the meaning and measurement of productive engagement in later life
TRANSCRIPT
The Meaning and Measurement of ProductiveEngagement in Later Life
Christina Matz-Costa • Jacquelyn Boone James • Larry Ludlow •
Melissa Brown • Elyssa Besen • Clair Johnson
Accepted: 30 September 2013� Springer Science+Business Media Dordrecht 2013
Abstract This study draws from the work engagement literature to define engagement as
an indicator of role quality and to develop a measure—The Productive Engagement
Portfolio (PEP)—that can be used to assess engagement in work, volunteering, caregiving,
and informal helping among older adults. A Rasch measurement approach was used to
develop both Likert-based and semantic-differential-based measures of engagement across
4 roles. Items for both scales were developed through an iterative process that included
focus groups, 4 pilot tests, and one full-scale administration. Results suggest that the
psychological state of engagement can be conceptualized and measured on a meaningful
continuum defining a unidimensional and hierarchical construct ranging from lower to
higher levels of engagement. The technical characteristics of the items were found to be
C. Matz-Costa (&) � M. BrownGraduate School of Social Work, Boston College, McGuinn Hall, 140 Commonwealth Ave., ChestnutHill, MA 02467, USAe-mail: [email protected]
M. Browne-mail: [email protected]
J. B. JamesSloan Center on Aging & Work, Boston College, 3 Lake St. Bldg., 140 Commonwealth Ave., ChestnutHill, MA 02467, USAe-mail: [email protected]
L. Ludlow � C. JohnsonEducational Research, Measurement, and Evaluation Department, Lynch School of Education, BostonCollege, 336C Campion Hall, 140 Commonwealth Ave., Chestnut Hill, MA 02467, USAe-mail: [email protected]
C. Johnsone-mail: [email protected]
E. BesenCenter for Disability Research, Liberty Mutual Research Institute for Safety, 71 Frankland Rd.,Hopkinton, MA 01748, USAe-mail: [email protected]
123
Soc Indic ResDOI 10.1007/s11205-013-0469-6
invariant across each productive role type for both measurement approaches and the
meaning of person scores within a role were found to be independent of the response
format for both approaches. Using score conversion charts designed to translate the scale
scores into a form that is readily transparent and usable for practitioners, our scales can
easily and meaningfully chart a person’s level of engagement pre- and post-intervention.
The PEP instrument can also be used in survey research or by practitioners in community
or medical settings to assess the extent to which older adults are involved in roles that
enhance their overall quality of life.
Keywords Engagement � Role quality � Productive aging � Rasch measurement �Paid work � Volunteering � Caregiving � Informal helping
1 Introduction
Expectations about employment and other productive activities in later life are shifting. As
increasing numbers of older adults confront 15, 20, or even 30 years of relatively healthy
living beyond conventional retirement ages, society is just starting to grapple with how
older adults will want or need to spend their later life years and what their quality of life
will be. Policymakers and practitioners alike are being called upon to ensure that oppor-
tunities for purposeful living—which we know is critical to quality of life (Ryff and Singer
1998)—are available and accessible during these years. In order to accomplish this goal, it
is important to promote and support role involvement but also to enhance role quality.
Kahn (1990, 1992) suggests that quality is improved when individuals are psychologically
invested in role activities, i.e., engaged. Such engagement leads to active, full, and satis-
fying involvements rather than obligatory or emotionally bland ones. Understood this way,
role engagement can play an important role in one’s overall quality of life and may even
serve to promote and/or restore positive health and well-being in later life (e.g., Kielhofner
2008; Rowe and Kahn 1998a, b; Svanborg 2001).
Some roles appear to provide not only individual, but social benefits. Productive aging
proponents, for example, emphasize continued involvement in roles that produce goods or
services—whether paid or not (Herzog et al. 1989)—for maintaining health and vitality as
well as a sense of purpose in later life (Baker et al. 2005; Morrow-Howell et al. 2001).
These activities include paid work, caregiving, volunteering, and informal helping as
opposed to consumptive activities or activities that primarily benefit the individual (e.g.,
hobbies, watching TV, or exercising) (Morrow-Howell et al. 2001; Toepoel 2013).
The productive aging focus has received increasing attention as the movement toward
‘‘second acts for the greater good’’ gains momentum (e.g., encore.org). However, research
examining the effect of productive role occupancy per se on psychological well-being among
older adults has received mixed support (see Matz-Costa et al. in press). Further, while
several mechanisms have been purported to link role occupancy to health and well-being,
such mechanisms have not been empirically tested. This gap in the literature may be due, in
part, to inattention to role quality, and difficulties in measuring it across multiple roles.
Matz-Costa et al. (in press) make the distinction between engagement as involvement in
an activity (i.e., I engage in volunteer work on a regular basis) and engagement as one’s
subjective experience of an activity (i.e., I was very invested in my volunteer work today).
While studies of activity engagement in later life tend to focus on involvement, few studies
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have focused on engagement, perhaps due to the lack of measures that assess engagement
across productive roles (PRs). Thus, it is timely and important, from a research perspective,
to develop an ‘‘engagement portfolio’’ measure that can be used to empirically specify the
relationships among involvement, engagement, and health and well-being in later life.
Further, few tools exist to help practitioners who work with older adults in community or
medical settings to assess whether their clients assume different roles, such as caregiving
and volunteering, and the extent to which they are engaged (or not engaged) in these roles.
Such an assessment tool could help older adults to identify opportunities and barriers to
becoming involved in more positive, holistically engaging roles that could, in turn, have
important implications for health and well-being outcomes, both from a preventative as
well as restorative perspective.
The aim of the current study is to draw from the work engagement literature to define
engagement as role quality and to develop a measure—The Productive Engagement
Portfolio (PEP)—that can be used to assess engagement in PRs among older adults. By
proposing a definition and measure that is independent, or invariant, across diverse roles,
we demonstrate the robustness of the engagement construct and its applicability to a broad
range of PRs. We also emphasize the practical utility of our measure by going one step
further than most measure development studies to create score conversion charts that
translate PEP scale scores into a form that is readily transparent and usable for practitio-
ners. We focus on four PRs: workers (defined as those working for pay), volunteers
(defined as those providing unpaid work for a national or local organization), adult care-
givers (defined as those helping an adult who has trouble taking care of themselves), and
informal helpers (defined as those providing unpaid help to someone who does not reside
with them—excluding adult caregiving).
