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Personality and suicidal ideation in the elderly: Factorial invariance and latent means structures across age

29 May 2014-Aging & Mental Health (Routledge)-Vol. 18, Iss: 6, pp 792-800

TL;DR: The findings suggest that the elderly and young adults may be similar on personality and psychopathology variables predicting suicidal ideation than previously hypothesized, and implications are provided for enhanced assessment and intervention of the elderly high in neuroticism, depression, hopelessness, and with negative self-other perception.
Abstract: Objectives: Suicide among the elderly is a dramatic global health problem. Although fatal attempts are frequent in the elderly, research indicated that they rarely present long-term elaboration of suicidal ideation and communicate their intents. Consequently, risk factor detection and assessment are salient. Although evidence on the association between personality and suicidal ideation in young adults is accumulating, little is known about its relevance in the elderly. The purpose of the present study was to analyze the components of a measurement model that are invariant across young adults and older adults and then investigate the relations among dimensions of personality and suicide risk. We postulated a specific relation pattern a priori and tested the hypotheses statistically in order to examine the models for equivalency of the factorial measurement.Method: We investigated 316 young adults and 339 older adults, who were administered self-report questionnaires to assess depression, hopelessness, alte...
Topics: Suicidal ideation (65%), Personality (55%), Suicide prevention (54%), Neuroticism (52%), Extraversion and introversion (51%)

Summary (3 min read)

Introduction

  • Suicide among the elderly is a dramatic global health problem (World Health Organization, 2012).
  • Different life stressors mark the emergence of such conditions in the two groups, i.e. mainly retirement, social isolation, and loss of a partner in the elderly (Juurlink, Herrmann, Szalai, Kopp, & Redelmeier, 2004), and negative childhood experiences, poverty, ill-treatment in youth, and drug abuse (Pompili et al., 2011) in young adults.
  • Lynch et al. (1999) found in a sample of suicidal old adults that chronic behavioral and personality problems were related to previous episodes and early onset of depression.
  • According to Bowlby’s (1969, 1973, 1980) theory of personality development, early life experiences of attachment impact later self–other perceptions, determining significant variations in relationships functioning across life stages.
  • In particular, Zuckerman elaborated an alternative five-factor model of personality, in which traits present psychophysiological correlates and reliability across cultures (Zuckerman, Kuhlman, Joireman, Teta, & Kraft, 1993).

Participants

  • From November 2012 to May 2013, 655 participants aged 18–75 years were contacted at universities, markets, supermarkets, shops, banks, public parks, post offices, and senior centers in three Italian regions: Lombardia, Veneto, and Lazio, and their respective districts.
  • These three nonrandomly selected regions are highly representative of the current demographic background of Italy.
  • Lombardia and Veneto are located in the north part of the country, with approximately 9 million and 5 million residents, respectively, while Lazio is located in the central part of the country, with more than 5.5 million residents.
  • The respondents voluntarily participated in this study after providing written informed consent.
  • The authors created two 17-year age groups on the basis of participants’ age: the Young Adults and the Older Adults.

Measures

  • The Beck Depression Inventory Second Edition (BDI-II; Beck, Steer, & Brown, 1996) is a 21-item self-report measure of symptoms of depression.
  • BDI-II scores range between 0 and 63; categorical depression ratings are ‘minimal’ (0– 13), ‘mild’ (14–19), ‘moderate’ (20–28), and ‘severe’ (29–63).
  • Several authors have noted that although generally accepted in clinical and research contexts, the original dichotomous response format is likely to constrict measurement variance and determine lower sensitivity (Hayslip, Lopez, & Nation, 1991; Hill, Gallagher, Thompson, & Ishida, 1988; Neufeld et al., 2010).
  • The presentation of each picture is accompanied by two equal lists of nine differential semantic scales anchored by opposed terms.
  • In summary, the authors used the two general indicators, self-perception (Cronbach’s alpha ¼ .91) and other-perception (Cronbach’s alpha¼ .89), scored by adding up the score of the nine self-related and the nine other-related scales, respectively.

Statistical analyses

  • The authors used two-tailed t-tests for continuous variables, and chi-square tests with Yates’ correction where appropriate for categorical variables.
  • The CFA implies the formal specification of the measurement instrument in terms of a factor model, the statistical fitting of the factor model to the observed data (variances and covariances or correlations), the assessment of fit, and the interpretation of the results if the model is consistent with the data (Bollen, 1989; Byrne, 2010).
  • This multigroup model serves two important functions: it allows for invariance tests to be conducted across the groups simultaneously, and in testing for invariance, the fit of this configural model provides the baseline value against which subsequent specified invariance models can be compared.
  • In addition to the x2/df test, the authors utilized the comparative fit index (CFI; Bentler, 1990), the Tucker–Lewis index (TLI; Tucker & Lewis, 1973), the root mean square error of approximation (RMSEA; Steiger, 1990) and the standardized root mean square residual (SRMR; J€oreskog & S€orbom, 1996).
  • Specifically, the authors tested for equivalency of the factorial measurement, the scales representing the observed variables, and the underlying latent structure as well as the relations among dimensions of personality and SI risk across the Young Adults and the Older Adults.

