Dimensional Structure and Psychometric Properties of the Persian Version of the Existential Loneliness Questionnaire (ELQ)

doi:10.21203/rs.3.rs-3126417/v1

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Research Article

Dimensional Structure and Psychometric Properties of the Persian Version of the Existential Loneliness Questionnaire (ELQ)

https://doi.org/10.21203/rs.3.rs-3126417/v1

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published 01 Jan, 2023

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Background: The recent pandemic of Coronavirus and its associated excess mortality, made the man more prone to sense of isolation and of being alone existentially. Therefore, it is necessary to identify, assess, and reduce such negative feelings. The present study aims to provide a Persian adaptation of the existential loneliness questionnaire (ELQ) and to examine its dimensional structure and psychometric characteristics.

Methods: The ELQ items were translated into Persian using forward-backward translation method. Participant recruitment is conducted via social media platform and data is collected via online survey. Content validity was evaluated by the experts‘ judgement, followed by factor analysis, validity, and reliability tests. Two samples of university students were collected. Sample 1 consisted of 305 students aged 18-53 years, completed the Persian adaptation of the ELQ and several other instruments: De Jong Gierveld Loneliness Scale (DJGLS), Existential Anxiety Questionnaire (EAQ), Beck Depression Inventory (BDI-13), Meaning in Life Questionnaire (MLQ), and Satisfaction with Life Scale (SWLS). Sample 2 consisted of 262 students aged 18-50 years, completed only the Persian ELQ to conduct Confirmatory Factor Analysis (CFA) tests.

Results: According to Parallel Analysis (PA) and Exploratory Factor Analysis (EFA) results, a unidimensional structure was found for the Persian ELQ. And the results of the CFA test supported this finding. The Multi-group CFA test supported the measurement invariance of the questionnaire across two samples. Evidence of high internal consistency (α =.91) and adequate test-retest reliability (r= .73) was found as well. The correlational analyses revealed strong construct validity based on the ELQ scores‘ significant association with other criterion measures.

Conclusions: According to the findings, the Persian version of the ELQ is a reliable, valid and psychometrically suitable instrument for use in Iranian samples of university students.

Loneliness

Existential Loneliness

Dimensionality

Psychometrics

Validity

Reliability

Loneliness is a universally accepted concept in psychology literature; however, theoretical debates and disagreements over its nature continue. Loneliness is often defined as the negative subjective experience, the unpleasant or distressing feeling that results from the absence of satisfying interpersonal relationships; or from the lack of meaningful relationships or social companionship (1, 2). Existential loneliness is an ontological aspect of loneliness that is broadly described in relation to existential issues of being human, such as guilt, death, isolation, meaninglessness and the like (3). In existential literature, loneliness is described as a basic existential human concern (4), a part of being human (5) or a part of the human predicament (6). Existential loneliness as an intrinsic feature of human existence stems from the awareness of the painful fact that human is fundamentally alone. Such a basic sense of loneliness refers to unavoidable separateness from the world and others. This refers to a primary and fundamental separation from every creature and everything in the world (5, 7, 8). In this sense, ʺno matter how close one becomes to another… there is an ultimate unbridgeable gapʺ (4, p 404).

Ettema et al. have defined existential loneliness as ʺintolerable emptiness, sadness, and longing, that results from the awareness of one’s fundamental separateness as a human beingʺ (9, p 142). Existential loneliness is also considered to be everpresent, as it may be experienced by everybody at some point in life, specifically in confronting with life-threatening situations, like disease and death. It has been asserted that this type of loneliness has no permanent remedy, but instead can be momentarily palliated by defensive activities; when encountering such a feeling, people often tend to use psychic defenses and occupy their minds with hobbies, romantic relationships and vacations or with some tasks, such as living a busy life, actualizing oneʹs potentialities, and expressing oneself creatively, in order to protect themselves from the basic sense of loneliness. The fact is that such defenses temporarily alleviate negative, unpleasant states of isolation, but ultimately peopleʹs defenses may collapse in face of life threatening events over which they have no control (9, 10).

Existential loneliness is described as an everpresent feeling of aloneness, against which human defends oneself for much of the time but for which there is no permanent remedy (11).

There is a large body of research regarding loneliness among older people, but little is known about the existential loneliness in old-age (12). It is assumed that existential loneliness can appear at any time throughout life, but is more often present at the end-of-life when people get older. In fact, existential loneliness is considered as being interrelated with death and often defined in relation to it, as lonely confrontation with oneʹs own death or finitude. As a result, existential loneliness is assumed to be most evident in end-of-life-events (5, 7, 13). Also, studies have shown that people with deadly diseases, like cancer patients, are forced to face existential concerns and experience existential isolation (14). It is emphasized that people with serious psychiatric and physical diseases are more vulnerable to existential loneliness, such as schizophrenic patients (15), patients suffering from aphasia (16), people with advanced cancer (17, 18), women with breast cancer (19), HIV-infected gay men (13), and HIV-infected women (10).

