Extra-team connections for knowledge transfer between
Shoba Ramanadhan1,3*, Jean L. Wiecha2, Karen M. Emmons1, Steven
L. Gortmaker1and Kasisomayajula Viswanath1
As organizations implement novel health promo-
challenges related to knowledge management.
Staff social networks may be a useful medium
for transferring program-related knowledge in
multi-site implementation efforts. To study this
potential, we focused on the role of extra-team
connections (ties between staff members based in
different site teams) as potential channels for
knowledge sharing. Data come from a cross-sec-
tional study of afterschool childcare staff imple-
menting a health promotion programat 20 urban
sites of the Young Men’s Christian Association of
Greater Boston. We conducted a sociometric so-
cial network analysis and attempted a census of
91 program staff members. We surveyed 80 indi-
staff, who lead and support implementation, re-
spectively, in this study. A multiple linear regres-
sion model demonstrated a positive relationship
between extra-team connections (b 5 3.41, P <
0.0001) and skill receipt, a measure of knowledge
transfer. We also found that intra-team connec-
tions (within-team ties between staff members)
were also positively related to skill receipt. Con-
nections between teams appear to support knowl-
edge transfer in this network, but likely require
greater active facilitation, perhaps via organiza-
tional changes. Further research on extra-team
connections and knowledge transfer in low-
resource, high turnover environments is needed.
Institutions that address the needs of children and
youth, such as schools and afterschool childcare pro-
programs [1, 2]. Afterschool programs show great
promise for disseminating such programs given their
mission, a structure that supports program delivery
, and their reach of ;6.5 million children served
annually in the United States . Yet, a major chal-
programs is the implementation stage, in which
organizations incorporate and scale up programs
[5, 6]. Many barriers to implementation are organi-
for incorporation of a new program or way of work
across multiple sites . According to the Institute
for Healthcare Improvement , the spread of new
practices within an organization, or internal spread,
can be facilitated by a range of organizational sup-
ports, including: targeted leadership responsibilities,
identification of improved ideas, strong communica-
tion and social systems, a monitoring system and
effective knowledge management. In this study, we
focus on two of these supports: knowledge manage-
ment and communication/social systems.
1Department of Society, Human Development and Health
and2Harvard Prevention Research Center, Harvard School
of Public Health, 677 Huntington Avenue, 7th Floor, Boston,
MA 02115, USA
*Correspondence to: Shoba Ramanadhan. E-mail:
3Present address: Yale School of Public Health, 60 College
Street, PO Box 208034, New Haven, CT 06520-8034, USA.
? The Author 2009. Published by Oxford University Press. All rights reserved.
For permissions, please email: email@example.com
HEALTH EDUCATION RESEARCHVol.24 no.6 2009
Advance Access publication 15 June 2009
Knowledge management is a key driver of imple-
mentation processes as the spread of knowledge
between and within sites allows for faithful and
sustainable implementation of the program of in-
terest [8, 9]. As conceptualized by Nonaka and
Takeuchi [10, 11], knowledge can be categorized
as either explicit or tacit. The former can be com-
municated formally, e.g. in manuals, and expresses
the ‘what’ of implementation. Yet, much value and
competitive advantage comes from spreading tacit
knowledge, which focuses on the ‘why’ and ‘how’
of implementation. A comprehensive review of
implementation in health promotion programs by
Fixsen et al.  found that great strength for sup-
porting implementation comes in the form of
spreading tacit knowledge relating to the program.
This knowledge is context specific, difficult to sys-
tematize and depends on connections actively fos-
tered between staff members and experts within and
outside the organization, as well as with the target
Communication and social systems are crucial
for spread of innovations as they serve as channels
for the spread of information. We can understand
these systems as social networks that impact diffu-
sion and dissemination of programs, as exemplified
by the work of Rogers  and more recently
Greenhalgh et al. . The staff social network, or
the web of relationships among employees ,
provides channels for exchange of resources among
individuals and teams, including the spread of in-
novative ideas among staff. The number and quality
of staff members’ contacts have been linked with
individual and team performance . In the case
of multi-site implementation, the staff network
serves multiple functions, including supporting
training efforts and also allowing for spread of
best practices and internally developed knowledge
and adaptations. Here, we assess the ability of the
staff social network to spread tacit program-related
knowledge. Examples include transfer of key adap-
tations or results of experimentation and findings
that result from revisiting base assumptions .
