Vol.5, No.12A, 110-116 (2013) Health
Quality of life in the elderly: Psychometric properties
of the WHOQOL-OLD module in Mexico
Ana Luisa González-Celis1*, Juana Gómez-Benito2,3
1Division of Research and Graduate Studies, Faculty of Higher Education Iztacala, National Autonomous University of Mexico,
Mexico City, Mexico; *Corresponding Author: algcr10@hotmail.com
2Department of Behavioral Sciences Methodology, Faculty of Psychology, University of Barcelona, Barcelona, Spain
3Institute for Brain, Cognition and Behaviour (IR3C), University of Barcelona, Barcelona, Spain
Received 31 October 2013; revised 28 November 2013; accepted 8 December 2013
Copyright © 2013 Ana Luisa González-Celis, Juana Gómez-Benito. This is an open access article distributed under the Creative
Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original
work is properly cited.
The purpose was to examine and compare the
psychometric properties of a Mexican Spanish
version of the WHOQOL-OLD module. The in-
strument was applied to 285 individuals aged
over 60 years (mean = 69.26, SD = 6.52). All par-
ticipants completed a demographic data sheet,
the WHOQOL-OLD, the Beck Depression Inven-
tory (BDI), and the Geriatric Depression Scale
(GDS); 182 of the 285 participants also com-
pleted a quality of life questionnaire for diabetic
patients (DQOL). Acceptable levels of reliability
were found, with Cronbach’s alpha values be-
tween 0.70 and 0.90 for overall quality of life and
all domains except for autonomy, where the al-
pha value was low. The exploratory factor ana-
lysis carried out to examine the construct va-
lidity of the instrument yielded six domains: sen-
sory abilities, autonomy, past/present/future ac-
tivities, social participation, death and dying,
and intimacy (explained variance of 62.95%).
The mean overall quality of life score was 94.86
(SD = 13.68, range 50 to 120). The WHOQOL-OLD
module showed criterion validity and concurrent
validity with respect to the BDI (r = 0.516, p =
0.034), the GDS (r = 0.336, p = 0.002), and the
DQOL (n = 182, r = 0.159, p = 0.032). Discriminant
validity was also confirmed with respect to self-
perceived health (t = 2.701, d.f. = 225, p = 0.007)
and education (F(3, 280) = 9.015, p < 0.001), for
both overall quality of life and some of its di-
mensions, but this was not the case with respect
to gender (t = 1.292, d.f. = 283, p > 0.05). We
conclude that the Mexican Spanish version of
the WHOQOL-OLD module has adequate psy-
chometric properties.
Keywords: Quality of Life; Elderly; WHOQOL-OLD;
Psychometric Properties; Mexico
The proportion of people aged 60 and over worldwide
is growing faster than any other age group. Between
1970 and 2025, an increase in the number of older per-
sons of some 694 million (or 223%) is expected. Indeed,
it is estimated that by 2025 there will be around 1.2 bil-
lion people over the age of 60, while by 2050 there will
be 2 billion, with 80 percent of them living in developing
countries [1].
In addition to investigating and determining the pace
of the population’s aging, there is also a need to study
the quality of aging and, subsequently, to design inter-
ventions that can promote a healthy aging process. Con-
sequently, researchers in geriatrics are increasingly in-
terested in identifying the factors which are relevant to
the quality of life in older adults [2,3]
The WHO Quality of Life Group has recently devel-
oped the WHOQOL-OLD module [4]. Through a simul-
taneous transcultural methodology, this instrument is
designed to be suitable for cross-cultural comparisons.
Furthermore, alongside the WHOQOL-100 [5] and the
WHOQOL-BREF [6,7], it constitutes a useful alternative
tool for investigating quality of life in older adults, not
least as it includes relevant aspects that are not covered
by instruments originally designed for non-elderly popu-
Power et al. [4], representing the WHOQOL group,
emphasize that due to the specificities shown by the
older adult population in the different centers involved in
Copyright © 2013 SciRes. OPEN ACCESS
A. L. González-Celis, J. Gómez-Benito / Health 5 (2013) 110-116 111
international data collection, there is a need to develop
quality of life measurement tools directed toward older
adults, and to test these instruments in a transcultural
The aim of the present study was to evaluate the psy-
chometric properties of a Mexican Spanish version of the
WHOQOL-OLD module, specifically by analyzing its
internal consistency, construct validity, criterion validity,
concurrent validity and discriminant validity.