Results

  • As regards gender, the Young Adults comprised 179 (52.8%) (mean ¼ 25.8; SD ¼ 3.7) males and 160 (47.2%) females (mean ¼ 26.2; SD ¼ 3.9).
  • The Older Adults comprised 153 (48.4%) (mean ¼ 66.1; SD ¼ 3.7) males and 163 (51.6%) females (mean ¼ 66.6; SD ¼ 4.1), and no difference was found between the age of the participants in this group (t(314) ¼ 1.04; p ¼ .29).
  • On the basis of the working status, participants were divided into two groups: Unemployed and Employed.
  • No differences were found in the working status between the Young Adults and the Older Adults (x2(1) ¼ .05; p ¼ .80).
  • The sociodemographic characteristics are summarized in Table 1.

Baseline models

  • When the authors tested a model with all nine observed variables, namely depression, hopelessness, and neuroticism as indicators of suicidal ideation, and self–other perception, aggressiveness, activity, extraversion, and sensation seeking as indicators of personality, the results were unsatisfactory and statistically irrelevant, with all fitted indices outside the accepted values, and the loadings of aggressiveness (.038), activity (.168) and sensation seeking (.017) extremely low.
  • Hence, the authors excluded these last three variables from the model.
  • These results evidenced a misspecification, and the modification indices suggested that model fit would be improved with the estimation of the error covariance between self and other perception.
  • This specification yielded a moderate change in the goodness-of-fit statistics for both the Young Adults (x2(7) ¼ 42.66; p < .001; CFI ¼ .980; RMSEA ¼ .088) and for the Older Adults (x2(7) ¼ 30.23; p < .001; CFI ¼ .973; RMSEA ¼ .103).
  • The suggested subsequent estimation of the error covariance between depression and hopelessness, improved considerably the goodness-of-fit statistics.

Configural model

  • Results of this multigroup model testing for configural invariance revealed a x2(12) ¼ 43.38; x2/df ¼ 3.61; CFI ¼ .988; RMSEA ¼ .052, as expected, indicating that the hypothesized multigroup model was well fitting across the Young Adults and the Older Adults (cf. Model 1, Table 3).

Metric invariance

  • To test metric invariance, the authors imposed equality constraints on all factor loadings across both groups (cf. Model 2, Table 3).
  • The fit of this model to the data was acceptable, and modestly better fitting than the configural model (x2(16) ¼ 53.38; x2/df ¼ 3.33; CFI ¼ .986; RMSEA ¼ .049).

Scalar invariance

  • Model 4 (Table 4) tested whether variables and factor error variances were equal for both of the groups.
  • The fit of this model was excellent and significantly better than the fit of Models 2 and 3 (x2(27) ¼ 61.74; x2/df ¼ 2.28; CFI ¼ .987; RMSEA ¼ .036).
  • These results indicated that the error variances for the two latent factors and the eight observed variables were identical across groups.
  • In all nested models the differences in CFI were .01, reflecting model invariance (Cheung, 2008; Cheung & Rensvold, 2002).
  • The results indicate that the Elderly latent mean scores do not differ from Young Adults latent mean scores, and the inspection of the latent mean estimates revealed no significant differences both in suicidal ideation (.188; CR ¼ .466; p ¼ .641) and in personality ( 1.074; CR ¼ .466; p ¼ .714).

Discussion

  • In the present study, the authors tested a theoretical model representing a latent structure composed by a pattern of associations among personality characteristics and risk factors for SI across young adults and older adults.
  • The results show a comparable pattern of relations between the observed variables and their underlying latent constructs across the two groups, implying that both the young and the older adults scoring high in specific personality (self–other perception and introversion) and psychiatric (depressive symptoms and hopelessness) dimensions were similarly exposed to increased risk of SI.
  • This will allow to clarify direct and indirect relations among various sets of variables and to outline more comprehensive theoretical models.
  • Second, trained personnel should support the implementation of information, assessment, and prompt intervention policies in community-based old age psychiatry services as well as in medical and psychological emergencies.
  • The present study has some notable limitations.

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Aging & Mental Health
ISSN: 1360-7863 (Print) 1364-6915 (Online) Journal homepage: https://www.tandfonline.com/loi/camh20
Personality and suicidal ideation in the elderly:
factorial invariance and latent means structures
across age
Paolo Iliceto, Emanuele Fino, Ugo Sabatello & Gabriella Candilera
To cite this article: Paolo Iliceto, Emanuele Fino, Ugo Sabatello & Gabriella Candilera (2014)
Personality and suicidal ideation in the elderly: factorial invariance and latent means structures
across age, Aging & Mental Health, 18:6, 792-800, DOI: 10.1080/13607863.2014.880404
To link to this article: https://doi.org/10.1080/13607863.2014.880404
Published online: 30 Jan 2014.
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Citing articles: 8 View citing articles