Using the Fixsen model , we see improvement
of the practitioner knowledge base to be a key
implementation outcome. Other outcomes include
practitioner knowledge and skills, changes in the
organizational structure to support practitioner be-
havior change and changes in relationships with
important partners, such as consumers or systems
partners. This model also includes intervention out-
comes, changes in target audience behavior and
health outcomes. In previous work , we found
that the staff network may support formal training
efforts by provide informal training opportunities.
Specifically, we found that the number of connec-
tions reported to colleagues was linked with reports
of learning program-related skills. Here, we extend
the analysis to focus on a subset of staff connections
that may be useful for knowledge transfer between
site-based implementation teams. Though network
analysis is an established field, applications to
health promotion and prevention can be greatly in-
creased [17, 18]; additionally most studies focus on
interactions between interdisciplinary teams, not
those engaging in the same work in multiple loca-
tions . This study contributes to the literature by
assessing ways to utilize an existing resource, the
staff social network, to support health promotion
program spread across multiple sites of the same
Extra-team connections for knowledge
Given that implementation of innovative programs
across multiple sites relies on knowledge sharing
between site teams , we were interested in con-
nections that exist in networks outside of site teams,
but within the organization, referred to here as
tions, the team is often the functional unit of interest
for afterschool childcare programs . Extra-team
connections result in improved team performance
 as team members acquire diverse, novel knowl-
edge to meet their goals [19, 22]. Though extra-
team connections may extract a cost in terms of
attention and time spent managing relationships
[20, 23], they appear to be an important long-term
investment . Key organizational barriers to
knowledge transfer between teams are lack of sup-
port or reward for such transfer and lack of a system
by which to share knowledge . Extra-team
S. Ramanadhan et al.
connections serve as an important complement to
‘intra-team connections’, or connections among
members of the same team, which benefit produc-
tivity  by building alignment of group actions
with common goals .
In this analysis, we studied the role of extra-team
connections for knowledge transfer between after-
school childcare sites of the Young Men’s Christian
Association (YMCA) of Greater Boston implement-
ing a novel health promotion program. The YMCA
provides a useful example given that the organiza-
tion isfocusing on effective knowledge management
as part of a movement toward becoming a learning
organization . The goals of this study were to: (i)
characterize the distribution of extra-team connec-
tions in a network of staff engaged in multi-site
implementation of a novel program and (ii) describe
the relationship between these connections and
a marker of knowledge transfer.
Setting and design
In 2005, the YMCA of Greater Boston invited 24 of
37 urban afterschool sites to participate in a 3-year
health promotion project funded by US Department
of Education’s Carol White Physical Education
Program. The sites were chosen by YMCA man-
agement based on past success with delivery of
novel curricula and programs. Approximately 700
children attended these programs; roughly 70% of
whom received need-based financial assistance.
The racial/ethnic makeup of the population of chil-
dren served was estimated as: 45% White, 37%
African-American, 15% Hispanic/Latino and 3%
Asian/Pacific Islander or Other .
In the fall of 2005, the 24 sites began to imple-
ment the iPLAY program, a set of health promotion
and organizational changes guided by the YMCA
of the USA and the Institute for Healthcare Im-
provement Breakthrough Series model , with
evaluation assistance from scientists at the Harvard
School of Public Health. The program targeted
improvements in (i) physical activity, (ii) nutrition,
(iii) connections between staff and children and
parents/guardians and (iv) screen time (time spent
with television and videos). Staff were also charged
with using experimentation and data-driven decision
making to identify best practices for implementa-
tion within and across teams. Thus, communication
and spread of ideas between teams was an explicit
goal for implementation.