2.1. Participants
The sample comprised 285 elderly people aged be-
tween 60 and 98 years (mean = 69.26, SD = 6.52; 193
women, 92 men). They were recruited through health
centers or recreational day centers in two states of Mex-
ico, as well as in the capital, Mexico City. Their socio-
economic status was lower middle class, and the majority
had only a basic level of education. Regarding marital
status, 56% were married or had a partner, 29% were
widowed, and 15% were single, divorced, or separated.
2.2. Measures
Socio-demographic data. The socio-demographic in-
formation sheet included questions about gender, age,
educational level, marital status, and self-perceived heal-
th status.
WHOQOL-OLD. The WHOQOL-OLD is a 24-item
self-report instrument that is divided into six domains:
Sensory Abilities (SA); Autonomy (A); Past, Present,
and Future Activities (PPFA); Social Participation (SP);
Death and Dying (DD); and Intimacy (I) (4 items per
subscale). Each domain provides an individual score, and
an overall score is also calculated from the set of 24
items. Answers are based on a 5-point Likert response
scale, with items 1, 2, 6, 7, 8, 9, 10 being reverse scored.
Although all the response scales have five points they
vary in their anchors: “Not at all”/“An extreme amount”;
“Completely”/“Extremely”; “Very poor”/“Very good”;
“Very dissatisfied”/“Very satisfied”; “Very unhappy/Very
happy”). The Spanish version of the scale [8] was ada-
pted to colloquial features of Mexican Spanish. Total
scores on the WHOQOL-OLD range from 24 to 120,
with higher scores being indicative of better quality of
life (QoL).
Beck Depression Inventory (BDI) [9]. This instrument
assesses the presence and level of depressive symptoms
and when validated in a Mexican population [10] it
proved suitable for studying clinical and non-clinical
populations. Scores range from 0 to 63, with higher scores
indicating greater severity of depressive symptoms.
Geriatric Depression Scale. The 15-item version of
the Geriatric Depression Scale (GDS) [11] has previ-
ously been adapted for Mexican older adults by Gon-
zález-Celis & Sánchez-Sosa [12]. Possible total scores
range from 0 to 15, and a score of 5 or more indicates the
presence of depressive symptoms.
Diabetes Quality of Life (DQOL). The DQOL measure
[13] was developed for both type 1 and type 2 diabetes.
A Spanish version of the instrument was validated by
Robles-García, Cortázar, Sánchez-Sosa, Páez-Agraz, and
Nicolini-Sánchez [14], and it was subsequently adapted
for older Mexican adults by Hattori [15]. Its 46 items
measure four domains that are highly relevant to treat-
ment perceptions: satisfaction with treatment, impact of
treatment, worry about the future effects of diabetes, and
worry about social/vocational issues. Items are scored on
a 5-point Likert scale and are of two general formats.
One format asks about the frequency of negative impact
of diabetes itself or of the diabetes treatment (e.g., “How
often do you worry about whether you will pass out?”)
and provides response options from 1 (all the time) to 5
(never). The second format asks about satisfaction with
treatment and quality of life (e.g., “How satisfied are you
with the time you spend exercising?”) and is scored from
1 (very dissatisfied) to 5 (very satisfied). Higher scores
on DQOL items and subscales are, therefore, positive
and indicate the absence of problems and greater satis-
2.3. Procedure
All participants (N = 285) completed three instruments
(WHOQOL-OLD, BDI, and GDS), as well as the socio-
demographic data sheet. Only 182 patients completed the
DQOL. Subjects were interviewed and answered the
question “In general, do you consider yourself healthy or
unhealthy?” On the basis of their response they were
categorized as healthy or unhealthy, and this was taken as
an indicator of self-perceived, rather than actual, health
status. All participants were informed about the purposes
of the study and were ensured that all data obtained
would remain confidential. They all signed an informed
consent form that was approved by the Research Ethics
Committee of the university in which the study was car-
ried out. Interviewers were psychology undergraduates
who had previously received training in how to apply the
various instruments used. Depending on the status of the
participant, the instruments were self-administered, ad-
ministered with the interviewer’s help, or completely
administered by the interviewer. In cases where the in-
terviewer’s participation was required, they were asked
not to interfere with the subjects’ understanding of the
items and told not to rephrase or supply synonyms for
the words used in the instrument items.