Personality and suicidal ideation in the elderly: factorial invariance
and latent means structures across age
Paolo Iliceto
a
, Emanuele Fino
b
*, Ugo Sabatello
c
and Gabriella Candilera
d
a
S&P Statistics and Psychometrics Ltd, Rome, Italy;
b
Department of Developmental and Social Psychology, Sapienza University of
Rome, Rome, Italy;
c
Department of Pediatrics and Child Neuropsychiatry, Sapienza University of Rome, Italy;
d
Clinical Psychologist,
Private Practice, Rome, Italy
(Received 13 September 2013; accepted 30 December 2013)
Objectives: Suicide among the elderly is a dramatic global health problem. Although fatal attempts are frequent in the
elderly, research indicated that they rarely present long-term elaboration of suicidal ideation and communicate their
intents. Consequently, risk factor detection and assessment are salient. Although evidence on the association between
personality and suicidal ideation in young adults is accumulating, little is known about its relevance in the elderly. The
purpose of the present study was to analyze the components of a measurement model that are invariant across young adults
and older adults and then investigate the relations among dimensions of personality and suicide risk. We postulated a
specific relation pattern a priori and tested the hypotheses statistically in order to examine the models for equivalency of
the factorial measurement.
Method: We investigated 316 young adults and 339 older adults, who were administered self-report questionnaires to
assess depression, hopelessness, alternative five-factor model of personality, and self–other perception.
Results: Multigroup confirmatory factor analyses were conducted, yielding a final model with excellent fit to the data. This
model showed a similar pattern of associations between suicidal ideation and personality across both groups.
Conclusions: Although the elderly are exposed to specific life stressors associated with suicidal ideation, our findings
suggest that the elderly and young adults may be similar on personality and psychopathology variables predicting suicidal
ideation than previously hypothesized. Implications are provided for enhanced assessment and intervention of the elderly
high in neuroticism, depression, hopelessness, and with negative self–other perception.
Keywords: elderly; neuroticism; extraversion; suicide; hopelessness
Introduction
Suicide among the elderly is a dramatic global health
problem (World Health Organization, 2012). In industrial-
ized countries, suicides in the elderly are more frequent
than in other age groups, and in the last decade such trend
has seen a substantial increase (Baker, Hu, Wilcox, &
Baker, 2013; Ciulla et al., 2014; Legleye, Beck, Peretti-
Watel, Chau, & Firdion, 2010). In Italy, suicide is the
third major cause of death in the adult population, and
rates tend to rise with age (Pompili et al., 2010). Recent
epidemiological studies indicate a death rate of 6.1/
100,000 inhabitants among individuals aged 25–44, 8.4
among those aged 45–64, and 11.3 among those aged >65
(Istituto Nazionale di Statistica, 2011).
Although fatal attempts in the elderly are more fre-
quent than in younger adults, there is evidence that the
elderly are less likely to present long-term elaboration of
suicidal thoughts and to communicate their intent and ide-
ation (Conwell et al., 1998). Consequently, risk detection
and timely intervention are particularly salient. Howeve r,
the progressive increase in average life expectancy and
the aging of the population exhort researchers to investi-
gate and assess risk factor s for suicidal ideation (SI) in the
elderly.
Depression and hopelessness have been most consis-
tently indicated as major predictors of SI in the elderly
(Pompili et al., 2008 ; Szanto, Prigerson, & Reynolds III,
2001) as well as in younger adults (Haaga et al., 2002;
Vrshek-Schallhorn, Czarlinski, Mineka, Zinbarg, &
Craske, 2011). However, different life stressors mark the
emergence of such conditions in the two groups, i.e.
mainly retirement, social isolation, and loss of a partner
in the elderly (Juurlink, Herrmann, Szalai, Kopp, &
Redelmeier, 2004), and negative childhood experiences,
poverty, ill-treatment in youth, and drug abuse (Pompili
et al., 2011) in young adults. In particular, hopelessness
has been reported as the most common emotion experi-
enced among suicidal individuals (Shneidman, 1996), and
research supports a positive relation between scores at the
Beck Hopelessness Scale (BHS) (Beck, Weissman,
Lester, & Trexler, 1974) and measures of depression,
suicidal intent, and ideation in clinical and nonclinical
populations.
Furthermore, to date, few studies have investigated
suicidality in the elderly in relation to specific personality
traits. Lynch et al. (1999) found in a sample of suicidal
old adults that chronic behavioral and personality prob-
lems were related to previous episodes and early onset of
depression. Useda, Duberstein, Conner, and Conwell
(2004) found associations between depression, hopeless-
ness, and SI in the elderly within the broader framework
of neuroticism and introversion, and Tsoh et al. (2005)
*Corresponding author. Email: emanuele.fino@uniroma1.it
Ó 2014 Taylor & Francis
Aging & Mental Health, 2014
Vol. 18, No. 6, 792–800, http://dx.doi.org/10.1080/13607863.2014.880404

