infants in the United
States: Although infant mortality rates have declined for
both blacks and whites over the last three decades, a large
racial gap in infant mortality persists in the United States.
The slower relative decline for black infant mortality rates
is linked to an increased incidence of low birth weight (LBW)
infants in the African-American population (USDHHS, 1991).
This disparity exists in the State of Michigan and the United
States as a whole. The relationship between IMR and LBW is a
major public health issue that presents a challenge to
epidemiologists, health policy makers, health communicators,
hospitals and clinics, community members, and women's and

children's advocates across the nation.

2

In Michigan, The Mothers Offering Mothers Support
(MOMS) Program is an innovative parent-to-parent support
intervention that seeks to reduce the number of low
birthweight infants born to at-risk women. The MOMS Program
is based at Butterworth Hospital's Regional Perinatal Center
in Grand Rapids, and it offers support services to women in
western Michigan who are admitted to the prenatal clinic to
receive care for their high-risk pregnancies. In this
program, at-risk pregnant women in the prenatal clinic are
paired with volunteers: experienced parents from their
community who have previously given birth to a premature or
low birthweight infant. Services include weekly contact,
emotional and informational support, transportation
reimbursement to prenatal appointments, support in labor and
delivery, and parenting education.

In order to determine if these services are effective,
Butterworth Hospital and the Institute for Children, Youth,
and Families are co-investigating the relationships between
program activities and birth outcomes. On-going longitudinal
program evaluation includes qualitative interviewing and
quantitative analysis of questionnaires that evaluate changes
in perceived levels of client psychosocial variables: the
Maternal Social Support Index (Pascoe, Loda, Jeffries, and
Earp, 1981); Rosenberg Self Esteem (Rosenberg, 1965), and

the Profile of Mood States (McNair, Lorr, and Droppelman,

3

1971). Matched file data from hospital chart abstracts
provides additional information about participant demographic
characteristics, lifestyle, and medical risk variables.

In this study, the author developed the MEMO for MOMS in
an attempt to assess the significance of variables associated
with the adoption of prenatal health promotion in the
Butterworth Hospital MOMS Program. Because the MOMS Program
is a preventive innovation, it is appropriate to evaluate it
with variables modified from Diffusion Theory (Rogers, 1982).
The MEMO for MOMS is a questionnaire that attempts to measure
change agent success in the Butterworth MOMS community—based
health promotion effort. Specifically, a client's score on
the questionnaire indicates perceived volunteer support
parent effectiveness. It is hypothesized that elements of
perceived volunteer support parent effectiveness will have a
positive correlation with the amount of preventive health
behavior in which a pregnant client engages.

The theoretical implications of this study are linked to
previous work in community-based health promotion. For
example, the communication of health promotion to low-income
at—risk pregnant women by low-income women in the same
community who have experienced a previous low birthweight or
preterm birth is an example of community—based health
promotion. The MOMS program consists of local health
providers and community volunteers working together to

overcome individual and institutional barriers to prenatal

4

health: Through their efforts, they can realize an
improvement in prenatal health status and birth outcomes of
women in their community.

Theoretical linkages also exist with previous research
conducted in diffusion theory, particularly the implications
for evaluating the diffusion of health innovations. The mode
of health communication in a parent-to-parent support program
is an element in the process of diffusing a preventive
innovation: In this case, interpersonal communication is a
vehicle for diffusing information about health education and
social support. The women who are involved as health
promoters can be called "volunteer MOMS", ”lay health
workers", or "change agents”. Diffusion theory provides a
conceptual framework for determining the degree of the change
agent's effectiveness. Thus, the preventive prenatal
innovation can be evaluated in part by exploring the
perceived relationship that exists between the volunteer and
client. Social support interventions are frequently
evaluated with psychometric scales and linked medical records
that describe birth outcomes. Diffusion theory lends an
alternative framework for evaluating the process of health
communication.

Background

National Data

The infant mortality rate (IMR) is a standard by which
it is possible to compare the quality of maternal and child

health care delivery systems across international, national,

 

5

state, and local boundaries. The rate of infant mortality
refers to the number of infant deaths per 1,000 live births.
(MDPH, 1988). Infants are categorized as babies under one
year of age. According to the Report of the Secretary's Task
Force on Black and Minority Health, infant mortality rates
have two components: neonatal deaths that occur in the first
28 days of life, and postneonatal deaths that occur between
28 days and one year (USDHHS, 1986). neonatal deaths reflect
the pro-pregnancy health status of the mother, the quality of
prenatal care that she receives during her pregnancy, and the
care that she receives during delivery and in the post-partum
period. Postneonatal deaths are thought to reflect the
living conditions, quality of child care, and the degree of
medical care available for preventable illnesses.

It is helpful to examine rates over time to understand
trends in infant deaths. According to the USDHHS, the infant

mortality rate has declined from 1960 to 1980 (see Table 1).

Table l

 

U.8. INFANT MORTALITY RATES 1960-1980

 

1960 1970 1980
26.0 20.0 12.6

 

 

NOte. per 1,000 live births. Data from Health Status of

Minorities and Low-Income Group (p.102) by USDHHS, 1991,

washington, DC: 0.8. Government Printing Office.

 

6

One could logically conclude that the reduction in
infant mortality rates is due to inception of Medicaid (1965)
and the miracles of modern medicine made possible by the NICU
in the 19708. More than any other program, it was the
Medicare/Medicaid legislation of 1965 that established the
popular concept that health care is a right. Medicaid was
unique in that it has helped reduce financial barriers to
care as well as to bring appropriate health services to high-
risk mothers and children-~primary care as well as high tech
medical interventions made possible by modern equipment in
the neonatal Intensive Care Unit. However, despite the
overall decline in infant mortality rates, recent studies
indicate that the incidence of infant mortality is not
declining equally among different ethnic groups (USDHHS,
1986, 1991; MDPH, 1988).

The most recent national statistics on the status of
minority health indicate that the racial disparity is
actually increasing. In 1960, the rate for black infants was
193% of the rate for white infants; in 1987, the rate was

208% higher for blacks than whites (see Table 2).

Table 2

 

INFANT MORTALITY RATES BY RACE 1960-1987

 

1960 1970 1980 1987
black 44.3 32.6 21.4 17.9

white 22.9 17.8 11.0 8.6

 

 

(Table 2 cont'd.)
NDtQ- per 1,000 live births. Data from Health Status of

Mipogities and Legelncome Group (p.100) by USDHHS, 1991,

washington, DC: U.S. Government Printing Office.

In order to understand the reasons for the growing gap
between black and white infants in infant mortality rates, it
is helpful to understand the etiology of infant moribidity
and mortality. For example, there are many conditions that
lead to infant mortality, among them birth defects,
accidents, sudden infant death syndrome, and disorders
related to low birth weight or pretenm labor. .Although both
white and black infants suffer from common causes of infant
mortality, there is a striking dissimilarity in the incidence
with which infants die from disorders related to low birth
weight. Black infants die from complications related to low
birth weight and preterm labor at nearly four times the rate

of white infants (see Table 3).

Table 3

 

CAUSES OF INFANT MORTALITY BY RACE

 

 

causes of infant mortality ratio black: white
a. congenital anomalies 1.1
b. SIDS 1.9
c. disorders related to LBW/PTL 3.9

d. respiratory distress syndrome 1.9

 

 

(Table 3 cont'd.)
Nope. per 1,000 live births. Data from Health Status of

ginorieies and Lowaincoge Group (p.105) by USDHHS, 1991,

washington, DC: U.S. Government Printing Office.

These findings about the primary causes for infant
mortality are paralleled by USDHHS statistical analysis of
the discrepancy between the percentage of low birth weight
infants in black and white populations. Over the past two
decades, the ratio between black and white low birth weight
infants has increased from 2.04 to 2.23. Thus, the racial
disparity in the distribution of infant deaths related to low
birth weight and preterm labor may be due to the increasing
number of low birth weight infants born to African American

women (see Table 4).

Table 4

 

PERCENT OF INFANTS OF LON BIRTNNEIGNT BY RACE

 

 

1&9 m9 £81
black 13.9 12.5 12.7
white 6.8 5.7 5.7
ratio 2.04 2.19 2.23

 

Note. per 1,000 live births. Data from Health Status of

Minorities and LoweIncome Group (p.108) by USDHHS, 1991,

Washington, DC: U.S. Government Printing Office.

 

9

According to a recent government report, risk factors
for infant mortality include live birth order (first and
third or higher); maternal characteristics, including
advanced maternal age as well as young age; low educational
attainment; marital status; maternal substance abuse; and
late initiation of prenatal care (USDHHS, 1991). Risk
factors for infant deaths related to low birth weight may
include maternal age, marital status, inadequate prenatal
care, smoking, substance abuse, and poverty (MDPH, 1988).
Recent studies call for a more in-depth investigation of the
relationships that exist between poverty, ethnicity, and poor
birth outcomes (Collins and David, 1990; Hansell, 1991;
Kleinmen, Pierre, Madans, Land, and Schram, 1988; Lia
Hoaberg et a1., 1990; Machala and Miner, 1991; Reed, 1990;
Sable, 1990; Starfield et al. 1991; and Zambrana, R.,
Dunkel-Schetter, C., and Scrimshaw, S., 1991). It is
interesting that, although ethnicity is clearly associated
‘with increased risk of infant mortality and low birthweight,
government reports do not explicitly recognize it as a risk
variable in and of itself. Perhaps this is because of a
desire to avoid propagating the myth of race as a biological
rather than sociological variable. At any rate, this is an
omission that needs to be duly noted.

