Organizational readiness for change in
healthcare settings is an important factor in successful implementation
of new policies, programs, and practices. However, research on the topic
is hindered by the absence of a brief, reliable, and valid measure.
Until such a measure is developed, we cannot advance scientific
knowledge about readiness or provide evidence-based guidance to
organizational leaders about how to increase readiness. This article
presents results of a psychometric assessment of a new measure called
Organizational Readiness for Implementing Change (ORIC), which we
developed based on Weiner’s theory of organizational readiness for
change.
Methods
We conducted four studies to assess the
psychometric properties of ORIC. In study one, we assessed the content
adequacy of the new measure using quantitative methods. In study two, we
examined the measure’s factor structure and reliability in a laboratory
simulation. In study three, we assessed the reliability and validity of
an organization-level measure of readiness based on aggregated
individual-level data from study two. In study four, we conducted a
small field study utilizing the same analytic methods as in study three.
Results
Content adequacy assessment indicated
that the items developed to measure change commitment and change
efficacy reflected the theoretical content of these two facets of
organizational readiness and distinguished the facets from hypothesized
determinants of readiness. Exploratory and confirmatory factor analysis
in the lab and field studies revealed two correlated factors, as
expected, with good model fit and high item loadings. Reliability
analysis in the lab and field studies showed high inter-item consistency
for the resulting individual-level scales for change commitment and
change efficacy. Inter-rater reliability and inter-rater agreement
statistics supported the aggregation of individual level readiness
perceptions to the organizational level of analysis.
Conclusions
This article provides evidence in
support of the ORIC measure. We believe this measure will enable testing
of theories about determinants and consequences of organizational
readiness and, ultimately, assist healthcare leaders to reduce the
number of health organization change efforts that do not achieve desired
benefits. Although ORIC shows promise, further assessment is needed to
test for convergent, discriminant, and predictive validity.
Keywords
Readiness for changeMeasure developmentPsychometrics
Introduction
Attempts
to implement new programs, practices, or policies in organizations
often fail because leaders do not establish sufficient organizational
readiness for change [1].
Organizational readiness refers to ‘the extent to which organizational
members are psychologically and behaviorally prepared to implement
organizational change’ [2].
When organizational readiness is high, members are more likely to
initiate change, exert greater effort, exhibit greater persistence, and
display more cooperative behavior, which overall results in more
effective implementation of the proposed change [3].
Conversely, when organizational readiness is low, members are more
likely to view the change as undesirable and subsequently avoid, or even
resist, planning for the effort and participating in the change
process.
Although organizational readiness for change in healthcare settings has been identified as an important issue [4],
research on the topic is hindered by the absence of a brief, reliable,
and valid measure of the construct. Until recently, the primary focus in
the literature has been on individual readiness for change, not on
organizational readiness for change [2]. Although there have been several attempts at measuring organizational readiness (e.g., [5–7]), most available instruments are not theory-based and exhibit limited reliability and validity [2, 6].
Furthermore, those with desirable psychometric properties have too many
items to be practical for use in busy healthcare settings [4].
Until a brief, reliable, and valid measure is developed, we cannot
advance scientific knowledge of the determinants or outcomes of
readiness or provide evidence-based guidance to organizational leaders
about how to increase readiness.
In
this article, we report the results of a psychometric assessment of a
new, theory-based measure we call Organizational Readiness for
Implementing Change (ORIC). We developed ORIC by drawing on Weiner’s
theory of organizational readiness for change [8]
and assessed its content adequacy, structural validity, reliability,
and construct validity in a series of studies. These studies provide
psychometric evidence for a brief yet robust measure that could be used
to advance implementation science and practice.
Conceptual framework
Organizational
readiness for change is a multilevel construct that can be assessed at
the individual or supra-individual levels (e.g.,
team, department, or organization). In this analysis, we focus on the
supra-individual level because the implementation of many promising
innovations in healthcare, such as patient-centered medical homes,
Accountable Care Organizations, and electronic health records, require
collective, coordinated actions by many organizational members [8].
There are three considerations that researchers should keep in mind
when measuring readiness for change at supra-individual levels. First,
items should be group-referenced (e.g., ‘We are ready to…’) rather than self-referenced (e.g., ‘I am ready to…’) so that they focus respondents’ attention on collective readiness rather than personal readiness [8].
Second, assessment should involve multiple respondents from the same
unit. Proxy reporting of collective readiness by single respondents (e.g., the CEO) is unlikely to generate valid data [2].
Third, inter-rater agreement should be checked before aggregating
individuals’ readiness perceptions to supra-individual levels of
analysis. If, for example, one-half of an organization’s members
perceive readiness to be high and one-half perceive it to be low, then
the average of organizational members’ perceptions of readiness
describes none of their views [8].
Organizational
readiness for change is not only a multilevel construct, but a
multi-faceted one. We used Weiner’s theory of organizational readiness
for change [8] to identify and define the two facets we aimed to measure as well as the immediate determinants of each (Figure 1).
The first facet of readiness, change commitment, reflects
organizational members’ shared resolve to implement a change. A
hypothesized determinant of change commitment is change valence.
Organizational members may value an organizational change for any number
of reasons; why they value it may be less important than how much they
value it. The second facet of readiness, change efficacy, reflects
organizational members’ shared belief in their collective capability to
implement a change [3, 8].
Hypothesized determinants of change efficacy include task knowledge,
resource availability, and situational factors. Change efficacy is
expected to by high when organizational members know what to do and how
to do it, when they perceive they have the resources they need to
implement the change, and when they perceive situational factors such as
timing to be favorable. An immediate outcome of readiness is
organizational members’ change-related effort. For example, when
readiness is high, organizational members are more likely to initiate
the change, put forth greater effort in support of the change, and
exhibit greater persistence in the face of obstacles.
Figure 1
Determinants and outcomes of organizational readiness for change. *Adapted from Weiner, B.J., A theory of organizational readiness for change. Implement Sci, 2009. 4: p. 67.
Given
the potential impact of organizational readiness for change on
implementation outcomes, a valid, theory-based measure would be useful
for research and practice. The measure should reflect both facets of
readiness—change commitment and change efficacy—and differentiate the
facets from their determinants to ensure direct measurement of the
readiness construct [9]. In addition to being valid and reliable, the assessment must be brief in order to be practical in busy healthcare settings.
Methods
We
conducted four studies to assess the psychometric properties of a newly
developed, theory-based measure of organizational readiness for
implementing change (ORIC). In study one, we assessed the content
adequacy of the new measure using quantitative methods [10].
In study two, we examined the measure’s factor structure and
reliability in a laboratory simulation. In study three, we assessed the
reliability and validity of an organization-level measure of readiness
based on aggregated individual-level data from study two. In study four,
we conducted a small field study to validate the results of study
three.
Study one
Method
Content
adequacy refers to ‘the degree to which a measure’s items are a proper
sample of the theoretical content domain of a construct’ [10].
Typically, researchers assess content adequacy by asking a small group
of experts to assess whether a measure’s items seem representative of
the construct’s theoretical content. Often, the assessment is informal
and qualitative. In this study, we took a formal, quantitative approach
by asking a large group of judges to rate the extent to which items
reflect the constructs they were intended to measure.
Design, participants, and procedures
Study
participants were a convenience sample of 98 students enrolled in
undergraduate, masters, and doctoral programs in health policy and
management at a university located in the southeastern United States.
Convenience samples are acceptable for content adequacy studies because
such studies require no particular expertise or experience, merely
sufficient reading skill and intellectual ability to perform the rating
task [10].
Twenty-eight percent of study participants were men, 72% women.
Fourteen percent were 18 – 21 years old, 19% were 22 – 25 were years
old, 18% were 26 – 28 years old, 7% were 29 – 31 years old, and 33% were
32 years old or older.
Study
participants were randomly assigned to complete one of two web-based
surveys. One survey consisted of 15 items that reflected two related
constructs: change commitment and change valence. The other survey
consisted of 15 items that reflected three related constructs: change
efficacy, task knowledge, and resource availability. Each survey
provided detailed instructions and examples of how to perform the rating
task. Using the definitions that we provided, participants rated the
extent to which they thought each item reflected each construct in the
survey. For example, participants receiving the first survey rated each
item twice: once to indicate the extent to which they thought the item
reflected change commitment, and again to indicate the extent to which
they thought the item reflected change valence. Rating was done using a
five-point ordinal scale in which a ‘1’ indicated that an item ‘does not
reflect the concept at all’ and a ‘5’ indicates that an item ‘reflects
the concept well’.
To
minimize ordering effects, one-half of the participants receiving the
first survey were randomly assigned to perform the change commitment
rating task first; the other one-half performed the change valence
rating task first. To minimize learning effects, items were presented in
random order within each rating task. The same procedure was used to
minimize ordering effects and learning effects in the second survey.
Measures
Five items in the first survey were written to measure change commitment (e.g.,
‘we are committed to implementing this change’). Ten items were written
to measure some aspect of change valence: perceived need (e.g., ‘we need to implement this change’), perceived benefit (e.g., ‘we believe this change will make things better’), perceived timeliness (e.g., ‘we see this change as timely’), and perceived compatibility (e.g.,
‘we feel this change is compatible with our values’). We also included a
‘distracter’ item to check on participants’ attention and diligence in
performing the rating task (e.g., ‘we know what it takes to implement this change’).
Six items in the second survey were written to measure change efficacy (e.g., ‘we can coordinate tasks so that implementation goes smoothly’). Four items were written to measure task knowledge (e.g., ‘we know what we need to do to implement this change’). Five items were written to measure resource availability (e.g.,
we have the resources we need to implement this change’). We also
included a ‘distracter’ item to check on participants’ attention and
diligence in performing the rating task (e.g., ‘the timing is good for implementing this change’).
Analysis
Content adequacy involves judgments of item content in relation to theoretically-defined constructs [9].
We considered the item adequate if it met three conditions: the item’s
highest mean corresponded to the intended aspect of organizational
readiness for implementation (e.g., change commitment and not change valence) [11];
the item’s mean on the intended aspect of organizational readiness for
implementation was at least 0.20 units higher than its mean on its
hypothesized determinants [11]; and the item’s mean must be greater than or equal to 4 on its intended aspect of organizational readiness [11].