1.1 Conceptualizing and Measuring Engagement
Theories that specify how individuals occupy different roles to varying degrees can pro-
vide insight into subjective role quality. Goffman (1961) long ago distinguished between
role embracement, where individuals feel inseparable from their roles, and role distancing,
where individuals feel removed from their roles (e.g., feigning excitement). Each of these
states are indicators of subjective role quality. Kahn (1990) applied the notion of role
embracement to the work role specifically, asserting that individuals protect themselves
from being alienated, on the one hand, or overwhelmed on the other, by alternately pulling
away from and moving toward their work roles.
Kahn coined the terms ‘‘personal engagement’’ and ‘‘personal disengagement’’ to
describe these calibrations of ‘‘self-in-role.’’ He defined personal engagement as ‘‘the
simultaneous employment and expression of a person’s ‘preferred self’ in task behaviors
that promote connections to [the] work and to others, personal presence (physical, cog-
nitive, and emotional) and active, full performances’’ (Kahn 1990, p. 700). Kahn thus
conceptualized engagement as a unique and important motivational state characterized by a
desire to invest one’s valuable resources into a role performance and to persist despite
obstacles. Personal disengagement, conversely, was described as ‘‘the uncoupling of selves
from…roles…[where] people withdraw and defend themselves physically, cognitively, or
emotionally during role performances’’ (p. 694).
Several approaches to the measurement of work engagement have emerged in the
academic literature, four of which were informed by Kahn (1990). Rothbard (2001) and
Saks (2006) developed items to capture Kahn’s idea of psychological presence, while both
Measurement of Productive Engagement in Later Life
123
May et al. (2004) and Rich et al. (2010) created items to assess each of Kahn’s three
dimensions of engagement (physical, emotional, cognitive).
Two additional scales conceptualize engagement (or its components) as a continuum.
The Maslach Burnout Inventory (Maslach et al. 1996) measures burnout, whereas its
reverse measures engagement. Likewise, the reverse of the disengagement subscale of the
Oldenburg Burnout Inventory (Demerouti et al. 2003) is used to measure engagement.
In a third line of research, engagement is seen as a construct in its own right. In other
words, it is not viewed as part of the burnout continuum, but as the positive antithesis of
burnout theoretically. The Utrecht Work Engagement Scale (UWES) (Schaufeli and
Bakker 2003), one of the most oft-cited measures of engagement in the academic literature,
defines it as ‘‘a positive, fulfilling work-related state of mind characterized by vigor,
dedication, and absorption’’ (Schaufeli et al. 2006, p. 702).
Each of these measurement efforts has made important contributions to the field and has
informed the current study in many ways. Like Rothbard (2001), May et al. (2004), Saks
(2006), and Rich et al. (2010), our measure is informed by Kahn’s theory. Similar to
Maslach et al. (1996) and Demerouti et al. (2003), we a priori theorized engagement as a
construct existing on a continuum, albeit one that ranges from low engagement to high
engagement, as evidence suggests that burnout is not necessarily the direct opposite of
engagement (Demerouti et al. 2010). Finally, like Schaufeli et al. (2006), we see
engagement as an affective-cognitive state, though we seek to expand this conceptuali-
zation to other PRs. In our view, engagement is characterized by positive affective and
cognitive states while performing any PR, not necessarily limited to work. Therefore, we
contend that work engagement represents just one of many settings within which varying
levels of engagement occur.
2 Method
2.1 Construct Definition
We see engagement as a situation-activated, affective-cognitive state. Engagement is
defined as:
A positive, enthusiastic, and affective connection with a role that both motivates and
energizes individuals. Engagement is characterized by a high degree of investment of
personal energies (whether physical, cognitive, or emotional) into a role, being
highly focused on the role activities to the point where other thoughts and distrac-
tions melt away, and an expression of genuine interest in the role.
Highly engaged individuals feel enlivened and invigorated by their PRs. Low
engagement is characterized by a lack of investment of personal energies (physical, cog-
nitive, or emotional), a lack of focus (distracted or thinking about other things), and a lack
of interest in role activities. Unengaged individuals feel indifferent about their role
involvement—in essence they are just ‘‘showing up’’.
Our instrument seeks to capture engagement as a unidimensional construct that assesses
different levels of interest, focus, and energy experienced while enacting a role. While
existing measures of work engagement generally conceptualize engagement as having
three dimensions, empirical psychometric tests have been largely inconclusive as to the
extent to which a 3-, 2-, or 1-factor model best fit the data. For example, some studies have
failed to find a clear factor solution for the UWES using exploratory or confirmatory
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approaches (e.g., Muilenburg-Trevino 2009; Sonnentag 2003). Thus, it is usually recom-
mended that the items can be treated as 1 factor for analyses, scoring, and reporting
(Schaufeli and Bakker 2003).
We argue that at the highest level of engagement, the facets of interest, energy, and
focus come together such that they cannot be disentangled. We also suggest that the
construct of engagement should be measured on an explicit continuum, ranging from
unengaged to highly engaged. As individuals move up the engagement continuum, we
theorize that they will exert more energy, display greater focus, and express higher interest
in their activity.
Given this definitional framework, we employed a Rasch measurement approach as the
appropriate assessment strategy. This item response theory approach assumes that scale
items are hierarchical in their degree of progression up the construct ‘‘ladder’’ (e.g.,
increasing difficulty/intensity/endorsement/severity) (Rasch 1960/1980). Item parameter
estimates then pertain to the difficulty of items ranging from an easier to achieve affective-
cognitive state (e.g., just showing up) through a more difficult to achieve affective-cog-
nitive state (e.g., immersing oneself completely in an activity). Person parameter estimates
pertain to the level of engagement that people have achieved on the continuum. Hence we
get a clear description of the level of interest-energy-focus that characterizes a low scoring
person versus the level of interest-energy-focus that characterizes a higher scoring person.
None of the existing instruments reviewed here were designed to explicitly include hier-
archically structured items (although some have applied item response theory—Rasch or
otherwise—in a post hoc fashion to scales that had been developed under classical test
theory assumptions, e.g., Gonzalez-Roma et al. 2006).
Our theoretical mapping of the construct in a hierarchical, multi-faceted fashion can be
seen in Table 1.
2.2 Item Generation
The items for each PEP scale, i.e., one each for work (PEP-W), formal volunteering (PEP-
V), adult caregiving (PEP-C), and informal helping (PEP-H), were generated through an
iterative process to ensure both face and content validity. We first generated an item pool
based on the theoretical framework described above, along with feedback from three 1.5-h
focus groups with older adults in community settings. We developed two parallel pools of
items using two different scaling approaches, one in which response options ranged from 1
(strongly disagree) to 7 (strongly agree)—a Likert-based approach (Likert 1932)—and
another in which respondents were asked to choose his or her position on a 7-point scale
between two bipolar adjectives or concepts—a semantic differential approach (Osgood
1952).
