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® National Association of Social and Applied Gerontology
www.agingandlongtermcare.com • www.jaltc.net
ISSN 2619-9017 | E-ISSN 2618-6535
31
ABSTRACT
Testing the Psychometric Properties of the
Geriatric Anxiety Inventory in a Sample of Older
Adults in Turkey
RESEARCH ARTICLE
KEY PRACTITIONER MESSAGE
1. Appropriate assessment tools are needed to disentangle diculties that occur as a consequence of aging and the physical
and psychological symptoms that accompany it.
2. GAI has a high degree of reliability and validity. Thus, professionals in psychology, gerontology, psychiatry, medicine, and
social work may use the inventory to evaluate Turkish older individuals' geriatric anxiety.
3. Research on older people with geriatric anxiety is also encouraged because these studies help clinicians gure out how to
help older people improve their health-related quality of life.
KEYWORDS: Geriatric Anxiety Inventory; GAI; older adults’ anxiety; psychometric; conrmatory factor analyses; reliability.
MITHAT DURAK , EMRE SENOL-DURAK
Bolu Abant Izzet Baysal University
2021, 4(2), 31-39
DOI: 10.51819/jaltc.2021.1089891
Correspondence: Mithat DURAK
Department of Psychology, Faculty of Arts and Science, Bolu Abant Izzet Baysal University,
Golkoy, Bolu, Turkey / mithat@mithatdurak.com
Anxiety is a prevalent illness among older adults, and it should
be assessed using psychometrically robust diagnostic tools
owing to the fact that physical symptoms suppress geriatric
anxiety. It is challenging to assess anxiety in older people
due to variations in worries, such as older adults being more
concerned about their lives and complaining of decreased
arousal. The Geriatric Anxiety Inventory (GAI) is a new, well-
known, and adaptable measure created to evaluate anxiety
in the older population while avoiding the abovementioned
issues. The present study aims to measure the psychometric
properties of the Turkish version of the GAI in a Turkish
sample of older adults (n = 199). In the current research,
ninety-four male (47.2%) and one hundred five female (52.8%)
participants are enrolled. Confirmatory factor analysis (CFA)
proves that the GAI three-dimensional model is statistically
significant. Good internal consistency results and corrected
item-total correlations prove the inventory's reliability.
Additionally, concurrent validity is shown to be reasonable
based on the association between geriatric anxiety and
many conceptually related variables (general anxiety, life
satisfaction, positive and negative affect), and discriminant
validity is found to be satisfactory based on the correlation
between geriatric anxiety and an unrelated measure
(social desirability). The psychometric characteristics
of the GAI are discussed in light of current findings on
the value of evidence-based evaluation in older people.
31
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Durak & Senol-Durak. Geriatric Anxiety Inventory
INTRODUCTION
Psycho-social and physical challenges in old age
render older people more prone to psychiatric
problems. Anxiety is one of these issues studied in a
population of older people (Areán, 1997; Ayers et al.,
2007) with a high prevalence (Kogan et al., 2000). If
anxiety is not appropriately managed, the well-being
of older people deteriorates. For instance, older people
with generalized anxiety disorder had poorer health-
related quality of life scores than their counterparts
(Wetherell et al., 2004). Contrary to popular opinion,
research shows that anxiety in older individuals is
a frequent but understudied problem. According to
Alwahhabi, this is an "underestimated, undertreated,
and understudied condition" (Alwahhabi, 2003, p. 180).
The severity of their bodily ailments overshadows
their anxiety levels. Some physical symptoms might
be caused by anxiety, so it is essential to look at
older adults' anxiety with evidence-based practices
when diagnosing and treating them (Therrien &
Hunsley, 2012). In terms of anxiety, there are certain
similarities and dierences between adults and older
adults. To begin with, the common characteristics in
older people and other age groups include certain
anxiety features, symptom presentation in panic
disorder, social anxiety in social phobia, symptom
presentation in obsessive-compulsive disorder,
and functional impairment in each anxiety disorder
(Wolitzky-Taylor et al., 2010).