In addition, we performed an analysis of variance (ANOVA) to compare
the item’s mean rating on the hypothesized theoretical construct (e.g., change commitment) to the item’s ratings on alternative constructs (e.g., change valence) [12].
Results
In Table 1,
the first five items (C1 – C5) were intended to measure change
commitment. The first four of these items (C1 – C4) satisfied all three
conditions of the content adequacy test. The fifth item (C5) did not
satisfy any condition of the content adequacy test. Study participants
rated this item as equally reflecting the concepts of change commitment
and change valence. In the absence of more semantic context, the verb
‘want’ could connote either motivation (commitment) or desire (value) to
implement change. Although this item did not pass the content adequacy
test, we retained it for further testing in circumstances where the
semantic context was more clearly defined. None of the items intended to
measure change valence (V1 – V10) passed the content adequacy test as
measures of change commitment. This suggests that study participants
were able to distinguish items intended to measure change commitment
from items intended to measure its hypothesized determinant. Also, the
distracter item (D1) did not satisfy the three conditions for fit with
the construct of change commitment or change valence.
Table 1
Content
adequacy assessment of items intended to measure the change commitment
dimension of organizational readiness for implementation (study one)
Mean rating for commitment
Mean rating for valence
Pass condition 1?
Pass condition 2?
Pass condition 3?
C1. We are committed to implementing this change.
4.78*
2.52
Yes
Yes
Yes
C2. We are determined to implement this change.
4.64*
2.28
Yes
Yes
Yes
C3. We are motivated to implement this change.
4.26*
2.79
Yes
Yes
Yes
C4. We will do whatever it takes to implement this change.
4.73*
2.41
Yes
Yes
Yes
C5. We want to implement this change.
3.47
3.32
No
No
No
V1. We feel this change is compatible with our values.
2.23
4.37*
Yes
Yes
Yes
V2. We need to implement this change.
3.10
3.6
Yes
No
No
V3. We believe this change will benefit our community.
2.13
4.28*
Yes
Yes
Yes
V4. We believe it is necessary to make this change.
2.91
3.78*
Yes
No
No
V5. We believe this change will work.
2.41
3.34*
Yes
No
No
V6. We see this change as timely.
2.21
3.37*
Yes
No
No
V7. We believe this change is cost-effective.
2.23
3.06*
Yes
No
No
V8. We believe this change will make things better.
2.30
4.47*
Yes
Yes
Yes
V9. We feel that implementing this change is a good idea.
2.54
4.14*
Yes
Yes
Yes
V10. We value this change.
2.30
4.73*
Yes
Yes
Yes
D1. We know what it takes to implement this change.
3.10*
1.93
N/R
N/R
N/R
* Denotes statistically significant differences (p < 0.05) for one-way ANOVA between mean ratings for Commitment and Valence.
Notes:
The first five items were intended to measure change commitment (C).
The last item was a distractor (D). The remaining items were intended to
measure aspects of change valence (V). The following definitions were
provided to participants: Change commitment
refers to organizational members’ shared resolve to pursue courses of
action that will lead to the successful implementation of the change
effort. Change valence refers to the
value that organizational members assign to a specific, impending
organizational change. For example, do they think the change is needed,
important, beneficial, or worthwhile?
In Table 2,
the first six items (E1 – E6) were intended to measure change efficacy.
All six items satisfied all three conditions of the content adequacy
test. None of the items intended to measure task knowledge (K1 – K4) or
resource availability (A1 – A5) passed the content adequacy test as
measures of change efficacy. This finding suggests that study
participants were able to distinguish items intended to measure change
efficacy from items intended to measure its hypothesized determinants.
Finally, the distracter item (D2) did not satisfy the three conditions
for fit with change efficacy, task knowledge or resource availability.
Table 2
Content
adequacy assessment of items intended to measure the change efficacy
dimension of organizational readiness for implementation (study one)
Mean rating for efficacy
Mean rating for task knowledge
Mean rating for resource availability
Pass condition 1?
Pass condition 2?
Pass condition 3?
E1. We can keep the momentum going in implementing this change.
4.40*
1.80
1.56
Yes
Yes
Yes
E2. We can manage the politics of implementing this change.
4.24*
1.84
1.66
Yes
Yes
Yes
E3. We can support people as they adjust to this change.
4.28*
1.94
2.16
Yes
Yes
Yes
E4. We can get people invested in implementing this change.
4.42*
1.96
1.78
Yes
Yes
Yes
E5. We can coordinate tasks so that implementation goes smoothly.
4.34*
2.34
1.58
Yes
Yes
Yes
E6. We can keep track of progress in implementing this change.
3.54*
2.18
1.54
Yes
Yes
Yes
K1. We know how much time it will take to implement this change.
1.69
4.64*
1.62
Yes
Yes
Yes
K2. We know how much time it will take to implement this change.
1.71
4.82*
1.64
Yes
Yes
Yes
K3. We know what resources we need to implement this change.
1.77
4.62*
2.32
Yes
Yes
Yes
K4. We know what each of us has to do to implement this change.
2.32
4.80*
1.64
Yes
Yes
Yes
A1. We have the equipment we need to implement this change.
2.00
2.30
4.88*
Yes
Yes
Yes
A2. We have the expertise to implement this change.
2.80
2.94
4.48*
Yes
Yes
Yes
A3. We have the time we need to implement this change.
2.59
2.54
4.52*
Yes
Yes
Yes
A4. We have the skills to implement this change.
2.95
3.02
4.37*
Yes
Yes
Yes
A5. We have the resources we need implement this change.
1.91
2.38
4.85*
Yes
Yes
Yes
D2. The timing is good for implementing this change.
2.55
1.76
2.00
N/R
N/R
N/R
*
Denotes statistically significant differences (p < 0.05) for ANOVA
between mean ratings for Efficacy, Task Knowledge, and Resource
Availability.
Notes:
The first six items were intended to measure change efficacy (E). The
next four items were intended to measure task knowledge (K). The next
five items were intended to measure resource availability (A). The last
item was a distractor (D). The following definitions were provided to
participants: Change efficacy refers
to organizational members’ shared beliefs (or confidence) in their
collective capabilities to organize and execute the courses of action
required to implement the change successfully. Task knowledge refers to organizational members’ knowledge
of the tasks that have to be performed, the resources that will be
needed, the amount of effort that will be required, and the amount of
time that it will take to implement a change. Resource availability refers to organizational members’ perceptions of the availability of money, people, equipment, and other resources needed to implement a change.
Table 1 and Table 2
note statistically significant differences identified by the ANOVA
procedures comparing each item’s mean rating on its hypothesized
theoretical construct and its ratings on alternative constructs.
Study two
Method
In
study two, we ascertained the factor structure and reliability of our
new measure in a laboratory study wherein we manipulated the two aspects
of organizational readiness in vignettes that described a hospital
about to implement a major organizational change.
Design, participants, and procedures
The
study used a 2 (high- versus low-change commitment) × 2 (high- versus
low-change efficacy) between-subjects design. Study participants read
one of four randomly assigned vignettes that described a hospital’s
readiness to implement meaningful use of electronic health records. They
then rated the hospital’s readiness for implementation as they believed
a hospital employee would rate it. Hospital readiness was manipulated
in the vignettes by describing various levels of the following: employee
knowledge of meaningful use, employee morale and enthusiasm, resources
available for implementation, and situational factors such as leadership
stability and timing of the implementation. Study participants were a
convenience sample of 140 students enrolled in undergraduate, masters,
and doctoral programs in health policy and management or health behavior
at a university located in the Southeastern United States. These
programs familiarize students with the structures, workforce, and
services of healthcare organizations. Twenty-six percent of study
participants were men; 74% were women. Eleven percent were 18 – 21 years
old, 25% were 22 – 25 years old, 28% were 26 – 28 years old, 16% were
29 – 31, and 20% were 32 years old or older. A convenience sample was
acceptable because participants needed only sufficient intellectual
capability to comprehend the vignette and perform the rating task. This
approach has been used in previous studies [13].
Measures
Participants
rated the hospital’s readiness for implementation on 12 items using a
5-point ordinal scale that ranged from ‘disagree’ to ‘agree’ (Additional
file 1
contains the items). All five items used to assess change commitment in
study one were included. Although one of the change commitment items
did not pass the content adequacy tests (‘We want to implement this
change’), we retained it in order to see how it performed in a more
clearly defined semantic context (i.e.,
the vignettes). All six items used to assess change efficacy in study
one were also included. A seventh change efficacy item was added (‘We
can handle the challenges that might arise in implementing this change’)
in order to capture the organization’s ability to respond to problems
that emerge during implementation. Although not included in study one,
this item passed a content adequacy test involving the same methods but
with only 10 study participants. Item content did not change from study
one to study two, although item wording did. In study two, efficacy
items were phrased ‘People who work here are confident that…’ This
wording was not used in study one because it would have made it obvious
to raters that they were efficacy items (based on the use the word
‘confident’), which would have defeated the purpose of the content
adequacy test.
Analysis
To
determine whether change commitment and change efficacy are distinct,
yet related facets, we conducted an exploratory principal-axis factor
analysis (EFA) with oblique rotation, followed by a confirmatory factor
analysis (CFA) specifying two factors. We chose oblique rotation because
we expected, based on theory [9],
that change commitment and change efficacy represented interrelated
facets of organizational readiness and, therefore, would be correlated.
Oblique rotation allows for identification of unique contributions to
variance and excludes contributions to variance from overlap between the
correlated factors [14].
To determine the number of factors to retain in the EFA, we ran the
parallel analysis procedures (PA), which Zwick and Velicer [15]
found outperforms other methods such as the Kaiser criterion, scree
plot, and Bartlett’s chi-square test. In PA, a set of random data
correlation matrices are created and their eigenvalues are computed.