A common concern in the measurement of positive psychological constructs is
acquiescence bias (Friborg et al. 2006), which can occur when scales consist only of
positively worded items. The traditional remedy, however, of transforming positive items
into their reverse, ‘‘… may introduce errors, as negations of positive constructs may
appear contra-intuitive’’ (Friborg et al. 2006, p. 873) and may lead to an artificial factor
structure since positively worded items and negatively worded items tend to factor
separately (Bakker and Demerouti 2008). Friborg and colleagues, using a measure of
resilience, found that a semantic differential response format, in which some of the items
were presented in their negative form by placing the positive differentials on the right for
half of the items and on the left for the rest, effectively reduced acquiescence bias
without diminishing psychometric properties. We employed a semantic differential
Measurement of Productive Engagement in Later Life
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approach as a complementary measure of engagement in an effort to address these
potential weaknesses.
In both approaches (Likert-based—named PEP-WL, PEP-VL, PEP-CL, and PEP-HL—
and semantic differential—named PEP-WSD, PEP-VSD, PEP-CSD, and PEP-HSD), we
devised items that explicitly captured low, low moderate, moderate, high moderate, and
high levels of engagement, guided by our theoretical mapping of the engagement construct
presented in Table 1. This meant crafting items to represent low to high engagement for
each of our theoretical domains (interest, focus, and energy) for each of our four PRs. We
originally conceptualized perseverance as a fourth domain but later collapsed it with
energy to maintain a natural wording of items.
Scale development proceeded through four pilot samples and one full scale admin-
istration. Pilot 1 was conducted with friends, family and co-workers to gain feedback on
the extent to which the item wording and response options were clear or confusing.
Pilot 2 was conducted with older adult volunteers from community settings to get
feedback on the degree to which the items across the PRs appropriately captured their
lived experiences. Pilot 3 was conducted with graduate students in research methods
and psychometrics courses to ask about double-barreled item structures, preferences for
different response options, ambiguity in terms, and transparency in ‘‘correct’’ responses.
Pilot 4 was aimed at producing a sample of 50 older adults in each of three roles—paid
work, volunteering, and caregiving—in order to run initial Rasch models to explore
how the items were functioning. Respondents were recruited from Survey Sampling
International’s (SSI) diverse web panel of survey respondents ages 50–64 and age 65
plus.
Each pilot was analyzed and revisions made before the next was administered—words
were eliminated or replaced when they were confusing, items were dropped when
redundant, and new items were added to fill in gaps in the engagement continuum. Thus, an
initial pool of items was developed that worked well across each of the PRs and for each of
the response formats. The 17 initial Likert and semantic differential items are presented in
Table 2. A high total score on either the Likert-based scale or the semantic differential
scale indicates a higher level of engagement. Scores could range from 17 to 119.
Table 1 Theorized hierarchical mapping of the engagement construct
Interest Energy Focus
Highengagement
Strongidentification/embracement
Receives energies back frominvolvement
Completely wrapped up in it,in a positive way/transcendent
Highmoderateengagement
Becomes fun/like play
Devote a lot of personal energies andwant (am motivated) to keep devotingenergies/persevere
Time passes quickly/thoughts of other thingsfade to the background
Moderateengagement
Enthusiastic/excited
Devote significant personal energies toit/at least some discretionary effort
Focus in
Lowmoderateengagement
Basic interest Invest enough energy to do a good job Pay attention
Lowengagement
Uninterested/Bored
Invest the minimum amount of energy toget by/Give up when pushed
Unattentive/distracted
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Table 2 Semantic differential and likert-based item pool generation
Semantic differential item Likert-based item Theoreticaldomain
Label
1 When it comes to my activities, Iusually [go well above and beyondwhat is required/do the minimumrequired] (REV)
When it comes to my activities, Iusually go well above and beyondwhat is required
Energy
2 When it comes to my activities,getting so focused that I forgeteverything else around me is[easy/difficult] (REV)
When it comes to my activities,getting so focused that I forgeteverything else around me is easy
Focus F2
3 Pushing myself to accomplish goalswithin my activities is something[I avoid/I really enjoy]
Pushing myself within my activitiesis something I really enjoy
Energy E3
4 To say I feel invigorated when I aminvolved in my activities would be[an understatement/anexaggeration] (REV)
To say I feel invigorated wheninvolved in my activities would bean understatement
Energy E1
5 When I am involved in my activities, Iusually find that [time goes byslowly/time flies]
When I am involved in my activities, Iusually find that time flies
Focus
6 When it comes to my activities, Iusually feel [enthusiastic/indifferent] (REV)
I feel enthusiastic about myactivities
Interest I3
7 When I am involved in my activities,other thoughts and worries [are onmy mind/fade to the background]
When I am involved in my activities,other thoughts and worries fade tothe background
Focus
8 When I am involved in my activities,it feels like [a chore/fun]
When I am involved in my activities,it feels like fun
Interest
9 When I am involved in my activities,I usually [give my full attention/tend to pay only minimalattention] (REV)
When I am involved in my activities,I usually give my full attention
Focus F3
10 To me, my activities are[fascinating/rather unstimulating](REV)
To me, my activities are fascinating Interest I2
11 When I am involved in my activities, Iusually [welcome distractions/resistdistractions]
When I am involved in my activities, Iusually resist distractions
Focus
12 For me, experiencing strong positiveemotions when involved in myactivities (like inspiration, pride,or passion) is [atypical/typical]
For me, experiencing strong positiveemotions when involved in myactivities (like inspiration, pride,or passion) is typical
Interest I1
13 When it comes to investing myphysical, intellectual, and/oremotional energy into my activities,I usually [am eager to do so/have toforce myself] (REV)
I am eager to invest my physical,intellectual, and/or emotional energyinto my activities
Energy
14 I find my activities to be [dull/interesting]
I find my activities to be interesting Interest
Measurement of Productive Engagement in Later Life
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2.3 Sample
The full-scale, formal administration of the 17-item PEP was stratified for activity
involvement: 120 paid workers, 120 volunteers, 120 caregivers, and 120 informal helpers.
Participants were asked to complete both scales (Likert-based and semantic differential)
for just one of their current activities. The 480 individuals ranged from age 50–89
(M = 63.18; SD = 8.32). Respondents were 60.6 % female; 38.8 % with a bachelor’s
degree or higher; 90.9 % Caucasian; 57.9 % married/cohabitating; and 92.1 % living
independently. The sample was obtained using the same approach as pilot 4 described
above, with the stratification for age and activity involvement yielding 120 respondents per
role, rather than 50.