Older adults, however, have a number of unique
features that make assessing anxiety more dicult
and complicated (Gould et al., 2021). It is also said
that older people do not suer from overwhelming
and unmanageable anxiety but rather have cognitive
worries about their lives (Gould et al., 2021). They
are also less likely to report negative emotional
experiences (Wolitzky-Taylor et al., 2010), which
might be due to changes in sympathetic nervous
system activity with aging (Kogan et al., 2000). Older
adults are more concerned about their health than
younger ones, which is reected in their level of
anxiety (Wolitzky-Taylor et al., 2010). As a result, the
nature of anxiety in old age is relatively dierent from
that in other age groups. Additionally, professionals
will benet from assessing anxiety using procedures
that are applicable in the real world (Gould et al.,
2021).
Since their medical illnesses may be part of their
psychological well-being, it is critical to identify
anxiety in the older adult population (Areán, 1997;
Therrien & Hunsley, 2012). Individuals receiving home
care are also at risk of developing psychological
disorders such as anxiety, which should be assessed
by professionals (Diefenbach et al., 2009). Similarly, in
order to assess anxiety, professionals would focus on
the medical conditions of older people as well as their
functional level, both of which complicate evaluation
(Ayers et al., 2007). Certain symptoms indicative of
physical diculties may be a result of their anxiety.
Distinguishing physical and psychological challenges
in old age is tricky. Additionally, as indicated before,
specic anxiety symptoms might alter in the sample
of older persons (Alwahhabi, 2003); thus, evaluating
anxiety in the older adult using generic anxiety
measures is deemed "imprudent" (Kogan et al.,
2000).
Several self-report questionnaires are available to
assess anxiety in a sample of older people, such as
the State-Trait Anxiety Inventory (STAI; Kvaal et al.,
2005), Beck Anxiety Inventory (BAI; Areán, 1997),
Penn State Worry Questionnaire (PSWQ; Meyer
et al., 1990), General Health Questionnaire (GHQ;
Goldberg & Hillier, 1979), and Hospital Anxiety and
Depression Scale (HADS; Zigmond & Snaith, 1983).
These instruments are available on scales that are
used to measure the anxiety of people of all ages.
They are not designed to assess older adults'
anxiety or address the objections expressed to such
assessments. Researchers attempt to compensate
for the shortcomings of such assessments (i.e.,
STAI) by using equivalent alternative scales and
contemplating higher cut-o points for older adults
(Kvaal et al., 2005). Additionally, certain items
associated with cognitive components of these
measures, such as those in the BAI (Areán, 1997)
and items including somatic claims (Byrne et al.,
2010), do not function properly in the population of
older adults. The response style of some of these
scales, such as the STAI, has been criticized as being
excessively complex for older adults, and reversal
items, such as those in the HADS, add to older
adults' doubts about such statements (Byrne et al.,
2010). Additionally, researchers recommend taking
extreme caution when administering these scales
(e.g., BAI) to older adults for therapeutic purposes
(Areán, 1997).
The Geriatric Anxiety Inventory (GAI) is a well-known
questionnaire used to measure the anxiety level of
older adults (Pachana et al., 2007). GAI is designed to
resolve the aforementioned criticisms by using a less
convoluted answer style, fewer somatic items, and
no reverse items (Byrne et al., 2010). GAI items are
chosen based on existing measurements with the
assistance of focus groups that include older people,
Journal of Aging and Long-Term Care
33
geropsychologists, and geriatric psychiatrists
(Pachana et al., 2007). The GAI is composed of
twenty items arranged in an agree-disagree style.
The inventory has high discriminant validity to
distinguish patients with and without generalized
anxiety disorder (GAD), with satisfactory reliability
and validity outcomes. According to receiver
operating characteristic analysis (ROC), using a
cut-o score of 10/11, 83% of psychogeriatric
patients accurately categorized generalized anxiety
disorder with high sensitivity (73%) and specicity
(80%). When the psychometric features of a sample
of older Australian women are examined, it is
discovered that the cut-o score of the inventory is
8/9 on the inventory (Byrne et al., 2010). Similarly,
the Portuguese adaptation of the GAI demonstrates
that a cut-o score of 8/9 dierentiates severe
anxiety from other types of anxiety in older adults
with or without a mental illness (Ribeiro et al., 2011).
Similarly, using ROC analysis, the cut-o values for
generalized anxiety disorder are determined to be
13 points (83.3% sensitivity and 84.6% specicity) in
the Brazilian Portuguese language (Massena et al.,
2015).