2.4. Statistical Analysis
The data obtained were examined by means of de-
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A. L. González-Celis, J. Gómez-Benito / Health 5 (2013) 110-116
scriptive analysis and psychometric tests for reliability
and validity (using IBM SPSS Statistics 19). Internal
consistency was assessed on the basis of Cronbach’s al-
pha (criteria of acceptability 0.70 < 0.90), which tests the
strength of the association between each scale item and
the full scale. Factor analysis was used to examine the
dimensionality of the questionnaire, with the following
criteria being applied: the correlation matrix should in-
clude many coefficients of 0.30 and above; the Kai-
ser-Meyer-Olkin (KMO) index of sampling adequacy
(KMO) [16,17] should exceed the threshold of 0.60;
Bartlett’s test of sphericity should be statistically signifi-
cant at p = 0.001 so as to support the factorability of the
correlation matrix and to confirm that the use of factor
analysis was appropriate [18]; and eigenvalues had to be
greater than 1.0 in order to support the construct validity
of the scale. Criterion validity and concurrent validity
(convergent and divergent) were tested by assessing the
strength of Pearson’s r correlations between the scale and
similar or relevant/dissimilar measures (WHOQOL-OLD
with respect to the BDI, GDS, and DQOL). Discriminant
validity was tested by means of the Student’s t test or
ANOVA, examining the relationship between the WHO-
QOLOLD and each of its domains and socio- demo-
graphic variables (gender, educational level, and self-
perceived health status). Statistical significance was set
at p < 0.05, and effect sizes were measured by means of
Cohen’s d [19].
Cronbach’s alpha as a measure of internal consistency
reached satisfactory values for each facet score (range
from α = 0.75 to α = 0.85) and also for the total score (α =
0.88) (Table 1). These alpha values are similar to those
reported by the WHO Quality of Life Group.
The 24 items of the WHOQOL-OLD were subjected to
principal components analysis (PCA), using SPSS, in
order to examine the factor structure. The suitability of
conducting a factor analysis with these data was first as-
Table 1. Cronbach’s alpha values for the Mexican population
and those reported by the WHOQOL-OLD Group.
Domains Mexico
(N = 285)
field trial sample
(N = 5566) [4,8]
Sensory Abilities (SA) 0.78 0.84
Autonomy (A) 0.56 0.72
Activities (PPFA) 0.75 0.74
Social Participation (SP) 0.79 0.79
Death and Dying (DD) 0.83 0.84
Intimacy (I) 0.85 0.88
Total Score (Overall) 0.88 0.89
sessed based on the aforementioned criteria, which re-
vealed the following: many of the correlations in the cor-
relation matrix were 0.30 or above; the KMO index of
sampling adequacy was 0.85, exceeding the recom-
mended value of 0.60 [16,17]; and Bartlett’s test of
sphericity [18] was statistically significant (chi-square
2835.758, 276 degrees of freedom, p < 0.0001), support-
ing the factorability of the correlation matrix. PCA re-
vealed the presence of six components for which the ei-
genvalues exceeded 1, and together these explained
62.95% of the total variance in QoL between respondents:
component 1 explained the largest proportion of the vari-
ance (13.33%), this being supported by inspection of the
scree plot [20]. Applying the Kaiser criterion of retaining
all components with eigenvalues above 1, most items (n =
21/24) loaded strongly (0.4+): on the first component
three items loaded strongly (0.4+) and one loaded moder-
ately (0.3+); four items loaded strongly (0.4+) on each of
the second, third, and fourth components; on the fifth
component three items loaded strongly (0.4+) and one
loaded mildly (0.2+); and on the sixth component, two
items loaded strongly (0.4+), one loaded mildly (0.2+),
and one item did not load, it loading instead on the fifth
component (Table 2).
There is no gold standard QoL measure to assess crite-
rion validity, but concurrent validity (convergent and dis-
criminant) was tested here. The WHOQOL-OLD corre-
lated positively with the DQOL (r = 0.159, p < 0.032), as
would be expected, and negatively with both the BDI (r =
0.516, p < 0.034) and the GDS (r = 0.336, p < 0.002).