Respondents’ involvement in each of the roles was determined using questions derived
from the Americans’ Changing Lives Study (House 2003). Paid employment was assessed
by asking respondents whether they currently work for pay; volunteering by asking if they
did volunteer work in the last 4 weeks for any national or local organization (e.g., a church
or other religious organization, a school or educational organization, etc.); caregiving by
asking if they currently were involved in helping a friend or relative age 18 or older who
has trouble taking care of themselves because of a physical or mental illness, disability, or
for some other reason (includes caring for them directly or arranging for their care by
others); and, informal helping by asking if they provided unpaid help in the last 4 weeks to
someone who does not reside with them (excluding ill/disabled), including providing
transportation, shopping, running errands, helping with housework or car maintenance, or
providing childcare.
2.4 Rasch Measurement Model
As described more fully in Ludlow et al. (2013), the Rasch model (1960), in addition to
being a statistical model to estimate item response probabilities, proposes measurement
principles that aid in the construction of a ‘‘set of well chosen test problems’’ (p. 78). These
include the notion that the construct can be conceptualized as a continuum ranging from
lower to higher levels, the items should demonstrate wide variation and uniform spread
Table 2 continued
Semantic differential item Likert-based item Theoreticaldomain
Label
15 For me, getting so wrapped up inmy activities that I practicallyhave to tear myself away is [afrequent occurrence/a rareoccurrence or does not happen](REV)
I frequently get so wrapped up inmy activities that I practicallyhave to tear myself away
Focus F1
16 When I am involved in my activities,I usually feel [bursting withenergy/sluggish] (REV)
When I am involved in my activities,I usually feel bursting with energy
Energy E2
17 When it comes to my activities, I[barely invest the energy necessaryto complete the job/invest theenergy necessary to do a good job]
When it comes to my activities, Iinvest the energy necessary to do agood job
Energy
Bold indicates items retained in the final 9-item scale
C. Matz-Costa et al.
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defining the hypothesized continuum, and the items should be hierarchical in their pro-
gression along this continuum.
Based upon these principles, the initial set of items were written, administered and
analyzed. Decisions about which items to retain or revise were guided first and foremost by
our theoretical construct mapping (Ghiselli et al. 1981). Thus, items that did not display a
close match between their theoretical and empirical ordering along the engagement con-
tinuum were discarded. Second, we sought consistency in the progression of items across
all PRs. Our goal was to develop a measure of engagement that was invariant across all 4
role types. Hence, items were discarded when the hierarchical progression differed sig-
nificantly across roles or across Likert-based and semantic differential approaches. Third,
to be sure that each of our theoretical domains (interest, energy, and focus) was adequately
sampled at the low, moderate and high levels of our proposed construct hierarchy, we
retained at least three items per domain. However, we also sought to keep each of the eight
possible scales (four roles-by-two measurement approaches) as short as possible. Finally,
items that were highly ‘‘misfitting’’ under the Rasch model (described in further detail
below) were omitted as well as items with the lowest factor analysis loadings. The final
9-items, bolded in Table 2, represent those that best met the above criteria across PRs and
that were thought to be meaningful and representative of the theoretical engagement
domain.
2.5 Statistical Analyses
The Rasch rating scale model (Andrich 1978; Rasch 1960; Wright and Masters 1982) was
employed for analyses of the eight sets of items. This model is appropriate when the
response categories have an order in their probability of response that stays the same across
all the items in a scale—whether the scale is Likert-based or semantic differential-based.
The model produces for each item and person a ‘‘difficulty’’ and ‘‘level of engagement’’
estimate, respectively. These estimates are reported as logits (Wright and Masters 1982;
Ludlow and Haley 1995). Higher scoring (highly engaged) people and harder to achieve or
agree with items will have positive logit estimates while lower scoring (not highly
engaged) people and easier to achieve or agree with items will have negative estimates. As
shown below, these person and item estimates simultaneously portray the progression of
the items as they define the continuum forming the engagement construct and the location
of each person’s level of engagement along the continuum. The WINSTEPS software
package (Wright and Linacre 1998, Version 3.73.0) was used for these analyses.
3 Results
Figure 1 contains the ‘‘variable map’’ for the Volunteer Engagement Semantic Differential
Scale (PEP-VSD). This specific role and measurement approach was chosen to illustrate
the features and details that a Rasch analysis yields. The other seven scale variations
underwent the same analysis and interpretation process.
The left column in Fig. 1 represents individual persons (designated by pound signs and
periods) and the right column represents individual items (designated by abbreviations
which are keyed to Table 2). The items are ordered by their logit estimates from easiest to
positively endorse (bottom of the map) to hardest to positively endorse (top of the map).
Similarly, the participants are ordered from lowest scoring (bottom of the map) to highest
scoring (top of the map). Only high scoring people are expected to strongly endorse the
Measurement of Productive Engagement in Later Life
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hard items (and all items below the hardest ones). Similarly, low scoring people are
expected to strongly endorse only the easiest items and weakly endorse, if at all, the items
above them. The ‘‘M’’ to the right represents the mean item difficulty—which is set for
Fig. 1 Map of Rasch measurement person and item hierarchies for the volunteer semantic differential scale(PEP-VSD, item numbers keyed to Table 2). Person n = 120, Item n = 9; each ‘‘#’’ is 3 persons, each ‘‘.’’ is1–2 persons, the ‘‘=’’ indicates that 6 empty lines were deleted. The map was restricted to be consistent withthe maps of other roles, i.e., persons scoring above ?2 are located at 2 on this map
C. Matz-Costa et al.
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statistical reasons at zero. The ‘‘A’’ to the left represents the person average level of
engagement. If we are successful in terms of Rasch principles, our engagement scale
should progress meaningfully along a continuum of easier-to-harder to endorse engage-
ment levels.
As seen in Fig. 1, starting at the bottom of the volunteer engagement variable map it is
easiest to fully endorse item F3 (give my full attention), followed by item I3 (feel
enthusiastic). I2 (activities are fascinating) is slightly harder, followed by E3 (enjoy
pushing myself to accomplish goals), E2 (feel bursting with energy), and I1 (experience
strong positive emotions). A slight gap occurs in the item distribution and F2 (get so
focused that I forget everything else around me) and E1 (feel invigorated) group together
near the top. F1 (get so wrapped up I have to tear myself away) defines the highest level on
the volunteer engagement variable because it is the hardest to fully endorse.