Quarterly mandatory training sessions were de-
livered to coordinators from each site, who were
expected to share information with other coordina-
tors, as well as colleagues at their sites. Training
and technical assistance were provided by the pro-
gram director, the individual hired to support
iPLAY program implementation during the 3-year
grant period. For this study, staff reported on their
personal characteristics and professional relation-
ships with colleagues in November and December
2007 using a self-administered survey. The Human
Subjects Committee at the Harvard School of Pub-
lic Health approved this study.
Twenty of the 24 sites were still implementing the
program when this study began, 26 months after
program inception. These 20 sites were overseen
by eight branches, which in conjunction with an-
other eight branches comprise the YMCA of
Greater Boston. All 91 staff members at these sites
who provide childcare and were on the staff roster
on 1 November 2007 were invited to participate in
the study. A total of 80 staff members took the
survey, yielding a response rate of 88%. Non-
responders were either absent during survey admin-
istration (10) or left the organization before being
Of the 80 respondents, two categories of staff
members were included in this analysis: 20 coordi-
nators (implementation leaders) and 53 general staff
members (individuals who supported program
implementation). The 20 coordinators represent
19 sites as the coordinator at one site left the orga-
nization before being interviewed and another site
employed two coordinators. We excluded data from
seven supervisors as their job functions prevent
useful comparisons with coordinators and general
staff. Given our interest in measuring sustainable
channels for knowledge transfer between site
teams, we did not survey the program director. This
person neither was a member of a site team nor was
his position a permanent part of the program (it only
existed for the 3-year grant period) and thus would
not be a lasting component of the program. For
these reasons, we restricted our focus to members
of site teams.
To collect our network data, we utilized standard
social network analysis data collection procedures
[23, 28]. We defined our network based on interac-
tions related to the iPLAY program and asked staff
members to list colleagues with whom they inter-
acted for ‘sharing information, skills or talking
through challenges and successes’ regarding the
program. Using the roster method, we presented
respondents with a list of staff members involved
in the iPLAY program; there was no limit on the
number of individuals they could list. Reports of
network connections based on this methodology
have shown strong construct validity through trian-
gulation between individual and peer reports .
We focused on routine program-related interac-
tions, rather than activities in a specific time period,
for increased validity .
The independent variable of interest was extra-team
connections or the number of connections noted by
respondents to iPLAY colleagues in other teams.
This measure is based on directional relations
between individuals , which means that each
connection has a source (the respondent) and a des-
tination (the contact who was listed). We focused
on the subset of connections reported by the respon-
dent about others as these connections may be per-
ceived as functionally useful to the respondent.
Here this function may be related to the ability to
gain resources from listed contacts.
We utilized a marker of knowledge transfer, skill
receipt, as our dependent variable. After listing
program-related contacts, respondents were asked
if they gained any of a set of six skills from these
colleagues. The six skills were those targeted by the
program training curriculum: connecting with chil-
dren, connecting with parents, program planning,
program implementation, data analysis and pro-
gram evaluation. The variable skill receipt is the
total number of skill receipt reports across the six
skills. If a respondent noted two important contacts
and noted gaining three and five skills respectively
from those contacts, the skill receipt value would be
8. Studies of skill gains among teachers suggest that
individuals are able to accurately self-report gaining
novel skills .
Other important variables
An important complement to extra-team connec-
tions is the variable intra-team connections, which
measures connections noted by respondents to col-
leagues based on the same team. Again, the focus is
on connections reported by respondents to others,
which indicates that the relationship may be useful
to the respondent. To provide context for our meas-
ures of extra- and intra-team connections, we also
present descriptive measures that take into account
tie direction. ‘Out-degree’ is the number of individ-
uals nominated by a respondent  and defines the
group from whom knowledge might also be gained.
‘In-degree’ is a complement to out-degree and is
defined as the number of individuals who listed
the respondent as an important contact, here with
relation to the iPLAY program.
We conducted a sociometric network analysis, in
which we assessed all members of the bounded
social network  to identify channels of commu-
nication that can support knowledge transfer be-
tween teams. The network analysis included all
respondents and nominated colleagues in the net-
work, specifically the members of 20 site teams
engaged in implementing the iPLAY program.