These eigenvalues are compared to those computed from the study data,
and only those factors from the study data with eigenvalues greater than
those from the random data are retained. To interpret the retained
factors and assess item performance, we used the following conventions:
factor loadings greater than 0.6, factor cross-loadings less than 0.3,
communalities greater than 0.5, and face-valid factor membership [16].
To assess CFA model fit, we used the following rules of thumb:
comparative fit index (CFI) and Tucker-Lewis fit index (TLI) equal to or
greater than 0.95, standard root mean square residual (SRMR) less than
0.05, and root mean square error of approximation (RMSEA) equal to or
less than 0.06 [17].
We
then formed scales for change commitment and change efficacy based on
the CFA results and computed alpha coefficients for each scale to assess
inter-item consistency. Finally, we conducted a 2 × 2 analysis of
variance (ANOVA) to determine whether change commitment and change
efficacy varied as expected by the manipulation of information in the
vignettes.
Results
EFA
yielded two factors with eigenvalues greater than 1 and greater than
those generated from the PA of 10 random data correlation matrices. All
five items intended to measure change commitment (C1 – C5) exhibited
factor loadings greater than 0.6 on the first retained factor,
cross-loadings less than 0.25 on the second factor, and communalities
greater than 0.5 (see Table 3).
Five of the seven items intended to measure change efficacy exhibited
factor loadings greater than 0.6 on the second retained factor,
cross-loadings less than 0.25 on the first factor, and communalities
greater than 0.5. Based on these results, we interpreted the factors as
Change Commitment (factor one) and Change Efficacy (factor two). Two
items intended to measure change efficacy exhibited loadings between 0.5
and 0.6 on the Change Commitment factor and cross-loadings on the
Change Efficacy factor less than 0.25. These items were: (1) ‘People who
work here confident that they can keep the momentum going in
implementing this change’, and (2) ‘People who work here feel confident
that the organization can get people invested in implementing this
change’. Apparently, these items had a motivational connotation that
study participants associated with items intended to measure change
commitment. Since these two items did not load on the expected factor
(and lacked face validity as measures of change commitment), we dropped
them and re-ran the EFA. Re-analysis did not alter the number of factors
or the pattern of factor loadings for the remaining items. We then ran a
two-factor CFA using the ten items retained from the re-analysis. The
two-factor CFA converged and demonstrated a strong fit when change
commitment and change efficacy were allowed to correlate. The
comparative fit index (CFI) equaled 0.98, the Tucker-Lewis fit index
(TLI) = 0.97, the standard root mean square residual (SRMR) was 0.04 and
the root mean square error of approximation (RMSEA) was = 0.06.
Standardized parameter estimates are provided in Table 4. No post hoc modifications were necessary given the good fit indicated by the fit indices; residual analysis did not indicate any problems.
Table 3
Exploratory and confirmatory factor analysis of organizational readiness for implementation items (study two)
EFA factor loadings
CFA* standardized factor loadings
Mean
Standard deviation
I
II
I
II
C1. Are committed to implementing this change
3.07
1.33
0.80
0.07
0.872 (0.025)
C2. Are determined to implement this change
2.82
1.29
0.85
0.04
0.898 (0.021)
C3. Are motivated to implement this change
2.87
1.45
0.92
−0.04
0.874 (0.024)
C4. Will do whatever it takes to implement this change
2.58
1.20
0.68
0.10
0.784 (0.036)
C5. Want to implement this change
3.29
1.32
0.77
−0.07
0.769 (0.038)
E1. Feel confident that they can keep the momentum going in implementing this change
2.53
1.22
0.55
0.16
--
--
E2. Feel confident that they can manage the politics of implementing this change
2.78
1.07
0.01
0.73
0.763 (0.042)
E3. Feel confident that the organization can support people as they adjust to this change
2.77
1.29
0.16
0.66
0.800 (0.038)
E4. Feel confident that the organization can get people invested in implementing this change
2.92
1.46
0.58
0.10
--
--
E5. Feel confident that they can coordinate tasks so that implementation goes smoothly
2.71
1.16
0.02
0.84
0.768 (0.041)
E6. Feel confident that they can keep track of progress in implementing this change
2.97
1.15
0.09
0.63
0.684 (0.051)
E7. Feel confident that they can handle the challenges might arise in implementing this change
2.91
1.29
−0.03
0.79
0.838 (0.033)
Notes: All items begin ‘People who work here…’. Bold EFA results indicate the highest factor loading for each item.
*Standardized factor loadings for two factor confirmatory factor analysis; Standard Error in parenthesis.
Analysis of variance summary for vignette hospitals (study two)
Change
Change
Commitment
Efficacy
Source
df
F
Η
F
η
CC
1
50.29***
0.24
1.15
0.01
CE
1
0.00
0.00
23.48***
0.14
CC X CE
1
24.64***
0.12
6.87**
0.04
Residual
137
Notes: The dependent variables are the Change Commitment and Change Efficacy Scales.
CC = change
commitment factor (high versus low, manipulated in
vignettes).CE = change efficacy factor (high versus low, manipulated in
vignettes).
Eta-squared describes
the ratio of variance explained in the dependent variable by a
predictor while controlling for other predictors.
**p <0.01.
***p <0.001.
Alpha
coefficients for the five-item Change Commitment Scale and the
five-item Change Efficacy Scale were 0.92 and 0.88 respectively. The
correlation between the unit-weighted scale scores was similar to that
between the factors (r = 0 0.56, p <0.001).
The
2 × 2 ANOVAs revealed small- to medium-size main effects for each
manipulation in the vignette and small-size interaction effects (see
Table 4) [18].
The manipulation of information about change commitment and change
efficacy explained 36% of the variation in the Change Commitment Scale
scores and 19% of the Change Efficacy Scale scores. The variance
accounted for seemed reasonable given that study participants had to
infer the level of change commitment and change efficacy in the
vignettes. Plots of the marginal means (not shown) indicate that
participants had no difficulty distinguishing change commitment and
change efficacy when these factors, individually or jointly, were low.
They had more difficulty distinguishing them when both factors were
high.
Study three
Method
Having
established, at least provisionally, the reliability of our new measure
at the individual level of analysis, we sought next to ascertain its
reliability and validity at the organization level of analysis.
Organizational readiness for implementing change is one of many
constructs that are potentially relevant to implementation science that
can be conceptualized at the organizational level of analysis even
though the source of data for the construct resides at the individual
level. Although it is tempting to simply compute an organization-level
mean from the individual-level data, it is important to first check the
reliability and validity of that mean to determine whether it is an
adequate representation of the organization-level construct [19, 20].
Organizational readiness is conceived as a ‘shared team property’, that
is, a psychological state that organizational members hold in common [8].
Whether this shared team property exists in any given organization is
an empirical issue that requires examination of inter-rater reliability
and inter-rater agreement. If sufficient inter-rater reliability and
inter-rater agreement exist (i.e.,
organizational members agree in their readiness perceptions), then
analysis of organizational readiness as a shared team property can
proceed. That is, an organization-level mean can be computed that
reliably and validly reflects the perceptions of organizational members
as a group. If insufficient inter-rater reliability and inter-rater
agreement exist (i.e.,
organizational members disagree in their readiness perceptions),
organizational readiness as a shared team property does not exist. In
that case, an organization-level mean does not reliable and validly
reflect the perceptions of organizational members as a group. In study
three, we assess whether change commitment and change efficacy can be
measured reliably and validly at the organizational level of analysis
using individual-level data from study two.
Design, participants, and procedure
Study
three involved the same design, participants, and procedures as study
two. Thus, the data were the same, but they were analyzed differently.
In study three, we treated the 140 study participants as if they were
employees of the hospitals depicted in the vignettes. Thus, for each of
the four hospitals, there were 35 ‘employees’ rating the hospital’s
readiness to implement meaningful use of electronic health records. One
of the advantages of using data from a laboratory study is that we can
test whether our measures reliably and validly differentiate
organizations that systematically differ by design in levels of change
commitment and change efficacy.
Measures
Study three used the five-item Change Commitment Scale and the five-item Change Efficacy Scale developed in study two.
Analysis
To
assess the reliability of the organization-level means for change
commitment and change efficacy, we computed values for two intraclass
correlation coefficients—ICC(1) and ICC(2)—from a one-way random-effects
ANOVA. ICC(1) provides an estimate of the extent to which
individual-level variability on a given measure is explained by higher
level units [20, 21].
ICC(1) can also be interpreted as an estimate of the extent to which
raters are interchangeable—that is, the extent to which one rater in a
group could represent all raters within that group [20].
The larger the value of ICC(1), the more alike the raters are. ICC(2)
is a mathematical function of ICC(1), adjusted for group size. ICC(2)
indicates the reliability or stability of group-level means in a sample [22].
The larger the value of ICC(1) and the larger the number of respondents
per group, the more reliable the group means and, hence, the greater
the value of ICC(2).
To
assess the validity of the organization-level means as measures of
organization-level constructs, we computed and tested the statistical
significance of two indices of inter-rater agreement: rWG(J) and ADM(J). The rWG(J) index indicates the extent of consensus,
agreement, or within-unit variability in a multi-item scale by comparing
within-group variances to an expected variance under the null
hypothesis of no agreement [20]. We assumed the null followed a uniform (rectangular) distribution. The ADM(J) index, also known as the mean absolute deviation, is used less often than the rWG(J), but allows more direct conceptualizations of
inter-rater agreement in the units of the original measure. Both the
indices and their respective critical values, which were obtained from
an empirical distribution based on 100,000 simulations and corresponded
to a 0.05 level of statistical significance, were calculated using the
Multilevel Modeling in R package [23, 24]. The rWG(J) critical value is calculated based on the 95th percentile and the ADM(J) based on the 5th percentile [23]. Formulae for rWG(J), ADM(J), ICC(1), and ICC(2), can be found in the Appendix.
Results
The
one-way ANOVA for the Change Commitment Scale yielded an ICC(1) of
0.72, and an ICC(2) of 0.98 (p <0.001). The one-way ANOVA for the
Change Efficacy Scale yielded an ICC(1) of 0.51, and an ICC(2) of 0.97
(p <0.001). The magnitude and statistical significance of these
correlations indicate the organization-level means for the Change
Commitment scale and the Change Efficacy scale were reliable. More
individual-level variance was explained by hospital (vignette)
assignment for change commitment than for change efficacy (72% versus
51%).