Together, the items form a ‘ladder that persons climb’ as they become more and more
engaged. The ordering is consistent with our a priori theorizing represented in Table 1 and
while there are some gaps in the structure of the variable—particularly between Il and
F2—overall, there is excellent coverage of the engagement continuum for the volunteer
role with the semantic differential response format.
Analysis of each of the variable maps across the PRs and measurement approaches
(Likert-based and semantic differential) are strikingly similar in terms of the mapping of
the engagement continuum. As shown in Figs. 2 and 3, the easiest (F3: give my full
attention) and hardest (F1: get so wrapped up I have to tear myself away) items are the
same across all PRs and across both measurement approaches. The remaining items,
though not in identical ordering across all eight maps, show great similarity in their
placement. For example, we see consistency in the placement of the energy items across
each of the eight maps, with E1 (feel invigorated) as the most difficult energy item to
endorse, followed by E2 (feel bursting with energy), with E3 (enjoy pushing myself to
accomplish goals) as the easiest energy item to endorse. The similarities in the person-item
maps across roles and across measurement approaches provides strong empirical evidence
that (1) the psychological state of engagement is theoretically the same, regardless of the
role, and (2) engagement can be conceptualized (and measured) on a continuum ranging
from low to high engagement.
High correlations between item difficulties for pairs of items across the various roles
(e.g., PEP-WL and PEP-CL, r = .84–.96) and scoring formats (e.g., PEP-WL and PEP-
WSD, r = .90–.97) indicate that the meaning of engagement is the same across role and
format. Also, high correlations (r = .70–.85) between person scores across approaches
(e.g., PEP-WL and PEP-WSD) indicate that the meaning of engagement for a person
produces the same score interpretation regardless of which scoring approach is taken.
3.1 Goodness-of-Fit
Rasch goodness-of-fit analyses for both items and persons are generally based upon
residuals, i.e. the difference between an observed response and the response expected
under the statistical model (Wright and Masters 1982; Ludlow 1983). The INFIT, reported
in Table 3, is a variance-weighted average of the squared standardized item residuals.
Positive ZSTD (similar to a z-statistic) and MNSQ values larger than 1.0 occur when
responses are unexpectedly high or low. Negative ZSTD and MNSQ values less than 1.0
occur when responses are more consistent than expected. We chose to use moderate-valued
criteria in order to not overlook indications of misfit and we used them in combination with
Measurement of Productive Engagement in Later Life
123
one another. Hence we focused on MNSQ values greater than 1.4 and ZSTD values greater
than 3.0.
Given that there are (9 items*8 scales) = 72 fit statistics to consider and that some
percentage may be expected to be relatively large simply due to chance, we observe only
six instances where one of the items provoked unexpected responses on one of the 72
combinations of roles and measurement formats: (1) F1 on Volunteer-L; (2) F2 on Work-L;
(3) F3 on Caregiving-L; (4) E1 on Caregiving-L; (5) F1 on Work-SD; and (6) I1 on
Caregiving-SD. There appears to be no item-specific, measurement format-specific, or
role-specific problem although caregiving did have three instances out of 18 possible
where some degree of unexpected responses occurred (Table 4).
Fig. 2 Maps of Rasch measurement person and item hierarchies across roles for semantic differential scales(item numbers keyed to Table 2). Person n = 120, Item n = 9; each ‘‘#’’ is 3 persons, each ‘‘.’’ is 1–2persons, each‘‘=’’ indicates that 5 empty lines were deleted. Maps were restricted to show an identical rangeacross roles, i.e., persons scoring above ?2 are located at 2 on these maps
C. Matz-Costa et al.
123
One of the purposes of developing both Likert-based scales and semantic differential
scales was to assess whether a semantic differential approach could mitigate against the
afore-mentioned acquiescence bias. Like many existing work engagement scales (e.g., the
UWES), only positively keyed Likert-based items were included in the final analyses due
to the fact that in initial piloting all reverse-keyed Likert-based items were discarded
because they did not meet the criteria described above. The semantic differential format,
however, allowed for half of the items to be negatively keyed while also meeting item
retention criteria. But did this approach actually reduce the acquiescence bias? The
‘‘person separation’’ statistics (Wright and Masters 1982) ranged from 2.76 to 3.58 for the
Likert-based scales and from 1.89 to 2.17 for the semantic differential scales, suggesting
that the semantic differential approach did not, in fact, address this issue any better than the
Likert-based approach (see Ludlow et al. 2013).
Fig. 3 Maps of Rasch measurement person and item hierarchies across roles for likert-based scales (itemnumbers keyed to Table 2). Person n = 120, Item n = 9; each ‘‘#’’ is 3 persons, each ‘‘.’’ is 1–2 persons.Maps were restricted to show an identical range across roles, i.e., persons scoring above ?2 are located at 2on these maps. Person mean ‘‘A’’ for the volunteer role fell outside the displayed range of the map at 2.54
Measurement of Productive Engagement in Later Life
123
Ta
ble
3R
asch
item
fit
stat
isti
csfo
rre
duce
d9-i
tem
bes
tfi
ttin
gm
odel
s:li
ker
t-bas
edver
sion
Item
Wo
rkV
olu
nte
erC
areg
ivin
gIn
form
alh
elpin
g
dIn
fit
MN
SQ
Infi
tZ
ST
Dd
Infi
tM
NS
QIn
fit
ZS
TD
dIn
fit
MN
SQ
Infi
tZ
ST
Dd
Infi
tM
NS
QIn
fit
ZS
TD
(1)
F1
1.2
11
.10
.81
.35
1.4
53
.0.8
21
.07
.51
.53
1.2
82
.0
(2)
F2
.37
1.4
22
.8.9
01
.27
1.9
.42
1.0
4.4
.73
1.3
92
.5
(3)
F3
-1
.52
1.0
3.2
-1
.54
.93
-.4
-1
.59
1.4
73
.1-
1.7
0.9
4-
.4
(4)
E1
.42
1.1
91
.4.8
11
.02
.2.4
31
.59
3.8
.42
.72
-2
.1
(5)
E2
.43
.83
-1
.3.4
1.7
5-
1.9
.32
.65
-2
.9.2
8.8
0-
1.5
(6)
E3
-.0
1.8
4-
1.2
-.1
31
.05
.4.1
4.6
1-
3.4
-.2
7.7
7-
1.7
(7)
I1.0
1.8
9-
.8-
.45
1.1
-.3
91
.07
.6-
.35
1.1
31
.0
(8)
I2-
.17
.85
-1
.1-
.38
.85
-1
.1.2
7.7
6-
1.9
.42
.98
-.1
(9)
I3-
.73
.77
-1
.7-
.96
.63
-2
.9-
.43
.69
-2
.5-
1.0
6.7
5-
2.0
Sep
.a5
.88
6.4
15
.70
6.9
8
aS
ep.
refe
rsto
‘‘se
par
atio
n’’
—th
eex
tent
tow
hic
hth
eit
ems
are
no
n-o
ver
lap
pin
gin
thei
rd
efinit
ion
of
the
con
stru
ct.