The inventory developers propose modifying a few
terms in the GAI items to improve comprehension
when evaluating psychometric properties in another
culture (Byrne & Pachana, 2011). The inventory is
translated into Brazilian Portuguese (Massena et
al., 2015), Portuguese (Ribeiro et al., 2011), French-
Canadian (Champagne et al., 2018), Japanese
(Kashimura et al., 2021), Spanish (Marquez-Gonzalez
et al., 2012), and Persian (Shati et al., 2021). To make
cultural sense in the Portuguese translation, the item
" I oen feel like I have butteries in my stomach " is
changed to " I feel like having a knot in the throat"
(Ribeiro et al., 2011). In that version, there are two
components to the inventory, according to Bartlett's
Test of Sphericity and Kaiser-Meyer-Olkin (KMO),
with anxiety symptoms accounting for 43.4% of the
total variance and somatic symptoms accounting for
18% of the total variance, respectively. In contrast to
the two-factor structure, the Spanish version of the
study with older adults demonstrates that the GAI has
a three-factor structure (cognitive, arousal/physical
activation, and somatic dimensions), with varimax
rotation accounting for 51% of the variance (Marquez-
Gonzalez et al., 2012). The internal consistency of
this version is excellent (.91). In recent publications,
the one-dimensional structure of the GAI has been
discovered in the Japanese version (Kashimura et
al., 2021), the Chilean version (Miranda-Castillo et al.,
2019), and the French-Canadian version (Champagne
et al., 2018), as well as in studies with the geriatric
population (Johnco et al., 2015). Furthermore, the
inventory's unidimensionality is noted in a meta-
analysis of GAI. As a result, there is no consensus on
the factor structure of the inventory, as illustrated by
a metanalysis of GAI (Champagne et al., 2021).
GAI has been recognized as an eective tool for
assessing the anxiety of older people living in the
community, primary care centers, or geriatric
hospital (Byrne & Pachana, 2011; Johnco et al., 2015;
Massena et al., 2015). The earlier anxiety measures,
which are constructed for an adult population, are
insucient to assess the extent of anxiety in older
people. There are several instruments for assessing
anxiety; however, the GAI's benets include being
set up for older people, oering an agree/disagree
response style, not needing to reverse items, and
getting a small number of items. The purpose of this
research is to examine the psychometric properties
of the GAI in terms of reliability, factor structure, and
concurrent and discriminant validity in a sample of
older Turkish people. Conrmatory factor analyses
are performed to explore the factor structure of the
GAI; Cronbach's alpha is calculated to assess the
inventory's reliability; and correlations between the
scale and related or unrelated constructs such as
general anxiety, life satisfaction, positive and negative
aect, and social desirability are investigated to gure
out the GAI's concurrent or discriminant validity.
METHOD
Participants
The current research included 94 male (47.2%) and
105 female (52.8%) individuals (N = 199), with a
mean age of 69.92 (SD = 7.53; range = 60 to 92).The
majority (n = 104; 52.3%) of participants are married,
while others are single (N = 63; 31.7%), divorced (N
= 18; 9.0%), and separated (N = 8; 4.0%). In terms
of education, the participants have completed an
elementary school (N = 59; 29.6%), a secondary
school (N = 18; 9.0%), a high school (N = 41; 20.6%),
a two-year vocational school (N = 19; 9.5%), and
an university (N = 23; 11.6%), or not completed
any school but are literate (N = 39; 19.6%). Over
two-thirds of the individuals (67.8%; n = 135) live
in apartments, while only one-third (32.2%; n = 64)
live in retirement facilities. Additionally, two groups
were formed using the responses of participants
to the following question: how would you assess
your current general health status? Individuals who
rated their current health condition as "very bad" and
34
and "not good” were grouped together, but those
who rated it as "good" or "very good" were grouped
together. The rst group was dubbed "perception of
poor health" (N = 105; 52.8%), whereas the second
was dubbed "perception of excellent health" (N = 94;
47.2%).
Measures
To assess the Geriatric Anxiety Inventory's
psychometric properties, the Beck Anxiety Scale,
Satisfaction with Life Scale, Positive Negative Aect
Scale, and Social Desirability Scale are employed in
the present study.