According to MDPH statistics, Michigan has a poor track
record when it comes to taking care of pregnant women and
babies: in 1984, Michigan had the highest non-white infant

mortality rate in US. In that year it also tied for first

10

place tie with Pennsylvania for the highest LBW rate. Again,
the relationship between low birth weight and infant
mortality rates can be compared and contrasted with the
national divide: In Michigan, the greater racial disparity
in the incidence of low birth weight infants (see Table 5)
may explain in part the fact that 76.4% of non-white infant

deaths were infants weighing less than 2500 g. (MDPH, 1988).

Table 5

 

 

INCIDENCE* OF LBW INFANTS IN’MICHIGAN‘ 1986

 

black white ratio
140 54.3 2.58

 

Note. per 1,000 live births. Data from Minority Health in
Michigan (p.73) by MDPH, 1988, Lansing, MI.

Review of the Literature

Community-based Health Promotion

Goeppinger, Lassiter, and Wilcox (1982) define community
health as community competence. It involves the presence of
four conditions that are necessary elements in the process of
community health: 1) the commitment to community
collaboration as a way to identify the problems and needs of
a community; 2) the ability to achieve a working consensus
on goals and priorities; 3) the ability to agree on ways

and means to implement the agreed-upon goals; and 4) the

 

11

ability to collaborate effectively in the required actions.
In essence, this process involves the cooperation of members
from the professional health service delivery service as well
as individuals from a community's informal helping system or
"hidden health care system" (Levin, 1983). In this way,
caretaking, emotional support, advice, and advocacy can be
organized across several social networks as a strategy for
community health promotion (Israel, 1985).

Communityawide approaches are especially advisable when
one attempts to understand determinants of women's health
(Rodriquez-Trias, 1992). Because women are central players
in family and community dynamics, health policy makers,
providers and researchers cannot ignore the complex
ecological factors that contribute to their health problems.
Health promotion must be viewed as a collaborative process
created with community members as well as an array of tactics
designed by an agency to produce certain behavioral outcomes
in a certain population: the goal is to foster change in the
social environment and not only the knowledge--attitude--
behavior hierarchy of isolated individuals. Truly
collaborative efforts must work to create effective health
promotion programs that have goals that are compatible with
the needs of the program participants. To this end, there is
a need for collaboration with community members at all stages
of program development, implementation, and evaluation (Eng,

Salmon, and Mullan, 1992).

12

The utilization of peer health workers to provide health
education and services to underserved populations is an
intervention widely used in other nations and one that
originally gained popularity in the United States during the
Great Society initiatives under the Economic Opportunity
legislation of the mid 1960's. Projects in maternal and
child health were designed to employ peer health workers of
similar culture and community characteristics as the target
population to bridge the socio-cultural gap between providers
and families as well as to provide informational and
supportive health care services to underserved groups. Lay
health workers often shared similar cultural backgrounds and
neighborhoods with their clients, and they were thought to be
able to gain access to and establish contact with individuals
who otherwise might be unapproachable. Further,
paraprofessionals often reported experiencing personal
advancement opportunities and significant personal growth as
a result of their training and outreach work (Riessman,
1965). Today, increasing health care costs and the growing
proportion of lowbincome women with inadequate prenatal
health care has led public health providers to a renewed
interest in the use of peer health workers for education,
outreach, and advocacy (Committee for the Study of the Future
of Public Health, 1988).

A review of the literature indicates that peer health
workers are successful in teaching concepts of primary or

secondary prevention as well as to increase maternal-child

13

health services compliance and utilization (Chamberlain,
1987). Recent studies suggest that indigenous lay health
workers can be effective in delivering educational and social
support programs for at-risk pregnant women (Amezcua, 1990;
Giblin, Poland, and Ager, 1990; Levin, 1983; Meister,
warrick, de Zapien, and WOod, 1992; Pharis and Levin, 1991).
Aided by persuasive communication and amenable health policy,
prenatal volunteers could influence women to adopt behavioral
changes that would reduce their risks of premature and lowa
birthweight babies. Potential benefits include increased
physical health, preventive health care, increased self-
esteem, reduced dependency on social services, renewed
psychological growth, and increased positive parenting
skills. Similarly, a community-based intervention can make
environmental changes act as buffering agents between
maternal risk factors and the health of a newborn baby:
Community—based parent-to-parent support programs are
designed to reduce the risk of LBW babies in at-risk
populations by offering support services and advocacy to
women who need them most.

An analysis of volunteer prenatal programs in Michigan
(Meyer et al., unpublished manuscript) indicates that
community-based health promotion programs for at-risk
pregnant women provide a wide range of services. Services
vary between programs and often reflect the nature of the
parent organization as well as the needs of the client

population. In general, services can be broken down into

14

five categories: one-to-one peer support (non-medical);
one-to-one non-peer support; assistance to access prenatal
care; provision of prenatal care; and material support.
One-to-one peer support (non-medical) includes making home
visits, recruiting clients, completing intakes, counseling,
giving nutritional, prenatal, and parenting information,
offering emotional support. One-to-one non-peer support
includes the delivery of similar services, but is offered to
the client by someone of a different community, background,
culture, or socioeconomic status. Assistance to access
prenatal care is a category that includes referrals (such as
how to apply for W1C, Medicaid, or where to make appointments
for prenatal care), phone calls for appointment reminders or
advocacy, and transportation, travel reimbursement, or child
care. Some programs actually provide prenatal medical care,
i.e. monthly checkups, diagnostic tests, labor and delivery,
or support in labor and delivery. Finally, material support
can provide housing, pregnancy testing, maternity clothes,
baby clothes, cribs and car seats.

Social Supppgt

Can non-medical social support improve a woman's
ability to make informed decisions about being pregnant and
about managing her pregnancy, thereby potentially enhancing
the prospects for her pregnancy outcome? This question is
one being asked by public health workers, nurses, and doctors
who are concerned about the growing racial disparity in

infant mortality rates in America. Social support may be

15

seen as the quantity and quality of emotional, instrumental,
informational, or financial aid that is obtained from one's
social network. It is postulated that social support may
influence physical health in many ways: the provision of
advice, services, or access to new social contacts; direct
economic or physical assistance; exposure to the forces of
social control and peer pressure; and the stress-buffering
effects of intimacy, nurturance, and reassurance of worth
(Berkman, 1984).

Several studies suggests that changes in psychosocial
attitudes and social support may act as mediating variables
between risk factors and birth outcomes (Norbeck and Tilden,
1983; Pharis and Levin, 1991; O'Hara, 1986; Meister et al.,
1992; Giblin et a1, 1990; Olds, D., Henderson, C., Tatelbaum,
R., and Chamberlin, R., 1986; Heins, Nance, and Ferguson,
1987). There is substantial evidence to suggest that there
is a strong negative correlation between a woman's level of
social support and her risk of pregnancy complications.
Several recent studies suggest that strong negative
correlations exist between social support, depression, life
stress, poor weight gain, cigarette smoking, alcohol and
substance abuse (Giblin et al., 1990; Zuckerman, Amaro,
Bauchner, and Cabral, 1989; Pharis and Levin, 1991; Meister
et al., 1992). Of particular interest is the finding that
women living in high-violence neighborhoods are significantly
:more likely to experience pregnancy complications than women

living in lower violence neighborhoods (Zapata, Rebolledo,

16

Atalah, Newman, and King, 1991; Romano, Bloom, and Syme,
1991). Within high-violence neighborhoods, lower levels of
social support were significantly associated with a woman's
alcohol use during pregnancy, partner substance use, and risk
of pregnancy complications (Amaro, Fried, Cabral, and
Zuckerman, 1990). Despite the intuitively appealing nature
of these findings, one must note that these studies are not
without limitations in research design: the majority of the
studies in the field of social support and pregnancy are not
longitudinal in nature (Broadhead, Kaplan, James, et al,
1983); As such, correlation, but not causation, can be
inferred between the presence of social support and outcome
variables. In addition, measurement may be a problematic
issue if the prevalence of a risk variable is obfuscated by
the limitations of self-reporting techniques. Future
research needs to focus on prospective studies that examine
the relationships between social support and community health
in greater detail.

weenig and Midden (1991) treat the subject of social
network influences on diffusion and persuasion. Their
findings support the hypothesis that the effectiveness of a
persuasive communication program aimed at promoting adoption
decisions depends on the successful achievement of two
successive processes: infonmation diffusion and persuasion.
In essence, they link the process of information diffusion to
the number of social ties in an individual's social network,

and the adoption decision to the strength of communication

17

ties. Although their research pertains primarily to the
diffusion of an environmental innovation (the adoption of
energy conservation measures), their findings are relevant to
preventive health innovations as well. The authors found
that a direct tie with a community volunteer of the project
group was a significant positive predictor of program
awareness. Second, they found that adoption decisions were
positively related to advice received from strong ties (i.e.
family member, opinion leader, or close friend) and not to
advice received from.weak ties (i.e. acquaintances, casual
friends, work associates). One can apply these findings to
community-based health promotion efforts: in order for
diffusion to occur, there is a need for collaboration between
community members and agency. The number of weak social ties
between clients and community program volunteers can be
increased to stimulate communication and information
dissemination; Participation of community members and
client's strong network ties can minimize potential
conflicting messages between clients and their family,
friends, and opinion leaders (St. Clair and Anderson, 1989).
In their work that investigates the epidemiological
evidence for a relationship between social support and
health, Broadhead et a1. (1983) state that a strong argument
can be made for a causal relationship between social support
(the independent variable) and health (the dependent
variable). This conclusion is qualified by the finding that

a review of literature does not demonstrate the necessary

18

antecedent-consequent relationship necessary to indicate
causality: many studies are retrospective or cross-
sectional, and so can only express confidence in their
results in terms of correlation. However, the authors
suggest that three variables should be mentioned for their
statistical interaction or effect modification of social
support: education; gender; and baseline health status.
Education may also interact with social support so that the
least educated receive the greatest benefit; social support
is apparently of greater benefit to women than men; and
social support may be more beneficial to those already in
poor health. These three variables (low educational
attainment, female gender, and medical/social risk status)
are representative of the demographic characteristics of the
clients in the MOMS prenatal health innovation.