Itis
the
rati
oo
fth
est
andar
dd
evia
tio
no
fth
eit
emes
tim
ates
toth
em
ean
stan
dar
der
ror
of
tho
sesa
me
esti
mat
es
C. Matz-Costa et al.
123
Tab
le4
Ras
chit
emfi
tst
atis
tics
for
reduce
d9-i
tem
bes
tfi
ttin
gm
odel
s:se
man
tic
dif
fere
nti
alver
sion
Item
Work
Volu
nte
erC
areg
ivin
gIn
form
alhel
pin
g
dIn
fit
MN
SQ
Infi
t
ZS
TD
dIn
fit
MN
SQ
Infi
t
ZS
TD
dIn
fit
MN
SQ
Infi
t
ZS
TD
dIn
fit
MN
SQ
Infi
t
ZS
TD
(1)
F1
.83
1.4
73.2
.91
1.1
61.2
.74
1.3
22.3
1.2
01.3
32.4
(2)
F2
.01
1.1
41.0
.58
1.0
6.5
.15
1.2
31.7
.47
1.4
62.9
(3)
F3
-1.2
3.7
2-
2.1
-.9
91.3
32.2
-.9
71.1
21.0
-1.1
2.7
9-
1.8
(4)
E1
.66
1.0
8.7
.64
1.4
32.9
.52
1.0
2.2
.47
.81
-1.3
(5)
E2
.19
.52
-4.3
.00
.51
-4.3
.12
.68
-2.7
-.1
5.7
1-
2.4
(6)
E3
-.4
41.0
9.7
-.1
5.9
9.0
-.3
8.7
5-
2.1
-.3
81.1
31.1
(7)
I1.1
71.2
71.9
.04
1.3
32.2
-.2
21.6
94.6
.05
1.2
01.5
(8)
I2.0
7.8
4-
1.2
-.3
7.6
9-
2.5
.20
.44
-5.5
.08
.69
-2.5
(9)
I3-
.26
.66
-2.8
-.6
6.5
0-
4.5
-.1
7.6
8-
2.8
-.6
3.6
4-
3.3
Sep
.a5.7
75.3
35.1
06.3
6
aS
ep.
refe
rsto
‘‘se
par
atio
n’’
—th
eex
tent
tow
hic
hth
eit
ems
are
non-o
ver
lappin
gin
thei
rdefi
nit
ion
of
the
const
ruct
.It
isth
era
tio
of
the
stan
dar
ddev
iati
on
of
the
item
esti
mat
esto
the
mea
nst
andar
der
ror
of
those
sam
ees
tim
ates
Measurement of Productive Engagement in Later Life
123
4 Discussion
The purpose of this study was to propose a definition of engagement that is invariant across
role types, and to present evidence of a new, Rasch-based (1960) measure of engagement
in the later life productive activities of paid work, volunteering, caregiving, and informal
helping—the PEP. Evidence suggests that the PEP scales hold promise for illuminating the
lived experiences of role involvement among older adults. Specifically, results of Rasch
measurement models provide strong empirical support that: (1) the psychological state of
engagement can be conceptualized and measured on a meaningful continuum defining a
unidimensional and hierarchical construct ranging from lower to higher levels of
engagement; (2) the technical characteristics of the items are invariant across diverse PRs
for both Likert-based and semantic differential approaches; and (3) the meaning of person
scores within a role is independent of the response format. These findings demonstrate the
robustness of the engagement construct and its applicability to a broad range of PRs.
While the semantic differential scales were not found to address acquiescence problems
frequently observed within Likert-based measures of positive psychology constructs, they
did allow for both positively- and negatively-keyed items to be included in the scale, which
can be beneficial in flagging respondents who are not reading questions carefully.
4.1 Value of the Engagement Scales
The importance of defining and assessing this indicator of role quality for an older adult
population within PRs is evident in research that has demonstrated a relationship between
involvement in PRs and measures of health and subjective well-being, such as life satis-
faction, positive self-concept and reduced rates of depression and mortality (Baker et al.
2005; Bambrick and Bonder 2005; Lum and Lightfoot 2005; Rozario et al. 2004). The
mechanisms through which these activities exert their effects on health and subjective
well-being are unclear, but insights from the work engagement literature suggest that
engagement may play a key role in this process (Bakker and Leiter 2010; Torp et al. 2013).
The present investigation contributes to the building of a nomological net (Cronbach and
Meehl 1955) for a more broadly conceptualized engagement construct that can be used to
examine these pathways more fully.
4.2 Practical Applications of the Engagement Scales
Since scores on Rasch scales represent a person’s location within a carefully scaled series
of items, one is able to directly interpret what a given score on the measure means along
with what it would take to move an individual from a given location on the scale to a
higher one. We take the Rasch approach one step further than most Rasch measure
development studies by creating score conversion charts (see Tables 5, 6) which make it
possible to delineate how the actual raw scores of people translate into locations on the
engagement variable and what it means to be at a particular location. For example, say a
person had a score of 36 on the Likert-based version of the volunteer scale (PEP-VL-
Table 5). We can say that this individual has low to moderate engagement on our scale and
on average, feels neutral about the items that were placed on the item hierarchy at roughly
this level and those just above this level, but slightly disagrees with the items at the highest
level and agrees to some extent with the items below this level. More specifically a score of
36 on the PEP-VL suggests that the person tends to give his or her full attention, feels
enthusiastic, sometimes experiences strong positive emotions, may find their activities to
C. Matz-Costa et al.
123
Ta
ble
5S
core
con
ver
sio
nch
art:
lik
ert-
bas
edv
ersi
on
Work
Volu
nte
erC
areg
ivin
gH
elpin
gE
ngag
emen
t
level
Des
crip
tion
of
score
Des
crip
tion
of
engag
emen
tex
per
ience
Item
s
63
63
63
63
Hig
hes
t
engag
emen
t
Thes
epeo
ple
stro
ngly
agre
ew
ith
all
item
s
54–62
54–62
54–62
54–62
Extr
emel
y
hig
h
engag
emen
t
On
aver
age,
thes
epeo
ple
agre
eor
stro
ngly
agre
ew
ith
ever
yit
em
Com
ple
tely
wra
pped
up
inth
eta
sk,
toth
e
poin
tof
hav
ing
tote
arth
emse
lves
away
.