The theoretical and research literature supported the idea that loneliness in general, existential loneliness in particular, has negative consequences on physical and mental health. Empirical studies have revealed that there is a close relationship between loneliness and depression (20, 21), anxiety (22), life satisfaction (23) and meaning in life (24, 21). It has also been indicated that existential loneliness is closely associated with negative psychological outcomes, e.g., depressive symptoms and suicidal ideation (25, 26), existential anxiety and meaninglessness (25, 26, 27, 28). In fact, existential anxiety and meaninglessness are concepts generally overlapping with existential loneliness (4, 9, 10). Existential loneliness is thought to be primary source of anxiety for human beings (29). Regarding relationships between existential loneliness and mental health, it is necessary to develop a suitable psychometric instrument that can measure existential loneliness accurately.

Since 1970s, various instruments have been developed to measure loneliness, including the Belcher Extended Loneliness Scale (BELS) (30), the USLA Loneliness Scale (31), the New York University Loneliness Scale (NYULS) (32), the Differential Loneliness Scale (DLS) (33), the Loneliness Rating Scale (LRS) (34), the Loneliness and Aloneness Scale for Children and Adolescents (LACA) (35), the Emotional and Social Loneliness Scale (ESLI) (36), the Social and Emotional Loneliness Scale for Adults (SELSA) (37), the Three-Item Loneliness Scale (TILS) (38), the University of Philippines Loneliness Assessment Scale (UPLAS) (39), and the Buenos Aires Loneliness Scale (BALS) (40). Some of these instruments (such as USLA, TILS, UPLAS and BALS), inspired by global approach, address unidimensional nature of loneliness, while others inspired by multidimensional approach, address multifaceted nature of loneliness and measure different forms of loneliness, such as emotional, social, etc. According to global approach, loneliness is a unitary phenomenon varying in experienced frequency or intensity. But multidimensional approach views loneliness as a multifaceted phenomenon which cannot be assessed by a single global measure.

The main problem is that only two instruments measure existential loneliness: The BELS (30) and the Existential Loneliness Questionnaire (ELQ) (27). The BELS consists of 60 items with 8 subscales one of which is existential loneliness (8 items). This factor has been criticized for inadequacy of its subset items (41, 10), and for being lengthy and unwieldy (34). Unlike the BELS, the ELQ (consisting of 22 items) was particularly developed to assess existential loneliness using a small sample included 47 HIV–infected women who are more vulnerable to experience existential concerns. After a decade, Gökdemir-Bulut and Bozo (25) Translated the ELQ into Turkish and studied its psychometric properties.

Since in Persian language, there is no psychometric instrument particularly assigned to measure existential loneliness, so the ELQ was chosen to translate into Persian. The purposes of the present study was to examine factorial structure and psychometric properties (e.g. validity and reliability) of the Persian ELQ in the samples of university students, as Mayers et al. (27) recommended the replication of the questionnaire with larger samples by performing factor analysis.

Participants

The present study included two samples of university students. Sample 1 was used for all of the statistical analyses but sample 2 only for confirmatory factor analysis. Sample 1 was a convenience sample that consisted of 305 participants who were students of Islamic Azad University (72.5% female, n = 221; 27.5% Male, n = 84) with ages ranging between 18 and 53 years (M = 26.6, SD = 8.1). The participants reported their perceived socioeconomic status as low (n = 43, 14.1%), middle (n = 238, 78%), and high (n = 24, 7.9%). Also, Participantsʹ marital status was as follows: 72.8% single (n = 222), 23.3% married (n = 71), and 3.9% divorced (n = 12). Sample 2 was a convenience sample consisted of 262 students of Islamic Azad University (58.8% female, n = 154; 41.2% male, n = 108) with ages ranging between 18 and 50 years (M = 27.23, SD = 8.16).

Instruments

The sociodemographic characteristics were asked at the beginning by seven questions about participantsʹ gender, age, marital status, job, education, income and socioeconomic status.