What is the relationship between social support and
diffusion? Although this topic is not directly addressed in
the literature, it would seem that certain elements of change
agent success are positively correlated with social support.
Take for instance, three variables: perceived empathy,
trustworthiness, and client-orientation in terms of
interpersonal interaction. These three variables are
elements of the MEMO for MOMS questionnaire. Intuitively, it
would appear that the more that a lay health worker shares
elements of social support with a client (for example,
intimacy, emotional support, material or informational

resources, and advice), the more that the client would be

 

19

inclined to make positive attributions about the degree of
empathy, trust, and client-orientation in their interpersonal
interaction. In turn, these attributions would increase the
potential for information diffusion and adoption of
innovation. The relationship between diffusion variables and
change agent success will be explored in greater detail in
the Methods section.

Diffusion Theopy

According to Green and Raeburn (1990), an ecological
model of health promotion defines health as ”the product of
the individual's continuous interaction and interdependence
'with the family, the community, the culture, the societal
structure, and the physical environment in which she lives."
It is perhaps with such insight that Rogers (1983) discusses
diffusion theory, the roles of the change agent, her
strengths and her weaknesses in relation to the ecology.

Rogers defines diffusion as the process by which an
innovation is communicated through certain channels over time
among the members of a social system. A preventive
innovation is "a new idea that an individual adopts in order
to avoid the possible occurrence of some unwanted event in
the future” (Rogers, 1983). Proper prenatal care is an
example of a preventive innovation: Medical experts indicate
that proper prenatal care, adequate nutrition, and avoidance
of risk behavior during pregnancy may reduce the risk of
giving birth to a premature or low birthweight infant (Olds

et al., 1986; Lia Hoaberg et al., 1990).

20

However, because of the uncertainty of the desired
consequences, preventive innovations often do not enjoy a
rapid rate of adoption. For example, any pregnant woman
knows that there is no guarantee that she will give birth to
a perfectly healthy baby. A.woman may follow doctor's orders
and adhere to a strict regimen of proper prenatal care,
adequate nutrition, and avoidance of risk behavior during
pregnancy; yet, despite her efforts to adopt a healthy
lifestyle during pregnancy, it is possible that she may still
give birth to a low birthweight infant. On the other hand,
another woman who drinks alcohol in moderation, smokes half a
pack of cigarettes a day, and disregards health-promoting
behaviors in pregnancy may nonetheless give birth to a
perfectly normal infant.

While medical experts can never be certain of the
desired consequences of preventive prenatal care, they can
also experience difficulty in communicating the nature of
this uncertainty: not all pregnant women in the lay public
are familiar with technical terminology, probability, or the
concept of statistical uncertainty. In this instance, a
doctor might have difficulty explaining the nature of risk to
an at-risk pregnant woman, let alone persuading the woman to
effect behavioral change. Therefore, it is the job of the
health outreach worker as an intermediary to communicate the
risk -- as well as the uncertainty' (National Research
Council, 1989) inherent in the failure to adopt healthy

behavior during pregnancy .

21

According to Rogers, "a change agent is an individual
who influences clients' innovation decisions in a direction
deemed desirable by a change agency. If an agency with
resources to influence policy initiatives were to feel that
health promotion for high-risk pregnant women in our society
is a priority, then Rogers' change agent could be employed
to influence innovation decisions which concern nutrition and
proper prenatal care. This hypothetical relationship mirrors
the situation in Maternal Support Services or Maternal Infant
Outreach programs, where state health departments employ
paraprofessionals to encourage client compliance with
prenatal care.

Rogers' "Generalizations 9-1 to 9-12" state that "a
change agent's relative success in securing the adoption of
innovations by clients is positively related to: 1) the
extent of change agent effort in contacting clients; 2) a
client-orientation, rather than a change agency-orientation;
3) the degree to which the diffusion program is compatible
‘with client's needs; 4) the change agent's empathy with
clients; 5) higher social status among clients; 6) greater
social participation; 7) higher education; and 8)
cosmopoliteness (i.e. a cosmopolitan nature exhibited by
those not bound by local or national habits or prejudices)."

Further, he generalizes that ”change agent success is
positively related to: 9) homophily (i.e. the degree to
which pairs of individuals who interact are similar in

certain attributes, such as beliefs, education, social

22

status, and the like) with clients; 10) credibility in the
clients' eyes; 11) the extent to which she works through
opinion leaders; and 12) an increase in clients' ability to
evaluate innovations" (Rogers, 1983).

Rationale

In order to explain the rationale for this study, it is
necessary to define the variables being measured and to
clearly explain the logic behind the expected results. The
independent variable is the client's MEMO for MOMS score
(indicates perceived volunteer support parent effectiveness);
The dependent variable is client preventive health behavior
(measured by number of prenatal visits; sufficient weight
gain; smoking, drinking alcohol, or substance abuse). The
relevant hypotheses are as follows:

Ho: No relationship is posited between a client's score
on the MEMO for MOMS (indicates perceived volunteer support
parent effectiveness) and the amount of preventive health
behavior in which a pregnant client engages (number of
prenatal visits; sufficient weight gain; quitting smoking,
drinking alcohol, or substance abuse).

H1: Positive correlations are posited to exist between
a client's level of preventive health behavior and the
following variables:

a. program compatibility with client needs (items 8-9
and 25-30);

b. an increase in clients' ability to learn about or

evaluate innovations (items 22-24);

23

c. change agent credibility in terms of technical
expertise and trustworthiness (items 17-19);

d. perceived homophily between client and change agent
(items 15-16);

e. perceived client-orientation in terms of perceived
quality of interpersonal interaction (items 4-5);

f. perceived change agent empathy (items 6-7);

9. level of educational attainment (from demographic
data);

h. frequency of change agent contact with client
(items 1-3);

i. degree to which change agent's advice is perceived
to be consistent with that of opinion leaders (items 20-21);

j. social participation among clients (frequency of
contact with and number of new members in social network)
(items 10-11);

k. cosmopoliteness of client (items 12-14); and

1. social status of client (from demographic data).
Variables are drawn from Rogers list of "Generalizations 9-1
to 9-12". They are presented in order from strong positive
to weak positive as an organizational scheme only; no
hypothesis is made about the relative strengths of each
hypothesis.

Ho: Inter-volunteer differences will be reflected in
client scores and preventive health behaviors.

H1: Inter-volunteer differences will be reflected in

client scores and preventive health behaviors.

24

This investigation is conducted in an attempt to
understand and evaluate a preventive intervention that seeks
to reduce the incidence of premature and low birthweight
infants in an at-risk population. The goal of the program
is to enable the support parent to provide material and
emotional support to the client in an effort to improve birth
outcomes. If a client scores high on the MEMO for MOMS, it
indicates that the client perceives herself and her support
parent to have certain characteristics. According to
diffusion theory, the presence of these attributes in the
client and the support parent is a predictor of change agent
success. A high level of change agent success increases the
probability that the client will adopt the preventive
innovation. It follows that a client who perceives her
support parent to be effective is more likely to engage in
preventive health behavior than a client who does not
perceive her support parent to be effective. Certain
attributes, such as client ability to learn about or evaluate
innovations, program compatibility with client needs, and
change agent credibility (in terms of technical expertise and
trustworthiness), may play a more influential role in client
adoption of preventive health behaviors than other factors.
However, it is beyond the scope of this study to predict the

strength of relationships between all relevant variables.

METHODS

Psychometric Theogy

In social science research, theory plays an important
role in the development of measurement scales. According to
Suen (1990), psychometric theory is the science behind scale
development. Scales are collections of items that reveal the
level of an underlying theoretical variable (DeVellis, 1991).
Central issues in psychometrics include: how to develop
items; how to select items; how to transform responses into
numerical scores; how to assess the quality of these scores;
how to interpret these scores; and how to ascertain that the
scores are not biased against certain groups of individuals.
Elements of Instrument Design

The MEMO for MOMS questionnaire fuses concepts from
communication theory and human ecology. It is designed to
measure change agent success in parent-to-parent support
programs for at-risk pregnant women. The items in MEMO for

MOMS have been developed from a wide variety of sources, and

 

include conceptual elements from instruments such as
Nerbeck's Social Support Questionnaire (Norbeck, Lindsey, and
Carrieri, 1981), the Maternal Social Support Index (Pascoe,

1981), and the Cardsort Rating of 32 Program Services (Pharis

25

26

and Levin, 1991). Additional material was derived from
literature that explored the nature of resources and demands
in stress and social support during pregnancy (Norbeck and
Tilden, 1983; Romano, Bloom, and Syme, 1991).