Participants reported optimum levels of QoL when DQOL
was better (higher scores), and when BDI and GDS
scores were low.
In terms of the discriminant validity of the WHO-
QOL-OLD, Ta bl e s 3 -5 show comparisons of the quality
of life scores (for each domain and total) obtained by dif-
ferent subgroups defined by self-perceived health status,
educational level, and gender. Healthy participants scored
higher than unhealthy participants on all domains of qual-
ity of life and, therefore, also on overall QoL. The effect
size of these differences was medium in all cases except
for Autonomy, Death and Dying, and Intimacy, where the
effect was small (Table 3). With regard to educational
level, the analysis showed that quality of life scores (both
by domain and overall) increased in line with participants’
level of education (Table 4).
Finally, the results for gender only revealed significant
differences between men and women on the QoL scores
for the domains SP and Death and Dying (Table 5).
Factor analysis supported the multidimensional struc-
ture of the Mexican Spanish version of the WHOQOL-
OLD module. However, more detailed examination of the
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A. L. González-Celis, J. Gómez-Benito / Health 5 (2013) 110-116
Copyright © 2013 SciRes. OPEN ACCESS
Table 2. Rotated component matrixa.
Items 1 2 3 4 5 6
Social Participation
18. Satisfied with opportunity to participate in community 0.805
17. Satisfied with level of activity 0.787
16. Satisfied with the way you use your time 0.775
14. Have enough to do each day 0.348
23. Opportunities to love 0.863
24. Opportunities to be loved 0.856
21. Feel a sense of companionship in life 0.735
22. Experience love in your life 0.728
Death and Dying
7. Afraid of not being able to control death 0.863
6. Concerned about the way you will die 0.830
8. Scared of dying 0.811
9. Fear pain before death 0.712
Sensory Abilities
2. Loss of sensory abilities affect participation in activities 0.849
1. Impairments to senses affect daily life 0.838
10. Problems with sensory functioning affect ability to interact 0.678
20. Rate sensory functioning 0.515
Past, Present and Future Activities
12. Satisfied with opportunities to continue achieving 0.618
13. Received the recognition you deserve in life 0.443
19. Happy with things to look forward to 0.438
15. Satisfied with what you’ve achieved in life 0.277
5. People around you are respectful of your freedom 0.738
3. Freedom to make own decisions 0.714
4. Feel in control of your future 0.286
11. Able to do things you’d like 0.716
% of Variance Explained 13.328 11.996 11.537 9.977 9.959 6.152
Cumulative % of Variance Explained 13.328 25.324 36.861 46.837 56.796 62.948
Extraction method: principal component analysis. Rotation method: varimax with Kaiser normalization. a.Rotation converged in 6 iterations.
Table 3. Comparison of quality of life scores (domains and overall) by self-perceived health status: Student’s t test, probability values,
and effect size d.
QOL Domain Health status N Mean SD t df p d
Unhealthy 134 15.13 3.11 2.15 225 0.033 0.29**
Sensory Abilities Healthy 93 16.06 3.38
Unhealthy 134 16.07 2.80 1.51 225 0.132 0.20*
Autonomy Healthy 93 16.63 2.67
Unhealthy 134 15.92 3.18 3.10 225 0.003 0.41**
Past/Present/Future Activities Healthy 93 17.10 2.52
Unhealthy 134 15.83 3.21 2.47 225 0.014 0.33**
Social Participation Healthy 93 16.83 2.69
Unhealthy 134 15.34 4.52 1.15 225 0.253 0.15*
Death And Dying Healthy 93 16.02 4.29
Unhealthy 134 15.48 3.68 1.08 225 0.280 0.14*
Intimacy Healthy 93 16.03 3.94
Unhealthy 134 93.77 14.11 2.70 225 0.007 0.36**
Total Score QoL Healthy 93 98.68 12.52
Note: Sum of N in each domain does not equal 285 (total sample) due to missing data, *Small effect size, **Medium effect size.
A. L. González-Celis, J. Gómez-Benito / Health 5 (2013) 110-116
Table 4. Comparison of quality of life scores (domains and overall) by educational level: ANOVA and probability values.