Thus, an individual who was invited to participate,
but did not fill out a survey, may exist in the dataset
if he/she was nominated by a respondent.
S. Ramanadhan et al.
sess relational data; we used UCINET-6  for this
purpose. Network data observations are not indepen-
supporting classical regression techniques cannot be
met. Thus, we utilized techniques developed for net-
work data, specifically the t-test and regression pro-
cedures in UCINET [34, 35]. The major difference is
that the significance tests are appropriate as they are
based on random permutations of matrices. Here, the
significance levels were determined based on distri-
butions created from 10000 random permutations.
We constructed a multiple linear regression model
to estimate the relationship between extra-team con-
nections and skill receipt. The data met requirements
for linear regression in their originalform. The initial
model included our predictor of interest as well as
several covariates selected due to their theoretical
relevance inthe implementationliterature, including:
Intra-team connections, staff gender, tenure in years
with the YMCA, position (general staff or coordina-
tor) and number of staff members at the site. We
removed the variable position due to its high corre-
lation with the dependent variables  (r = 0.41).
We removed covariates that were non-significant
(P value > 0.05) and whose removal did not change
the parameter estimates of remaining variables by
>10%. The final version of the model included only
the dependent and independent variables of interest,
as well as intra-team connections.
As seen from Table I, general staff members tended
to be young (under 25), worked part-time, reported
a high school education or some college/an associ-
ate’s degree. As a group, coordinators tended to be
older, had higher education levels, worked more
hours each week at the YMCA and had longer ten-
ure than general staff. Differences between groups
were statistically significant for education levels,
weekly hours spent at the YMCA and tenure; differ-
ences in age between groups were borderline sig-
nificant (P = 0.06). Among general staff and
coordinators, substantial percentages of staff (67
and 30%, respectively) reported <2 years experi-
ence with YMCA Afterschool Programs, meaning
that they began working with the program after
iPLAY implementation began. We also noted
that coordinators (compared with general staff)
reported significantly higher numbers of connections
to others (out-degree) and were also nominated
by others (in-degree) more than general staff
(P < 0.001 for both comparisons).
Network and team-level analysis
Overall, the network had density of 0.02, meaning
that only 2% of potential connections were realized
in the network. As seen in Fig. 1, connections be-
tween teams were less common than those within
teams. We found a total of 57 out of 6151 (;1%) of
potential extra-team connections were reported,
compared with 91 of 346 (;26%) of intra-team
connections. We found that twoteams reported zero
extra-team connections. The average was 2.85
[standard deviation (SD) = 1.72]. For intra-team
connections, two teams reported zero intra-team
connections (related to the program), with an aver-
age of 4.55 connections (SD = 6.48). Teams of staff
members are based in sites, which are nested within
branches (the higher organizational unit). Most ex-
ternal links (48 of 57) occurred between teams
based in sites belonging to the same branch.
Coordinators averaged 1.80 extra-team connections
(SD = 1.74). Seventeen of 20 coordinators reported
at least one extra-team connection. Over two-thirds
of general staff (68%) reported zero extra-team con-
nections, with an average of 0.40 (SD = 0.63). The
difference in average number of extra-team connec-
tions between coordinators and general staff was
statistically significant (P < 0.001). For intra-team
connections, coordinators averaged 2.05 connec-
tions (SD = 2.78), compared with an average of
0.94 (SD = 0.72) for general staff, a borderline sta-
tistically significant difference (P = 0.06). Also,
although our analysis excluded the program
director, in a separate assessment, a total of 27%
of respondents (75% of coordinators and 13% of
general staff) noted a connection to that individual.
In the multiple linear regression analysis, pre-
sented in Table II, extra-team connections were
positively associated with skill receipt (b = 3.41,
P < 0.0001), independent of the covariate. Simi-
larly, intra-team connections was positively associ-
ated with skill receipt (b = 1.50, P = 0.004),
independent of other variables. The R2value for
this model was 0.58 and the adjusted R2was 0.56.