The 31-item.questionnaire (see Appendix C) is designed
to rate client perception of change agent success. Answers
are constructed along an adjectival response scale, with
three to six discrete responses possible for each item.
Respondents are asked to circle the most accurate response.
.A review of health measurement scales indicates that "the
minimum number of categories used by raters should be in the
region of five to seven” (Strainer and Norman, 1989, p. 27).
This ”rule of thumb” is often used because a smaller number
of categories tends to reduce instrument reliability
(Nishisato and Torii, 1970). However, for the target
audience of clients with low educational attainment, four
possible answers are given for items with adjectival
responses. This is because simpler answers give clearer
options for client selection. Options range along a
continuum, for example: ”often... sometimes... seldom...
never”; "very well... quite well... somewhat well... not at
all well"; "a lot... somewhat... a little... not at all";
”usually... sometimes... seldom... never"; "not enough...
just about right...too much"; and numerical responses (i.e.
"0... 1-2... 3-4... 5-6... 7 or more"). These responses are
paired with questions that measure frequency, intensity,

contingency, quality, and quantity, respectively. ”Does not

27

apply" is an option for contingent questions that measure
intensity or quantity rather than frequency. Item 31 is an
open-ended question used to uncover client-generated
anecdotal evidence. This qualitative material may assess
change agent effects that are not tapped by the first 30
items.

An attempt has been made to represent each variable in
the questionnaire by more than one item. However, this does
not apply to generalizations 5 and 7 because they measure
social status among clients and higher education. These two
items will be gathered by standard demographic questions that
are routinely attached to client questionnaires by the staff
in the hospital setting within which the study will be
conducted. Items 1-3 seek to measure change agent contact
‘with client; items 4-5 are designed to measure client-
orientation; items 6-7 attempt to measure change agent
empathy; items 10-11 are intended to measure social
interaction among the client population; items 12-14 seek to
measure cosmopoliteness in terms of social interaction and
exposure to mass media; items 15-16 are designed to measure
homophily; items 17-19 were written to measure credibility
in terms of technical expertise and trustworthiness; items
20-21 are intended to measure consistency of advice with that
of opinion leaders; items 22-24 try to assess client ability
to evaluate innovations; and items 8-9 and 25-30 attempt to
measure compatibility with client needs. It must be noted

that elements of material and emotional support (Thoits,

28

1982) form the nexus of items in the client need category.
Grouping of the items is orchestrated by the distinct
socioemotional and instrumental components of social support
(Thoits, 1982). Many of these items are conceptually based
in a cardsort rating device that measures social support for
low-income women (Pharis and Levin, 1991).
Reiiability and Validity of MEMO for MOMS

Reliability is defined as the degree of consistency or
stability with which the instrument measures an attribute
(Smith, 1988). Reliability can be established by a variety
of methods. Internal consistency can be tested by comparing
one part of the instrument with another. The 31 item scale
represents twelve distinct yet presumably interrelated
factors: Individually, each factor represents a distinct
facet of the relationship between change agents and clients;
when viewed as an ensemble, the instrument is composed of
items that operationalize change agent success. The alpha
coefficient has a single value for any given set of data, and
is equal to the mean of all possible split-half coefficients
associated with a particular set of data. However, in the
MEMO for MOMS scale, each variable is often represented by
only two items. As such, this method for assessing
reliability does not appear to be the most appropriate.

Validity refers to whether the instrument really
measures what it intends to measure (Smith, 1988). Face
validity was established by expert evaluation to determine

whether items adequately covered the conceptual model and

29

were appropriate for self-administration by the client
population. Dr. Lee Anne Roman, a published expert in the
field of Neonatal Intensive Care Unit parent support, Dr.
James Dearing, a professor of Communication and diffusion
theory, and Christie Deeds, a paraprofessional coordinator at
the Butterworth MOMS program.were in complete agreement that
there was sufficient congruence between the conceptual model
and the questionnaire. Items that seek to measure specific
elements of change agent success integrate Roger's treatment
of diffusion theory (1983) and volunteer services offered by
the Butterworth MOMS program.

A hypothetical relationship will be tested between
change agent success and preventive health behavior (PHB) by
correlational analysis. Scored questionnaire results will be
compared with level of client PHB: relationships will be
examined between level of PHB and 1) total client score on
the MEMO for MOMS; and 2) client score on the 12 subscales
that represent variables of perceived change agent success.
Correlations will be analyzed for strength and significance
using SPSS. It is hypothesized that perceived change agent
success will have a strong positive correlation with client
level of PHB.

We

The questionnaire will be administered to clients in the
MOMS program at Butterworth Hospital. Correlational analysis
will test the hypotheses that: 1) perceived change agent

success has no correlation with client preventive health

30

behavior in the Butterworth Hospital MOMS Program; and 2)
that no inter-volunteer differences exist between client
scores . In order to reject the null hypothesis, client
scores on the MEMO for MOMS must have a strong (positive)
correlation with the amount of preventive health behavior in
which they engage. Preventive health behavior (PHB) will be
measured by information provided on the client's hospital
chart abstract and the baby's birth certificate. Specific
PHBs include: 1) the absence of risk behaviors (i.e.
smoking, alcohol, cocaine, or inadequate weight gain); and 2)
the total number of client prenatal visits. 'Risk behaviors'
‘will be scored positively or negatively, depending on how
they impact prenatal health. 'Prenatal visits' will be
scored according to the total number of prenatal clinic
visits. Thus, stated, PHB level will be measured and coded
so that PHB a (total prenatal visits) + (weight gain) -
(alcohol use) - (tobacco use) - (cocaine use). To this end,
the more preventive health behaviors in which a client
engages, the higher her score will be.

Two supporting hypotheses are suggested. First,
correlations of varying intensity should exist between a
client's level of preventive health behavior and those
items in the MEMO for MOMS questionnaire that attempt to
represent the following variables: program
compatibility with client needs (items 8-9 and 24-30);
an increase in clients' ability to evaluate innovations

(items 22-24); credibility in terms of technical

31

expertise and trustworthiness (items 17-19); homophily
(items 15-16); client-orientation in terms of perceived
quality of interpersonal interaction (items 4-5); change
agent empathy (items 6-7); level of educational
attainment (from demographic data); change agent
contact with client (items 1-3); consistency of change
agent's advice with that of opinion leaders (items 20-
21); social participation among clients (items 10-11);
cosmopoliteness (items 12-14); and social status (from
demographic data). Second, since each change agent has
more than one client, inter-volunteer differences should
be reflected in client scores and preventive health
behaviors. By coding each client questionnaire by
volunteer, we can determine which, if any, change agent
variables remain relatively constant between clients.
Method of Administration

The questionnaire was mailed out one time only to
program participants (n=72), with a cover letter from the
paraprofessional program coordinator. The letter explained
the reason for the evaluation, encouraged clients to return
their completed questionnaires, and mentioned that a gift
certificate would be procured for each client upon the
receipt of her completed program evaluation (the gift
certificate was a $5 coupon for Meijer; It was funded by a
federal research grant as an incentive to increase the
response rate in the target population). In fact, despite

this incentive, an initially low response rate of 23 (32%)

32

and nine returned questionnaires (client had moved and left
no forwarding address) in the first three weeks prompted us
to follow up on collecting data for the program evaluation.
As a result, the paraprofessional program coordinator and
investigator made telephone calls to remind the 40 clients
who had not yet responded to send in their questionnaires as
soon as possible. When appropriate, they offered to help
clients complete the survey over the telphone by filling in

their responses on a blank questionnaire.

RESULTS

llow-u

Eighteen clients did not have telephone numbers in the
program.records, so follow-up call were not feasible. Out of
32 follow up phone calls made, one client was contacted in
person, messages were left for five clients with relatives,
seven client numbers did not answer, and 19 had moved. Over
all, at least 28 clients (39% of the total participants) had
moved and left no forwarding address since the time of their
involvement in the MOMS Program. This high mortality rate
illustrates one major difficulty associated with conducting
outreach evaluation on prenatal support programs for at-risk
women: locating the program participants. On-going program
evaluation will compare the characteristics of clients who
responded to the questionnaire with those who did not. The
goal will be to identify ways in which the response rate can
be increased in future research that involves participants in

the MOMS program.

33

34

gerticipants

Of 23 returned questionnaires, 18 were essentially
complete and could be matched by case number with clients who
had participated in the pilot study during their pregnancy.
This was a crucial linkage because birth certificate
information about prenatal PHB was stored in the data base
that was created during the pilot study. The mean age of
study participants was 21.8 years. Sixty-nine percent were
white, 19% were African American, 6% were Asian, 6% were
Hispanic, and 6% were from other ethnic categories. Eighty-
eight percent of the participants were single and 12% were
married. The mean level of education in the population was
11 years; however, 44% were high school graduates, 18% had
earned a GED, and 11.8% had attended college but not received
a diploma. The majority of study participants were on
Medicaid (76.5%); the rest had private insurance (11.8%),
were uninsured (5.9%), or had "other" insurance (5.9%). Most
respondents had been involved in the MOMS program for six
months or less (61.1%); others had spent seven months to a
year (22.7%), or more than one year (16.7%) in the program.

Because of the low response rate, we decided to compare
demographic characteristics of respondents and non-
respondents. Respondents and non-respondents were quite
similar in educational, economic, and marital status. For
example, 53% of respondents had fewer than 12 years of
education compared with 49% of non-respondents; eighty-eight

percent of respondents and 80% of non-respondents were

35

single; seventy-six percent of respondents and 69% of non-
respondents were on Medicaid. However, there was a racial
disparity between respondents and non-respondents: Non-
respondents were much more likely to be minorities than
respondents (46% vs. 31%).
Meap and §tandard peviation of Perceived Change Agent Success
M

Total MEMO for MOMS scores were calculated by adding up
responses for each coded item. The scale had a possible
range of 29-167, with 167 as the highest level of perceived
change agent success. MEMO for MOMS scores ranged between 46
and 126, with a mean of 98 and a standard deviation of 22.
PHB scores ranged from 5 to 87, with a mean of 36 and a
standard deviation of 18. Overall, clients perceived that
volunteers had high levels of credibility, empathy, client
orientation in interpersonal interaction, advice congruent
with that of opinion leaders, and the ability to implement
program goals compatible with client needs. Clients also
perceived that they had learned a lot about pregnancy,
childbirth, and parenting from their program involvement.