For the Change Commitment Scale, the sample values for rWG(J) and ADM(J) for the ensemble of four hospitals were 0.87 and 0.73 respectively. For the Change Efficacy Scale, the sample values for rWG(J) and ADM(J) for the ensemble of four hospitals were 0.82 and 0.80 respectively. Table 5 summarizes the empirical distributions in terms of their means, medians, standard deviations, 5th percentiles, and 95th percentiles. For both scales, the sample values for the ensemble of hospitals for rWG(J) exceeded the 95th percentile of their
corresponding null distributions and the corresponding p-values were
almost zero. Likewise, the sample values for ADM(J) for the ensemble of hospitals were smaller than the 5th percentile of their corresponding null distributions and the corresponding p-values were almost zero. Therefore, for both the rWG(J) and ADM(J) indexes, the null hypothesis of no agreement in the ensemble of hospitals in the sample was rejected.
Table 5
Significance tests for the means ofrWG(J)andADM(J)for vignette hospitals as a group (study three)
Distribution based on simulation
Variable
Mean
Median
Standard deviation
5thpercentile
95thpercentile
Sample values
p value
Change commitment (5 items)
ADM(J) mean
1.20
1.20
0.03
1.15
1.25
0.73
0.00
rWG(J) mean
0.11
0.11
0.07
0.00
0.25
0.87
0.00
Change Efficacy (5 items)
ADM(J) mean
1.20
1.20
0.03
1.15
1.26
0.80
0.00
rWG(J) mean
0.12
0.11
0.08
0.00
0.25
0.82
0.00
Note: For each of the four statistics (ADM(J) mean and rWG(J) mean for each scale), we obtained an
empirical distribution based on 100,000 simulated random samples. The
distributions are summarized in terms of their means, medians, standard
deviations, and 5th and 95th percentiles. Consider the rWG(J) mean for the five-item Change Commitment
scale. Its sample value was 0.87. Simulations under the uniform
(rectangular) null distribution indicate that the empirical distribution
has a mean of 0.11 and a 95th percentile of 0.25, which is much lower than the observed value of 0.87. Thus, the corresponding p-value is 0.00. Therefore, the conclusion is that based on the mean rWG(J) we reject the null hypothesis that there is no agreement in the ensemble of four vignette hospitals.
Table 6 reports for each scale the sample values for rWG(J) and ADM(J) for the four hospitals and the 95th and 5th percentiles of the null distributions for rWG(J) and ADM(J) respectively. For both scales, the sample values for rWG(J) for all four hospitals exceeded the 95th percentile of the null distribution for rWG(J). Likewise, for both scales, the sample values for ADM(J) for all four hospitals were smaller than the 5th percentile of the null distribution for ADM(J). These results indicate that sufficient
inter-rater agreement exists for each of the four hospitals to justify
the construction of an organizational readiness for implementing change
measure from individual-level perceptual data. The organization-level
means for the Change Commitment Scale and the Change Efficacy Scale for
each hospital are shown in second and third columns of Table 6.
Table 6
Significance tests for the means ofrWG(J)andADM(J)for each vignette hospital (study three)
Change commitment (CC)
Change efficacy (CE)
Simulation-based
Simulation-based
Sample values
Percentiles
Sample values
Percentiles
Vignette
CC mean
CE mean
rWG(J)
ADM(J)
0.95 rWG(J)
0.05 ADM(J)
rWG(J)
ADM(J)
0.95 rWG(J)
0.05 ADM(J)
Hospital 1
4.33
3.83
0.95
0.54
0.40
1.11
0.89
0.73
0.42
1.10
Hospital 2
3.21
2.33
0.83
0.85
0.42
1.10
0.89
0.69
0.44
1.09
Hospital 3
2.07
2.99
0.82
0.83
0.44
1.10
0.67
0.99
0.43
1.10
Hospital 4
2.07
2.14
0.86
0.71
0.42
1.10
0.83
0.78
0.42
1.10
Note:
Organizational readiness was manipulated in the vignettes as follows:
Hospital 1 high commitment-high efficacy; Hospital 2 high commitment-low
efficacy; Hospital 3 low commitment-high efficacy; and Hospital 4 low
commitment-low efficacy. The hospital-level means for change commitment
(CC) and change efficacy (CE) were consistent with the experimental
manipulation. For all four hospitals, the sample values for rWG(J) exceeded the 95th
percentile values of the empirical distributions derived from 100,000
simulated random samples. Likewise, for all four hospitals, the sample
values for ADM(J) were smaller than the 5th
percentile values of the empirical distributions derived from 100,000
simulated random samples. Therefore, for each hospital, we reject the
null hypothesis of no agreement based on the uniform (rectangular)
distribution.
Study four
Method
Design, participants, and procedure
For
study four we used a convenience sample of international
non-governmental organizational (INGO) staff (n = 311) from around the
world who responded to an online survey about their organizational
readiness to implement mobile technology for monitoring and evaluation
systems in health programs. All INGOs were based in the United States.
Of the study participants, 54.5% were men and 45.5% were women. Three
percent of respondents were under 25 years old, 35% were 25 – 35 years
old, 35% were 36 – 45 years old, 20% were 45 – 55 years old, and 7% were
older than 55. A total of 44% of respondents were based in the United
States and 56% were based in other countries (primarily in Africa).
Measures
The
online survey in this study included four items to assess change
commitment and five items to assess change efficacy. One of the five
change commitment items used in study two and study three (‘We will do
whatever it takes to implement this change’) was inadvertently dropped
in survey construction.
Analysis
We
conducted a two-factor CFA to assess factor structure, computed alpha
coefficients for the resulting scales to assess inter-item consistency,
computed ICC(1) and ICC(2) from a one-way random-effects ANOVA to assess
the reliability of organization-level means, and tested the statistical
significance of rWG(J) and ADM(J) to assess the validity of organization-level
means. For these assessments, we included only organizations (n = 10)
represented by more than five survey respondents.
Results
The
two-factor CFA model converged and demonstrated a good fit when change
commitment and change efficacy were allowed to correlate. The
comparative fit index (CFI) equaled 0.97, the Tucker-Lewis fit index
(TLI) = 0.96, the standard root mean square residual (SRMR) was 0.05 and
the root mean square error of approximation (RMSEA) was = 0.08. No
post-hoc modifications were necessary given the good fit indicated by
the fit indices; residual analysis did not indicate problems.
Standardized parameter estimates are provided in Table 7.
Table 7
Confirmatory factor analysis of organizational readiness for implementation items (study four)
CFA* standardized factor loadings
Mean
Standard deviation
I
II
C1. Are committed to implementing this change
3.07
1.33
0.928 (0.020)
C2. Are determined to implement this change
2.82
1.29
0.884 (0.025)
C3. Are motivated to implement this change
2.87
1.45
0.745 (0.044)
C5. Want to implement this change
3.29
1.32
0.824 (0.033)
E2. Can manage the politics of implementing this change
2.78
1.07
0.785 (0.043)
E3. Can support people as they adjust to this change
2.77
1.29
0.791 (0.042)
E5. Can coordinate tasks so that implementation goes smoothly
2.71
1.16
0.832 (0.037)
E6. Can keep track of progress in implementing this change
2.97
1.15
0.647 (0.058)
E7. Can handle the challenges might arise in implementing this change
2.91
1.29
0.743 (0.047)
Notes:
All items began with ‘We’ where ‘We’ referred to the respondent’s
global organization. All statements concluded with ‘to mobile technology
for MandE systems’.
*Standardized factor
loadings for two factor confirmatory factor analysis; Standard Error in
parenthesis for CFA: CFI = 0.9768 TLI = 0.955; SRMR = 0.052;
RMSEA = 0.08.
Alpha
coefficients for the four-item Change Commitment Scale and the
five-item Change Efficacy Scale were 0.91 and 0.89 respectively. The
correlation between the unit-weighted scale scores was similar to the
correlation between the factors (r = 0.60, p < 0.001).
The
one-way ANOVA for the Change Commitment Scale yielded an ICC(1) of 0.09
(p < 0.02), and an ICC(2) of 0.56. Using interpretative conventions,
the ICC(1) value approximates a ‘medium’ effect size and the ICC(2)
value suggests a moderate level of reliability [15, 25].
The one-way ANOVA for the Change Efficacy Scale yielded an ICC(1) of
0.02, and an ICC(2) of 0.16 (p <0.30). Using interpretative
conventions, the ICC(1) value indicates a ‘small’ effect size and the
ICC(2) suggests a low level of reliability. These correlations are lower
than those obtained in study three, where we could manipulate and
standardize the information that respondents received about the
readiness of the four hypothetical hospitals depicted in the vignettes.
However, these correlations are close to the values reported for
subjective measures in implementation studies in healthcare settings
(median = 0.04; interquartile range = 0.01 – 0.06) [26].
Although results would support the aggregation of individual-level data
into an organization-level mean for change commitment, they would not
support such aggregation for change efficacy.
A
different picture emerges from an analysis of the inter-rater agreement
statistics. For the Change Commitment Scale, the sample values for rWG(J) and ADM(J) for the ensemble of 10 INGOs were 0.82 and 0.72 respectively. For the Change Efficacy Scale, the sample values for rWG(J) and ADM(J) for the ensemble of 10 INGOs were 0.82 and 0.76 respectively. Table 8 summarizes the empirical distributions in terms of their means, medians, standard deviations, 5th percentiles, and 95th percentiles. For both scales, the sample values for rWG(J) for the ensemble of INGOs were larger than the 95th
percentile of their corresponding null distributions and the
corresponding p-values were almost zero. Likewise, the sample values for
ADM(J) for the ensemble of INGOs were smaller than the 5th percentile of their corresponding null distributions and the corresponding p-values were almost zero. Therefore, for both the rWG(J) and ADM(J) indexes, the null hypothesis of no agreement in
the ensemble of INGOs was rejected for both the Change Commitment Scale
and Change Efficacy Scale. Using interpretive conventions, the values
obtained for the ensemble of INGOs suggest ‘strong within-group
agreement’ for both change commitment and change efficacy [15, 27].