Our findings not only support the management
mandate to create channels between teams for
knowledge transfer but also suggest that creation
and utilization of such links may require greater
active facilitation. The investment in connections
between teams may allow the organization to
spread tacit program-related knowledge between
sites , thus allowing the organization to change
continuously and maintain competitiveness in the
market [37, 38]. We found that respondents who
reported higher numbers of extra-team connections
reported higher levels of skill receipt, our measure
of knowledge transfer. We also found that the num-
ber of intra-team connections was positively related
to skill receipt, though with a smaller effect. The
number of intra- and extra-team connections
explained a large amount (58%) of the variance in
skill receipt, pointing to the importance of these
Table I. Descriptive data: staff characteristics and connection patterns (n = 73)
(n = 73)
(n = 53)
(n = 20)
General site staff
Younger than 25
Highest level of education completed
High school or less
Some college/associate’s degree
Bachelor’s degree or higher
Hours worked at YMCA each week
20 hours or less
31–40 + hours
Years with YMCA afterschool programs
1 year to <2 years
2 years to <5 years
Out-degree: mean (SD)
In-degree: mean (SD)
+P< 0.10;*P <0.05;and **P< 0.01for resultsof contingencytabletests for categoricalvariablesand t-tests for comparisonof means.
S. Ramanadhan et al.
Despite the potential utility of links between
teams, we found that in this network, only 1% of
such potential linkages existed. The low numbers
of extra-team connections in the network may reflect
the difficulty and investment required for building
such connections . Although there is likely to
be a threshold for the marginal utility of additional
connections between teams, this network will likely
benefit from great extra-team connections. Similarly,
the extra-team focus mustbe developed in relation to
the intra-team connections, as too much of an extra-
team focus may negatively impact the team’s
efficiency . When assessing the base network
structure for knowledge transfer between teams, we
found that 17 of 20 coordinators (those charged with
leading implementation) and 18of20teams reported
at least one extra-team connection. Though a norma-
tive level of connectivity is not defined by the liter-
ature, the isolation of some teams and leaders
suggests the need for intervention. Cross-sectional
data prevented us from determining whether individ-
uals tapped into existing connections for knowledge
transfer, or if they actively sought out expertise
among their peers, thus simultaneously increasing
the number of connections and skill receipt transac-
tions. Regardless of the direction of this influence,
we expect that higher levels of connectivity will
increase access to knowledge .
In addition to knowledge transfer, increased
connection between teams may offer a protective
effect for knowledge management in the network
Fig. 1. Network diagram representing program-related connections among program staff (n = 73). Black circles represent general staff;
black squares represent coordinators. Individuals are clustered by site teams and dotted ellipses show branch membership of sites.
Table II. Association between extra- and intra-team
connections and skill receipt among staff involved in a multi-
site implementation project (n = 73)
R2= 0.58, adjusted R2= 0.56
aEstimate derived from multiple linear regression model,
unstandardized coefficients presented.
as a whole, given the high levels of turnover
among staff. This is an endemic problem in after-
school childcare programs, with annual staff turn-
over rates estimated between 25 and 40% annually
[40, 41]. For this program, over half of staff mem-
bers joined the organization after program imple-
mentation had begun. High turnover results in
reduced connections among staff , loss of tacit
knowledge from the organization  and reduced
performance  and improved knowledge trans-
fer between teams can buffer the effects of such
loss of staff.