Existential Loneliness Questionnaire (ELQ)

The ELQ was developed by Mayers et al. (27) to measure existential loneliness among 47 HIV-infected women, consisting of 22 items rated on a 6-point Likert scale. These items met the Rasch model’s criteria and were internally highly consistent (α = .90). Items 1, 2, 7, 14, and 18 are reverse. Getting high scores on this questionnaire means high level of existential loneliness. Gökdemir-Bulut and Bozo (25) reported a high internal consistency (α = .88) and adequate test-retest reliability (r = .75) for the Turkish version of the ELQ. They also reported a three-factor structure for the questionnaire: loneliness in social ties (α = .84), loneliness in close relationships (α = .70), and finding meaning in life (α = .80).

Beck Depression Inventory (BDI-13)

This is a short form of the Beck Depression Inventory designed by Beck and Beck (42) and translated into Persian by Dadfar and Kalibatseva (43). The inventory consists of 13 groups of statements designed to measure frequency and intensity of depressive symptoms. A higher score of the inventory indicates a more intensified depression. The Persian version of the BDI-13 possesses good concurrent and discriminant validity and high internal consistency (α = .85) (43).

Existential Anxiety Questionnaire (EAQ)

The EAQ is a true-false rating scale designed by Weems et al. (44) to measure existential anxiety as conceptualized in the work of Tillich (45). It consists of 13 items half positively worded and half negatively worded. The scale has good internal consistency (α = .71) and test-retest reliability (r = .72). It has also good convergent and incremental validity estimates (46). Etemad et al. (47) reported adequate reliability and good construct validity with the three-factor structure for the Persian version of the EAQ: death-fate (α = .51), emptiness-meaninglessness (α = .41), and guilt-condemnation (α = .51).

De Jong Gierveld Loneliness Scale (DJGLS)

The DJGLS designed by De Jong Gierveld and colleagues (48, 49) and translated by Hosseini et al. (50) into Persian, was used to assess participants‘ feeling of loneliness. A higher score of the scale indicates a more sense of interpersonal loneliness. The scale consists of 11 items with two subscales; five items positively formulated assess social loneliness (α = .88) and six items negatively formulated assess emotional loneliness (α = .88), and all items assess general loneliness (α = .84). The Persian version of the DJGLS possesses good reliability and validity (50).

Satisfaction with Life Scale (SWLS)

The SWLS developed by Diener et al. (51) and translated by Bayani et al. (52) into Persian, was used to assess participants‘ satisfaction with life. It consists of 5 items rated on a 7-point Likert scale. A higher score of the scale indicates a more satisfaction with life. The Persian version of the SWLS possesses good concurrent and discriminant validity, high internal consistency (α = .83) and acceptable test-retest reliability (r = .70) (52).

Meaning In Life Questionnaire (MLQ)

The MLQ designed by Steger et al. (53) and translated by Mesrabadi et al. (54) was used to measure participants‘ meaning in life. This 10-item scale consists of two subscales, Presence of Meaning and Search for Meaning, each is measured by 5 items rated on a 7-point Likert scale. A higher score of the scale reflects a higher level of presence of and search for meaning. Subscales MLQ-P and MLQ-S possess acceptable test-retest reliability (r = .70 and .73 respectively) and high internal consistency (α = .82 and .88 respectively) (53).

Procedure

The study was conducted between March and May 2022. At first, the permission to translate and adapt ELQ was received from one of the creators A. Mayers via email and then, the questionnaire was translated by two experts who were fluent in Persian and English. The method of translation was forward-backward translation. Three items (6, 8 & 22) designed for HIV population, were changed into general statements to be applicable in various populations. After translation, participants were selected among students of Islamic Azad University via convenience sampling. The Sample 1 participants were chosen among students of disciplines in social sciences but the Sample 2 participants were chosen among students of disciplines in natural sciences. The package given the students of sample 1 consisted of Persian versions of the ELQ, DJGLS, EAQ, BDI-13, MLQ and SWLS. The sample 2 students completed only the Persian version of ELQ. All data were collected via online surveys. Participants were recruited through social media platforms. The link of questionnaire package was distributed to potential participants through Gmail, WhatsApp, and Telgeram. First page of this package provided participants with full information about the study (https://survey.porsline.ir/s/IAisaex). Informed consent was obtained from participants electronically at the beginning.