In contrast to the results for ICC(1) and ICC(2), these results would
support the aggregation individual-level into organization-level means
for both change efficacy and change commitment.
Table 8
Significance tests for the means ofrWG(J)andADM(J)for international non-governmental organizations (study four)
Distribution based on simulation
Variable
Mean
Median
Standard deviation
5thpercentile
95thpercentile
Sample values
p value
Change commitment (4 items)
ADM(J) mean
1.15
1.15
0.05
1.06
1.23
0.72
0.000
rWG(J) mean
0.20
0.19
0.08
0.07
0.33
0.82
0.000
Change Efficacy (5 items)
ADM(J) mean
1.15
1.15
0.05
1.07
1.22
0.76
0.000
rWG(J) mean
0.21
0.20
0.08
0.08
0.34
0.82
0.000
Note: For each of the four statistics (ADM(J) mean and rWG(J) mean for each scale), we obtained an
empirical distribution based on 100,000 simulated random samples. The
distributions are summarized in terms of their means, medians, standard
deviations, and 5th and 95th percentiles. Consider the rWG(J) mean for the four-item Change Commitment
scale. Its sample value was 0.82. Simulations under the uniform
(rectangular) null distribution indicate that the empirical distribution
has a mean of 0.20 and a 95th percentile of 0.33, which is much lower than the observed value of 0.82. Thus, the corresponding p-value is 0.00. Therefore, the conclusion is that based on the mean rWG(J) we reject the null hypothesis that there is no agreement in the ensemble of 10 INGOs.
Table 9 reports the sample values and the 95th and 5th percentiles of the null distributions for rWG(J) and ADM(J), respectively, for each scale for the 10 INGOs. In eight of the INGOs, for both scales the sample values for rWG(J) exceeded the 95th percentile of the null distribution and were smaller than the 5th percentile of the null distribution for ADM(J). These results indicate sufficient inter-rater
agreement for these eight INGOs to justify the construction of
organization-level means for change commitment and change efficacy from
individual-level data. For INGO 3 and INGO 8, the sample values for rWG(J) for the two scales did not exceed the 95th percentile of the null distribution nor were the sample values for ADM(J) for the two scales smaller than the 5th percentile of the null distribution for ADM(J). These results indicate insufficient
inter-rater agreement for two INGOs to justify the construction of
organization-level means for change commitment and change efficacy from
individual-level data.
Table 9
Significance tests for the means ofrWG(J)andADM(J)for each international non-governmental organization (study four)
Change commitment (CC)
Change efficacy (CE)
Simulation-based
Simulation-based
Sample values
Percentiles
Sample values
Percentiles
Vignette
CC mean
CE mean
rWG(J)
ADM(J)
0.95 rWG(J)
0.05 ADM(J)
rWG(J)
ADM(J)
0.95 rWG(J)
0.05 ADM(J)
INGO 1
4.54
4.00
0.92
0.60
0.62
0.94
0.83
0.72
0.67
0.95
INGO 2
4.30
4.30
0.90
0.67
0.77
0.79
0.87
0.72
0.75
0.86
INGO 3
4.02
4.35
0.57
0.90
0.79
0.74
0.78
0.82
0.81
0.76
INGO 4
3.37
3.41
0.85
0.69
0.76
0.80
0.91
0.60
0.81
0.79
INGO 5
4.03
4.15
0.81
0.76
0.57
1.00
0.82
0.82
0.61
1.00
INGO 6
3.94
4.39
0.96
0.45
0.70
0.85
0.92
0.52
0.70
0.88
INGO 7
4.08
4.37
0.84
0.69
0.42
1.08
0.89
0.65
0.45
1.09
INGO 8
3.48
3.50
0.67
0.94
0.69
0.89
0.55
1.07
0.70
0.92
INGO 9
3.72
3.98
0.88
0.69
0.73
0.84
0.83
0.81
0.60
0.91
INGO 10
3.94
4.20
0.80
0.79
0.61
0.96
0.82
0.80
0.61
0.99
Note: CC = change commitment scale (4 items); CE = change efficacy scale (5 items). For eight INGOs, the sample values for rWG(J) exceed the 95th
percentile values of the empirical distributions derived from 100,000
simulated random samples. Likewise, the sample values for ADM(J) were smaller than the 5th
percentile values of the empirical distributions derived from 100,000
simulated random samples. Therefore, these INGOs, we reject the null
hypothesis of no agreement based on the uniform (rectangular)
distribution. For two INGOs (INGO 3 and INGO 8), sample values for rWG(J) did not exceed the 95th
percentile values of the empirical distributions derived from 100,000
simulated random samples. Likewise, the sample values for ADM(J) were not smaller than the 5th
percentile values of the empirical distributions derived from 100,000
simulated random samples. Therefore, for these two INGOs, we do not
reject the null hypothesis of no agreement based on the uniform
(rectangular) distribution.
Discussion
In
this article, we provide psychometric evidence in support of a new,
brief, theory-based measure of organizational readiness for change,
which we call Organizational Readiness for Implementing Change (ORIC).
Content adequacy assessment indicated that the items that we developed
to measure change commitment and change efficacy reflected the
theoretical content of these two facets of organizational readiness and
distinguished these two facets from hypothesized determinants of
readiness. Exploratory and confirmatory factor analysis in the lab and
field study revealed two correlated factors, as expected, with good
model fit and high item loadings. Reliability analysis in the lab and
field study showed high inter-item consistency for the resulting
individual-level scales for change commitment and change efficacy.
Inter-rater reliability and inter-rater agreement statistics supported
the aggregation of individual level readiness perceptions to the
organizational level of analysis.
As
expected, the lab study provided stronger evidence than the field study
for the reliability and validity of organization-level means as
representations of organization-level measures of readiness. In the lab
study, we manipulated and standardized the information that study
participants received about the organizational readiness of the
hospitals depicted in the vignettes to implement meaningful use of
electronic health records. In the field study, we made no effort to
present study participants with consistent information about their
organization’s readiness to use mobile phone technology to monitor and
evaluate international health and development programs. Likewise, we
made no effort to select international non-governmental organizations
that might be expected a priori
to vary widely in organization readiness. To our knowledge,
organizational leaders made no effort to shape organizational members’
perceptions of readiness. Even under these conditions, organizational
members exhibited ‘strong agreement’ in their perceptions of
organizational readiness, and the overall level of readiness among the
set of participating organizations was high.
The discrepant results in the inter-rater reliability statistics [i.e., ICC(1) and ICC(2)] and inter-rater agreement statistics (rWG(J) and ADM(J)) for change efficacy highlight an important
difference in how these two types of statistics measure ‘similarity’ in
organizational members’ ratings. Inter-rater reliability indicates the
relative consistency (or rank order consistency) in ratings, whereas
inter-rater agreement indicate the absolute consensus (or
interchangeability) in ratings. LeBreton and colleagues [15]
observe that strong levels of inter-rater agreement can be masked by
subtle inconsistencies in the rank orders of ratings, especially when
the between-unit variance is restricted (e.g.,
all organizations are rated high or low). For example, two sets of
ratings on a seven-point scale (rater one = 7, 6, 6, 7, 7, 6, 6, 7, 7;
rater two = 6, 7, 7, 7, 7, 6, 6, 6, 7, 7) would generate a mean rWG(J) of 0.94 and an ICC(1) of only 0.04. LeBreton et al.
encourage investigators to examine multiple indicators of inter-rater
reliability and inter-rater agreement, but caution that one type of
statistic may be more relevant than another depending on the research
question. In this case, we were interested in the psychometric question
of whether individual perceptual data on readiness could be aggregated
to the organization-level of analysis. Our field study results suggested
that sufficient consensus existed within the INGOs to measure readiness
at the organizational level; however, our results also suggested, for
the participating INGOs, between-group variation in change efficacy
scores might be insufficient to warrant an organization-level analysis
of the determinants or outcomes of this facet of readiness.
Although
ORIC shows promise, further psychometric assessment is warranted.
Specifically, the measure should be tested for convergent, discriminant,
and predictive validity. Convergent validity could be assessed by
comparing ORIC to other reliable, valid, but much longer measures, such
as the Organizational Readiness for Change Assessment [5] or the Texas Christian University (TCU) Organizational Readiness for Change instrument [28].
Discriminant validity could be assessed by comparing ORIC to measures
of constructs related to, yet distinct from, organizational readiness
for change (e.g.,
organizational culture). Finally, predictive validity could be assessed
by examining the association of ORIC with hypothesized outcomes of
readiness, such as championing change and implementation effectiveness [8].
Assessment of predictive validity is particularly important for
determining whether organizational level readiness should be a key
priority for leaders of organizational change efforts.
Limitations
This
study had a few limitations. First, one item in the Change Commitment
Scale was dropped inadvertently in the field test in study four. Results
from our previous three studies suggest that including the item would
not have adversely affected the reliability and validity of the scale in
study four. Nevertheless, future field studies should check this.
Second, we carried forward to study two one item (i.e.,
‘We want to perform this change’) that did not satisfy the conditions
for content adequacy in study one. We did so because we believed
participants may not have had sufficient semantic context to determine
the meaning of ‘want.’ We obtained encouraging results for this item
from the exploratory and confirmatory factor analysis in the laboratory
study (study two and 3) and the confirmatory factor analysis in the
field study (study four). Nevertheless, further testing on this item is
warranted.
Third,
in study two and study three we asked graduate and undergraduate
students to assess organizational readiness as if they were an employee
of the hospital described in the vignette. This approach may raise
concerns about the validity of these data because the students are not
in fact hospital employees. However, we believe this approach is
appropriate for our study because it has been used in several previous
studies [29, 30],
the students were enrolled in programs (health policy and management or
health behavior) that familiarize students with healthcare settings,
and the results of our field test with actual employees (study four)
support findings from study two and study three.