The Geriatric Anxiety Inventory (GAI) is developed to
assess anxiety symptoms in older people with twenty
items arranged in an agree-disagree style (Pachana
et al., 2007). The inventory's psychometric properties
are thoroughly explained in the introduction section.
The Beck Anxiety Inventory (BAI) is a twenty-one-
item questionnaire designed to assess the presence
of anxiety on a four-point Likert scale (Beck et al.,
1988). Cronbach's alpha for the BAI is .92, and its
test-retest reliability over a one-week period is .75.
The inventory has two subscales: subjective anxiety/
panic symptoms and somatic complaints. Although
the inventory is not explicitly designed for older adults,
it has been utilized in studies conducted with older
people (Areán, 1997). Ulusoy et al. (1998) translated
the BAI into Turkish with a high internal consistency
(.93) and current validity, as shown by STAI.
The Social Desirability Scale-17 (SDS-17) is a true/
false format scale designed to evaluate socially
desirable responses (Stöber, 2001). A higher score
on the scale indicates a greater degree of social
desirability. The scale's reliability and validity were
investigated with people ranging in age from 18
to 89. The SDS-17's internal consistency is good
and acceptable (α = .75), and its scores correlated
satisfactorily (varying from .52 to .85) with alternative
measures of social desirability in terms of convergent
validity (e.g., Eysenck Personality Questionnaire-Lie
Scale, Sets of Four Scale, Marlowe-Crowne Scale).
The Satisfaction with Life Scale (SWLS) is a ve-item,
seven-point Likert-type scale that measures overall
life satisfaction (Diener et al., 1985). Higher scores
indicate a higher level of life satisfaction. The scale's
internal consistency (.87) and test-retest reliability
(.82) are acceptable. The scale is composed of a
single factor. Scale is adapted into Turkish by Durak
et al. (2010).
The Positive and Negative Aective Scale (PANAS)
is a ve-point Likert-type scale with twenty items
assessing positive and negative aect (Watson et al.,
1988). The scale assesses both positive and negative
aspects of aect. For the Turkish version of the
scale, Gencoz (2000) found that the factors' internal
consistency ranged from .83 to .86, while their test-
retest reliability ranged from .40 to .54.
Procedure Control of Data for Analyses
Prior to data collection, permission was obtained from
the inventories' creators for adaptation. GAI items
were translated into Turkish by four independent
English-speaking translators who were uent in
Turkish and specialists in the eld of psychology.
Following that, the text's authors double-checked the
accuracy of the item translations. Any disagreements
were settled by a joint agreement. The inventory
items were then translated backward from Turkish
to English, and English-Turkish comparison forms
were sent to the GAI developers. The measures were
given to older adults who live at home or in two rest
homes. All participants were informed of the goal of
the present study, and their permission was obtained.
RESULTS
Control of Data for Analyses
The descriptive statistics and correlational analyses
were conducted using IBM's SPSS-26 soware (IBM-
Corp, 2019). Conrmatory factor analysis (CFA) is
used to validate the GAI's factor structure using the
AMOS-26 program (Arbuckle, 2019). The p-value
threshold was set at .05 in all analyses to determine
signicance. In order to prevent probable outliers in
the data from inuencing the results, data cleaning
and outlier control were carried out (Tabachnick
& Fidell, 2013). Aer one multivariate outlier
was eliminated from the analysis, analyses were
performed on the remaining 199 cases.
Conrmatory Factor Analyses
To examine the adequacy of the unidimensional
and three-dimensional (cognitive, arousal/physical
activation, and somatic anxiety) models of the GAI,
conrmatory factor analyses are performed by
AMOS 26 program (Arbuckle, 2019). Those factorial
solutions are mentioned by psychometric studies
of the GAI in dierent languages (Champagne et al.,
2018; Kashimura et al., 2021; Marquez-Gonzalez et
al., 2012; Massena et al., 2015; Ribeiro et al., 2011;
Shati et al., 2021).
Durak & Senol-Durak. Geriatric Anxiety Inventory
Journal of Aging and Long-Term Care
35
The conrmatory factor analysis (CFA) was used
to ascertain the inventory's unidimensionality and
multidimensionality based on model t indices. The
Tucker-Lewis Index (TLI), Comparative Fit Index
(CFI), Incremental Fit Indices (IFI), p of Close Fit
(PCLOSE), Root Mean Square Error of Approximation
(RMSEA), Chi-Square (Χ2), and Standardized Root
Mean Square Residual (SRMR) were all employed to
determine model t (Hu & Bentler, 1999; Kline, 2016).