The data for mean scores is presented in Table 6.

36

Tab e 6

Means eng §tandapds Deviation of Perceived Change Agent
Suecese Variabies

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

variable i R“ SD cases variable i R“ SD cases
contact 10.0 1-23 5.59 18 cred 9.79 3—12 2.80 19
orient 5.86 2—8 1.56 21 opinion 5.85 2-8 1.53 20
empathy 6.45 2-8 1.93 20 eval 8.95 3—12 2.67 21
cl needs 21 .82 8-32 5.77 17 8138 1.75 1-4 1. 12 20
social 2.45 0—20 3.42 20 ED 11.23 1-16 2.1 1 22
eosmop 10.95 219 3.1 1 22 PHB 36.22 '32-98 18.10 46
homoph 5.14 2-8 1.93 21 memotot 98.09 29- 167 22.02 1 1

 

 

* denotes possible range of scores.

Part-Whole Copparison

Preliminary analysis of the data revealed that certain
variables had a stronger positive correlation with the total
MEMO for MOMS score than others. For example, volunteer
credibility (items 17-19) and program compatibility with
client needs (items 8-9 and 25-30) had equally strong
positive correlations with the total score (r=.88, p.01).
Next, consistency of advice with the that of opinion leaders
(items 20-21) was strongly correlated with total score
(r=.85, p.01). Client ability to evaluate interventions
(items 22-24) was also strongly correlated with the total

score (r=.83, p.01). Perceived empathy (items 6-7) and

37

perceived homophily (items 15-16) also had strong
correlations with the total score (r=.82, p.01) and (r=.80,
,p=.01), respectively. Total contact was significantly
associated with the total score (r=.78, p.01). Client
orientation in interpersonal interaction (items 4-5) was also
associated with total score (r=.75, p.01).

Items that attempted to measure the four remaining
variables, education (years of school); socio-economic status
(insurance); social participation among clients (10-11); and
cosmopoliteness (12-14), were not significantly correlated
‘with total score. In addition, these variables were neither
significantly correlated with other variables in the
questionnaire nor with one another.

However, the data indicates that certain variables in
the questionnaire were strongly associated with others. For
example, client ability to learn from or evaluate the
innovation was strongly correlated with client-orientation in
interpersonal interaction (r=.83, p=.01). Other strong
positive correlations included: ability to learn/evaluate
and volunteer credibility (r=.81, p=.01); volunteer advice
consistent with that of opinion leaders and volunteer
credibility (r=.82, p=.01); volunteer credibility and client-
orientation in interpersonal interaction(r=.79, p=.01);
volunteer credibility and perceived empathy (r=.79, p=.01);
homophily and volunteer credibility (r=.77, p=.01); client

ability to learn/evaluate and program compatibility with

38

client needs (r=.72, p=.01); and homophily and client ability
to learn/ evaluate (r=.72, p=.01). The data on part-whole

comparison is presented in Table 7.

Table 7

Part-Whole Coeperison of MEMO f0; MOMS

 

 

 

 

 

 

 

dient- client opinion evaluate

contact orientation needs homophily credibility leaders (learn)
contact 1 (X) 54‘ 37 .37 65' 66" 65’ 64"
client-
orientation 54" 1.00 .37 .59' .50 .79‘ .56" .E‘
empathy l 37 37 If!) .66‘ .64' 79‘ .59“ .64“
client I
needs 37 59* .66“ MI) .68‘ .615" .49 .72'I
homophily 65* .50 64* .68“ 1.(X) .77' 73" .72“
credibility .66* .79: .79: .65" {77* 1.00 82* .81"
Opinion

 

.65“ .56" .56“ .49 .73* 82* 1.00 .66*

 

.64" .&* .64* .72" .72* .81 " .66“ 1-00

 

 

 

-.41 31 -.02 OZ -. 15 .20 -.O4 .00

 

—. 12 -.04 -.11 .02 -. 14 -.06 -.08 -.02

 

.01 .15 .21 -.09 -31 .23 .40 .27

 

 

 

 

 

 

 

 

 

 

.78" .75‘ .3: .88" H)" .89* 85* .83“

 

39

Table 7 (cont'd.)

 

 

 

 

 

 

 

 

 

 

 

 

 

To summarize the data in Table 7, significant
correlations existed between variables measuring perceived
change agent success. For example, volunteer credibility was
correlated with consistency of advice with opinion leaders
(r=.82, p.01), client ability to learn from levaluate
prenatal intervention (r=.81, p.01), client-orientation in
interpersonal interaction (r=.79, p.01), empathy (r=.79,
‘p.01), homophily (r=.77, p.01), and program compatibility
‘with client needs (r=.65, p.01). Client ability to learn
from levaluate prenatal intervention had strong positive
correlations with the same variables: Client-orientation in
interpersonal interaction (r=.83, p.01), program
compatibility with client needs (r=.72, p.01), homophily
(r=.72, p.01), credibility (r=.81, p.01), empathy (r=.64,
(p.01), and consistency of advice with opinion leaders (r=.66,
(p.01). Socio-economic status, education, cosmopoliteness,
and social participation among clients showed no significant

correlations with other variables.

40

ipgluepce e: Perceived Qhange Agent Success on PHB
Although the total MEMO for MOMS score was not

significantly associated with client PHB (r=.12), certain
variables were more strongly associated with PHB than others:
Social participation (“-56), consistency of advice with that
of opinion leaders (.40), and education (‘-39) were most
strongly correlated with PHB, although not at significant
levels. In addition, certain items in the questionnaire were

:moderately correlated with individual PHBs (see Table 8).

Table 8
Correlations eetyeen Scale Items and Client PHB

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

item neat-gain risk status
umkmmmh A6 50
«names .6” 37
fikmbfip 29 38
comforts 53 .51
hmndnm

‘ Nancy 31 .49
kmnflnm
parenting .44 31
mother agrees .62* .16
health habit -37 .68*
e p. 05

# includes medical risk as well as behavioral risk.
. coefficient cannot be computed.

41

As illustrated in Table 8, alcohol use has a moderate
negative correlation with level of perceived empathy
(understanding r=.62, p.05; reassure (r=-.49, p.05);
friendship (r=-.50, p.05); comfort (r=.-53, p.05); and
ability to learn about/evaluate interventions in pregnancy
(r=-52, p.05) and parenting (r=-.46, p.05). weight gain was
correlated with ability to reassure (r=.67, p.05) and advice
that agreed with that of the client's mother (r=.62, p.05).
Helping with a health habit was associated with risk status
(r=.68, p.05). These relationships will be explored in the
discussion section.

Up to this point, the analysis has focused on examining
significant correlations between variables. It is sometimes
helpful to take a closer look at the correlations that are
not significant. On a hunch that tobacco use should be more
strongly correlated with item 27 “help with a health habit"
(r=.32), the author decided to use a cross tab to examine the
relationship in greater detail. All seven respondents who
felt that their volunteer was ”not at all helpful" in helping
them change a health habit (i.e. smoking, drinking alcohol,
weight gain, or substance abuse), were non-smokers. The
relationships presented in Table 9 will be examined in the

discussion section.

42

Table 9
The Reiationship Between Tobacco Use and Health Habit

dgmaws

O
10
20

 

Responses to item 31 were anecdotal, and thus varied
widely. Of the 14 respondents who answered item 31, seven
made positive statements about the MOMS program, one made a
negative statement about her volunteer partner, and six said
that they would like to have had more contact with their MOMS

partner.

DISCUSSION

Limitations of the Study

Along with any study that cannot control the total
environment and its actors, there are certain limitations of
this research that must be acknowledged. One directly
relates to the results not being generalizable outside the
program population. Although the demographic characteristics
of the program participants are roughly comparable to the
state-wide population of low-income pregnant women,
enrollment in the program is voluntary. Thus, the population
under study may have different perceptions of the benefits
involved with a social support prenatal program than the
larger clinic population.

A second limitation of this study lies in the
descriptive nature of the research. Because the methodology
is primarily qualitative, the MEMO for MOMS is neither
reliable nor valid as a tested measure of change agent
success. To this end, the data must be interpreted with
caution. Although the original intent of this research was
to create an instrument to measure the construct of change
agent success, the research design may have precluded the

verification of this condition.

43

44

As previously stated, because of time constraints, the
study is cross-sectional, rather than longitudinal. Second,
the questionnaire was not pro-tested for three reasons: to
begin with, the number of the program participants was small
(n=72) and the probability great that the sample size was
too small to attain a sufficient level of statistical power
in order to reject the null hypothesis in an untested 30-item
questionnaire (Lipsey, 1990). Further, the characteristics
of the program participants were not represented in the
general population, so it was not practical to administer the
pretest to a group of undergraduate students. Finally,
program coordinators recognized that clients in the MOMS
parent-to-parent-support program do not have an easy time
‘with filling out lengthy program evaluations: Administering
the questionnaire to the program participants through the
mail on consecutive days would not have encouraged a high
rate of return.