Fourth,
we could not test for a higher-order organizational readiness for
change construct because the structural component of the model would be
under-identified with only two factors. Our field study results suggest,
however, that constructing a higher-order factor might not be advisable
given the moderate correlation of the Change Commitment and Change
Efficacy scales and the differences they exhibited in inter-rater
reliability. Researchers might wish to retain the scales rather than
combine them because they capture related, yet distinct facets of
organizational readiness to implement change.
Finally,
in study four we did not collect information about the efforts
organizational leaders undertook to increase readiness of employees.
Such information could have proved useful for assessing why inter-rater
reliability for the Change Efficacy Scale did not support aggregation of
the individual-level data into an organizational-level mean. For
example, it is possible that some individuals were provided more
information about the impending change than others, resulting in
different views on the organization’s readiness. Finally, because each
organization in study four exhibited a high level of readiness, it would
be useful to test ORIC in a sample with more variation in readiness
between organizations.
Conclusion
A
brief, reliable, and valid measure of organizational readiness for
change, such as ORIC, could advance implementation research and
practice. For research, such a measure would enable the testing of
theories about the determinants and consequences of organizational
readiness. Such advancements could lead to answers for a number of
important questions: Is organizational readiness for change important
for all types of changes and in all types of organizations? Is readiness
a necessary, but not sufficient, condition for effective implementation
of a change? Is there a readiness threshold that should be met prior to
beginning implementation of the change? Do all organizational
representatives need to be ready for the change, or is readiness only
important for specific groups of individuals? Healthcare leaders could
use answers to such questions, combined with ORIC, to assess
organizational readiness for change in their own settings. Doing so
would be useful for developing implementation strategies and allocating
resources for a specific change. Ultimately, valid measurement of
organizational readiness for change could reduce the number of health
organization change efforts that either do not lead to desired benefits
or fail altogether.
Appendix
Reliability: Variance Within and Between Groups
The
intraclass correlation coefficient (ICC) provides an indication of the
proportion of group-level variance. ICC(1) equals the correlation
between the values of two randomly drawn individuals from a single
randomly drawn group. This correlation is commonly interpreted as the
proportion of variance in a target variable that is accounted for by
group membership. ICC(2) represents the reliability of the group mean
scores and varies as a function of ICC(1) and group size, so that large
group sizes can result in high ICC(2) values, even if ICC(1) values are
low.
Values obtained from a One-Way Analysis of Variance (ANOVA)
ICC(1)=MSB−MSWMSB+(N−1)(MSB)
ICC(2)=MSB−MSWMSB
Where MSB = Mean Square Between; MSW = Mean Square Within; N = Number of Individuals in the Group.
Cohen et al. rWG(J)and ADM(J)
The index rWG(J)
compares the observed within-group variances to an expected variance
under the null hypothesis of no agreement. For a discrete scale of J
parallel items, rWG(J) is defined as:
Where s¯2 is the average of the observed variances on the J items, and σ2 is the variance of a null distribution
corresponding to some null response pattern. The most natural candidate
to represent non-agreement, which has often been used, is the uniform
(rectangular) distribution, accordingly for an item with number of
categories which equals A.
The ambiguity in choosing the right null distribution has been recognized as one of the drawbacks of using rWG(J) and motivated the introduction of alternative
indices. Burke et al. (1999) introduced the AD index, defined as
follows. For the j th item (j =1,… J):
ADM(j)=1n∑k=1n∣∣Xjk_X¯¯¯j∣∣
Where n is the number of respondents, Xjk is the k th respondent’s score on item j, and X¯¯¯j is the mean of the respondent’s score on item j. This statistic is also known as the mean absolute deviation.
The index ADM(J) is defined as the average of the ADM(J)’s over the J items.
ADM(J)=1J∑j=1JADM(J)
Declarations
Acknowledgements
This
project was supported by funded by the North Carolina Translational and
Clinical Sciences Institute, the National Institutes of Health (NIH)
Clinical and Translational Science Award (CTSA) at UNC-Chapel Hill
(UL1TR001111). Dr. Christopher M. Shea (KL2TR001109, UL1TR001111) and
Dr. Denise A. Esserman (UL1TR000083) were supported by the National
Center for Research Resources and the National Center for Advancing
Translational Sciences.
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Komité Avaliasaun, ne ' ebé prezide husi ema
sira ne ' ebé hili hosi Seniór Asosiadu Vise-Prezidente ba Estudante
Asuntu no Dekanu Estudante, serve hanesan komisaun permanente iha
Divizaun Estudante Asuntu sira-nia laran.
Membru komité koletivamente iha responsabilidade kona-ba avaliasaun koordenasaun no avaliasaun inisiativa ho Divizaun. Membru
komité sei inklui funsionáriu administrativu, klasifika no lisensiatura
asistente sira oin-oin kona-ba servisu iha Divizaun. Funsaun espesífika ba komité ida-ne'e inklui atu:
Promove kultura ida iha Estudante Asuntu ne ' ebé fó kbiit ba
funsionáriu sira iha departamentu idak-idak atu utiliza prátika
avaliasaun no avaliasaun ba dezenvolvimentu, ezekusaun, no refinement
kona-ba programa no servisu sira no atu inkorpora dadus iha planeamentu
estratéjiku no prosesu foti desizaun;
Identifika no implementa estratéjia atu halekar komunika avaliasaun no
avaliasaun dadus iha Divizaun no iha Universidade nuneʼe fakuldade,
funsionáriu no estudante sira bele hatene oinsá Divizaun apoia misaun
Universidade nian, nune'e mós oinsá sujestaun ne ' ebé afeta mudansa
pozitivu sira kona-ba programa, servisu, polítika no prosesu; Mantein kalendáriu anuál ida atu koordena no duplikasaun avaliasaun postu no avaliasaun esforsu; Fo oportunidade formasaun kontinua ne ' ebé maksimiza kapasidade membru funsionáriu kona-ba avaliasaun no avaliasaun prátika;
Avalia no rekomenda mudansa ba Rezultadu Aprendizajen Divizaun nian
hodi garante katak sira ne ' ebé aliña ho no avansa ba ema sira-ne ' ebé
tradisaun hosi Universidade; Halo revizaun ba planu avaliasaun postu no fornese komentáriu atu hadi'a kualidade no efikásia; no
Artezanatu definisaun operasionál ba informasaun ne ' ebé atu klarifika
oinsá fonte dadus iha relasaun ho constructs ne ' ebé hetan sukat
(ezemplu, iha eskola GPA oinsá mak ita hakarak atu sukat koléjiu pré
aptitude akadémiku entre estudante BGSU).
Garante estudante asesu ba kualidade, abranjente no cost-effective kuidadu saúde nian.
Hala'o avaliasaun nesesidade hodi utiliza no tailoring estabelese
avaliasaun instrumentu (ezemplu, UCLA Freshman Levantamentu, ACHA-NCHA,
fokus grupu). Avalia servisu atuál ne ' ebé bazeia ba nesesidade sai avaliasaun no servisu. Dezenvolve planu ba refinement servisu.
Halo revizaun atuál polítika kona-ba revizaun kolega, ajusta presiza ne
' ebé bazeia ba industria prátika di'ak liu, no asegura kumprimentu ba
Ashe adekuada hotu-hotu iha unidade. Dezenvolve/identifika programa no fó formasaun espesífika atu hadi'a servisu opiniaun kona-ba funsionáriu Ashe.
Identifika estratéjia atu kontinua servisu kustu ladún karu ba
estudante sira no atu garante forsa finanseira ne ' ebé naruk ba Ashe. Duplikasaun
prosesu atu nune'e hamenus burokrasia, brainstorm idea sira ba
efisiênsias, avalia redusaun fakar no kustu rendimentu, no dezenvolve
mota reseita foun.
Dezenvolve planu ida ba tinan 3-5 finanseiru estratéjiku ne ' ebé ho
kuidadu no transparente projetu oin-oin kona-ba finansiamentu senáriu no
prioridade sira. Planu sira tenke fó
matadalan ba desizaun finanseira ne ' ebé halo ba funsionáriu,
teknolojia, progresu ne ' ebé kapitál, no seluk-seluk tan.
Fornese servisu sentraliza estudante atu kapasita no promove saúde
fíziku, mentál no sosiál ba estudante UCLA hotu-hotu atu nune'e bele
ajuda sira hodi hetan susesu.
Apoiu atuál ka investiga oportunidade foun ba programa/funsaun ne ' ebé
bele fornese Ashe iha área sira kona-ba prevensaun no wellness
(ezemplu, Estudante Saúde 101 online revista tempo –). Alvu publisidade atu habelar koñesimentu kona-ba servisu Ashe no benefísiu UC RÓ. Liu tan dezenvolve portál sira nu'udar meiu ida ne ' ebé hato'o informasaun no kuidadu. Liu tan defini, avalia, no dezenvolve kuidadu primária fornesedór abordajen.
Hadi'a komunikasaun no kolaborasaun ho servisu UCLA seluk no unidade
(ezemplu, CAPs, Saúde, Edukasaun, Jules Stein, Sentru Med, kontaktu husi
resposta H1N1) atu nune'e bele fó prestasaun ida ne ' ebé koordenadu
liu kona-ba kuidadu.
Dezenvolve lubuk ida ne ' ebé luan kona-ba referrals no rekursu sira ba
estudante sira ho objetivu ida atu promove abordajen ida ne ' ebé
balansu no abranjente liu atu tau matan. Formalizasaun kona-ba lista kona-ba rekursu, no halo disponivel ba estudante sira hanesan surat ka liuhusi web ligasaun.
Fó ambiente rewarding, apoiu no seguru ba ita-nia funsionáriu sira.
Apoia ba kresimentu ne ' ebé profisionál liu husi identifikasaun no halo existe edukasaun kontinua. Hadi'a uza kona-ba Pesoál Jestaun Prosesu (PMP) liu husi formasaun kontinua no dezenvolvimentu jestores no superior. Halo
revizaun ba opsaun sira ba komentáriu directional barak, inklui veíkulu
ba funsionáriu sira ne ' ebé formál sujestaun kona-ba dezempeñu
jerente/superiór.