Statistical Analyses

First, content-based validity was examined through Aiken’s V coefficient (significant values ≥ .80) estimated in terms of the experts‘ scores (55). Second, missing values and outliers were examined and descriptive statistics for each item were calculated using SPSS 21, and univariate and multivariate normality was checked by evaluating item skewness, kurtosis, and Mardia‘s test using Lisrel 8.8. Third, dimensional structure of the items was checked using Parallel Analysis (PA) and Exploratory Factor Analysis (EFA). To determine the number of factors (56), the PA with optimal implementation and the EFA with the estimation method of Robust Unweighted Least Squares (RULS) and polychoric correlations matrix were conducted using FACTOR 11.05.01. The Weighted Least Square Mean and Variance Adjusted (WLSMV) was the estimator (57). Then, Confirmatory Factor Analysis (CFA) and multi-group CFA (MGCFA) were run using Lisrel 8.8 and the Configural,

metric, and scalar measurement invariance between two samples were calculated. Following Hu and Bentler (58, 59), model fit was evaluated using a number of adjustment indices and common cut-off criteria, including Chi-Square ( χ²), Normed Chi-Square (χ²/df) < 2.5, comparative fit index (CFI) ≥ 0.95, goodness of fit index (GFI) ≥ 0.90, Tucker–Lewis index (TLI) ≥ 0.95, root mean square error of approximation (RMSEA) ≤ .060, and standardized root mean square residual (SRMR) ≤ .080. For nested models, adjustment indices and cut-off criteria were used as evidence for measurement invariance: ΔCFI ≤ 0.01, ΔSRMR ≤ .03 (60), and ΔRMSEA < 0.01 supposed to be adequate for ordinal variables (61). Fourth, after exploring the structure of the questionnaire, correlational analyses were conducted to examine convergent and discriminative validity. And the association between ELQ scores with other measures was estimated using SPSS 21. Finally, the internal consistency was tested using Cronbach’s alpha and split-half correlation coefficients (acceptable values ≥ .70) and the test-retest reliability was evaluated using test-retest reliability coefficient (acceptable values ≥ .70).

Content validity

Content validation was based on the expert assessment. To examine content validity quantitatively, the questionnaire was administered to 5 experts who were asked to evaluate the relevance and clarity of each item on a five-category rating; for example, 1 = completely irrelevant, 2 = irrelevant, 3 = less relevant, 4 = relevant, and 5 = extremely relevant. Based on the Aiken‘s table (55), the cutoff value was of .80. Thus, according to the two validity criteria (relevance, and clarity), two V coefficients were estimated for each item. Finally, all items were presented acceptable (See table 1).

Descriptive Statistics

Related to sample 1, statistical descriptions including mean, standard deviation, variance, skewness and kurtosis were calculated for each item of the ELQ (see table 1). The assumption of univariate normality was verified for data of sample 1 because univariate values of skewness and kurtosis was in acceptable range (between ‒2 and + 2) for each item (62). The foundation for factor analysis is correlational statistics based on the multivariate normality (63). The test of multivariate normality in was run in terms of Mardia’s indexes (64) and resulted in statistically significant non-normality, meaning that dataset deviates from multivariate normal distribution in sample 1 (Skewness z: 22.22, p < .001; Kurtosis z: 13.29, p < .001) and sample 2 (Skewness z: 31.95, p < .001; Kurtosis z: 16.37, p < .001).

Explratory Factor Analysis

To examine factorial structure of the Persian ELQ, an EFA was performed on sample 1. Since dataset did not follow multivariate normality and for the ordinality of variables (e.g., Likert-type scale), the extraction method of RULS, based on the polychoric correlation matrix (57) was used. This method is in fact free from multivariate normality assumption (63). Also, the PA has been already suggested as one of the best methods for determining number of factors (65). According to the PA based on Minimum Rank Factor Analysis (MRFA), the factors number was estimated to be one. Also, results of the Closeness to Unidimensionality Assessment Test (66) recommended a unidimensional structure for the dataset. An EFA was conducted on the 22 item ELQ. Sampling adequacy was calculated with Kaiser-Meyer-Olkin (KMO) and Bartlett’s sphericity tests. The KMO index was 0.916 with a bootstrap Confidence Interval (CI) at 95% (.838 .904) and Bartlett’s test was significant (χ ²(231) = 3405.9, p < .0001). The Optimal implementation of PA resulted in the extraction of one general factor explaining the 47.35% of the variance. As a result of item analysis, items 5 and 11 were removed for the sake of low factor loading (< .40) and low item-total correlation (< .30) (67). Thus, a new EFA was performed on 20 remaining items. The KMO was of .927 with 95% CI (.861 .920) and Bartlett’s test was significant (χ ²(190) = 3413.6 p < .0001). The main factor explained the 51.25% of the variance. The first eigenvalue was 8.83 and others were less than one. And factor loadings of the unrotated matrix

