The Gerontologist
Vol. 40, No. 5, 531–539
Copyright 2000 by The Gerontological Society of America
Cognitive Status and Relocation Stress: A Test of
the Vulnerability Hypothesis
Jerrold Mirotznik, PhD, MPH,1 and Lenore Los Kamp, BSN, RN2
Purpose: This study investigated whether cognitively impaired nursing home residents are at particular risk of experiencing harmful effects during a mass, intra-institutional,
interbuilding relocation. Design and Methods: A pretest–
post-test experimental-comparison group design was used.
Data on cognitive status, functional capacity, psychosocial
health status, physical health status, and mortality were abstracted from the Minimum Data Set Plus and were analyzed
using continuous and discrete survival analyses, controlling for
covariates as well as baseline status of outcome variables. Results: None of the Relocation ⫻ Cognitive Status interaction effects were significant. Relocation main effects indicated that
movers in general were more likely than nonmovers to decline
in physical health status. Evidence also emerged for a positive
long-term effect of moving on psychosocial health status. Implications: These findings suggest cognitively impaired residents
are not at unusual risk of harmful effects as a consequence of
mass, interbuilding transfer. Given the significant relocation main
effects, though, caution must be taken in moving cognitively impaired residents, as it should be in moving any residents.
expectation that they will be discharged some time
prior to their death (Holmes, Teresi, & Monaco,
1992), residents also experience transfers out of
SCUs (Krovach, 1998).
In particular, two kinds of intra-institutional relocations have been noted to occur as a result of the establishment of an SCU in a facility: “Intrabuilding
transfers,” that is, moving residents from one room to
another within the same building, and “Interbuilding
transfers,” that is, moving residents out of one building into another building within the same nursing
home complex (Reingold & Werner, 1994).
Curiously, during this period as intra-institutional
transfers have increased in frequency, the number of
articles published on relocation effects has noticeably
declined (Mirotznik, 1995). Most research on this phenomenon dates from prior to 1985. Important questions remain, however. One such question concerns
whether cognitively impaired nursing home residents
are at particular risk of negative relocation effects. This
question takes on added significance given current
estimates that 48% of nursing home residents have a
diagnosed dementia (Leon & Moyer, 1999) and given
the increasing incidence of intra-institutional relocation of such residents as a consequence of the establishment of SCUs (Krovach, 1998).
The present study investigated a mass, intra-institutional, interbuilding transfer of long-term care nursing
home residents. Its aim was to determine whether
cognitive status moderated relocation effects.
Key Words: Cognitive impairment, Morbidity, Mortality, Intrainstitutional transfer
Since the mid-1980s there has been an enormous
proliferation of dedicated special care units (SCUs)
for nursing home residents with dementia (Ohta &
Ohta, 1988). As a consequence, an increase in the
occurrence of intra-institutional transfers among residents of long-term care facilities has undoubtedly occurred. The development of an SCU in a facility often
entails transferring residents out of an area to construct the unit (Reingold & Werner, 1994). Previously
admitted residents who meet the admission criteria of
a newly opened SCU may be relocated into the unit.
Residents admitted to non-SCUs who exhibit cognitive decline may be transferred into an already existing SCU (Weiner & Reingold, 1989). In addition, because about half of SCUs admit residents with the
Review of the Literature
It is a truism in the relocation literature that cognitively impaired nursing home residents are at particular risk of experiencing harmful relocation effects
(Blenkner, 1967; Goplerud, 1979; Kowalski, 1981;
Pastorello, 1975; Yawney & Slover, 1973). However,
a critical review of the literature indicates a lack of
adequate evidence to support this belief.
Typically, the moderating influence of cognitive status has been determined by contrasting subsets of movers in one of two ways: (a) by comparing relocated residents who are cognitively impaired with those who are
not impaired for differences on an outcome variable
(e.g., mortality and/or morbidity; Friedman et al., 1995;
This study was supported by Alzheimer’s Association Grant RG3-96003. We thank the administration of Metropolitan Jewish Health System
for its cooperation and Martin Piccochi for data management.
Address correspondence to Dr. Jerrold Mirotznik, Department of
Health and Nutrition Sciences, Brooklyn College, 2900 Bedford Avenue,
Brooklyn, New York 11210. E-mail: [email protected]
1
Department of Health and Nutrition Sciences, Brooklyn College.
2
Visiting Nurse Service of New York.
Vol. 40, No. 5, 2000
531
Kral, Grad, & Berenson, 1968; Lander, Brazill, & Ladrigan, 1997; Marlowe, 1974; Nirenberg, 1983) or (b)
by comparing relocated residents exhibiting deterioration on an outcome variable (e.g., those who died) and
those exhibiting no change (e.g., those who survived)
for a difference in terms of cognitive status (Aldrich,
1964; Guttman & Herbert, 1976; Lieberman & Tobin,
1983, pp. 150–153; Markus, Blenkner, Bloom, &
Downs, 1972; Miller & Lieberman, 1965; Ogren &
Linn, 1971). In general, studies that have compared
subsets of movers in these two ways have found evidence of a positive association between cognitive impairment and posttransfer deterioration. Specifically,
five studies found greater mortality among the cognitively impaired (Aldrich, 1964; Kral et al., 1968; Lieberman & Tobin, 1983, p. 152; Marlowe, 1974; Markus et
al., 1972), whereas two studies did not (Guttman &
Herbert, 1976; Ogren & Linn, 1971). And five studies
documented greater morbidity among the cognitively
impaired (Friedman et al., 1995; Kral et al., 1968;
Lander et al., 1997; Miller & Lieberman, 1965; Nirenberg, 1983), whereas three did not (Lieberman & Tobin,
1983, pp. 151–152; Marlowe, 1974).