Halo avaliasaun ba nesesidade sira ne ' ebé internu liuhusi funsionáriu
satisfasaun levantamentu no hodi utiliza seluk instrumentu apropriadu
(ezemplu, pasta eleisaun diskusaun grupu). Adapta desfavoresidus prosesu no operasaun sira, bainhira apropriadu, atu responde ba benefisiu sira-neʼe.
Fó klareza no transparénsia kona-ba prioridade, papel no
responsabilidade tomak iha organizasaun tomak, inklui komité makeup no
papél iha prosesu foti desizaun. Garante katak deskrisaun servisu hotu-hotu mak oras ne'e.
Dezenvolve planu kontinjênsia Ashe atu nune'e bele fó la ' ós de'it
kontinuidade negósiu maibé mós seguransa no jestaun emerjénsia prosesu
hodi garante ambiente servisu ne ' ebé seguru ida.
Estabelese orientasaun ne ' ebé klaru kona-ba rekoñesimentu finanseiru
no seluk efetivu kona-ba dezempeñu funsionáriu no kontribuisaun sira.
Buka inovasaun teknolójiku nu'udar meius ida ba efisiênsias ne ' ebé boot liu no kualidade ne ' ebé di'ak liu kona-ba kuidadu.
Kria planu estratéjiku ida ba teknolojia, identifika tendénsia, buat
neʼebé importante liu, no estabelese timelines atu inkorpora foun ka
dezenvolve teknolojia hirak ne ' ebé promove efisiênsias kuandu nia sei
"respeita nesesidade individuál no valór umanu interasaun" (Estudante
Asuntu Planu Estratéjiku).
Standardize configurations hardware no software iha Sentru Ashe Nian atu
foti vantajen hosi folin ne ' ebé negosia universidade no komunikasaun
entre unidade no indivíduu.
Identifika no buka oportunidade sira ba dezenvolvimentu web no
teknolojia ne ' ebé sei rua atende nesesidade tratamentu no oportunidade
rendimentu ba Sentru Ashe Nian.
Hatama asaun-hotu hatene efisiênsias iha aspetu hotu-hotu kona-ba
operasaun Ashe, inklui kompra prioridade, fasilidade upgrades,
resiklajen no teknolojia nian.
munication no Kolaborasaun (Universidade Meta 1 no 7)
Identifika divizaun oin-oin inisiativa ida ne ' ebé mak sei lori
sentimentu ida ne ' ebé boot liután kona-ba unidade ba divizaun.
Kontinua hametin parseria ho Asuntu Akadémiku no jestaun Atendementu
hodi retention, lisensiatura no lisensiatura susesu akadémiku no
estudante sira ne ' ebé internasionál. Defini, kria no sustenta intensional pontu kontaktu entre Estudante Asuntu no Finansa no Administrasaun Haluan sira-nia relasaun ho parseiru sira iha komunidade no habelar estensaun. Mantein no promove relasaun pozitivu sidade/gown. Aumenta partisipasaun inan-aman sira, konforme apropriadu. Dezenvolve no implementa planu ida atu "fó-hatene ita-nia istória".
Diversidade (Universidade Objetivu 5)
Envolve, apoiu no lidera esforsu diversidade no inkluzaun iha se. Kria planu diversidade divisional hodi aliña ho planu estratéjiku no rekursu. Aumenta diversidade Estudante Asuntu funsionáriu sira. Fó korajen no apoiu ba envolvimentu funsionáriu iha diversidade no kompeténsia sira ne ' ebé kulturál abilidade harii.
Finanseiru-serbisu nuʼudar Atan no Fasilidade (Universidade Objetivu 7)
Harii instalasaun foun no renovate fasilidade sira ne ' ebé eziste tanba presiza.
Dezenvolve planu tinan tolu atu identifika fatin ida ne ' ebé
permanente ba eskritóriu divizaun ne ' ebé oras ne'e iha Conklin no
eskritóriu departamentu ne ' ebé dadaun ne'e lokaliza iha Math/Siénsia. Ho intensaun atu envolve divizaun iha inisiativa dezenvolvimentu; define knaar ida-ne ' ebé klaru ba Asuntu Estudante iha kampaña. Kontinua estensaun hodi alums ne ' ebé inklui uzu aumenta "Ida" sistema ba kódigu alums loloos. Aliña divizaun finansa kona-ba prioridade no mantein serbisu nuʼudar pozitivu atan estadu dólar amerikanu; identifika efisiênsias kuandu posivel. Aumenta reseita husi mota. Aumenta alfabetizásaun finanseiru ba divizaun pesoál.
Dezenvolvimentu Profisionál no Rekoñesimentu (Universidade Objetivu 6)
Kontinua atu promove no fó apoiu kona-bá dezenvolvimentu profisionál ba dezempeñu funsionáriu aumenta no aprendizajen. Dezenvolve planu ida ba atividade dezenvolvimentu profisionál populásaun divizaun.
Hakaʼas an atu hetan rekoñesimentu nasionál, rejionál ka lokál ba
fasilidade programátiku, no funsionáriu sira ne ' ebé individuál
accomplishments.
Teknolojia (Universidade Objetivu 7)
Maksimiza uza Campus Labs atu hetan ita-nia avaliasaun, avaliasaun no
objetivu benchmarking atu "fó-hatene ita-nia istória" entre votante
hotu-hotu. Kria planu ida
ne ' ebé intensional ba merkadu no promove rezultadu husi avaliasaun
inisiativa, ne ' ebé inklui uzu ba meiu komunikasaun sosiál.
Uza komentáriu capture mekanizmu atu dezenvolve dadus kona-bá ne ' ebé
iha relasaun ho estudante sira ne ' ebé aprende, partisipasaun no
atitude.
Timor-leste
nu’udár Nasaun illa Ki’ik ida ne’ebé
Dezenvolve hela ne’ebé mak ninia rikusoin nasionál nian hetan iha ninia rekursu
naturál. Ba jerasaun barak ona, Timor oan sira uza sira nia matenek kona-bá
ambiente nian hodi bele sobrevive iha ninia kondisaun sira ne’ebé dala ruma aat
liu.
Ezemplu ida ne’ebé sei uza nafatin to’o ohin loron,
Tara Bandu,dezenvolve husi Timoroan sira, husi kedas sira nia istória no
interasaun nian ne’ebé naruk ho ambiente, no kontribui ona ba ninia
konservasaun.
Timor-Leste riku iha diversidade étnika no kultura
nian, ne’ebé mak rezulta iha variasaun bara-barak iha sistema sira matenek indíjena
nian, lisan, no estrutura governasaun nian apezarde ninia área jeográfika ne’ebé
relativamente ki’ik. Mudansa maka’as ne’ebé akontese ona iha Timor-Leste foin
lailais ne’e, espesialmente dezde ninia independénsia iha tinan 2002, fó ona
impaktu sira ne’ebé boot tebes ba iha ambiente no mós sistema úniku sira husi
matenek tradisionál nian ne’ebé mak fó motivasaun ba ninia sustentabilidade.
INDICE
Titulo I
Introdusaun
Objetivu
1.Atu Estudante sira komprende
kona ba Papel komunidade ba progressu lei tradisional iha ambiente do suku
2.Atu estudante bele hatene konseitu
kona ba servisu apredisajem
3.Estudante sir bele komprende
hakerek sistematiku konseitu
Benifisiu
1.Benifisiu ba Estudante
2.Benifisiu ba Universidade
3.Benifisiu ba Ministeriu
Edukasaun.
Titulo II
Teoria
Papel komunidade
ba Mudansa lei tradisional iha ambiente do suku
dezenvolve estratejia ida hodi
responde ba kestaun sira hanesan hirak ne’ebé temi ona iha leten, no mós planu
asaun ida hodi implementa atividade sira tuir UNESCO nia programa sira SIDS no
Sistema Matenek Lokál ba period kada
Tinan. Ba dala uluk iha Timor-Leste, autoridade barabarak reprezenta governu, ONG sira, universidade sira no mós
líder komunitária sira halibur hamutuk hodi fahe sira nia perspetiva no
esperiénsia kona-bá matenek ekolójiku no prátika tradisionál sira, no
estabelese diálogu entre sira.
Matenek ambientál husi ema
lokál no raina’in sira nu’udár elementu
esensiál ida husi dezenvolvimentu sustentável nian no mós konservasaun ba
diversidade biolójika no kulturál nian, hirak-ne’e hotu, bele uza hodi
estabelese ninia rezisténsia hodi hasoru mudansa globál nian.
Atu rekoñese ninia importánsia
no iha kompromisu atu promove matenek lokál no Rai Nain nian ba dezenvolvimentu sustentável iha Suku.
Ida-ne’e refleta iha estratejia médiu prazu iha mos parte balun liu hosi ninia
Plataforma nian hodi implementa Estratejia ba Dezenvolvimentu Sustentável husi
Nasaun illa Ki’ik sira ne’ebé Dezenvolve hela, no mos Programa Seluk tan ne’ebe
Adisiona.
Instituisaun
akadémiku sira no mós líder komunitária sira hodi komprende kona-bá aspetu
oioin husi matenek ekolójiku tradisionál nian no haree oinsá mak ida-ne’e bele
integradu iha konservasaun ambientál no dezenvolvimentu sustentável iha Suku
Laran. hodi promove atividade sira iha Suku Laran, iha parseria ho parseiru
lokál sira.
Tradisionál Iha Kontestu Uma Lulik Nian
Uma lulik
sira distrito 13 iha Timor-leste Laran Tomak ,Sekretaría Estadu ba Kultura nian
no Haburas Foundation. Husi peskiza ida hakerek ona livru ida ho naran As uma
lulik do distrito de Ainaro ne’ebé sei publika iha Tinan 2011.