If a model's t indicators of IFI, TLI, and CFI exceed
.90 (Bentler & Bonett, 1980), it is deemed more t.
Additionally, RMSEA and SRMR values between
0 and .05 and PCLOSE values greater than .05 are
important markers of the best tting model owing
to their ability to detect subtle model changes (Hu &
Bentler, 1999; Schermelleh-Engel et al., 2003).
The model was tested to investigate the association
between previously identied factorial structure and
data acquired from Turkish older adults using AMOS
26 (Arbuckle, 2019). The tested one-factor solution
did not satisfy the desired criteria; Χ2 (167, N = 199)
= 466.84, p = .001; RMSEA = .094, IFI = .861, TLI =
.843, CFI = .860, Χ2/df = 2.76. On the other hand,
three-factor solution presented better adequate t,
Χ2 (167, N = 199) = 363.72, p = .001; RMSEA = .077,
IFI = .908, TLI = .894, CFI = .907, Χ2/df = 2.178. Freeing
parameter constraints between e2 (Item-10) and e3
(Item-13) may help improve the model, as shown
by modication indices. The model t improved
considerably further when the covariance between
error terms of two items was taken into account as a
free parameter in the new analysis; Χ2 (166, N = 199)
Figure-1. The standard regression weights
= 336.72, p = .001; RMSEA = .072, IFI = .920, TLI = .908,
CFI = .920, Χ2/df = 2.028. The standard regression
weights in this analysis are demonstrated in Figure-1.
The three-factor solution model matches the data
better than the single-factor solution model, based
on these ndings.
Internal Consistency Results
The internal consistency was assessed independently
for the whole scale and each factor. Internal
consistency coecient for the whole inventory was
.94, with corrected item-total correlations ranging
between .45 (item-12) to .77 (item-17). In terms
of three factors; internal consistency coecient
for cognitive anxiety was .91, with corrected item-
total correlations ranging between .53 (item-2) to
.78 (item-17), internal consistency coecient for
arousal/physical activation was .84, with corrected
item-total correlations ranging between .56 (item-
20) to .73 (item-10), internal consistency coecient
for somatic anxiety was .78, with corrected item-
total correlations ranging between .42 (item-6) to .67
(item-19).
Concurrent and Discriminant Validity
To examine concurrent validity, participants’
scores on GAI are compared with conceptually
related constructs of general anxiety (BAI scores),
life satisfaction (SWLS scores), and positive and
negative aect (PANAS scores). The GAI was
positively correlated with general anxiety (r =
.50 p = .001) and negative aect (r = .57, p = .001).
36
Durak & Senol-Durak. Geriatric Anxiety Inventory
On the other hand, the GAI was negatively correlated
with positive aect (r = -.29, p = .001) and SWLS (r =
-.19, p = .008) (see Table-1). To examine discriminant
validity by social desirability, participants’ scores on
GAI were compared with SDS-17. The GAI was not
signicantly correlated with social desirability (r = .02,
p = .822) (see Table 1). Furthermore, the discriminant
validity of the GAI was tested using an independent-
samples t-test. GAI scores for the perception of poor
health group (X = 6.66, SD = 6.18) were signicantly
higher than for excellent health group (X = 4.05, SD =
5.39), t(197) = 3.15, p = .002.
Table-1. Correlations between variables and descriptive values of the variable
1. 2. 3. 4. 5. 6.
1. Geriatric Anxiety (GAI) .50*** -.29*** .57*** -.19** .02
2. General Anxiety (BAI) -.28*** .57*** -.29*** -.15*
3. Life Satisfaction (SWLS) -.40*** .32*** .10
4. Negative Aect (PANAS-P) -.22** -.17*
5. Positive Aect (PANAS-N) -.04
6. Social Desirability (SDS-17)
X 5.43 14.42 25.31 16.94 30.44 11.05
SD 5.95 12.08 5.96 5.57 6.95 2.75
Min. (Possible) 0 0 5 10 10 0
Max. (Possible) 20 63 35 50 50 17
Note (1). ***p ≤ .001, **p ≤ .01, *p ≤ .05
Note (2). X = mean, SD = standard deviation
DISCUSSION
Aging includes several physical and psychological
diculties that are overshadowed by each other.