Interpreting these subgroup differences as proof of
the greater susceptibility of the cognitively impaired
to relocation stress is, however, problematic. The
greater mortality and/or morbidity among relocated
residents who are cognitively impaired may merely
reflect the fact that such residents deteriorate at a
higher rate in general, regardless of the occurrence of
relocation (Coffman, 1981, 1983; Csank & Zweig,
1980; Goldfarb, Fisch, & Gerber, 1966; Tobin & Lieberman, 1976; van Dijk, Dippel, & Habbema, 1991).
In the terminology of analysis of variance (ANOVA),
differences among subgroups of relocated residents
may signify a main effect of cognitive status as opposed to an interaction between cognitive status and
relocation stress. The only way of disentangling these
possibilities is by contrasting cognitively impaired
and unimpaired movers to comparable groups of
nonmovers. Should movers who are cognitively impaired significantly deteriorate in comparison to their
controls, while movers who are cognitively unimpaired either not differ in outcome or improve in
comparison to their controls, one would be able to
conclude that cognitive impairment heightened vulnerability to relocation stress.
Four studies in the literature investigated the impact of cognitive status on relocation outcome by
contrasting a group of movers with an external control group of nonmovers. Of these, two failed to find
evidence in support of the greater vulnerability of the
cognitively impaired (Goldfarb, Shahinian, & Burr,
1972; Lieberman & Tobin, 1983, p. 149). Of the remaining two studies, one found moderately impaired
patients (Pruchno & Resch, 1988) and the other severely impaired patients (Csank & Zweig, 1980) to be
at greatest risk. A fifth study (Mirotznik, 1995), which
used relocated residents as they existed at any earlier
period as their own controls, found that moderately
cognitively impaired and unimpaired residents as a
group experienced more effects, including a positive
prerelocation and negative postrelocation response,
than did residents who were severely impaired.
In summary, of the 17 separate studies investigating the cognitive status vulnerability hypothesis, 12
lacked a comparison group of nonmovers and the remaining 5 have yielded contradictory findings. As
such, the evidence does not allow one to conclude
with confidence that cognitively impaired residents
are at particular risk of harmful relocation effects.
Further, given that only two studies (Mirotznik, 1995;
Pruchno & Resch, 1988) investigated the moderating
effect of cognitive status in an intra-institutional relocation, the question of how the cognitively impaired
react in this type of transfer warrants further research.
Theoretical Models
Three broad types of theoretical models have been
suggested to explain how cognitive status influences
relocation outcome. These explanations may be labeled stress-reaction models, coping models, and
stressor-coping models. Stress-reaction models assume that the cognitively impaired and unimpaired
experience relocation differently, that it involves a
differential degree of stress for these two groups.
Lawton and Simon’s (1968) environmental docility
hypothesis, for example, suggests that the cognitively
impaired are more dependent on their external environment and that, consequently, relocation involves
more of a disruption for them (Pruchno & Resch,
1988). (For another example, see Grad, in Csank &
Zweig, 1980.)
Coping models emphasize the lessened abilities
and resources of the impaired for dealing with relocation. Schulz and Brenner (1977) hypothesized that
perceived control and predictability during relocation influence outcome. This model suggests that the
cognitively impaired may not be able to buffer themselves from the stress of relocation by developing a
sense of personal control or by rendering the change
more predictable by availing themselves of preparation programs (Pruchno & Resch, 1988).
Stressor-coping models elaborate upon the particular aspects of the relocation stressor that induce
stress as well as incorporate the notion of the lack of
availability of coping resources. Csank and Zweig
(1980) suggested that the cognitively impaired are incapable of experiencing anxiety and deleterious effects in anticipation of relocation. Rather, stress results for the impaired from the actual relocation itself,
specifically, from loss of a familiar environment that
triggers an anxiety reaction. It is this anxiety reaction
coupled with a lack of coping resources that results
in heightened vulnerability to negative relocation effects. (For other examples, see Aldrich, 1964; Markus
et al., 1972.)
Two stressor-coping models distinguish the moderately from the severely impaired, but make different
predictions. Lieberman and Tobin’s (1983) pathognomonic sign model suggests that the severely impaired
may be so limited in their capacity to cope that they
are likely to experience deleterious effects regardless
532
The Gerontologist
of the degree of stress inherent in the particular relocation. The effect of relocation on those with adequate coping resources (i.e., the moderately impaired
and the unimpaired) would largely depend on the exact
nature of the relocation stressor. Pruchno and Resch’s
(1988) modified environmental docility hypothesis suggests the highly impaired are unlikely to be affected by
relocation because they lack the threshold capacity
needed for dependency on environmental cues. The
moderately impaired, in contrast, are very dependent
on such cues and, as such, experience relocation as
highly stressful. The unimpaired are also unlikely to
be affected because they have the coping reserves for
adjusting to change.
Zweig, 1980), Markus and colleauges (1972), and
Schultz and Brenner (1977). The modified docility
hypothesis, argued by Pruchno and Resch (1988),
suggests a curvilinear pattern, with those highest and
lowest in impairment exhibiting the fewest effects
and those with moderate impairment exhibiting the
greatest effects. Lastly, the pathognomonic sign
model of Lieberman and Tobin (1983) suggests a
nonlinear pattern, whereby individuals with high impairment would necessarily experience harmful effects, whereas those below that threshold level (i.e.,
the moderately impaired and the unimpaired) would
not. Hence, the following specific questions were addressed in this study:
Hypotheses
1. Are cognitively impaired residents less likely than
cognitively unimpaired residents to experience an
anticipatory stress reaction, that is, negative relocation effects manifested in preparation for or in
anticipation of the actual physical transfer?
2. Are cognitively impaired residents more likely
than cognitively unimpaired residents to exhibit
negative relocation effects during the impact and/
or settling-in stages of the relocation process?
3. Do severely or moderately cognitively impaired
residents exhibit more harmful postrelocation effects? In other words, do posttransfer effects manifest a linear, curvilinear, or a nonlinear pattern
with regard to cognitive status?