Uma lulik ho matenek tradisional:
definisaun provisorio
Tuir
ha’u-nia hanoin ita tenki haree uluk tiha ba artigu ida ho nia títulu mak maka foin
bele hakat ba kestaun seluk. Tan ne’e hanoin kona-ba termu sira hanesan uma
lulik ho matenek tradisionál. Define ona matenek tradisionál hanesan
koñesementu, prátika ho representasaun lubun ida ne’ebé tutan ho dinámiku.
Matenek ida ne’e rezultadu ne’ebé simu tutan mai husi povo -nia istória ho nia
relasaun ho natureza. Koñesementu sira ne’e iha
1.Estudante Universidade ka Instituisaun Superior
2.Licwnciatura,Mestradu,Doutoramentu .
Klarifikasaun Termus
1.Universu
simbóliku hanesan estrutura ba signifikadu sira ne’ebé ema
uza hodi koko esplika tansá mundu ne’e mak hanesan ne’e duni no mos tansá mundo
ne’e labele oin-seluk fali.
2.Kauza ne’ebé halakon matenek tradisionál
Ohin
loron matenek tradisionál barak lakon tiha-ona. Ha’u bele hato’o exemplu ida
husi ha’u-nia esperiénsia rasik bainhira halo peskiza. Iha momentu ha’u buka
hela relasaun siklu produksaun ekonómiku tradisionál ho matenek tradisionál
ha’u husu ba ema barak kona-ba fulan jentiu sira-nia naran ho sira-nia
signifia. Komesa husi tinan 2007 mai to’o agora ha’u hetan tetun terik ninian
de’it. 65 Ha’u nunka hetan resposta kompleta ho lian seluk
mai to’o agora.Balu sei hanoin-hetan fulan
ida ka rua nia naran, maibé sira nunka hatete tinan tomak nia fulan sira-nia
naran hotu kedas. Uluk antropólogu ida mai halo peskiza iha Timo-Leste hakerek
duni fulan sira-nia naran kompletu tanba ema Timor sei uza hela
(haree
Forbes 1884). Agora ema uza de’it fulan ne’ebé mai husi lian-portugués
(fulanFevreiro, fulan-Março, ho seluk-seluk tan), fulan-jentiu sira ne’e la uza
ona.
Matenek
tradisionál nia lakon akontese tanba kauza barak. Ida mak istória Timor-Leste
nian. Se ita haree ba istória bele hetan informasaun ne’ebé sei hatudu katak
destrukasaun uma lulik ho matenek tradisionál nia lakon komesa akontese ona
bainhira portugues sira tama Timor (haree de Castro 1867). Maski hanesan
ne’e ita bele hatete katak tempu ne’ebé matenek tradisionál lakon maka’as liu
maka sékulo XX nia laran. Akontese pelo menos dala haat:
Iha
2ª Guerra Mundial nia laran (fulan-Fevreiro 1942 to’o fulan-Janeiro 1943).
Momen-1. tu ida ne’e Japaun mai okupa Timor ho ema Timor 40.000 mate. Situasaun
ida ne’e
halakon
patrimoniu no matenek barak ne’ebé iha mos relasaun ho uma lulik. Funu-Sivíl
(1974). Iha momentu peskiza bainhira ami husu ba lia-na’in sira hodi-bain-2.
hira
maka sira-nia uma aat, balu hatán katak akontese duni iha momentu Funu-Sivíl.
Sira hatete katak maun-alin oho malu, sobu ka sunu sira-nia uma lulik.
Akontesemento ida ne’e ema barak tauk fó-hatene sai tanba to’o ohin balu sei
laran-moras hela. Ema balu hatete katak tanba ida-idak kaer partido ida-idak
mak sira ba hasoru malu, sai oho malu. Balu mos hatete katak ema fa’an partido
sira-nia naran hodi subar sira-nia hanoin aat (hanesan mos istória malu entre
fetosaa-umane ho problema seluk-seluk tan).
Invasaun
ho okupasaun indonesia (1975-1999). Iha tempu indonesia nia laran, uma 3. lulik
ho kultura no matenek tradisionál barak lakon tiha, liuliu iha momentu rua: ida
mak
momentu
Indonesia tama mai Timor, ida fali mak tempo milisia sira (1999) (McWilliam
2005: 1).
Akontesemento
iha tempu funu halakon matenek tradisionál barak loos. Tanba matenek ida ne’e
la’os aprende iha eskola maibé aprende rona husi inan-aman, fó no simu matenek
2. PROSESU NE ' EBÉ ENVOLVE IHA DEZENVOLVIMENTU NORMÁL NO ABNORMAL
2.1. eventu báziku kona-ba dezenvolvimentu normál labele 2.1.1. DNA no chromosomes 2.1.2. kontrolu transcriptional 2.1.3. kontrolu translational 2.1.4. kontrolu post-translational no importante tebetebes ba membrane proteins 2.1.5. placentation 2.2. abnormal dezenvolvimentu 2.2.1. jenétiku nu'udar kestaun 2.2.2. nutrisaun 2.2.3. krítiku no sensibilidade periodu durante dezenvolvimentu 2.2.4. abnormalities dezenvolvimentu placental 2.2.5. Toxicokinetics no toxicodynamics 2.2.5.1. transferénsia placental 2.2.5.2. biotransformation 2.2.6. estrutura-atividade relasaun
3.1.3.5. poder sira ne ' ebé estatístiku 3.1.3.6. quantifying estudu 3.2. estudu animál esperimentál 3.2.1. espésie 3.2.2. dosages no nivel dose 3.2.3. grupu kontrolu pozitivu 3.2.4. kontrole istóriku 3.2.5. dosing rejime sosiá 3.2.6. dalan ba administrasaun 3.2.7. Númeru kona-ba animál no análize estatístiku 3.2.8. nia observasaun kona-ba animál sira ne ' ebé isin-rua 3.2.9. nia observasaun kona-ba progeny 3.2.10. pekuária no prátika laboratóriu
4. POSTNATAL MANIFESTASAUN OIOIN
4.1. introdusaun 4.2. hahalok 4.2.1. estratéjia abut 4.2.1.1. behavioural funsaun atu avalia 4.2.1.2. koko atu uza iha estudu behavioural 4.2.1.3. atu hili espésie 4.2.1.4. variante bele kontrola 4.2.2. métodu avaliasaun kona-ba funsaun sira ne ' ebé espesífiku 4.2.2.1. dezenvolvimentu fíziku 4.2.2.2. dezenvolvimentu reflex 4.2.2.3. funsaun sensory 4.2.2.4. funsaun motor 4.2.2.5. atividade, reactivity no emotionality 4.2.2.6. dezenvolvimentu kognitivu 4.2.2.7. hahalok sosiál 4.2.3. relevánsia estudu behavioural ba risku ne ' ebé umanu avaliasaun 4.3. reproduction 4.3.1. normál gametogenesis no dezenvolvimentu, mutilasaun ba órgaun seksuál, konsepsaun-laek 4.3.2. mekanizmu dezenvolvimentu abnormal 4.3.3. teste prosedimentu 4.3.3.1. "fertilidade koko" kona-ba progeny tuir espozisaun maternidade 4.3.3.2. estudu multigeneration 4.3.3.3. atu hili espésie 4.3.3.4. doses, rute no durasaun tratamentu 4.3.3.5. aprezentasaun kona-ba rezultadu 4.4. transplacental carcinogenesis 4.4.1. prinsípiu no mekanizmu kona-ba asaun 4.4.1.1. sensibilidade komparativu adultus nian no organizmu ne ' ebé fetal ba carcinogens 4.4.1.2. dependénsia ba faze nian dezenvolvimentu maternidade 4.4.1.3. espésie no espesifisidade nesesiadade 4.4.1.4. mekanizmu organotropism 4.4.1.5. metabolism carcinogens industriais kímika i petrolífera iha nian organizmu materna, placenta, no embryo
4.4.2. relasaun entre teratogenesis no carcinogenesis 4.4.3. prinsípiu jerál kona-ba teste transplacental carcinogenicity 4.4.3.1. espésie 4.4.3.2. faze isin-rua 4.4.3.3. dose no dalan ba administrasaun 4.4.3.4. avaliasaun ba rezultadu 4.4.4. métodu ho potensia ba futuru 4.4.4.1. transplacental laran mediasaun akollimentu kultura 4.4.4.2. espozisaun pré no postnatal ba carcinogens no promove fatór 4.4.4.3. Intraamniotic no tama intrafetal téknika
5. IHA VITRO DEZENVOLVIMENTU NO NAUN-MAMMALIAN ANIMÁL SISTEMA: KANDIDATURA AGORA NO FUTURU
5.1. ámbitu vitro iha sistema dezenvolvimentu 5.2. esensiál no desirable karakterístika teste selesaun kurtu-prazu nian 5.3. sei hili kurtu-prazu ne ' ebé koko 5.4. sistema dezenvolvimentu disponivel 5.4.1. tomak-embryo kultura (animál warm-blooded) 5.4.1.1. faze maturation no preimplantation ovum 5.4.1.2. embryos mammalian postimplantation 5.4.1.3. chick embryo iha kultura 5.4.1.4. chick embryo iha ova 5.4.2. orgaun kultura 5.4.2.1. orgaun kultura limb buds 5.4.2.2. orgaun kultura pancreas nian 5.4.2.3. palatal shelves orgaun kultura 5.4.2.4. tooth anlagen orgaun kultura 5.4.2.5. ladi'ak ki'ik de'it orgaun kultura 5.4.2.6. kidney ki'ik de'it orgaun kultura 5.4.2.7. orgaun kultura gonads ki'ik de'it no sistema duct asesória 5.4.2.8. thyroid tissue orgaun kultura 5.4.2.9. sistema kultura orgaun seluk 5.4.3. kultura embryos naun-mammalian ka naun-avian 5.4.3.1. estudu kona-ba dezenvolvimentu ikan 5.4.3.2. estudu kona-ba dezenvolvimentu amphibia, lurchae, urchins tasi, no seluk invertebrates 5.4.4. sistema kultura Tissue 5.4.5. "cells namkari husi Micromass" kultura limb ki'ik de'it no lung 5.4.6. estudu ho tissues naun-ki'ik-de'it