Extr
emel
yfo
cuse
d,
ener
giz
ed,
and
inte
rest
edin
the
task
44–53
45–53
41–53
44–53
Hig
h
engag
emen
t
Thes
epeo
ple
–to
var
yin
gdeg
rees
–gen
eral
ly
agre
ew
ith
all
the
item
s
Alw
ays
giv
efu
llat
tenti
on—
toth
epoin
tth
at
they
forg
etab
out
oth
erth
ings.
Fas
cinat
ed
by
acti
vit
ies
and
freq
uen
tly
exper
ience
stro
ng
posi
tive
emoti
ons.
Invig
ora
ted
by
acti
vit
ies
and
ver
ym
uch
enjo
ypush
ing
them
selv
es;
hav
eto
tear
them
selv
esaw
ay
from
the
task
F1:
Hav
eto
tear
myse
lf
away
(W,
V,
C,
H)
40–43
41–44
39–40
40–43
Hig
h
moder
ate
engag
emen
t
On
aver
age,
thes
epeo
ple
feel
neu
tral
about
the
item
sin
this
sect
ion
and
inth
eab
ove
sect
ion.
They
agre
eto
som
eex
tent
wit
hth
e
item
sin
the
bel
ow
sect
ions
Giv
efu
llat
tenti
on,
feel
enth
usi
asti
c,
exper
ience
stro
ng
posi
tive
emoti
ons,
find
acti
vit
ies
fasc
inat
ing,
and
hav
ea
lot
of
ener
gy.
Not
nec
essa
rily
invig
ora
ted
by
acti
vit
ies,
nor
sofo
cuse
dth
atev
eryth
ing
else
isfo
rgott
en.
Does
not
hav
eto
tear
self
away
F2:
So
focu
sed
that
I
forg
etev
eryth
ing
else
(W,
V,
C,
H)
E1:
Fee
lin
vig
ora
ted
(W,
V,
C,
H)
E2:
Burs
ting
wit
h
ener
gy
(W,
V,
C).
I2:
Act
ivit
ies
are
fasc
inat
ing
(H)
36–39
36–40
37–38
36–39
Low moder
ate
engag
emen
t
On
aver
age,
thes
epeo
ple
feel
neu
tral
about
the
item
sin
this
sect
ion
and
the
above
sect
ion,
but
slig
htl
ydis
agre
ew
ith
the
item
inth
eto
pse
ctio
n.
They
agre
eto
som
e
exte
nt
wit
hth
eit
ems
inth
ebel
ow
sect
ions
Giv
efu
llat
tenti
on,
feel
enth
usi
asti
c,
som
etim
esex
per
ience
stro
ng
posi
tive
emoti
ons,
may
find
acti
vit
ies
fasc
inat
ing,
and
som
etim
eshav
ea
lot
of
ener
gy.
Not
nec
essa
rily
invig
ora
ted
by
acti
vit
ies,
nor
so
focu
sed
that
ever
yth
ing
else
isfo
rgott
en.D
o
not
hav
eto
tear
them
selv
esaw
ay
E3:
Push
ing
myse
lfis
som
ethin
gI
real
ly
enjo
y(W
,V,C
,H
)
I1:
Exper
ienci
ng
stro
ng
posi
tive
emoti
ons
typic
al(W
,V
,H
).
I2:
Act
ivit
ies
are
fasc
inat
ing
(W,
V,
C)
E2:
Burs
ting
wit
h
ener
gy
(H)
Measurement of Productive Engagement in Later Life
123
Tab
le5
con
tin
ued
Work
Volu
nte
erC
areg
ivin
gH
elpin
gE
ngag
emen
t
level
Des
crip
tion
of
score
Des
crip
tion
of
engag
emen
tex
per
ience
Item
s
27–35
27–35
27–36
27–35
Low en
gag
emen
t
On
aver
age,
thes
epeo
ple
slig
htl
ydis
agre
eor
feel
neu
tral
about
the
item
inth
isse
ctio
n,
and
are
likel
yto
be
neu
tral
tow
ard
the
item
inth
ebel
ow
sect
ion.T
hey
tend
todis
agre
e
wit
hit
ems
above
this
sect
ion
Giv
eth
eir
atte
nti
on,
but
do
not
hav
ehig
h
level
of
inte
rest
or
dev
ote
agre
atdea
lof
ener
gy
tota
sk
I3:
Fee
len
thusi
asti
c(W
,
V,
C,
H)
I1:
Exper
ienci
ng
stro
ng
posi
tive
emoti
ons
typic
al(C
)
9–26
9–26
9–26
9–26
Extr
emel
y
low
engag
emen
t
Thes
epeo
ple
dis
agre
e–to
var
yin
gdeg
rees
–
wit
hal
lit
ems
Do
not
pay
atte
nti
on
toth
eta
skan
ddo
not
dev
ote
ener
gy
nor
hav
ein
tere
stin
task
F3:
Giv
em
yfu
ll
atte
nti
on
(W,
V,
C,
H)
Ther
ear
ea
few
dis
crep
anci
esin
term
sof
whic
hit
ems
fall
inw
hic
hca
tegory
;it
emnum
ber
skey
edto
Tab
le2
C. Matz-Costa et al.
123
Ta
ble
6S
core
con
ver
sio
nch
art:
sem
anti
cd
iffe
ren
tial
ver
sion
Wo
rkV
olu
nte
erC
areg
ivin
gH
elp
ing
En
gag
emen
tle
vel
Des
crip
tion
of
score
Des
crip
tion
of
engag
emen
tex
per
ience
Item
s
63
63
63
63
Hig
hes
ten
gag
emen
tT
hes
ep
eop
lest
ron
gly
agre
ew
ith
all
item
s
54
–62
54
–62
54
–6
25
4–
62
Ex
trem
ely
hig
hen
gag
emen
t
On
aver
age,
thes
ep
eop
leag
ree
or
stro
ng
lyag
ree
wit
hev
ery
item
Com
ple
tely
wra
pp
edu
pin
the
task
,to
the
po
int
of
hav
ing
tote
arth
emse
lves
away
.E
xtr
emel
yfo
cuse
d,
ener
giz
ed,
and
inte
rest
edin
the
task
46
–53
46
–53
46
–5
34
6–
53
Hig
hen
gag
emen
tT
hes
ep
eop
le–
tov
ary
ing
deg
rees
–g
ener
ally
agre
ew
ith
all
the
item
sA
lway
sg
ive
full
atte
nti
on
—to
the
po
int
that
they
forg
etab
ou
to
ther
thin
gs.