The study is also limited in that the response rate was
very low (33%). The rate of return precluded an inter-
volunteer rating that would have tested the hypothesis that
total MEMO f0; MOMS scores vary between volunteers. Further
research should focus on demographic characteristics of
respondents and clients who failed to return the
questionnaire, as well as alternate methods for collecting

data from hard-to-reach clients.

45

Finally, the study is limited in the way that the
questionnaire responses were coded. Specifically, all items
were not weighted equally. This discrepancy in coding scheme

allowed certain variables to have a greater impact on the

total MEMO go; MQM§ and PHB scores than others.
Mxemining Relatiopehipe in the Part-Whole Comparison

It can be helpful to take a closer look at three
relationships in the part-whole comparison: the relative
mean scores of each variable in the questionnaire; the
correlations between variables and total score; and the
associations between variables. By examining these
relationships, we can reach a clearer understanding of what
it means to measure perceived change agent success.

According to the data in Table 6, clients perceived that
volunteers had high levels of credibility, empathy, client
orientation in interpersonal interaction, advice congruent
‘with that of opinion leaders, and the ability to implement
program goals compatible with client needs. Clients also
reported that they had learned a lot about pregnancy,
childbirth, and parenting from their program involvement.
This finding indicate that these variables may measure
valuable skills that volunteers exercise in their interaction
with clients.

Analysis of the data in Teple 7 indicated that certain
variables had a stronger positive correlation with the total
MEMO for MOMS score than others. These variables include

volunteer credibility, program.eompatibility with client

46

needs, consistency of advice with the that of opinion
leaders, client ability to evaluate interventions, perceived
empathy, perceived homophily, total contact, and client
orientation in interpersonal interaction. These variables
may be strongest predictors of perceived change agent success
because they are contingent upon volunteer performance. In
contrast, items that attempted to measure education, socio-
economic status, social participation among clients, and
cosmopoliteness were client-specific, and thus not
significant predictors of total score.

The data in Table 7 suggest significant correlations
existed between variables measuring perceived change agent
success. velunteer credibility and client ability to learn
from levaluate prenatal interventions were strongly
correlated with one another. Both variables were also
correlated with consistency of advice with opinion leaders,
client-orientation in interpersonal interaction, empathy,
homophily, and program compatibility with client needs.

One interpretation of these data would be to suggest
that volunteers are perceived to be highly credible if they
are perceived to be consistent with opinion leaders, client-
oriented, empathetic, homophilous, and responsive to client
needs. In turn, perhaps clients learn more if they perceive

their volunteers to be credible sources of information.

47

Inter-I Ana sis 0 Per e'ved Ch e A ent uccess and PHB
Data from Table 7 indicate that this study failed to
reject the null hypothesis. Total level of client PHB was
not significantly associated with MEMQ ior MOMS score or
perceived change agent success variables. One must question
whether the MEMQ_ie;_MQM§ scale is actually measuring
perceived change agent success; further, is perceived change
agent success related to PHB? It is possible that missing
data prevents us from answering these questions: The
correlation between PHB and memotot was calculated from 11
cases; associations between PHB and MEMO for MOMS variables
were drawn from only eight cases. More often than not,
incomplete birth certificate information or unanswered
questionnaire items left a gap in the data set; this missing
data stops us from drawing valid conclusions about the
relationship between the MEMO for MOMS scale and PHB.
However, as illustrated by the data in Table 8, several
items attempting to measure perceived change agent success
variables are associated with client PHB. Items six
(understands problems), seven (reassures), eight
(friendship), nine (comfort), 22 (learn about pregnancy), and
24 (learn about parenting) are negatively correlated with
alcohol use. Items seven (reassures) and 20 (mom agrees with
advice) are correlated with adequate weight gain in
pregnancy. These correlations could be interpreted to mean
that a volunteer's mentoring and teaching have a positive

effect on client PHB.

48

Item 27 (help with a health habit) is associated with
total risk score. This may mean that women most at risk are
more likely to value the advice that a volunteer gives about
changing a health habit. One must note here that the total
risk score includes medical variables as well as lifestyle
variables. These medical risk factors may act as confounding
variables to inflate the total risk score: in reality, women
who score high on item 27 (health habit) may not be at high
risk for lifestyle variables. Instead, it may be their level
of.medica1 risk that leads them to value their volunteer's
advice about health habits.

One surprising finding was the absence of a significant
correlation between item 27 “help with a health habit" and
tobacco use in the client population (r=32, p.14). A closer
examination of the data (see Table 9) indicates that this
association may be misleading because of a flaw in instrument
design: that is, of the eight respondents who answered 1)
"not at all" to the health habit question, seven were non-
smokers. These non-smokers may have answered that they did
not value their volunteer's ability to help them with a
health habit because the question did not apply to them-

This finding argues persuasively for greater use of
discretion in selecting item response options.

Finally, responses to open-ended question 31 indicate
that clients generally viewed the program in a favorable
light, describing volunteer partners as "wonderful",

“helpful", “understanding", or “great". Most respondents

49

indicated that they would have liked to have had more contact
‘with their volunteer, either during their pregnancy or after
giving birth. Travel distance, length of time in the
program, and end of program involvement soon after pregnancy
were all cited as factors contributing to 'insufficient
contact'. In one client's words, "I really needed a support
person to talk to. I was alone 18 hours a day and afraid.

My baby is now 16 months old and I still could use someone
with a baby to talk to." This anecdotal evidence suggests
that most clients in the MOMS program, especially mothers who
are socially isolated, might profit from more frequent

contact with their volunteer support parents.

CONCLUSIONS

This preliminary investigation, while primarily
descriptive in nature, could be the foundation for a more in-
depth study of perceived change agent success in prenatal
health promotion programs. As previously stated in the
section pertaining to study limitations, a larger, more
representive sample might increase the generalizability of
the findings as well the statistical power of the MEMO for
MQM§ scale. A longitudinal research design with a pretest,
T1, and T2 data would also strenghten the scientific merit of
this study. Alternative methods for collecting data should
also be explored because mailed self-administered
questionnaires did not have a high rate of return. One
option to increase the survey response rate might be to
engage clients in face-to-face interviews six weeks after
program entry and again at time of program completion. In
addition, any data missing from individual items in the
questionnaires could be filled in by entering the mean
response for each item across all respondents. This
procedure would increase the total number of cases for

correlational analysis.

50

51

As mentioned in the discussion section, more careful
selection of item response options, coding, and indexing
schemes could increase the future probability of rejecting
the null hypothesis. To this end, “does not apply" could be
included as a response option for items 26 and 27. In
addition, careful indexing could ensure that all variables
are weighted equally.

When creating a new scoring index for the dependent
variable, items measuring PHB could be assigned values
ranging from 1-3, depending on whether the behavior was
optimal, acceptable, or unacceptable: Obstetric guidelines
suggest that for the number of prenatal visits, an optimal
range would be considered 10-14; for weight gain, 24-35 lbs.
would be optimal; for alcohol, tobacco, and cocaine, an
optimal level would be zero usage. Optimal levels would be
assigned a value of three points. For all items, acceptable
levels would receive two points, and unacceptable levels
would receive one point. Thus, the PHB scale's possible
range would change from the current '32-98 to 5-15: The
higher the score, the higher the client level of PHB. This
method of coding would ensure that each item has an equal
impact on total PHB level.

For the independent variable, or 'memotot', creating a
new index would also ensure that each variable would have the
same potential to impact the total score. For example, the
variable 'client needs' is represented by eight items in the

questionnaire, and 'client orientation' has only two. Each

52

item currently has a possible range of 1-4, so clients can
receive 32 points for 'client needs' and 8 points for ‘client
orientation'. A new index would allow four points as the
maximum score for each variable: Thus, a client who scored
six points on 'client orientation' would receive three
points; one who scored 25 points on 'client needs' would
also receive three points. According to this method of
indexing, the possible range for 'memotot' would change from
29-167 to 12-48.

In a more refined version of the MEMO for MOMS, it might
also be advisable to exclude items that attempt to measure
cosmopoliteness and social participation among clients in the
prenatal support program. The inclusion of these variables
in the questionnaire may be an example of a reality
isomorphism that occurs when theory does not always fit well
with the constraints of practice: Diffusion Theory has most
frequently been used for evaluating innovations in developing
nations. There, perhaps cosmopoliteness and social
participation are major factors in client ability to adopt
innovations. In the context of an American prenatal health
innovation, cosmopoliteness and social participation could be
replaced with more culture-specific variables: for example,
'exposure to prenatal health promotion through mass media'
and 'strength/size of social networks'. To this end, future
research in the field of the diffusion of prenatal
innovations should tailor Diffusion Theory to evaluate health

promotion programs in a culturally-sensitive manner.

APPENDICES

APPENDIX A

STUDY EXPLANATION

April 15,1992

Dear MOMS partner:

At this time, we would like to ask you to participate in a MOMS program evaluation.
This means that we need you to complete two short questionnaires that tell us how you
feel about the MOMS program. The questions are designed to describe your experience
in the MOMS program, as well as the relationship that exists between you and your
MOMS partner. This information will help us keep the program sensitive to the needs
and concerns of program participants.

It is important for you to be aware that all research questionnaires will be given a code
number and that your identity will be kept confidential. Your role as a MOMS partner
will not be jeopardized if you choose not to participate in the evaluation. If you have any
questions about the consent or evaluation process, please feel free to give us a call at
Michigan State University (517) 353-6617 or Butterworth Hospital (616) 732-2627.

We have tried to keep these surveys as short as possible, and feel that it should not take
you very much time to complete them. We would appreciate your efforts to fill out the
questionnaires and return them in the stamped, self -addressed envelope as soon as

possible. Thanks for considering our request for additional information. We need your
help to make our program and community a better place.