reported a positive association between depression and
neuroticism, and a negative association between depres-
sion and extr aversion in old adults with previous suicide
attempt. In the same vein, Wiktorsson et al. (2013) found
that suicide attempters aged 75 and above scored higher
on neuroticism than comparisons, and lower on the extra-
version scale.
Research has recently addressed individual differences
in SI to internal working models (Davaji, Valizadeh, &
Nikamal, 2010; Sheftall, Mathias, Furr, & Dougherty,
2013). According to Bowlby’s (1969, 1973, 1980) theory
of personality development, early life experiences of
attachment impact later self–other perceptions, determin-
ing significant variations in relationships functioning
across life stages. Consistently, previous studies showed
that adults with less secure attachment styles are charac-
terized by less self-confidence and higher levels of nega-
tive effect, and are more lik ely to ideate and attempt
suicide (Fraley & Shaver, 2000).
In addition, although evidence on the role of personal-
ity dimensions in suicide in young adults is accumulating,
little is known about their relevance in the elderly. How-
ever, to date most of the research on SI has employed the
NEO Personality Inventory (NEO-PI; Costa & McCrae,
1992). The NEO-PI represents a lexical approach to the
assessment of personality. More recently, theorists have
focused on the association between personality traits and
relevant behavioral and biological characteristics (Block,
1995; Zuckerman, 1992), going beyond the descriptive
analysis of personality, toward a causal and psychobiolog-
ical appro ach. In particular, Zuckerman elaborated an
alternative five-factor model of personality, in which traits
present psychophysiological correlates and reliability
across cultures (Zuckerman, Kuhlman, Joireman, Teta, &
Kraft, 1993). Understanding the interplay between such
personality characteristics and psychopathology will aid
clinicians in the identification and assessment of the
elderly who are at risk of suicide.
Consequently, the purpose of the present study was to
analyze the components of a measurement model that are
invariant across the young adults and the elderly, and then
investigate the relations among dimensions of personality
and SI risk. We postulated a specific relationship pattern a
priori and then tested the hypotheses statistically in order
to examine the models for equivalency of the factorial
measurement. Specifically, nine scales representing
depression, hopelessness, attachment representations of
the self and the other, and the alternative five-factor model
of personality, as well as the underlying latent structure of
these observed variables characterizin g dimens ions of
personality and SI risk, were tested in young adults and
older adults.
Method
Participants
From November 2012 to May 2013, 655 participants aged
18–75 years were contacted at universities, markets,
supermarkets, shops, banks, public parks, post offices, and
senior centers in three Italian regions: Lo mbardia, Veneto,
and Lazio, and their respective districts. These three non-
randomly selected regions are highly representative of the
current demographic background of Italy. Lombardia and
Veneto are located in the north part of the country, with
approximately 9 million and 5 milli on residents, respec-
tively, while Lazio is located in the central part of the
country, with more than 5.5 million residents. All partici-
pants came from lower to upper middle class, with various
educational and socioeconomic backgrounds, representing
well enough the Italian population. The respon dents vol-
untarily participated in this study after providing written
informed consent. We created two 17-year age groups on
the basis of participa nts’ age: the Young Adults and the
Older Adults. The Young Adults (N ¼ 339) group ranged
from 18 to 35 years (mean ¼ 26.2; SD ¼ 3.8) and the
Older Adults group (N ¼ 316) ranged from 58 to 75 years
(mean ¼ 66.38; SD ¼ 3.9).
Measures
The Beck Depression Inventory Second Edition (BDI-II;
Beck, Steer, & Brown, 1996) is a 21-item self-report mea-
sure of symptoms of depression. The internal consistency
was assessed by means of Cronbach’s alpha (.92).
Respondents choose statements that reflect how they have
felt over the past 2 weeks. BDI-II scores range between 0
and 63; categorical depression ratings are ‘minimal’ (0–
13), ‘mild’ (14–19), ‘moderate (20–28), and ‘severe’
(29–63). The authors found, in their assessed clinical sam-
ple, a cut-off of 17 or greater with a 93% true-positive
rate and an 18% false-positive rate.
The BHS (Beck & Steer, 1987; Beck et al., 1974;
Pompili et al., 2009) is a 20-item true or false self-report
scale developed to operationalize the const ruct of hope-
lessness. Beck originally used this scale with adult psychi-
atric patients in order to predict who would commit
suicide and who would not. Responding to the 20 true or
false items on the BHS, individuals can either endorse a
pessimistic statement or deny an optimistic statement.
Research consistently supports a positive relation between
BHS scores and measures of depression, suicidal intent,
and current SI. Instead of the response format that
includes the true/false endorsement, in this case, to
increase the response sensitivity, we used a Likert-type
scale with 5-point format having two extreme options of
‘very strongly disagree’ (0) and ‘very strongly agree’ (4).
To obtain the measure of hopelessness, we reversed the
scoring of positive items, and then we summed the 20
items to yield a total score ranging from 0 to 80. In this
sample, the instrument showed a good reliability
(Cronbach’s alpha ¼ .83). This change is consistent with
previous research measuring hopelessness in the elderly
(Abraham, 1991; Neufeld, O’Rourke, & Donnelly, 2010).
Several authors have noted that although generally
accepted in clinical and research contexts, the original
dichotomous response format is likely to constrict
measurement variance and determine lower sensitivity
(Hayslip, Lopez, & Nation, 1991; Hill, Gallagher, Thompson,
& Ishida, 1988; Neufeld et al., 2010). In particular,
Aging & Mental Health 793