Therefore, as evidence-based practices, proper
assessment tools are necessary to dierentiate
problems (Therrien & Hunsley, 2012). As one of the
well-known and widely used measures in dierent
languages, the present study aims to evaluate the
psychometric aspects of the GAI.
Based on the GAI results in distinct cultures, the
unidimensionality of the factor structure is assessed
by CFA. The ndings proved that the evaluated one-
factor solution did not satisfy the essential criteria
for model t. Multidimensionality of inventory is
revealed in Portuguese (two-factor structure, Ribeiro
et al., 2011) and Spanish (three-factor structure,
Marquez-Gonzalez et al., 2012) versions of the GAI,
while mostly unidimensionality of the inventory
is supported in other versions (French-Canadian
version Champagne et al., 2018; Japanese version,
Kashimura et al., 2021; Chilean version Miranda-
Castillo et al., 2019). CFA results by t indices and the
ratio of Χ2 to df revealed that the GAI’s three-factor
solutions provided the most satisfactory t.
Correlations between errors might obfuscate model
testing ndings and diminish the likelihood of a
repeatable perfect tting model. Using comparable
language or phrases with remarkably similar
meanings while building a scale, on the other hand,
increases the possibility of correlations between error
terms. This perspective is consistent with Bollen and
Lennox's (1991) statement that researchers oen
assume errors are unrelated in order to facilitate
debate. However, correlations between error terms
are permissible when applied conservatively other
than random changes to improve model t. Aer
performing conrmatory factor analysis (CFA),
the model t was even better when the covariance
between e2 (Item-10) and e3 (Item-13) was taken
into account as a free parameter in the new analysis.
Both items are related to the same latent factor
(arousal/physical activation). "I oen feel nervous"
(item-10) and "I think of myself as a nervous person"
(item-13) are comparable statements that sound
equal to the ear.
The inventory's internal consistency is satisfactory as
the original version of the inventory (Pachana et al.,
2007). Regarding concurrent validity examinations by
conceptually related constructs, the GAI signicantly
correlated with BAI, supporting Pachana et al.'s (2007)
results. Like Diefenbach et al.'s study (2009), GAI
with BAI’s factorial structure relations is consistent.
Furthermore, GAI’s concurrent validity with SWLS
and SPANE is also satisfactory. As expected, there is
a positive correlation between the GAI and negative
aect, and there is a negative correlation between
Journal of Aging and Long-Term Care
37
the GAI and positive aect and satisfaction with life.
As proved by discriminant validity with SDS-17, the
inventory's relations with social desirability are in the
expected range. Therefore, the GAI can be a more
distinct concept than desirability.
There are methodological limitations in the present
study. Test-retest reliability of the inventory cannot be
examined in the present study. Also, factor structure
cannot be examined in terms of the living place of
older adults (at home versus in institution), physical
health problems (having problems versus not having
problems) (Gould et al., 2014), and presence of
having an anxiety disorder. Also, the role of cognitive
impairment on psychometric ndings cannot be
compared in the present study, which is evaluated by
(Rozzini et al., 2009). The psychometric aspects of the
GAI are recommended to be assessed with dierent
older adult groups in future studies.
The GAI has satisfactory reliability and validity results.
Therefore, the inventory can be used by professionals
(psychologists, gerontologists, psychiatrists,
physicians, social workers) in the professional
eld to evaluate Turkish older adults in describing
their geriatric anxiety. Additionally, the inventory
may be used to assess three subdimensions of
geriatric anxiety. With GAD, it will be feasible to
identify the anxiety areas of older adults and tailor
the therapeutic process to the sub-area (cognitive,
arousal, or somatic) in which they score the highest.
For instance, practitioners may save time using
cognitive psychotherapy strategies with older adults
with high cognitive geriatric anxiety scores. Similarly,
depending on the amount of arousal, it may occur to
apply behavioral approaches in the rst place in those
who feel anxiety. Strengthening communication skills
to assist clients with high somatic anxiety ratings in
lowering their anxiety would save the expert time.
Further studies exploring psycho-social diculties in
geriatric anxiety are also encouraged. Those studies
help professionals set a target of help in promoting
health-related quality of life among older adults.
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