Several authors (Borup, 1981; Kasl, 1972; Pastorello, 1975; Tobin & Lieberman, 1976; Yawney &
Slover, 1973) have described relocation as a process
consisting of distinct stages: (a) a decision and preparation stage prior to relocation, also known as an anticipatory stage, (b) an impact stage within which the
actual physical transfer occurs, and (c) a settling-in or
long-term adjustment stage. Each of these stages may
have its own dynamics and its own potential for
stress (Tobin & Lieberman, 1976). During the first
stage, stress may result from anticipation of the imminent relocation. There is evidence to suggest that anticipation of life events, including relocation, can be
quite stressful (Kasl, 1972; Tobin & Lieberman, 1976;
Zweig & Csank, 1976). During the second stage,
stress may result from the physical move itself and
actual loss of a familiar environment, whereas during
the third stage it may result from the difficulty of adjusting to a new environment.
The theoretical models described above to explain
the greater vulnerability of the cognitively impaired
focus on events that occur during Stages 2 and 3 of
the relocation process. They suggest that the cognitively impaired are likely to exhibit negative effects as
a result of an actual change in their environment. Indeed, one of the models explicitly argues against the
possibility of the cognitively impaired experiencing
stress in anticipation of relocation (Csank & Zweig,
1980). On the basis of these models, therefore, one
would predict that the cognitively impaired, in comparison with the unimpaired, would be more likely to
exhibit deleterious effects postrelocation as opposed
to prerelocation.
Further, on the basis of the various models, it is
possible to derive competing predictions about the
pattern of these negative postrelocation effects. Several
of the models suggest a positive linear relationship
between cognitive impairment and negative effects.
For instance, the environmental docility hypothesis
(Lawton & Simon, 1968) implies that the more impaired
the individual, the more dependent he or she is on
his or her external environment and, consequently,
the greater the deleterious effects. Such a linear pattern also appears to be implied in the models of Aldrich (1964), Csank and Zweig (1980), Grad (Csank &
Vol. 40, No. 5, 2000
Methods
Setting
This study was conducted at two nursing homes
that were participating agencies of Metropolitan Jewish Health System (MJHS): Shorefront Jewish Geriatric Center and MJG Nursing Home, both located in
Brooklyn, New York. On July 1, 1994, all of the residents of Shorefront experienced a mass, intra-institutional, interbuilding relocation, moving into a new
replacement facility constructed next to their former
building. MJG Nursing Home, Shorefront’s sister facility, did not experience an equivalent move.
Residents were informed of the upcoming move in
January 1994. Also, at that time formal preparation
procedures began. Therapeutic recreation staff, social workers, and nursing staff provided residents
with information and emotional support, helped residents identify roommate preferences, helped select
belongings to take to the new facility, and, when
needed, introduced the residents to new staff and/or
other residents. Families of residents were also notified about the upcoming relocation and asked to provide support to the residents. During the postmove
period, staff continued to provide both emotional
support and information and were encouraged to
confer frequently with one another regarding residents’ coping and general health status.
Two points are noteworthy about this relocation.
First, given the preparation and support provided to
residents, this move needs to be seen as a best case
scenario. Should deleterious effects occur in this in533
stance, it would suggest that in interbuilding moves
without such preparation and support, there may be
a greater likelihood of harmful effects. A second
point concerns the fact that residents who underwent
the interbuilding transfer were aware at least 6
months prior to relocation that they were going to be
moved. As such, it is possible that during the months
prior to the move, some of the residents experienced
changes in health status in anticipation of relocation
(Mirotznik, 1995).
reliability, whereas, in comparison, the MDS items
for mood exhibited poorer reliability. Several groups
of investigators have documented that the MDS cognitive status items correspond closely with scores on
the Mini-Mental State Examination and also with
other measures of cognitive status (Hartmaier et al.,
1995; Morris et al., 1994; Phillips, Chu, Morris, &
Hawes, 1993). Mor and colleagues (1995), conducting a confirmatory factor analysis, documented that
MDS items representing the constructs of social engagement, mood problems, conflicted relationships,
and behavior problems factored as predicted. In contrast, Frederiksen, Tariot and De Jonghe (1996) found
that although the MDS measures of ADLs, cognitive
impairment, and communication correlated highly
with comparable rating scales scores, the MDS measures of problem behavior and mood did not. Similarly, using confirmatory factor analysis, Casten, Lawton, Parmelee and Kleban (1998) found evidence for
the hypothesized factor structure of the MDS measures of cognition, ADLs, and time use (MDS section
Sense of Initiative/Involvement), but not for social
quality (MDS section Unsettled Relationships), depression, and problem behavior. The findings for the
MDS continence items are mixed. Although Resnick,
Brandeis, Baumann, and Morris (1996) as well as
Hawes and associates (1995) found that these items
had excellent interrater reliability, Crooks, Schnelle,
Ouslander, and McNees (1995) documented a weak
and nonsignifciant correlation between MDS continence ratings and physical checks for wetness performed by nursing home staff.
Evidence suggests that MDS items may be less reliable for the cognitively impaired (Casten et al.,
1998), particularly those items based on staff observation and assessment (Phillips et al., 1993). MDS
items based on medical records exhibit the highest
interrater reliabilities that in practical terms differ
little between the cognitively impaired and intact
(Phillips et al., 1993). Evidence also indicates that
the internal consistency reliability of the MDS items
representing ADLs does not vary across levels of cognitive impairment (Phillips & Morris, 1997).
Study Design
The study used a variation of the pretest–posttest
experimental-comparison group design. The experimental group consisted of 405 residents at the Shorefront facility admitted by July 1993 who underwent
the interbuilding transfer. The comparison group
consisted of 383 MJG Nursing Home residents admitted to that facility by July 1993 who did not undergo
such a transfer. Although each nursing home had a
larger patient census, a number of residents from the
two facilities were excluded from the study. For example, given the focus on long-term nursing home
residents, at Shorefront 47 and at MJG Nursing Home
83 subacute residents (i.e., those admitted for shortterm rehabilitation and discharged back to the community relatively quickly) were excluded. In addition,
to increase the comparability of the experimental and
comparison groups, all Hospice and Maximum Care
Unit patients at MJG Nursing Home were excluded.