Table.1: Items Descriptive Statistics

Items	M	Std	Var	Sk^a	K^b	A^c	A^d
Q1-I am happy with the way I have lived my life.	3.08	1.418	2.010	.210	− .926	.95	1.0
Q2-I have goals in my life.	2.45	1.459	2.129	.696	− .601	.90	.90
Q3-I am surrounded by strangers I cannot connect with.	2.28	1.259	1.585	.909	.102	1.0	.95
Q4-I feel lonely.	2.87	1.574	2.479	.488	− .866	.95	.90
Q5-When I feel lonely, I do whatever I can not to think about those feelings.	3.14	1.639	2.687	.300	-1.119	1.0	.95
Q6-I have had trouble finding people I can talk to.	2.36	1.479	2.186	1.027	.109	.90	.95
Q7-I feel I have people I can trust and rely on if I need them.	2.82	1.519	2.308	.404	-1.052	.95	.95
Q8-My fears of being rejected makes it harder to be around other people.	2.25	1.312	1.722	.975	.220	.95	1.0
Q9-If I had the right relationship, I would never feel alone.	3.23	1.860	3.459	.216	-1.407	1.0	.90
Q10-I stay in bad relationships too long in order not to be alone.	1.94	1.300	1.691	1.423	1.274	.95	1.0
Q11-I immediately get involved in new relationships as soon as I break up.	1.90	1.239	1.536	1.482	1.556	.95	1.0
Q12-I feel helpless.	2.38	1.444	2.086	.923	− .078	1.0	.95
Q13-I feel alone.	2.81	1.523	2.319	.561	− .673	.95	.90
Q14-I mean something to others	2.63	1.322	1.748	.481	− .539	.95	.95
Q15-Important relationships have ended or become weaker.	2.65	1.429	2.043	.663	− .391	.90	.95
Q16-I feel at the mercy of the world.	2.69	1.480	2.190	.615	− .529	.95	.95
Q17-I feel dead (inside).	2.48	1.573	2.474	.896	− .277	1.0	.90
Q18-The universe is full of meaning.	2.44	1.439	2.070	.826	− .322	.95	1.0
Q19-I feel that there is little point to life.	2.24	1.381	1.908	1.050	.322	1.0	.95
Q20-No one else in the world can understand my feelings.	2.74	1.573	2.475	.654	− .635	1.0	1.0
Q21-My world seems so different from everybody else’s.	2.85	1.586	2.517	.583	− .818	1.0	.90
Q22-I feel hopeless about having a romantic relationship.	2.64	1.796	3.225	.713	− .933	1.0	1.0
M: Mean, Std: Standard Deviation, Var: Variance, Sk: Skewness, K: Kurtosis, A: Aiken‘s Validity Index (V coefficient)
a. Std. Error = 0.117, b. Std. Error = 0.234, c & d. p < 0.05, A^c = Relevance, A^d = Clarity

were between .52 and .84. The results of the EFA and item-total correlations for remaining 20 items of Persian ELQ are presented in Table 2. The fit indices of one-dimensional model were as follows: χ² (170) = 294.613 (P < .001); CFI = .989 with 95% CI (.988 .993); GFI = .985 with 95% CI (.984 .987); RMSR = .061 with 95% CI (.059 .061); TLI = .988 with 95% CI (.986 .992); and RMSEA = .049 with 95% CI (.0446 .0478). These results demonstrated a relatively good fit.

Table 2

The results of Exploratory Factor Analysis of the Persian ELQ
Items	Eigenvalue	Factor Loading	Communality	Item-Total Correlation
Q1 ‎	8.832	.612	.374	.573
‎Q2	.688	.672	.452	.610
‎Q3	.484	.535	.286	.481
‎Q4	.373	.804	.647	.743
‎Q6	.233	.640	.410	.574
‎Q7	.160	.578	.334	.528
‎Q8	.092	.631	.398	.550
‎Q9	.040	.590	.348	.528
‎Q10	.002	.529	.280	.461
Q12	− .021	.786	.618	.711
‎Q13	− .042	.773	.597	.717
‎Q14	− .103	.645	.416	.594
‎Q15	− .122	.654	.427	.610
‎Q16	− .149	.755	.570	.697
‎Q17 ‎	− .198	.845	.714	.767
‎Q18	− .229	.623	.388	.573
‎Q19	− .244	.713	.508	.604
‎Q20	− .278	.605	.366	.552
‎Q21	− .330	.549	.301	.480
Q22	− .354	.639	.399	.559