Sincerely,

Lee Anne Roman, RN, PhD. Judy Lindsay, R.N., M.A.

Joe Moore, MD.

Program Research Staff

53

APPENDIX B

INFORMED CONSENT FORM

NAME:

 

I understand that Butterworth Hospital is conducting a study about the MOMS Parent-to-
Parent Support Program. This research is being directed by Judy Ferdi g, Dr. Joseph
Moore, Dr. Lee Anne Roman, and Marcy Meyer of Butterworth Hospital and the Institute
of Children, Youth, and Families at Michigan State University.

I understand that information I gave on the MEMO for MOMS questionnaire may be
released to project staff in order to be included in a descriptive study of MOMS clients.

I understand that a record may be kept of information that I share verbally or in writing
with the MOMS program nurses about my concerns and feelings about my role as a
MOMS client, unless I specify that a particular segment of information may not be used

for study purposes.

I understand that all information that I give will be treated CONFIDENTIALLY and that
my name will NOT appear on any written records or reports.

This project has been explained to me and I understand the explanation given.

I understand that I am under N0 obligation to participate in this study, and that if I
choose NOT to participate, this will not affect my involvement in the MOMS program at
Butterworth Hospital.

I understand that I am free to discontinue my participation in the study at any time
WITHOUT penalty from Butterworth Hospital or project stafT. I also understand that I
may refuse to answer any question asked of me.

I understand that, at my request, I can receive a summary of research findings of this
project after my participation is completed.

SIGNED(Mother) DATE

SIGNED DATE
(Parent's signature if under 18 years of age)

SIGNED (Witness) DATE

54

APPENDIX C

Code #:
Date:

MEMO for MOMS

This is a short survey that will tell us how you feel about the MOMS program.
You and your baby are very important. We need your feedback to make our program and
community a better place. In addition to circling the best answer for each question, feel
free to say what you truly feel... we need to know what you think. Your name won't be
on this paper. So, answer this the best you can, and know that we welcome your opinions
and answers to any questions we forgot to ask (please put additional comments at the
end). Thanks for your help.

1) How many times a month does your MOMS partner call you on the telephone?
0 1 2 3 4 5 6 7 8 10 or more

2) How many times a month do you see your MOMS partner?

0 1 2 3 4 5 6 7 8 10 or more

3) How do you feel about the frequency of your contact?

NOT ENOUGH JUST ABOUT RIGHT TOO MUCH
(1) (3) (2)

4) How well does your MOMS partner listen to you when you need someone to talk to?

VERY WELL QUITE WELL SOMEWI-IAT WELL NOT AT ALL WELL
(4) (3) (2) (1)

5) How often does your MOMS partner ask you what you think about the MOMS
program?

OFTEN SOMETIMES SEIDOM NEVER
(4) (3) (2) (l)

6) When you're having a problem, how often do you think that your MOMS partner
understands what you're going through?

USUALLY SOMETIMES SELDOM NEVER
(4) (3) (2) (1)

55

56

7) How much does your MOMS partner reassure you by sharing experiences when you
feel anxious about your pregnancy?

A LOT SOMEW HAT A LITTLE NOT AT ALL
(4) (3) (2) (1)

8) How much do you value your friendship with your MOMS partner?

A LOT SOMEW HAT A LITTLE NOT AT ALL
(4) (3) (2) (1)

9) How much does your MOMS partner comfort you when you feel stressed out?

A LOT SOMEWHAT A LITTLE NOT AT ALL
(4) (3) (2) (1)

10) How many times a week do you talk with another woman in the MOMS program?
0 1 2 3 4 5 6 7 8 10 or more
1 1) How many mothers have you met through the MOMS program?
0 l 2 3 4 5 6 7 8 10 or more
12) How often do you travel out of your neighborhood?

OFTEN SOMETIMES SELDOM NEVER
(4) (3) (2) (1)

13) How many minutes per day do you read magazines or newspaper?

NONE A FEW MINUTES 15 MINUTES 1/2 HOUR 1 HOUR OR MORE
14) How many hours a day do you watch TV?

0 l 2 3 4 5 6 7 8 10 or more

15) How much do you and your MOMS partner have in common?

A LOT SOMEWHAT A LITTLE NOT AT ALL
(4) (3) (2) (l)

16) How much do you and your MOMS partner think alike ?

A LOT SOMEWHAT A LITTLE NOT AT ALL
(4) (3) (2) (1)

17) How much do you value the advice your MOMS partner gives you about your
pregnancy?

A LOT SOMEW HAT A LITTLE NOT AT ALL
(4) (3) (2) (1)

57

18) How much do you value the advice your MOMS partner gives you about taking care
of your baby?

A LOT SOMEWHAT A LITTLE NOT AT ALL
(4) (3) (2) (1)

19) How much trust do you have in your MOMS partner?

A LOT SOMEWHAT A LITTLE NOT AT ALL
(4) (3) (2) (1)

20) How much does your mother‘s advice agree with the advice your MOMS partner
' gives you about your pregnancy?

A LOT SOMEWHAT A LITTLE NOT AT ALL
(4) (3) (2) (1)

21) How much does your best friend's advice agree with the advice your MOMS partner
gives you about your pregnancy?

A LOT SOMEWHAT A LITTLE NOT AT ALL
(4) (3) (2) ( 1)

22) How much have you learned about pregnancy from your MOMS partner?

A LOT SOMEWHAT A LITTLE NOT AT ALL
(4) (3) (2) (1)

23) How much have you learned about childbirth from your MOMS partner?

A LOT SOMEWHAT A LITTLE NOT AT ALL
(4) (3) (2) (1)

24) How much have you learned about taking care of your baby from your MOMS
partner?

A LOT SOMEWHAT A LITTLE NOT AT ALL
(4) (3) (2) ( 1)

25) How much has your MOMS partner encouraged you to go back to school or GED
classes?

A LOT SOMEWHAT A LITTLE NOT AT ALL
(4) (3) (2) (1)

26) If you have children, how often has your MOMS partner assisted you to arrange
child care for your child or children?

OFTEN SOMETIMES SELDOM NEVER
(4) (3) 2) (1)

27) How helpful has your MOMS partner been in helping you change a health habit?
(for example, smoking, alcohol, drugs, eating too much or too little)

VERY HELPFUL QUITE HELPFUL SOMEWHAT HELPFUL NOT AT ALL HELPFUL
(4) (3) (2) (1)

58

28) How much has your MOMS partner taught you about different birth control
methods?

A LOT SOMEWHAT A LITTLE NOT AT ALL
(4) (3) (2) (1)

29) How well does your MOMS partner help "cut red tape" for you or your family when
you need support services or medical referrals?

VERY WELL QUITE WELL SOMEWHAT WELL NOT AT ALL WELL
(4) (3) (2) (l)

30) How much has your MOMS partner helped you set some goals for your future?

A LOT SOMEWHAT A LITTLE NOT AT ALL
(4) (3) (2) (1)

31) Please add any thoughts you would like to share about the program in the space below.

APPENDIX D

MICHIGAN STATE UNIVERSITY

 

OFFICE 0! VICE PRESIDENT FOR RESEARCH EAST UNSING 0 MICHIGAN 0 40824-1046
AND DEAN Of THE GRADUATE SCHOOL

April 5. 1993

TO: Ms. Marcy Meyer
1312-1 University Village
East Lansing. MI 48823

RE: . [RB 4‘: 93-137
TITLE: BUTTERWORTI-I HOSPITAL MOMS PROGRAM EVALUATION
REVISION REQUESTED: NIA
CATEGORY: l-C
APPROVAL DATE: 04/01/1993

The University Committee on Research Involving Hm Subject! (UCRII-IS) review of this project is complete.
Impiasedtoadvisethsttherighuandwelfareofthehumnrbjeeuappartobeadcqmtelyprotectedand
methodstoobuininfomedconuntmappmpriste. MemmeUCRIHSspprovedthisprojectineludingany
revisionlistedebove.

UCRHISappmvduvdidfuoualndnryar.beginMngwithdreeppmvddmshownahove Investigates
planningtocontinueapmjectbeyondoneyenrnntseekupduedeutificndon. Reqtnetforrenewedapprovalnmst
beeccompeniedbyallfourofthefollowingmnduorym

1. Ibhumsubjocuprotoeolisthemneuinprwiomm

2. Memebeumiueflecuwfferedbythembjmduwthdrpuficipdmmdnmdy.

3. mmuummmwmmumwummurmammm
study.

4. Mhumtbeenschmgemmemanhmvimmrmmmwhiehwwmgm
nskmhummbjecnmmthumnedwhendnpmmolwininanymiewedmdsppmd.

Thereisannximumoffourarchespeditedrenswalspodble. Investigatonwishingtoeonnnueeprojeetbeyond
duttirncneedtosubmititagsin foreonrpletereview.

UCRIHS ”Way changes inproeednruinvolvinghummbjects. priortoininationofthechlnge.
Investiguorsnnrstnotify UCRIHS pmnrptlyofanyproblemsiuexpecudsideeMcomphinu. etc.) Involving
humnnrbjeetsduringtheconneofthework.

Ifwe can be of my future help. please do not hedtnte to contact us at ($17) 355-2180 or FAX (517) 336-1171.

' I—

Sincerely.

 

David a. warm. PILD.
ucruns Chair

05‘":ij
cc: Ms. Judy Lindsey

Dr.JoeephMoore
Dr.l..eeAnnsRonnn

MSU a on Alflrnume Amen/Equal Omrnwn Immuta-

s9

60

3533
February 22, 1993 Euggenmm

Joseph Moore, M.D.