Data were collected on all participants for a 24month time frame, from July 1993 through June
1995, representing four periods. The months from
July 1993 through December 1993 constituted the
baseline period; January through June 1994 constituted the prerelocation period; July through December 1994 constituted the short-term postrelocation
period; and January 1995 through June 1995 constituted the long-term postrelocation period.
Data
Data for this study were derived from the Minimum Data Set Plus (MDS⫹), a federally mandated,
standardized clinical assessment form for monitoring
the functional and medical status of nursing home
residents (Morris et al., 1990). There has been some
discussion in the literature about the utility of nursing
home resident assessment instruments for the purpose of research. In particular, concerns have been
voiced about the reliability and validity of the MDS⫹
(Hawes, Phillips, Mor, Fries, & Morris, 1992; Teresi &
Holmes, 1992). In recent years, a number of studies
have investigated the psychometric properties of the
instrument, indicating that the MDS⫹ appears to
measure certain dimensions better than others.
Hawes and colleagues (1995) found that the MDS
items for areas such as cognition, activities of daily
living (ADLs), continence, disease diagnoses, and administered medication exhibited excellent interrater
reliability. Psychosocial well-being exhibited good
Measures
A comprehensive MDS⫹ assessment is completed
at admission, annually, and in response to a significant change in a resident’s status. In addition, quarterly reviews are completed every 3 months on a large
subset of the MDS⫹ items. To have the requisite data
to measure health status in each period of the study,
only those items included in the quarterly assessment
were used. This meant that for each 6-month study
period, each participant had available a minimum of
two completed MDS⫹ assessments.
MDS⫹ items recorded quarterly were further
screened in terms of their reported psychometric
properties. Items suggested by the literature to have
questionable reliability and/or validity, such as those
pertaining to mood, problem behavior, unsettled relationship, and continence, were excluded. It is worth
534
The Gerontologist
noting that these items also exhibited poor local internal consistency reliability (data not shown).
To operationalize cognitive status we used the
MDS Cognitive Performance Scale (CPS; Morris et
al., 1994). The CPS, which is based on five MDS
items (comatose status, ability to make decisions,
short-term memory, making self understood, and selfperformance in eating), classifies residents into seven
categories: intact (0), borderline intact (1), mild impairment (2), moderate impairment (3), moderately
severe impairment (4), severe impairment (5), and
very severe impairment (6). In one validation study,
the CPS explained 74% and 75% of the variance, respectively, in MMSE scores and scores derived from a
combination of the MMSE and the Test for Severe Impairment (TSI; Morris et al., 1994). In a second validation study, the CPS, also when tested against the
MMSE as a criterion variable, showed 94% sensitivity,
94% specificity, and 96% diagnostic accuracy as measured by the area under the receiver operating characteristics curve (Hartmaier et al., 1995). For the purposes
of our study, the seven CPS categories were collapsed
into three broader groupings: intact (0–1), moderate impairment (2–3), and severe impairment (4–6).
To determine if the CPS measure was behaving as it
should within our sample (i.e., exhibited local validity)
we subjected it to a number of tests. Following Morris
and colleagues (1994) lead, we crosstabulated CPS
scores with the clinical diagnoses of dementia. Although neurological diseases are known to be underdiagnosed in nursing homes (Barnes & Raskind, 1981),
we hypothesized that the prevalence of diagnosed
cases of dementia should still increase across the
three CPS categories. As seen in Table 1, this pattern
did indeed emerge. Second, following Phillips and
Morris (1997) we assessed the association of CPS and
ADL scores (see below for ADL measure). The overall
correlation was .50. Table 1 indicates that ADL dependence increased linearly across the three CPS categories. And finally, a considerable body of research
indicates that cognitively impaired residents are at
risk of deteriorating over time (van Dijk et al., 1991).
Table 1 shows that the more impaired a resident was,
the greater the chances of dying over the 2-year period of 1993–1995.
ADLs consisted of five items, concerning bed mobility, transfer ability, locomotion, dressing, and toilet
use, each of which was scored from 0 (independence) to 4 (total dependence). Responses to the
items were summed and divided by the number of
answered items. The Cronbach’s alpha for the ADL
measure was .94.
Psychological well-being, derived from the Sense
of Initiative/Involvement section of the MDS⫹, consisted of seven items (e.g., “at ease interacting with
others,” “at ease doing planned or structured activities”), each coded in our study so that 0 represented
yes and 1 represented no. All seven items were
summed for a composite score that ranged from 0 to
7. The Cronbach’s alpha for this scale was .73.
Physical health status was operationalized on the
basis of several MDS⫹ items abstracted from paVol. 40, No. 5, 2000
Table 1. The Association of the Cognitive Performance Scale
With Dementia, ADLs and Mortality
Cognitive Performance Scale
Criterion Variables
Intact
(n ⫽ 276)
Moderate
Impairment
(n ⫽ 221)
Severe
Impairment
(n ⫽ 291)
Diagnosis of
dementia (%)***
ADLs (M)***
Mortality (%)***
15.9
1.6
9.8
53.4
2.3
14.0
85.9
3.4
23.0
Note: ADLs ⫽ activities of daily living.
***p ⬍ .001.
tients’ medical records. Specifically, measures were
constructed of the number of (a) diagnosed diseases,
(b) conditions and signs/symptoms, (c) administered
medications, (d) emergency room transfers, and (e)
hospital admissions. As suggested above, we also
had data on whether the resident expired (mortality)
during the study period.
Data were also abstracted on the following covariates: age, gender, length of stay, Medicare or Medicaid payment source for nursing home stay, primary
language (English or other), marital status (ever or
never married), and race (White or non-White).