Neufeld et al. (2010, p. 752) asse ssed SI in a sample of
older adults, changing the response format of the BHS to
a Likert-type scale. The results of the study provided sup-
port to the revised response format of the BHS, showing
good psychometric properties and enhancing measure-
ment sensitivity of SI among older adults.
The 9 Attachment Profile (9AP; Candilera, 2007) is a
semi-projective test for assessing the quality of the inter-
personal relationships based on self–other perception and
internal working models of adult attachment. Bowlby’s
notion of attachment representation involves ideas regard-
ing both the self and others, whereas a person’s representa-
tion of the self and the other could be characterized by one
of the two orientations, i.e. positive or negative. This mea-
sure consists of seven basic pictures. Each picture repre-
sents a situation with one black figure and one or more
white figures in different environments. The presentation
of each picture is accompanied by two equal lists of
nine differential semantic scales anchored by opposed
terms. In the first list, participants are asked to rate their
self-perception on a 9-point scale for each differential
semantic, and in the second list their perception of the
others. 9AP provides 18 bipolar scales regarding psycho-
logical and emotional constructs, nine self-related and nine
other-related: acceptance–rejection, friendliness–hostility,
power–submission, security–insecurity, availability
unavailability, calm–agitation, satisfaction–dissatisfaction,
independence–dependence, lack of competition–competi-
tion. Higher scores correspond to the first term of each
bipolar scale (positive representation), and lower scores
to the second term (negative representation). In summary,
we used the two general indicators, self-perception
(Cronbach’s alpha ¼ .91) and other-perception
(Cronbach’s alpha ¼ .89), scored by adding up the score of
the nine self-related and the nine other-related scales,
respectively.
The Zuckerman–Kuhlman–Aluja Personality Ques-
tionnaire (ZKA–PQ; Aluja, Kuhlman, & Zuckerman,
2010) is a 200-item questionnaire based on the theoretical
constructs of the alternative five-factor model of personal-
ity. The instrument measures aggressiveness (physica l
aggression, verbal aggression, anger, hostility), activity
(work compulsion, general activity, restlessness, work
energy), extraversion (positive emotions, social warmth,
exhibitionism, sociability), neuroticism (anxiety, depres-
sion, dependency, low self-esteem), and sensation seeking
(thrill and advent ure seeking, experience seeking, disinhi-
bition, boredom susceptibility/impulsivi ty). The authors
reported that alphas for aggressiveness, activity, extraver-
sion, neuroticism, and sensation seeking were .78–.81,
.76–.73, .75–.75, .74–.79, and .70–.72 for the Spanish and
American samples, respectively.
Statistical an alyses
We used two-tailed t-tests for continuous variables, and
chi-square tests with Yates’ correction where appropriate
for categorical variables. Factorial invariance and latent
mean structure were tested by structural equation model-
ing (SEM). SEM relies on several statistical tests to
determine the adequacy of model fit to the empirical data.
In SEM, it is possible to analyze relations between
observed variables and latent variables in addition to a
measurement model. The measurement model specifies
hypotheses about the relations between a set of observed
variables and the unobserved variables or constructs that
they were designed to measure. Confirmatory factor anal-
ysis (CFA) allows for a test of specific hypotheses con-
cerning the relation between observed variables and their
underlying latent constructs. On the basis of existing liter-
ature and consistent with theory, we anticipated several
relation patterns a priori and then tested the hypotheses
statistically. CFA seeks to determine if the number of fac-
tors and the loadings of measured (indicator) variables
conform to what is expected by the pre-established theory.
Our a-priori assumption was that each factor would be
associated with a specified subset of indicator variables.
The CFA implies the formal specification of the measure-
ment instrument in terms of a factor model, the statistical
fitting of the factor model to the observed data (variances
and covariances or correlations), the assessment of fit, and
the interpretation of the results if the model is consistent
with the data (Bollen, 1989; Byrne, 2010 ).
A series of multigroup CFA-nested models were con-
structed to examine the evidence of measurement invari-
ance (i.e. configural, metric, scalar, strict) and then the
latent mean structures (Vandenberg & Lance, 2000). In
testing for invariance, it is preferable first running a model
in which only the factor loadings are constrained equal
(i.e. a measurement model), and accordingly, provided
with evidence of group equivalence, these factor-loading
parameters remain constrained, and equality constraints
are then placed on the factor variances and covariances
(i.e. structural model) (Byrne, 2010).
Configural invariance requires that each common fac-
tor is associated with identical measurement sets across
groups, examining the strength of the relation between the
observed variables and their underlying latent constructs.
This model has no equality constraints imposed on the
estimated parameters, thus permitting different parameter
values across groups. This multigroup model serves two
important functions: it allows for invariance tests to be
conducted across the groups simultaneously, and in test-
ing for invariance, the fit of this configural model provides
the baseline value against which subse quent specified
invariance models can be compared.
Metric invariance is tested by imposing equality con-
straints on corresponding factor loadings and com paring
the fit of the constrained model to the configural model.
Metric invariance suggests that the observed variables
have identical meanings across groups. Scalar invariance
requires that the intercepts of the observed variables are
the same across groups and is tested by imposing equality
constraints on the intercepts and assessing model fit in
comparison to the metric invariant model. Strict invari-
ance assesses whether the data support equality of varia-
bles and factor residual variances across groups.
We used the following criteria to evaluate the overall
goodness of fit. The x
2
value close to 0 indicates little dif-
ference between the expected and observed covariance
794 P. Iliceto et al.