The question remains as to how organizations
might increase the level of connections between
site teams implementing novel programs. Active
development and support of connections between
teams by the larger organization appears to be key
for success in supporting tacit knowledge transfer
between teams and creating a learning organiza-
tion . By routinizing opportunities to meet
with and learn from other teams and a network
of experts within the organization, strong channels
for knowledge transfer can be developed [7, 12,
43]. For example, in this network, coordinators
may have reported higher numbers of extra-team
connections than general staff because they had
greater opportunities and obligation to network
with colleagues at other sites regarding the pro-
gram. The organization can also encourage teams
to assess resources they possess as a group versus
those they need to access via members of other
It may also be useful to target connections be-
tween teams that take advantage of the organiza-
tion’s structure . In this organization, afterschool
childcare programs are run by teams based in sites,
sites are overseen by a branch and 16 branches
comprise the YMCA of Greater Boston. The rela-
tionship between sites and branches is similar to
that between schools and school districts. About
85% of links between teams occurred between indi-
viduals in sites overseen by the same branch, which
may be a function of physical proximity of sites,
shared space for teamwork and facilitated opportu-
nities to interact for other purposes. Structural sup-
ports for collaboration, such as proximity and
co-location, support productive interactions be-
tween individuals from different teams [45, 46]
and should be utilized fully. Nonetheless, knowl-
edge worthy of transfer may be gained anywhere in
the organization, so over-reliance on proximity as
a determinant of communication channels should
Another important structural support for con-
nections between teams may come from the per-
son supervising the implementation process. In
this network, low levels of connections between
teams may also reflect reliance on the program
director, who often served as the conduit for in-
formation between sites. About one-quarter of
staff members noted a connection to the program
director, yet the group that connected with this
individual was predominantly composed of coor-
dinators, who were charged with knowledge shar-
ing between sites, so the impact of such a position
may have had a substitution effect. Senior man-
agement may need to take a long-term perspective
regarding building a knowledge-sharing network
at the intermediate expense of using someone
in this position to circulate knowledge and
impact implementation quickly [22, 24]. Overall,
many of these solutions point to opportunities to
use organization-level changes to better support
Limitations and strengths
The findings should be interpreted with a few key
limitations in mind. The first limitation relates to the
validity of our measures of program-related connec-
tions and skill receipt, which were collected via
self-report data and are subject to social desirability
bias. Though we do not have reliability or validity
data for the questions used, the literature suggests
that our methods were appropriate [29, 31]. The
second limitation relates to external validity, a com-
mon issue facing network and team research .
This analysis is limited to one network of non-ran-
domly selected sites, thus findings may not be gen-
eralizable to other networks, as organizational
context has a strong impact on network structures,
resources and functions . Third, the data in this
study are cross sectional; therefore, causation
S. Ramanadhan et al.
cannot be determined, though alternative explana-
tions also support our interpretation.
Despite these limitations, the assessment of
extra-team connections in a low-resource, high-
turnover service organization is a useful addition
to the literature as the majority of assessments focus
on professional settings. This study is strengthened
by a high response rate (88%) as well as the use of
sociometric analysis of a clearly defined network,
which allowed us to examine relationships among
all individuals in the network as well as the resour-
ces contained within those relationships. The study
also points to the utility of using social network
analysis to evaluate knowledge transfer among staff
and the successes or gaps in attempts to create a
Given the potential utility of extra-team connec-
tions for spreading knowledge in multi-site imple-
mentation projects, further study is warranted. Next
steps include testing the relationship between extra-
team connections and transfer of program-related
knowledge and skills utilizing more objective
measures of knowledge transfer. Also, further in-
vestigation into the complementary roles of extra-
and intra-team connections will point to ways in
which information brought into the team can best
be utilized and integrated into the team’s work .
The continued focus on channels for knowledge
transfer between teams in low-resource, high turn-
over environments has great practical utility. Given
the high cost of developing and maintaining con-
nections in a network, and particularly extra-team
connections, these connections must be developed
strategically, with an eye on the ultimate goal and
successful implementation of the program.
National Cancer Institute (5 R25 CA057711-14 to
S.R.); the Dana Farber/Harvard Cancer Center to
K.V. and a gift from the Pritzker Family Foundation
and the Pritzker Traubert Foundation to the Harvard
School of Public Health (funding for S.L.G. and
The authors are grateful to John Hirliman and
Donna Sullivan of the YMCA of Greater Boston
for their insight and support, as well as the staff
members implementing the iPLAY program for
their participation. The authors would also like to
thank Dr Elizabeth Bradley for her invaluable sug-
gestions and guidance.
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Received on October 13, 2008; accepted on May 11, 2009
S. Ramanadhan et al.