Fas
cinat
edby
acti
vit
ies
and
freq
uen
tly
exp
erie
nce
stro
ng
po
siti
ve
emoti
on
s.In
vig
ora
ted
by
acti
vit
ies
and
ver
ym
uch
enjo
yp
ush
ing
them
selv
es;
hav
eto
tear
them
selv
esaw
ayfr
om
the
task
F1
:H
ave
tote
arm
yse
lfaw
ay(W
,V
,H
)
40
–45
41
–45
41
–4
54
1–
45
Hig
hm
od
erat
een
gag
emen
t
On
aver
age,
thes
ep
eop
lefe
eln
eutr
alab
ou
tth
eit
ems
inth
isse
ctio
nan
din
the
abo
ve
sect
ion
.T
hey
agre
eto
som
eex
tent
wit
hth
eit
ems
inth
eb
elo
wse
ctio
ns
Giv
efu
llat
ten
tio
n,
feel
enth
usi
asti
c,ex
per
ience
stro
ng
po
siti
ve
emoti
on
s,fi
nd
acti
vit
ies
fasc
inat
ing,an
dhav
ea
lot
of
ener
gy.
Not
nec
essa
rily
invig
ora
ted
by
acti
vit
ies,
nor
sofo
cuse
dth
atev
ery
thin
gel
seis
forg
ott
en.
Do
esn
ot
hav
eto
tear
self
away
F1
:H
ave
tote
arm
yse
lfaw
ay(C
)F
2:
So
focu
sed
that
Ifo
rget
ever
yth
ing
else
(V,
H)
E1
:F
eel
inv
igora
ted
(W,
V,
C,
H)
E2
:B
urs
tin
gw
ith
ener
gy
(W)
I1:
Ex
per
ien
cin
gst
rong
po
siti
ve
emoti
on
sty
pic
al(W
)
Measurement of Productive Engagement in Later Life
123
Ta
ble
6co
nti
nued
Wo
rkV
olu
nte
erC
areg
ivin
gH
elp
ing
En
gag
emen
tle
vel
Des
crip
tion
of
score
Des
crip
tion
of
engag
emen
tex
per
ience
Item
s
36
–39
36
–40
37
–4
03
6–
40
Lo
w mo
der
ate
eng
agem
ent
On
aver
age,
thes
ep
eop
lefe
eln
eutr
alab
ou
tth
eit
ems
inth
isse
ctio
nan
dth
eab
ov
ese
ctio
n,b
ut
slig
htl
yd
isag
ree
wit
hth
eit
emin
the
top
sect
ion
.T
hey
agre
eto
som
eex
ten
tw
ith
the
item
sin
the
bel
ow
sect
ion
s
Giv
efu
llat
ten
tio
n,
feel
enth
usi
asti
c,so
met
imes
exp
erie
nce
stro
ng
po
siti
ve
emo
tio
ns,
may
fin
dac
tiv
itie
sfa
scin
atin
g,an
dso
met
imes
hav
ea
lot
of
ener
gy
.N
ot
nec
essa
rily
invig
ora
ted
by
acti
vit
ies,
nor
sofo
cuse
dth
atev
ery
thin
gel
seis
forg
ott
en.
Do
no
th
ave
tote
arth
emse
lves
away
F2
:S
ofo
cuse
dth
atI
forg
etev
ery
thin
gel
se(W
,C
)E
2:
Burs
tin
gw
ith
ener
gy
(V,
C,
H)
E3
:P
ush
ing
my
self
isso
met
hin
gI
real
lyen
joy
(V)
I1:
Ex
per
ien
cin
gst
rong
po
siti
ve
emoti
on
sty
pic
al(V
,H
)I2
:A
ctiv
itie
sar
efa
scin
atin
g(W
,C
,H
)
28
–35
28
–35
28
–3
52
8–
35
Lo
w eng
agem
ent
On
aver
age,
thes
ep
eop
lesl
igh
tly
dis
agre
eo
rfe
eln
eutr
alab
ou
tth
eit
emin
this
sect
ion
,an
dar
eli
kel
yto
be
neu
tral
tow
ard
the
item
inth
eb
elo
wse
ctio
n.
Th
eyte
nd
tod
isag
ree
wit
hit
ems
abo
ve
this
sect
ion
Giv
eth
eir
atte
nti
on
,b
ut
do
no
th
ave
hig
hle
vel
of
inte
rest
inta
skI1
:E
xp
erie
nci
ng
stro
ng
po
siti
ve
emoti
on
sty
pic
al(C
)I3
:F
eel
enth
usi
asti
c(W
,V
,C
,H
)E
3:
Pu
shin
gm
yse
lf(W
,C
,H
)I2
:A
ctiv
itie
sar
efa
scin
atin
g(V
)
9–
27
9–
27
9–
27
9–
27
Ex
trem
ely
low
eng
agem
ent
Th
ese
peo
ple
dis
agre
e–to
var
yin
gdeg
rees
–w
ith
all
item
sD
on
ot
pay
atte
nti
on
toth
eta
skan
dd
on
ot
dev
ote
ener
gy
no
rh
ave
inte
rest
inta
sk
F3
:G
ive
my
full
atte
nti
on
(W,
V,
C,
H)
Th
ere
are
afe
wd
iscr
epan
cies
inte
rms
of
wh
ich
item
sfa
llin
wh
ich
cate
go
ry;
item
nu
mb
ers
key
edto
Tab
le2
C. Matz-Costa et al.
123
be fascinating, and sometimes has a lot of energy when carrying out this activity. They are
not necessarily invigorated by activities, nor so focused that everything else is forgotten
and they do not have to tear themselves away. This measurement approach not only
describes a person’s status at a given time point and the meaning of a person’s score on the
scale but also provides a roadmap for explaining change (either lower or higher on the
scale) after a second administration of the scale.
The ability to assess change is particularly useful in the development of interventions
(Mayhew et al. 2011), as research has suggested that engagement is indeed malleable
(Heslin 2010). Thus, our scales can easily and meaningfully chart a person’s level of
engagement pre- and post-intervention. The PEP instrument can also be used in survey
research or by practitioners in community or medical settings to assess the extent to which
older adults are involved in roles/activities that enhance their overall quality of life and to
identify opportunities and barriers to engagement.
Acknowledgments This work was supported by a grant from the Alfred P. Sloan Foundation’s Programon Workplace, Work Force and Working Families to the Sloan Center on Aging & Work at Boston College(grant numbers 2008-6-15, 2011-6-23); the Boston College Institute on Aging; the Graduate School ofSocial Work at Boston College; and a Boston College research incentive grant.
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