matrices, with the probability leve l greater than .05,
evidencing the absence of meaningful unexplained vari-
ance. Moreover, to estimate a better goodness of fit, due
to the fact that x
2
is sensitive to sample size, we calculated
the ratio of x
2
to degrees of freedom that should be less
than 3 as acceptable data-model fit. In addition to the
x
2
/df test, we utilized the comparative fit index (CFI;
Bentler, 1990), the Tucker–Lewis index (TLI; Tucker &
Lewis, 1973), the root mean square error of approximation
(RMSEA; Steiger, 1990) and the standardized root mean
square residual (SRMR; J
oreskog & S
orbom, 1996). Indi-
cators of a well-fitting model are evidenced by CFI and
TLI greater than .95, RMS EA less than .06, and SRMR
less than .08 (Browne & Cudeck, 1989; Hu & Bentler,
1998, 1999). We compared nested models using the x
2
difference test, and the change in CFI. A critical ratio
(CR), as z statistic, equal or greater than 1.96 indicates a
difference betwee n latent means (Cheung, 2008; Cheung
& Rensvold, 2002).
We conducted multigroup CFA-nested models to
examine whether or not the components of the measure-
ment model and the underlying theoretical struct ure were
invariant across the two groups of interest (i.e. the Young
Adults and the Older Adults) to test the hypothesis if the
loadings of the observed variabl es on the factors conform
to what would be expected on the basis of pre-established
theory (Byrne, Shavelson, & Muth
en, 1989). Specifically,
we tested for equivalency of the factorial measurement,
the scales representing the observed variables, and the
underlying latent structure as well as the relations among
dimensions of personality and SI risk across the Young
Adults and the Older Adults.
To test for factorial equivalence, given that the estima-
tion of baseline models involves no between-group con-
straints, the data can be analyzed separately for each
group. Then we used the nine scales to measure the under-
lying constructs of personality and suicidal ideation,
which provided the basis for the hypothesized model in
the determination of the baseline model for each group
separately. If this model fits the data well for both the
groups, it will remain the hypothesized model under the
test for equivalence across the two groups.
We examined the configural invariance to investigate
multigroup representation of the baseline models with
freely estimated factor loadings for each of the groups
simultaneously. This configural model provides the base-
line value against which all subsequent specified invari-
ance models were compared. Provided the evidence of
invariance between the two groups, we estimated latent
mean differences, that is unobserved means derived from
the observed variable means loading on the factor. We
chose the Young Adults as reference group, and fixed to
zero the means of the latent factors, and the Older Adults
as comparison group, and let the means of the latent fac-
tors vary freely.
All analyses were carried out using SPSS 17.0 (SPSS
Inc., Chicago, IL, USA). CFA was applied with the use of
AMOS 16.0 (AMOS: analysis of moment structures) and
maximum likelihood estimation (Arbuckle, 2007).
Results
As expected, there was a significant difference between the
age of the two groups (t
(653)
¼ 133.01; p < .001). As
regards gender, the Young Adults comprised 179 (52.8%)
(mean ¼ 25.8; SD ¼ 3.7) males and 160 (47.2%) females
(mean ¼ 26.2; SD ¼ 3.9). No difference was found
between the age of the participants in this group (t
(337)
¼
.81; p ¼ .41). The Older Adults comprised 153 (48.4%)
(mean ¼ 66.1; SD ¼ 3.7) males and 163 (51.6%) females
(mean ¼ 66.6; SD ¼ 4.1), and no difference was found
between the age of the participants in this group (t
(314)
¼
1.04; p ¼ .29). No gender difference was found in the two
groups (x
2
(1)
¼ 1.25; p ¼ .26), while significant differences
were found in the years of education (x
2
(2)
¼ 48.6; p
.001), as among the Older Adults there were more individ-
uals with less years of education (23.7%), and less individ-
uals with more years of education (25.9%). On the basis of
the working status, participants were divided into two
groups: Unemployed and Employed. No differences were
found in the working status between the Young Adults and
the Older Adults (x
2
(1)
¼ .05; p ¼ .80). The sociodemo-
graphic characteristics are summarized in Table 1.
Baseline models
When we tested a model with all nine observed variables,
namely depression, hopelessness, and neuroticism as indi-
cators of suicidal ideation, and self–other perception,
aggressiveness, activity, extraversion, and sensation
Table 1. Sociodemographic characteristics of subjects.
Characteristics Young Adults (N ¼ 339) Older Adults (N ¼ 316) Statistics p
Age (years) 26.02 3.8
a
66.38 3.9
a
t
(653)
¼ 133.01 <.001
Sex x
2
(1)
¼ 1.25 .26
Males (%) 52.8 48.4
Females (%) 47.2 51.6
Education x
2
(2)
¼ 48.6 <.001
8 (%) 5.0 23.7
13 (%) 58.4 50.3
>13 (%) 36.6 25.9
Working status x
2
(1)
¼ .05 .80
Employed% 35.4 34.5
Unemployed% 64.6 65.5
a
Values shown as mean SD.
Aging & Mental Health 795

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5,269 citations


Journal ArticleDOI
Sören Kliem, Anna Lohmann, Thomas Mößle, Elmar Brähler1  +1 moreInstitutions (2)
25 Apr 2018-BMC Psychiatry
TL;DR: The BHS is a valid measure of hopelessness in various subgroups of the general population and a one-dimensional bi-factor model seems appropriate even in a non-clinical population.
Abstract: The Beck Hopelessness Scale (BHS) has been the most frequently used instrument for the measurement of hopelessness in the past 40 years. Only recently has it officially been translated into German. The psychometric properties and factor structure of the BHS have been cause for intensive debate in the past. Based on a representative sample of the German population (N = 2450) item analysis including item sensitivity, item-total correlation and item difficulty was performed. Confirmatory factor analyses (CFA) for several factor solutions from the literature were performed. Multiple group factor analysis was performed to assess measurement invariance. Construct validity was assessed via the replication of well-established correlations with concurrently assessed measures. Most items exhibited adequate properties. Items #4, #8 and #13 exhibited poor item characteristics– each of these items had previously received negative evaluations in international studies. A one-dimensional factor solution, favorable for the calculation and interpretation of a sum score, was regarded as adequate. A bi-factor model with one content factor and two method factors (defined by positive/negative item coding) resulted in an excellent model fit. Cronbach’s alpha in the current sample was .87. Hopelessness, as measured by the BHS, significantly correlated in the expected direction with suicidal ideation (r = .36), depression (r = .53) and life satisfaction (r = −.53). Strict measurement invariance could be established regarding gender and depression status. Due to limited research regarding the interpretation of fit indices with dichotomous data, interpretation of CFA results needs to remain tentative. The BHS is a valid measure of hopelessness in various subgroups of the general population. Future research could aim at replicating these findings using item response theory and cross-cultural samples. A one-dimensional bi-factor model seems appropriate even in a non-clinical population.

19 citations


Cites methods from "Personality and suicidal ideation i..."

  • ...(Iliceto, Fino, Sabatello, and Candilera [45] established measurement invariance regarding age in a larger model including the BHS, using a Likert scale and Iliceto and Fino tested for general model invariance in two random subsamples....

    [...]