Analytic Approach
For mortality we used continuous survival analysis
for categorical time-to-event data. For ADLs, psychological well-being, and the five physical health status
measures we used discrete survival analysis (Allison,
1982). Our analytic approach made use of all of the
assessment data for each individual (i.e., up to 14 assessments during the study period). And it allowed
the modeling of the effects of relocation status, cognitive status, and the interaction of Relocation Status ⫻
Cognitive Status, while controlling for baseline values of outcome variables as well as of extraneous covariates.
The time periods were defined for mortality as
number of days from the start of the prerelocation period. For ADLs, psychological well-being, and the
five physical health status measures, the time periods
were the number of months during the study period.
For mortality, failure was defined as the occurrence
of death, and for the other outcome measures it was
defined as a decline in a resident’s health status from
baseline (i.e., the MDS⫹ assessment immediately
preceding the prerelocation period). Following Phillips and colleagues (1997), who used MDS data to
document the effects of residence in an Alzheimer’s
disease special care unit, the month of decline was
identified as the month at the midpoint between the
assessment noting the decline and the previous assessment. Also similar to Phillips and colleagues, decline was operationalized as a 1 unit increase in a
scale or count score. So a resident whose ADL score
or number of administered medications changed
535
since baseline from 3 to 4 exhibited such a decline.
Residents whose baseline ADLs and psychological
well-being scores indicated they could not decline
further were excluded from the analysis of these two
outcome variables. Residents who did not die or decline from baseline or who exited the two facilities
prior to the end of the study period were considered
censored at the time of their last assessment. Exit rate
was found not to be associated with relocation status,
cognitive status, or the interaction of these two variables.
A Cox regression was fit for mortality. In Step 1, relocation status (movers vs. nonmovers), cognitive status (represented by two dummy variables for moderate and severe impairment), and the two Relocation
Status ⫻ Cognitive Status interaction terms were entered. To address the issue of resident selection bias,
in Step 2 the covariates in terms of which the two
nursing homes differed at baseline were entered. The
proportional hazard assumption was evaluated by
entering in Step 3 interaction terms representing the
product of each independent variable with survival
time. Significant Covariate ⫻ Survival Time interactions were to be retained in the final version of the
equation, thereby adjusting for violations of the proportional hazard assumption (Kleinbaum, 1996; Singer &
Willett, 1991). Significant interactions between theoretically central independent variables (relocation
status, cognitive status, and their interactions) and
survival time were to be further explored by segmenting time into three periods (prerelocation, short-term
postrelocation, and long-term postrelocation) and by
testing the relative risk of death within each period
separately (Kleinbaum, 1996).
Discrete survival analysis was conducted using logistic regression (Singer & Willett, 1991). A separate
regression was run for ADLs, psychological well-being,
and the five physical health status measures. These
regressions followed the same steps as the analysis
for mortality, with two exceptions. Prior to entering
the theoretically central independent variables, each
outcome variable was regressed on 18 dummy variables, representing each month of the study. In addition, these equations adjusted for all baseline values
of the outcome variables as well as initial differences
between movers and nonmovers.
frequent diagnoses were arteriosclerotic heart disease
(45%), cataracts (39%), dementias other than Alzheimer’s disease (29%), anemia (28%), arthritis (28%),
hypertension (28%), Alzheimer’s disease (24%), and
cerebrovascular accident (22%).
Movers and nonmovers were similar in terms of
age, gender, psychological well-being, number of
emergency room transfers, and number of administered medications (Table 2). Movers were somewhat
less likely to have been married and to have their stay
paid by Medicaid. They were more likely to speak
English as a primary language, to be non-White, and
to have their stay paid by Medicare. Movers were
more cognitively intact, had a shorter mean LOS, and
were less dependent in terms of ADLs. They also,
however, had a greater number of diagnosed diseases, conditions and signs/symptoms, and hospital
admissions than nonmovers.
The hazard ratios for the theoretically central independent variables of relocation status, cognitive status, and their interactions appear in Table 3. All ratios have been adjusted for differences between
movers and nonmovers in baseline values of length
of stay, marital status, race, Medicaid coverage,
Medicare coverage, primary language, ADLs, diagTable 2. Comparison at Baseline of Movers and Nonmovers in
Terms of Selected Variables
Results
Participant Characteristics
Of the total sample of 788 residents, 75% were
women, 96% were White, with a mean age of 83
years and a 3-year length of stay (LOS). Seventyseven percent spoke English as their primary language. For most, the source of payment for their nursing home stay was a combination of Medicaid and
self-pay/private insurance (92% and 95%, respectively). Only 10% had their stays covered by Medicare. Fifteen percent had never married, 18% were
still married, 60% widowed, and 7% separated or divorced. About 46% needed extensive assistance or
were totally dependent in terms of ADLs. The most
Variables
Movers
Nonmovers
Age (M)
Gender (%)
Female
Male
Race (%)***
White
Non-White
Marital status (%)*
Never married
Married
Widowed
Separated
Divorced
Medicaid (%)***
Yes
No
Medicare (%)***
Yes
No
English as primary language (%)***
Yes
No
Cognitive status (%)***
Intact
Moderately impaired
Severely impaired
Length of stay (M years)***
ADLs (M)***
Psychological well-being (M)
Diagnosed diseases (M)***
Conditions/signs/symptoms (M)***
Administered medications (M)
Emergency room transfers (M)
Hospital admissions (M)*
82.6
83.2
74
26
76
24
94
6
99
1
18
14
61
2
5
12
22
60
3
3
88
12
96
4
14
86
6
94
84
16
69
31
47
29
24
2.6
1.9
5.1
4.8
0.2
2.5
.02
.08
22
27
51
3.6
3.1
5.3
3.1
0.1
2.0
.02
.04
Note: ADLs ⫽ activities of daily living.
*p ⬍ .05; ***p ⬍ .001.
536
The Gerontologist
nosed diseases, conditions/signs/symptoms, and hospital admissions. In addition, the hazard ratios for the
seven morbidity outcome measures were adjusted for
the baseline values of these measures. Further, as indicated in Table 3, certain ratios were adjusted for significant Covariate ⫻ Survival Time interactions. For clarity,
the hazard ratios for the covariates are not presented,
but the full models are available from the first author.