Confirmatory Factor Analysis

CFA was performed to test the factorial structure resulted from the EFA. Since there were two samples of university students in this study, Multi-group CFA was conducted to understand whether factorial structure is equivalent across these samples. At first, the CFA was performed on each sample separately. The CFA with the RULS method based on polychoric correlation matrix was conducted on sample 1 and the results demonstrated a relatively poor fit. The goodness of fit indices were χ² (170) = 451.44 (p = 0.000); χ²/df = 2.65; CFI = .975; TLI = .972; GFI = .985, SRMR = .0588, and RMSEA = .073. Regarding modification indices, correlating error covariances of the items 1 and 2, 2 and 18, and 7 and 14 was selected as they were closely associated conceptually, i.e., items 1 and 2 focus on one‘s meaningfulness of life which has an indirect relationship to existential loneliness; similarly, items 2 and 18 also focus on the presence of meaning and purpose in one‘s life that has an indirect relationship to existential loneliness; and items 7 and 14 focus on one‘s perceived social support closely associated with the low level of existential loneliness. The modified model fit indices were as follows: χ² (167) = 364.78 (p = 0.000); χ²/df = 2.19; CFI = .982; TLI = .980; GFI = .987, SRMR = .0543, and RMSEA = .062. Figure 1 presents the path diagram of the model.

The CFA was also conducted on sample 2. As expected, results supported the unidimensional structure of the 20-item Persian ELQ, one-factor model demonstrated evidence of good fit: χ² (170) = 400.59 (p = 0.000); χ²/df = 2.35; CFI = .980; TLI = .978; GFI = .984, SRMR = .0654, and RMSEA = .072. Regarding modification indices, correlating error covariances of the items 1 and 2, 7 and 14, and 20 and 21 was selected for the sake of their theoretical and conceptual relationship. Similar to sample 1, items 1 and 2 focus on the meaning in life negatively correlated with the existential loneliness, and items 7 and 14 focus on the social support negatively correlated with the existential loneliness; and items 20 and 21 focus on one‘s sense of being disconnected or emotionally distanced from other people, which has a direct relationship to the existential loneliness. The modified model fit indices were as follows: χ² (167) = 322.79 (p = 0.000); χ²/df = 1.93; CFI = .986; TLI = .985; GFI = .987, SRMR = .0593, and RMSEA = .060. Figure 2 presents the path diagram of the model.

In the next, the MGCFA was conducted to examine structural and measurement invariance among the two samples. The result of configural invariance test indicated the same measurement model across two samples; it means that the same factor structure exists across two samples. The results indicated that the configural model fit the data well (SBχ² (360) = 474.64, p < .001, CFI = .992, RMSEA = .064, SRMR = .057). In the next step, metric invariance was tested by constraining factor loadings to be equal across samples. The results of the metric invariance test indicated that the fit values of metric model supported the invariance (SBχ² (359) = 468.17, p < .001, CFI = .992, RMSEA = .063, SRMR = .053). Compared to the configural model, the changes in goodness of fit indices were in acceptable range, providing support that metric invariance held. Finally, scalar invariance was tested by constraining item thresholds to be equal in addition to factor loadings across samples. The results showed that the values of scalar model fit the data well (SBχ² (378) = 515.14, p < .001, CFI = .990, RMSEA = .066, SRMR = .055). Compared to the metric model, the changes in goodness of fit indices were in acceptable range, providing support that scalar invariance held. Therefore, it was concluded that the factor loadings and item thresholds were invariant in the overall model. Generally, the configural, metric, and scalar invariance models were supported. The measurement invariance results are presented in Table 3.

Table 3

Testing for measurement invariance across two samples
Models	SBχ²	df	ΔSBχ²	Δdf	CFI	RMSEA	SRMR	ΔCFI	ΔRMSEA	ΔSRMR
Configural Invariance	474.64*	360	-	-	.992	.064	.057	-	-	-
Metric Invariance	468.17*	359	6.47	1	.992	.063	.053	0.00	.001	.004
Scalar Invariance	515.14*	378	46.97	19	.990	.066	.055	.002	− .003	− .002

*p < .001 - SBχ² = Satorra-Bentler chi-square; CFI = comparative fit index; RMSEA = root mean square error of approximation; SRMR = Standardized root mean square residual.

Reliability

Cronbachʹs alpha coefficient was estimated to assess the questionnaireʹs internal consistency (α = .91). Also, Spearman-Brown Coefficient was .89 and Guttman split-half coefficient was .88 (Part-1 α = .79 and Part-2 α = .88). To examine test-retest reliability, 58 participants from the sample 1 filled out the Persian ELQ again after one month. The test-retest correlation coefficient over one month-interval was estimated to be .73 (p < .01).

Convergent and Discriminant Validity

To assess convergent validity of the Persian version of the ELQ, relationship between existential loneliness with some related psychological constructs was evaluated. It was hypothesized that existential loneliness to be positively associated with general loneliness, existential anxiety and depression, consistent with the literature and previous studies on loneliness (25, 27). Regarding the validity evidence for the scale, Spearman’s correlation between ELQ and DJGLS, EAQ and BDI was positive and statistically significant. As expected, ELQ scores was positively associated with the DJGLS scores (r = .63, p < .01). EAQ scores (r = .51, p < .01) and BDI scores (r = .64, p < .01).