Journal ArticleDOI
Dan Zhang1, Yang Yang1, Yaoyao Sun1, Menglian Wu1  +6 moreInstitutions (2)
01 Sep 2017-Geriatric Nursing
TL;DR: As the first study on path analysis of SI of rural institutional elderly, the findings are significant and factors including self‐esteem and loneliness should be considered when interventions are being conducted.
Abstract: Background Chinese rural elderly are at higher risk of committing suicide. However, little is known about the suicidal ideation (SI) of institutional elderly residents in rural China. Methods 250 participants aged 60 or above living in Chinese rural nursing homes were recruited. Data were collected on subjects' SI, social-demographic characters, physical illness and psychological factors. Univariate comparisons and path analysis were conducted then. Results 19.5% (40/205) of the participants reported a current SI. Hopelessness and depression had significant direct impacts on SI, and self-esteem and loneliness can impact SI through the mediating of depression and hopelessness. Visiting frequency of children, number of physical illnesses and social activities can also affect SI through the mediating of loneliness or self-esteem. Conclusion As the first study on path analysis of SI of rural institutional elderly, the findings are significant. All these factors in our model should be considered when interventions are being conducted.

18 citations


Journal ArticleDOI
Yixiao Dong1, Denis Dumas1Institutions (1)
Abstract: This article aims to systematically review and synthesize the existing literature that has tested at least one of three types of measurement invariance (MI) of a personality measure: cross-cultural/ethnic invariance, gender invariance, and age-group invariance. A literature search was conducted using PsycINFO, PsycARTICLES, Psychology and Behavioral Sciences Collection, and PsycTESTS databases. The initial search yielded a total of 1,647 articles, and 95 studies derived from 75 peer-reviewed articles met all inclusion criteria. None of these studies achieved scalar or strict measurement invariance across cultural/ethnic groups, but many studies established scalar or strict invariance across gender (N = 13, 44.83%) or age (N = 10, 58.82%) groups. To further investigate patterns in this literature, an ordinal logistic regression revealed that age-group and gender invariance studies achieved significantly higher levels of invariance than cross-cultural MI studies, and confirmed that studies testing invariance across larger number of groups had significantly lower MI levels. Consequences and possible reasons for a lack of invariance, and suggestions for improving practices of investigating measurement invariance are discussed.

16 citations


Journal ArticleDOI
Abstract: The objective of this study was to explore the role of personality and self-esteem in later life within two established risk factors for suicidal ideation (SI)—Thwarted Belongingness (TB) and Perce...

12 citations


Cites result from "Personality and suicidal ideation i..."

  • ...These results are aligned with previous research that consistently demonstrates that high Neuroticism and low Extraversion are both predictive of high SI (Heisel & Flett, 2006; Iliceto et al., 2014; Segal et al., 2012; Useda et al., 2004)....

    [...]

  • ...These results are aligned with previous research that consistently demonstrates that high Neuroticism and low Extraversion are both predictive of high SI (Heisel & Flett, 2006; Iliceto et al., 2014; Segal et al., 2012; Useda et al., 2004)....

    [...]


References
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Journal ArticleDOI
Li-tze Hu, Peter M. Bentler1Institutions (1)
Abstract: This article examines the adequacy of the “rules of thumb” conventional cutoff criteria and several new alternatives for various fit indexes used to evaluate model fit in practice. Using a 2‐index presentation strategy, which includes using the maximum likelihood (ML)‐based standardized root mean squared residual (SRMR) and supplementing it with either Tucker‐Lewis Index (TLI), Bollen's (1989) Fit Index (BL89), Relative Noncentrality Index (RNI), Comparative Fit Index (CFI), Gamma Hat, McDonald's Centrality Index (Mc), or root mean squared error of approximation (RMSEA), various combinations of cutoff values from selected ranges of cutoff criteria for the ML‐based SRMR and a given supplemental fit index were used to calculate rejection rates for various types of true‐population and misspecified models; that is, models with misspecified factor covariance(s) and models with misspecified factor loading(s). The results suggest that, for the ML method, a cutoff value close to .95 for TLI, BL89, CFI, RNI, and G...

63,509 citations


"Personality and suicidal ideation i..." refers methods in this paper

  • ...Indicators of a well-fitting model are evidenced by CFI and TLI greater than .95, RMSEA less than .06, and SRMR less than .08 (Browne & Cudeck, 1989; Hu & Bentler, 1998, 1999)....

    [...]


Journal ArticleDOI
Peter M. Bentler1Institutions (1)
TL;DR: A new coefficient is proposed to summarize the relative reduction in the noncentrality parameters of two nested models and two estimators of the coefficient yield new normed (CFI) and nonnormed (FI) fit indexes.
Abstract: Normed and nonnormed fit indexes are frequently used as adjuncts to chi-square statistics for evaluating the fit of a structural model A drawback of existing indexes is that they estimate no known population parameters A new coefficient is proposed to summarize the relative reduction in the noncentrality parameters of two nested models Two estimators of the coefficient yield new normed (CFI) and nonnormed (FI) fit indexes CFI avoids the underestimation of fit often noted in small samples for Bentler and Bonett's (1980) normed fit index (NFI) FI is a linear function of Bentler and Bonett's non-normed fit index (NNFI) that avoids the extreme underestimation and overestimation often found in NNFI Asymptotically, CFI, FI, NFI, and a new index developed by Bollen are equivalent measures of comparative fit, whereas NNFI measures relative fit by comparing noncentrality per degree of freedom All of the indexes are generalized to permit use of Wald and Lagrange multiplier statistics An example illustrates the behavior of these indexes under conditions of correct specification and misspecification The new fit indexes perform very well at all sample sizes

19,626 citations


"Personality and suicidal ideation i..." refers methods in this paper

  • ...In addition to the x2/df test, we utilized the comparative fit index (CFI; Bentler, 1990), the Tucker–Lewis index (TLI; Tucker & Lewis, 1973), the root mean square error of approximation (RMSEA; Steiger, 1990) and the standardized root mean square residual (SRMR; J€oreskog & S€orbom, 1996)....