As presented in Table 3, none of the hazard ratios
for the Relocation Status ⫻ Cognitive Status interactions were significant, indicating that relocation effect was not moderated by level of cognitive impairment. Significant main effects emerged for relocation
status and cognitive status. Movers in comparison
with nonmovers exhibited greater rates of decline as
indicated by number of diagnosed diseases, number
of conditions, signs, symptoms, and hospital admissions. Further, severely cognitively impaired in comparison with cognitively intact residents, regardless of
relocation status, declined more quickly in ADLs.
None of the Relocation ⫻ Survival Time and Cognitive Status ⫻ Survival Time interactions for these
particular outcome variables were significant. This
suggests that relocation and cognitive status effects
occurred across the pre- and two postrelocation periods equally. An exception to this pattern was found
for psychosocial well-being. Whereas movers and
nonmovers exhibited similar rates of decline in this
outcome variable during the prerelocation and shortterm postrelocation periods, during the long-term
postrelocation period nonmovers declined at a higher
rate, as indicated in Table 3.
to harmful relocation effects during a prerelocation
period, and a short- and long-term postrelocation period. These effects were measured in terms of eight
outcome variables that covered mortality and physical and psychological morbidity. In spite of the large
number of outcome variables investigated across
three relocation periods, no evidence was uncovered
to support the cognitive impairment vulnerability hypothesis. This finding is consistent with two of the
studies in the literature that compared movers with a
control group of nonmovers (Goldfarb et al., 1972;
Lieberman & Tobin, 1983).
It was noted above that MDS items, particularly
those involving subjective assessment, are less reliable for cognitively impaired residents. This could
have attenuated the Relocation Status ⫻ Cognitive
Status interaction effects, especially for ADLs and
psychological well-being. Yet, the outcome variables
operationalized on more objective medical record
data (number of administered medications, hospital
admissions, etc.) also failed to exhibit significant interaction effects.
Our research uncovered four significant relocation
status main effects. Three of those effects indicated
that movers in general, regardless of cognitive status,
exhibited a decline in physical health across all three
relocation periods. The remaining effect suggested
that movers exhibited an improvement in psychological health during the long-term postrelocation period. This represents 10 times the number of significant relocation status main effects we would have
expected by chance alone (4/8⫽.5; .5/.05⫽10).
Some studies in the literature have documented anticipatory relocation effects (Tobin & Lieberman,
1976; Zweig & Csank, 1976); many others have documented postrelocation effects (for a review, see
Grant, Skinkle & Lipps, 1992). The present study sug-
Discussion
The present study tested whether cognitively impaired nursing home residents were more vulnerable
Table 3. Hazard Ratios for Relocation Status,a Cognitive Status,b and the Cognitive Status ⫻ Relocation Status Interactions, Adjusted
for Baseline Differencesc and Baseline Values of the Outcome Variablesd
Predictor Variables
Outcome Variablesd
Mortalitye
ADLs
Psychological well-beinge
Diagnosed diseasese
Conditions/signs/symptomse
Administered medicationse
Emergency room transferse
Hospital admissions
Relocation
Status
Moderate
Cognitive
Impairment
Severe
Cognitive
Impairment
Moderate
Relocation ⫻ Cognitive
Status
Impairment
Severe
Relocation ⫻ Cognitive
Status
Impairment
0.42
1.29
0.15f***
4.20***
6.10***
0.93
2.72
4.91***
1.01
1.83
0.87
1.62
1.35
1.05
3.15
2.10
1.51
5.04***
1.32
1.27
1.02
1.04
5.55
2.71
1.42
0.47
0.97
0.54
0.52
1.42
0.32
0.40
0.42
0.38
0.45
0.81
0.53
1.01
0.29
0.54
Note: ADLs ⫽ activities of daily living.
a
Nonmovers served as the reference group.
b
Cognitively intact served as the reference group for moderately and severely cognitively impaired.
c
All equations adjusted for length of stay, marital status, race, Medicaid coverage, Medicare coverage, primary language, ADLs, diagnosed diseases, conditions/signs/symptoms, and hospital admissions.
d
All equations except that for mortality also adjusted for baseline values of administered medications, emergency room transfers, and
psychological well-being.
e
Equation adjusted for selected Covariate ⫻ Survival Time interactions.
f
This hazard ratio represents the risk for movers versus nonmovers during the long-term post-relocation period.
***p ⬍ .001.
Vol. 40, No. 5, 2000
537
gests that relocation effects, in terms of physical
health at least, may begin prerelocation and continue
throughout the first year postrelocation. Of course,
the dynamics underlying and responsible for these
deleterious effects may differ during pre- and postrelocation phases. Research investigating those dynamics would seem to be warranted. A practical implication of our finding is that administrators and staff of
nursing homes about to undergo relocation must pay
attention to all residents, not just to those who are
cognitively impaired. Further, this attention must begin prerelocation and should extend to at least 12
months postrelocation. It is unclear why movers exhibited an improved psychological health status during the last 6 months of the postrelocation year. Future research might benefit by including additional
psychological measures and determining their behavior in contrast to physical health measures during
the various stages of the relocation process.
What implications do our results have for the
transfer of cognitively impaired residents into SCUs?
Prior to addressing this question, two qualifications
must be stated. First, given our design, caution
should be used in generalizing our findings to the
transfer of one individual at a time into SCUs. It is
possible that the dynamics of mass versus single-person transfers are different enough to result in different
outcomes for severely cognitively impaired residents,
and/or for residents in general. Research determining
the effects on the severely cognitively impaired versus the moderately impaired and the unimpaired of
single-person transfers between buildings and between rooms within a building would greatly contribute to our knowledge. Second, cognitively impaired
residents moved into SCUs may differ from those
who remain on nonspecialized units. Although the
literature is inconsistent, studies have found differences in cognitive functioning, ADLs, problem behaviors, and so forth (Holmes et al., 1990; Riter &
Fries, 1992). To the degree that cognitively impaired
residents selected for SCUs constitute a unique subset,
they may in fact respond to transfer in unique ways.