To assess divergent validity of the questionnaire, the negative relationship of existential loneliness with some concepts was evaluated. It was hypothesized that the existential loneliness to be negatively associated with life satisfaction and meaning in life, consistent with previous studies on loneliness (27, 25, 28). According to correlational analyses, ELQ scores had a significant negative association with SWLS scores (r = − .55, p < .01) and MLQ scores (r=-.52, p < .01) (see Table 4).

Table 4

Correlation coefficient matrix of measures
Measures	ELQ	SWLS	MLQ-P	MLQ-S	MLQ	EAQ	DJGLS	BDI
ELQ	1
SWLS	− .555*	1
MLQ-P	− .626*	.588*	1
MLQ-S	− .230*	.191*	.316*	1
MLQ	− .521*	.505*	.855*	.762*	1
EAQ	.514*	− .413*	− .564*	− .203*	− .496*	1
DJGLS	.631*	− .503*	− .707*	− .241*	− .614*	.591*	1
BDI	.646*	− .460*	− .447*	− .144**	− .384*	.512*	.511*	1
(p < .01) * (P < .01)

ELQ: Existential Loneliness Questionnaire, SWLS: Satisfaction with Life Scale, MLQ: Meaning in Life Questionnaire (MLQ-P: Presence of Meaning, MLQ-S: Search for Meaning), EAQ: Existential Anxiety Questionnaire, DJGLS: De Jung Gierveld Loneliness, BDI: Beck Depression Inventory.

As suggested by Mayers et al. (27) and Gökdemir-Bulut & Bozo (25), depression impacts the relationship between existential and general loneliness. By conducting multiple hierarchical regression test, it was found that depression explains 41% of the variance in existential loneliness (R² = .41, F (1,303) = 217.55, p < .001). Adding general loneliness to the regression equation indicated that general loneliness significantly explained 21% of the variance in existential loneliness beyond the variance explained by depression (R² = .63, ΔR² = .21, F (1,302) = 179.49, p < .001). Then, adding existential anxiety to the regression equation indicated that existential anxiety explained 2% of the variance in ELQ scores beyond the variance explained by depression and general loneliness (R² = .65, ΔR² = .02, F (1,301) = 16.14, p < .001). Also, adding meaning in life to the regression equation indicated that life meaning explained 3% of the variance in ELQ scores beyond the variance explained by depression, general loneliness and existential anxiety (R² = .68, ΔR² = .03, F (1, 300) = 25.11, p < .001). Accordingly, 68% of the variance in ELQ scores was explained by general loneliness, depression, existential anxiety, and meaning in life; this was considered as the indication of convergent validity. And 32% of the variance in the Persian ELQ scores was remained unexplained; this implied that existential loneliness is conceptually different from related concepts (divergent validity).

The present study was done to examine dimensional structure of the ELQ and evaluate its psychometric properties in Iranian population. Results from this study provides a promising start for

further development of the existential loneliness scale. The study revealed that the Persian ELQ is a unidimensional scale. Also, there was a good fit for such a model. The questionnaire appeared to be a reliable and valid instrument for assessing existential loneliness of Iranian students. Further studies on different populations with larger sample sizes should be done to examine the generalizability of the findings.

As stated by Mayers et al. (27), the ELQ was developed as a unidimensional scale particularly assessing the existential loneliness. Results of this study support such an assumption, however, these are not similar to those obtained by Gökdemir-Bulut and Bozo (25). In examining psychometric properties of the Turkish ELQ, they found three factors, i.e., loneliness in social ties, loneliness in close relationships, and finding meaning in life. The first and second factors seem to be relevant to social and emotional loneliness, respectively. According to them, the ELQ not only measure existential loneliness but also other kinds of loneliness, like interpersonal aspects of loneliness and so it is an aggregate scale. After them, Van Tilburg (68) investigated the multidimensionality of loneliness instruments. In search for evidence of multiple dimensions of loneliness, he combined the first and second factors― derived from the work of Gökdemir-Bulut & Bozo― into one dimension, namely ʹexistential loneliness in relationshipsʹ, and finally concluded that the ELQ subscale on relationships does not contribute sufficiently to the loneliness conceptualization, and is weakly homogeneous, insufficiently reliable. According to him, this dimension has similar components found in the conceptualization of social loneliness and emotional loneliness, due to addressing different aspects of loneliness.