    [...]


Book
28 Apr 1989-
Abstract: Model Notation, Covariances, and Path Analysis. Causality and Causal Models. Structural Equation Models with Observed Variables. The Consequences of Measurement Error. Measurement Models: The Relation Between Latent and Observed Variables. Confirmatory Factor Analysis. The General Model, Part I: Latent Variable and Measurement Models Combined. The General Model, Part II: Extensions. Appendices. Distribution Theory. References. Index.

18,996 citations


Book
01 Jan 1969-

18,226 citations


Book
21 Jul 2011-
TL;DR: Structural Equation Models: The Basics using the EQS Program and testing for Construct Validity: The Multitrait-Multimethod Model and Change Over Time: The Latent Growth Curve Model.
Abstract: Psychology is a science that advances by leaps and bounds The impulse of new mathematical models along with the incorporation of computers to research has drawn a new reality with many methodological progresses that only a few people could imagine not too long ago Such progress has no doubt revolutionized the panorama of research in the behavioral sciences Structural Equation Models are a clear example of this Under this label are usually included a series of state-of-the-art multivariate statistical procedures that allow the researcher to test theoryguided hypotheses with clearly confi rmatory ends as well as to establish causal relations among variables Confi rmatory factor analysis, the study of measurement invariance, or the multitraitmultimethod models are some of the procedures that stem from this methodology In this sense, it would be diffi cult to fi nd a scientifi c journal that publishes empirical works in psychology that does not address some of these issues, so their current transcendence is undeniable The manual written by the Full Professor of the University of Ottawa, Barbara M Byrne, is a link in a series of books that address this topic Throughout her long academic trajectory, Professor Byrne developed interesting and popular work focused on bringing the researcher and the professional layman—and not so layman—closer to the diverse statistical programs available on the market for data analysis from the perspective of structural equation models (ie, LISREL, AMOS, EQS) (Byrne, 1998, 2001, 2006) Bearing this in mind, the main goal of this work is to introduce the reader to the basic concepts of this methodology, in a simple and entertaining way, avoiding mathematical technicisms and statistical jargon For this purpose, we used the statistical program Mplus 60 (Muthen & Muthen, 2007-2010), an extremely suggestive software that incorporates interesting applications The authoress provides a practical guide that leads the reader through illustrative examples of how to proceed step by step with the Mplus, from the initial specifi cations of the model to the interpretation of the output fi les On the one hand, we underline that the data used proceed from prior investigations and can be consulted in the Internet, offering the reader the possibility of practicing with them (http://wwwpsypresscom/sem-with-mplus/ datasets/); on the other hand, updating the information with novel and apt bibliographic references allows the reader to study in more depth the diverse topics that are presented in the manual, if he or she so desires The book consists of four sections, with a total of 12 chapters The fi rst section, Chapters 1 and 2, addresses introductory terms related to structural equation models and working with the Mplus program at a user-level The second unit focuses on data analysis with a single group In Chapter 3, the factor validity of the self-concept is tested by means of confi rmatory factor analysis In Chapter 4, the authoress performs a fi rst-order confi rmatory factor analysis, in which she examines the validity of the scores of the Maslach Burnout Inventory (MBI) in a sample of teachers In Chapter 5, the internal structure of the scores on the Beck Depression Inventory-II is analyzed by means of second-order confi rmatory factor analysis in a sample of Chinese adolescents In the next chapter, the complete model of structural equations is tested, and the authoress examines the causal relation established between diverse variables (ie, work climate, self-esteem, social support) and Burnout The third section of the manual is, in my opinion, the most interesting, not only because of the expansion of the study of measurement invariance in recent years but also because of the expansion it may possibly have in the future In this section, Professor Byrne goes into multigroup comparisons Specifi cally, in Chapter 7, she examines the factor equivalence of the MBI in two samples of teachers by means of the analysis of covariance structures In this chapter, she introduces relevant concepts, such as types of invariance (confi gural, metric, and strict) or the invariance of partial measurement In Chapter 8, she also analyzes measurement invariance, using for this purpose the analysis of mean and covariance structures This analysis, in comparison to the analysis of covariance structures, allows contrasting the latent means of two or more groups With this goal, she verifi es whether there is measurement invariance between the scores on the Self-description Questionnaire-I in Nigerian and Australian adolescents In Chapter 9, she proposes a complete model of structural equations in which she tests the causal structure through the procedure of cross validation Lastly, in the fourth section, she reveals three very interesting topics, that are also up-to-date and that, to some degree, go beyond the initial goal of the book, such as the multitrait-multimethod models, latent growth curves, and multilevel models Summing up, the work “Structural Equation Modeling with Mplus: Basic concepts, applications, and programming” is of enormous interest and utility for all professionals of psychology and related sciences who, without having exhaustive knowledge of the details of structural equation models, wish to test their hypothetical models by means of the Mplus program No doubt, this is a reference manual, a must-read that is accessible and that has a high degree of methodological rigor We hope that the readers

15,530 citations


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