Butterworth Hospital

100 Michigan, NE

Grand Rapids. MI 49503

Dear Dr. Moore:

By means of the expedited review process, the Butterworth Hospital Research and
Human Rights Committee has given approval to the amendment of your study
'Providing Social Support in High Risk Mothers and Infants: Prenatal Positive
Parenting' (90-20). 'I‘hisamendmentdalswithaprogram followupevslustion
questionnairetobegiventothesurdypsttieipsnts.

The Human Rights Committee and the F.D.A. requires you arbmit in writing, a
progressreporttothecommitteebyianusry 1, l994mdyouwillneedrupprrml
should your study be ongoing at that time.
IfyouhsveanyquestionsplaseplmmeorlindsPoolatfl4-1291.

Thank you.

Sincerely,

saw

Jeffrey S. Jones, M.D.
Co—Chairperson. Butterworth Hospital Recesrch and Human Rights Committee
. ISJijn

c: Judy Lindsay

"‘7 ""1"" 5"?!" ‘-F "rm 340-“ “tn-w 495012560 to» are. ":1": “-41“. were

APPENDIX E

 

 

variable

item

value

 

 

SSSGSSS°°°"°‘”§.

i—i—N—t—HHNu—wwng
'<

momonth

frequenc

~qo~4>uuo

WMbWN—O

DONU—

 

 

orient

mxlO‘UIN

HWUIUIN

malisten

whathink

«hWNI—

bWNr—b

NN \O—fl I-t—UJ‘FN—‘ch ##H‘BWNU-ig
‘<

_

Wv—WN i-‘N
O

 

 

 

 

WQO‘MtfiN

 

WUINNt—N

 

10.0
5.0

10.0
10.0
25.0
40.0

 

 

maunders

reassure

 

hw—

kNN—e

 

N
'54:-

\IUIUJN

 

1 1.8
17.6
29.4
41.2

 

 

61

 

 

 

 

variable value frequency percent item value frequency percent
c1.needs 8 1 5.9 friaidsh l 3 17.6
16 2 1 1.8 3 3 17.6
18 2 11.8 4 1 1 64.7
20 1 5.9
21 2 1 1.8 comfort 1 2 l 1.8
22 1 5.9 2 2 1 1.8
23 2 1 1.8 3 2 1 1.8
24 1 5.9 4 l 1 64.7
25 l 5.9

27 2 1 1.8 encsehl 1 6 37.5
31 2 11.8 2 3 18.8
3 2 12.5
4 5 313
chilcare 1 9 60.0

2 l 6.7
3 2 133
4 3 20.0
helphlth 1 8 533

2 l 6.7
3 3 20.0
4 3 20.0
birthcont 1 6 353
2 7 41.2

3 1 5.9
4 3 17.6
mred tape 1 4 25.0
2 4 25.0
3 4 25.0
4 4 25.0
setgoals 1 3 18.8
2 3 18.8
3 6 37 .5
4 4 25.0

 

 

 

 

 

 

 

 

 

 

63

 

 

 

 

 

variable value frequency percent item value frequency percent
social 0 8 40.0 talk othr 0 14 82.4
1 4 20.0 2 1 5.9
2 3 15.0 3 l 5.9
5 1 5.0 5 l 5.9
6 l 5.0
8 1 5.0 othrmoms 0 6 353
9 1 5.0 1 6 353
1 1 1 5.0 2 2 11.8
5 2 l 1.8
7 1 5.9
cosmop 5 l 45 travel 1 l 5.6
7 3 13.6 2 2 l 1.1
8 l 45 3 3 16.7
9 3 13.6 4 12 66.71
10 l 45
l l 4 18.2 reachews 1 1 5.6
13 5 22.7 2 5 27.8
14 1 45 3 2 1 1.1
15 2 9.1 4 5 27 .8
17 1 45 5 5 27 .8
watch tv 0 l 5.6
l 1 5.6
2 2 l 1.1
3 3 16.7
4 2 l 1. l
5 4 22.2
6 2 l 1.1
7 1 5.6
8 2 1 1.1
homo 2 3 143 incornmon 1 4 23.5
3 1 4.8 2 5 29.4
4 3 143 3 5 29.4
5 5 23.8 4 3 l7 .6
6 5 23.8
8 4 19.0 thinksame l 3 17 .6
2 5 29.4
3 6 35.3
4 3 17.6

 

 

 

 

 

 

 

 

 

 

64

 

 

 

 

 

 

 

variable value frequency percent item value frequency percent
cred 3 1 53 advpreg 1 l 6.7
4 1 53 2 2 133
7 2 10.5 3 4 26.7
8 1 53 4 8 533
9 1 53
10 3 15.8 advcare 1 2 12.5
1 1 2 10.5 2 1 63
12 8 42.1 3 3 18.8
4 10 62.5
trust 1 3 17.6
2 1 5.9
3 5 29.4
4 8 47.1
opinion 2 1 5.0 agreemom 1 1 63
4 2 10.0 2 5 313
5 5 25.0 3 6 37.5
6 5 25.0 4 4 25.0
7 4 20.0
8 3 15.0 agreefrnd 1 1 63
2 4 25.0
3 6 37 .5
4 5 31.3
eval/learn 3 1 4.8 lrnpreg 1 2 11.8
4 2 95 2 2 1 1.8
7 2 9.5 3 5 29.4
8 1 4.8 4 8 47 . 1
9 6 28.6
10 1 4.8 lrnbirth 1 2 l 1.8
1 l 5 3.8 2 4 3.5
12 3 143 3 5 29.4
4 6 353
lrncare 1 3 17.6
2 1 5.9
3 7 41.2
4 6 35.3
SES 1 13 65.0
2 1 5.0
3 4 20.0
4 2 10.0
ED 3 1 4.5
10 4 18.2
1 1 4 18.2
12 10 45.5
13 2 9.1
14 1 4.5

 

 

65

 

 

 

variable value frequency percent item value frequency percent
PHB 5 1 2.2 pprenat l 1 13
7 1 2.2 4 3 4.0
10 1 2.2 5 2 2.7
1 1 1 2.2 7 2 2.7
14 2 43 8 5 6.7
16 2 43 9 3 4.0
18 1 2.2 10 8 10.7
19 1 2.2 1 1 6 8.0
20 l 2.2 12 10 133
24 3 65 13 6 8.0
27 2 43 14 9 12.0
29 2 43 15 13 173
30 l 2.2 16 3 4.0
34 2 43 19 1 13
37 2 43 20 l 13
38 1 2.2 24 1 13
39 2 43 26 l 13
40 l 2.2
41 3 65 lbgain 10 l 2.1
42 2 43 1 1 l 2.1
43 1 2.2 12 1 2.1
44 1 2.2 14 5 10.4
45 2 43 15 3 63
49 l 2.2 17 1 2.1
52 1 2.2 19 l 2.1
55 1 2.2 20 2 4.2
58 l 2.2 21 1 2.1
60 2 43 22 1 2.1
63 1 2.2 3 1 2.1
66 l 2.2 24 5 10.4
70 l 2.2 25 1 2.1
87 l 2.2 26 l 2.1
27 1 2.1
30 3 63
32 2 4.2
33 3 63
35 1 2.1
36 1 2.1
40 3 63
42 l 2.1
45 2 4.2
49 1 2.1
50 3 63
55 1 2.1
72 1 2.1

 

 

 

 

 

 

 

 

 

 

66

 

 

 

 

variable value frequency percent item value frequency percent

tobacco 0 50 69.4

1 1 1.4

2 1 1.4

5 1 1.4

6 1 1.4

10 9 12.5

12 1 1.4

15 1 1.4

20 6 83

40 l 1.4

alcohol 0 67 93.1

1 3 4.2

2 2 2.8

cocaine 0 69 97.2

1 2 2.8
memotot 46 1 9.1
82 l 9.1
87 1 9.1
93 1 9.1
96 1 9.1
102 1 9.1
103 l 9.1
109 1 9.1
114 l 9.1
121 1 9.1
126 1 9.1

 

 

 

 

 

 

 

 

 

 

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LIST OF REFERENCES

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Amezcua, C., McAlister, A., Ramirez, A., and Espinoza, R.
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Berkman, L. (1984). Assessing the Physical Health Effects of
Social networks and Social Support. Ann Rev Public
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Braithwaite, R., and Lythcott, N. (1989). Community
Organization and Development for Health Promotion Within
an Urban Black Community: A Conceptual Model. Health
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Broadhead, W., Kaplan, B., James, S., et al. (1983). The
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Support and Health. American Jougppl of Epidemiology,
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Chamberlain, R. (1987). Beyond Individual Risk Assessment:

Community Wide Approaches to Promoting the Health and
Development of Families and Children. Washington, DC:
The National Center for Education in Maternal and Child
Health.

Collins, J. and David, R. (1990). The Differential Effect of
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Committee for the Study of the Future of Public Health.
(1988). The Future of Public Health. washington, DC:
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Devellis, R. (1991). Scale Development: Theopy and
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Eng, E., Salmon, E., and Mullan, F. (1992). Community

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Community Health, 15, 1—12.

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68

Goeppinger, J., Lassiter, P., and Wilcox, B. (1982).
Community Health is Community Competence. Nursing
Outlook, 30, 464-467.

Giblin, P., Poland, M., and Ager, J. (1990). Effects of
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Green, L., and Raeburn, J. (1990). Contemporary Developments
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