QOL Domain Educational level N Mean SD F (3, 280) p
Illiterate 22 13.09 3.12 6.220 <0.0001
Elementary school 127 15.00 3.57
Middle school 69 15.48 3.24
Sensory Abilities
High school and College 66 16.44 2.98
Illiterate 22 14.86 2.80 5.409 <0.001
Elementary school 127 15.74 2.94
Middle school 69 16.72 2.36
High school and College 66 16.88 2.37
Illiterate 22 14.09 4.42 5.036 <0.002
Elementary school 127 16.02 3.08
Middle school 69 16.68 2.92
Past/Present/Future Activities
High school and College 66 16.76 2.45
Illiterate 22 14.82 3.72 1.290 >0.278
Elementary school 127 15.83 3.09
Middle school 69 16.17 2.86
Social Participation
High school and College 66 16.18 3.06
Illiterate 22 13.09 5.14 3.636 <0.013
Elementary school 127 15.20 4.61
Middle school 69 15.57 4.38
Death And Dying
High school and College 66 16.53 3.52
Illiterate 22 13.86 4.17 5.290 <0.001
Elementary school 127 15.32 3.57
Middle school 69 16.88 3.09
High school and College 66 16.17 3.82
Illiterate 22 83.81 16.60 9.015 <0.0001
Elementary school 127 93.11 14.44
Middle school 69 97.51 11.28
Total Score Quality of Life
High school and College 66 98.95 10.81
Note: Sum of N in each domain does not equal 285 (total sample) due to missing data.
Table 5. Comparison of quality of life scores (domains and overall) by gender: Student’s t test, probability values and effect size d.
QoL Domain Health Status N Mean SD t df p d
Female 193 15.55 3.27 1.70 283 0.091 0.20*
Sensory Abilities Male 92 14.81 3.68
Female 193 16.31 2.73 1.20 283 0.232 0.14*
Autonomy Male 92 15.89 2.72
Female 193 16.39 3.01 1.38 283 0.168 0.16*
Past/Present/Future Activities Male 92 15.85 3.27
Female 193 16.32 2.75 2.92 283 0.004 0.35**
Social Participation Male 92 15.10 3.57
Female 193 15.03 4.51 2.32 283 0.021 0.28**
Death And Dying Male 92 16.32 4.11
Female 193 15.99 3.71 1.32 283 0.188 0.16*
Intimacy Male 92 15.38 3.50
Female 193 95.59 13.81 1.29 283 0.197 0.15*
Total Score QoL Male 92 93.35 13.36
*Small effect size; **Medium effect size.
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A. L. González-Celis, J. Gómez-Benito / Health 5 (2013) 110-116
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WHOQOL-OLD (including a confirmatory factor analy-
sis with rotation) is required before its factor structure can
be confirmed.
The Mexican Spanish version of the WHOQOL-OLD
module showed acceptable correlations with the DQOL,
BDI, and GDS, this being consistent with the literature
[21]. All these correlations between the DQOL, BDI, and
GDS and scores on the six domains (and overall) of the
WHOQOL-OLD were statistically significant. Positive
coefficients indicated that higher quality-of-life scores
for older persons assessed with the WHOQOL-OLD are
associated with higher levels of quality of life in diabetic
patients, as measured by the DQOL; furthermore, nega-
tive coefficients indicated that the greater the level of
depressive symptoms, the poorer the overall and domain
scores for quality of life, as measured by the WHOQOL-
OLD [22,23]. This indicates that the Mexican Spanish
version of the WHOQOL-OLD has criterion validity
(convergent and divergent). This version of the WHO-
QOL-OLD was also shown to discriminate between
self-perceived healthy and unhealthy elders [2], and also
on the basis of educational level [24]. This was not case,
however, for gender, where the results are conflicting
The WHOQOL-OLD module is a useful alternative to
the WHOQOL-100 or WHOQOL-BREF for investigat-
ing the quality of life in older adults, not least as it in-
cludes relevant aspects not covered by instruments ori-
ginally designed for non-elderly populations. This study
has shown that the Mexican Spanish version of the
WHOQOL-OLD module (comprising 24 items spread
across six domains) has adequate psychometric proper-
ties. It may therefore be used to assess the quality of life
in relation to different health conditions found among the
elderly [26,27]. As such, it can help in considering the
needs, perceptions and interests of older adults [28].
This study was supported by grant 2009SGR00822
from the Agency for Management of University and Re-
search Grants, Government of Catalonia.
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