With these caveats in mind, our findings would
suggest that cognitively impaired residents are not at
unusual risk of experiencing harmful effects as a consequence of being transferred into SCUs. Although
this certainly leads to a more optimistic assessment of
the possible unintended consequences of SCUs than
would be suggested by previous relocation studies,
there remains good reason to be concerned. To say
that the cognitively impaired are not at special risk,
does not mean that they are at no risk. Recall that residents in general, including those who were moderately and severely cognitively impaired, exhibited deleterious relocation effects. The possibility would seem
to continue to exist that transfers into SCUs may indeed
cause harm and that the benefits derived from living in
an SCU might be somewhat offset by the stresses associated with being transferred into the unit. All of this
would indicate that caution should be taken in moving
cognitively impaired residents into SCUs, as it should
be in moving any residents. Our findings would also
suggest the need to study more directly the impact of
transferring cognitively impaired residents into SCUs.
References
Aldrich, C. K. (1964). Personality factors and mortality in the relocation of
the aged. The Gerontologist, 4, 92–93.
Allison, P. D. (1982). Discrete-time methods for the analysis of event histories. In S. Leinhardt (Ed.), Sociological methodology. (pp. 61–98). San
Francisco: Jossey-Bass.
Barnes, R. F., & Raskind, M. A. (1981). DSM-III criteria and the clinical diagnosis of dementia: A nursing home study. Journal of Gerontology, 36, 20–27.
Blenkner, M. (1967). Environmental change and the aging individual. The
Gerontologist, 7, 101–105.
Borup, J. H. (1981). Relocation: Attitudes, information, network, and problems encountered. The Gerontologist, 21, 501–511.
Casten, R., Lawton, M. P., Parmelee, P. A., & Kleban, M. H. (1998). Psychometric characteristics of the Minimum Data Set I: Confirmatory factor
analysis. Journal of the American Geriatrics Society, 46, 726–735.
Coffman, T. L. (1981). Relocation and survival of institutionalized aged: A
re-examination of the evidence. The Gerontologist, 21, 483–500.
Coffman, T. L. (1983). Toward an understanding of geriatric relocation.
The Gerontologist, 23, 453–459.
Crooks, V. C., Schnelle, J. F., Ouslander, J. P., & McNees, M. P. (1995).
Use of the Minimum Data Set to rate incontinence severity. Journal of
the American Geriatrics Society, 43, 1363–1369.
Csank, J. Z., & Zweig, J. P. (1980). Relative mortality of chronically ill geriatric patients with organic brain damage before and after relocation.
Journal of the American Geriatrics Society, 28, 76–83.
Frederiksen, K., Tariot, P., & De Jonghe, E. (1996). Minimum Data Set Plus
(MDS⫹) scores compared with scores from five rating scales. Journal of
the American Geriatrics Society, 44, 305–309.
Friedman, S. M., Williamson, J. D., Lee, B. H., Ankrom, M. A., Ryan, S. D.,
& Denman, S. J. (1995). Increased fall rates in nursing home residents
after relocation to a new facility. Journal of the American Geriatrics Society, 43, 1237–1242.
Goldfarb, A. I., Fisch, M., & Gerber, I. E. (1966). Predictors of mortality in
the institutionalized aged. Diseases of the Nervous System, 27, 21–29.
Goldfarb, A. I., Shahinian, S. P., & Burr, H. T. (1972). Death rate of relocated nursing home residents. In D. P. Kent, R. Kastenbaum, & S.
Sherwood (Eds.), Research planning and action for the elderly: The
power and potential of social science (pp. 525–537). New York: Behavioral Publications.
Goplerud, E. N. (1979). Unexpected consequences of deinstitutionalization of the mentally disabled elderly. American Journal of Community
Psychology, 7, 315–328.
Grant, P. R., Skinkle, R. R., & Lipps, G. (1992). The impact of interinstitutional relocation on nursing home residents requiring a high level of
care. The Gerontologist, 32, 834–842.
Guttman, G. H., & Herbert, C. P. (1976). Mortality rates among relocated
extended-care patients. Journal of Gerontology, 31, 352–357.
Hartmaier, S. L., Sloane, P. D., Guess, H. A., Koch, G. G., Mitchell, C. M.,
& Phillips, C. D. (1995). Validation of the Minimum Data Set Cognitive
Performance Scale: Agreement with the Mini-Mental Status Examination. Journal of Gerontology: Medical Sciences, 50A, M128–M133.
Hawes, C., Morris, J. N., Phillips, C. D., Mor, V., Fries, B. E., & Nonemaker, S. (1995). Reliability estimates for the Minimum Data Set for
nursing home resident assessment and care screening (MDS). The Gerontologist, 35, 172–178.
Hawes, C., Phillips, C. D., Mor, V., Fries, B. E., & Morris, J. N. (1992). MDS
data should be used for research. The Gerontologist, 32, 563–564.
Holmes, D., Teresi, J., & Monaco, C. (1992). Special care units in nursing
homes: Prevalence in five states. The Gerontologist, 32, 191–196.
Holmes, D., Teresi, J., Weiner, A., Monaco, C., Ronch, J., & Vickers, R.
(1990). Impacts associated with special care units in long-term care facilities. The Gerontologist, 30, 178–183.
Kasl, S. V. (1972). Physical and mental health effects of involuntary relocation and institutionalization on the elderly—a review. American
Journal of Public Health, 62, 377–383.
Kleinbaum, D. G. (1996). Survival analysis. New York: Springer.
Kowalski, C. N. (1981). Institutional relocation: Current programs and applied approaches. The Gerontologist, 21, 512–519.
Kral, V. A., Grad, B., & Berenson, J. (1968). Stress reactions resulting from
relocation of an aged population. Canadian Psychiatric Association
Journal, 13, 201–209.
Krovach, C. R. (1998). Nursing home dementia care units: Providing a
continuum of care rather than aging in place. Journal of Gerontological
Nursing, 24, 30–36.
Lander, S. M., Brazill, A. L., & Ladrigan, P. M. (1997). Intrainstitutional relocation. Effects on residents’ behavior and psychosocial functioning.
Journal of Gerontological Nursing, 23, 35–41.
538
The Gerontologist
An assessment of the Minimum Data Set for nursing homes. Alzheimer’s Disease and Associated Disorders, 11, 162–167.
Phillips, C. D., Sloane, P. D., Hawes, C., Koch, G., Han, J., Spry, K.,
Dunteman, G., & Williams, R. (1997). Effects of residence in Alzheimer’s disease special care units on functional outcomes. Journal of the
American Medical Association, 278, 1340–1344.
Pruchno, R. A., & Resch, N. I. (1988). Intrainstitutional relocation: Mortality effects. The Gerontologist, 28, 311–317.
Reingold, R., & Werner, R. (1994). The evolution of specialized dementia
care: The relationship between research and program planning. Alz–
heimer’s Disease and Associated Disorders, 8, S126–S132.
Resnick, N. M., Brandeis, G. H., Baumann, M. M., & Morris, J. N. (1996).
Evaluating a national assessment strategy for urinary incontinence in
nursing home residents: Reliability of the Minimum Data Set and validity of the resident assessment protocol. Neurology Urodynamics, 15,
583–598.
Riter, R. N., & Fries, B. E. (1992). Predictors of the placement of cognitively
impaired residents on special care units. The Gerontologist, 32, 184–190.
Schulz, R., & Brenner, G. (1977). Relocation of the aged: A review and
theoretical analysis. Journal of Gerontology, 32, 323–333.
Singer, J. D., & Willett, J. B. (1991) Modeling the days of our lives: Survival
analysis when designing and analyzing longitudinal studies of duration
and the timing of events. Psychological Bulletin, 110, 268–290.
Teresi, J. A., & Holmes, D. (1992). Should MDS data be used for research?
The Gerontologist, 32, 148–149.
Tobin, S. A., & Lieberman, M. A. (1976). Last home for the aged. San Francisco: Jossey-Bass.
van Dijk, P. T., Dippel, D. W., & Habbema, J. D. (1991). Survival of patients
with dementia. Journal of the American Geriatrics Society, 39, 606–610.
Weiner, A. S., & Reingold, J. (1989). Special care units for dementia: Current practice models. Journal of Long-Term Care Administration, 17,
14–19.
Yawney, B. A., & Slover, D. A. (1973). Relocation of the elderly. Social
Work, 18, 86–95.
Zweig, J. P., & Csank, J. Z. (1976). Mortality fluctuations among chronically
ill medical geriatric patients as an indicator of stress before and after relocation. Journal of the American Geriatrics Society, 24, 264–277.
Lawton, M. P., & Simon, F. (1968). The ecology of social relationships in
housing for the elderly. The Gerontologist, 8, 108–115.
Leon, J., & Moyer, D. (1999). Potential cost savings in residential care for
Alzheimer’s disease patients. The Gerontologist, 39, 440–449.
Lieberman, M. A., & Tobin, S. S. (1983). The experience of old age. New
York: Basic Books.
Markus, E., Blenkner, M., Bloom, M., & Downs, T. (1972). Some factors
and their association with post-relocation mortality among institutionalized aged persons. Journal of Gerontology, 27, 376–382.
Marlowe, R. A. (1974, February). When they closed the doors at Modesto.
Paper presented at the National Institute of Mental Health Conference
on the closure of state hospitals, Scottsdale, Arizona.
Miller, D., & Lieberman, M. A. (1965). The relationship of affect state and
adaptive capacity to reactions to stress. Journal of Gerontology, 20,
492–497.
Mirotznik, J. (1995). Response of noninterviewable long-term care patients
before and after interinstitutional relocation. Psychological Reports,
76, 1267–1280.
Mor, V., Branco, K., Fleishman, J., Hawes, C., Phillips, C., Morris, J., &
Fries, B. (1995). The structure of social engagement among nursing
home residents. Journal of Gerontology: Psychological Sciences, 50B,
P1–P8.
Morris, J. N., Fries, B.E., Mehr, D. R., Hawes, C., Phillips, C.D., Mor, V., &
Lipsitz, L. A. (1994). MDS Cognitive Performance Scale. Journal of
Gerontology: Medical Sciences, 49, M174–M182.
Morris, J. N., Hawes, C., Fries, B. E., Phillips, C. D., Mor, V., Katz, S., Murphy, K., Drugovich, M. L., & Friedlob, A. D. (1990). Designing the
national Residential Assessment Instrument for nursing homes. The
Gerontologist, 30, 293–307.
Nirenberg, T. D. (1983). Relocation of institutionalized elderly. Journal of
Consulting and Clinical Psychology, 51, 693–701.
Ogren, E. H., & Linn, M. W. (1971). Male nursing home patients: Relocation and mortality. Journal of the American Geriatrics Society, 19, 229–
239.
Ohta, R. J., & Ohta, B. M. (1988). Special units for Alzheimer’s disease patients: A critical look. The Gerontologist, 28, 803–808.
Pastorello, T. (1975). Relocation study: A presentation of findings and reports. Unpublished manuscript, Loretto Geriatric Center, Syracuse, NY.
Phillips, C. D., Chu, C. W., Morris, J. N., & Hawes, C. (1993). Effects of
cognitive impairment on the reliability of geriatric assessments in nursing homes. Journal of the American Geriatrics Society, 41, 136–141.
Phillips, C. D., & Morris, J. N. (1997). The potential for using administrative and clinical data to analyze outcomes for the cognitively impaired:
Vol. 40, No. 5, 2000
Received December 23, 1998
Accepted June 12, 2000
Decision Editor: Laurence G. Branch, PhD
539