The most important reason why Gökdemir-Bulut and Bozo (25) found three dimensions for Turkish version of ELQ is that they made a big and common mistake in adopting the statistical method for assessing dimensionality. Unfortunately, they performed Factor Analysis using inappropriate method of Principal Component Analysis (PCA). In fact, PCA is not the correct procedure for the EFA model (69, 70). When data distribution does not follow multivariate normality and the variables are ordinal (e.g., Likert-type scale), the Ordinal Least Square methods (e.g., ULS, MRFA, or DWLS) based on the polychoric correlation matrix, are the most appropriate estimation methods for conducting Factor Analysis (both EFA and CFA), and also the PA is the best option for assessing dimensionality or estimating the number of factors (63, 69, 70).

At the beginning of this study, the EFA test was conducted on the data (of sample 1) with PCA method with Varimax rotation and Kaiser Normalization. The KMO index was .927 and Bartlett‘s test was significant (χ² (231) = 2909.505, p < 0.001), and scree plot, factor loadings and eigenvalues suggested a four-factor structure. But there were several reasons why the Persian ELQ should be treated as unidimensional. The most important reason was that the factors were not theoretically meaningful (71) and items loaded under those factors could not be appropriately related and integrated into a common conceptual components. In other terms, sum of the items and sum of the factors could not be theoretically meaningful and did not contribute to the conceptualization of existential loneliness. Another issue was the existence of cross-loadings in regard to the items that loaded under two factors (e.g., 2, 3, 6, 7, 10, 11, 14, and 22) (71). Most importantly, there are two criteria for unidimensionality suggested by Reckase in 1979 (72). When these criteria are met from the EFA results unidimensionality can be concluded: (1) a factor analysis on the inter-item correlation matrix should show that the first factor accounts for at least 20% of the variance of the unrotated factor matrix, and (2) scree plot test should clearly show a sudden drop of eigenvalues, i.e. eigenvalue of the first factor clearly exceed that of the second (73, 74). Results showed that before rotation, almost all items, load on the first factor accounted for 39% of the total variance. As shown in Fig. 3, the scree plot test also showed a sudden drop of eigenvalues from the first factor to the second, third, and fourth factors. The first factor have the eigenvalue (8.525) clearly exceeded that of the second factor (1.442), third factor (1.274), and fourth factor (1.079). The steep slope showed four factors associated with the loading greater than eigenvalue of 1, and gradual trailing off showed the rest factors lower than eigenvalue of 1. among four factors with loadings greater than 1, one extracted communality factor is distinctly higher than others. Accordingly, the questionnaire is unidimensional in nature (74).

The fact is that the ELQ items address some social and emotional aspects of loneliness, not that they assess social and emotional kinds of loneliness. If the ELQ items measure a kind of loneliness other than existential loneliness, so this would be an important limitation. As a fact, existential loneliness has conceptually some interpersonal aspects so-called loneliness in social ties and loneliness in close relationships. To put it differently, the ELQ is based on a conceptualization of existential loneliness in which interpersonal aspects play an specific role. In the main, ʺintimate and social relationships are inseparable parts of the composite existential loneliness concept as stated in the literatureʺ (25, p 10). It is noteworthy that the ELQ description of existential loneliness (27) concentrates on the quality of interpersonal connections and much of its items pertain essentially to the quality of relationships (75). In fact, the lack of intimacy and close attachments as features of emotional loneliness (68), and the lack of social support and companionship as features of social loneliness are those conceptual components that are constituting the composite concept of existential loneliness.

Found in the literature, sometimes existential loneliness is suggested as the source of both emotional and social loneliness (10), and sometimes is considered alongside these kinds of loneliness (68). In general, existential loneliness may be a cause or be a consequence of social and emotional facets of loneliness. For example, empirical research have revealed that experience of existential loneliness may emerge due to the loss of meaningful interpersonal relationships and feeling of not belonging to others (76), or due to the loss of friends and social network (3), lack of intimate relationships with people (27, 28, 68), feeling of being abandoned by others, and not being understood by others (28, 77).

It is near impossible to make a sharp distinction between existential and social isolation, since existential isolation is usually accompanied by interpersonal isolation and can be made manageable by interpersonal relationship. As stated by Yalom (5) social and existential isolation (or loneliness) are closely interrelated and also have many common boundaries. In his view, major defences are usually relational in nature and fear of existential isolation is driving force behind many interpersonal relationships. Common defences are close attachment, constant searching for love, enduring unsatisfactory relationships, etc. (5).

Therefore, the problem of the ELQ is that most of its items are related directly or indirectly to interpersonal aspects, such as social and emotional. According to Mayers et al. (27) some items (e.g. 3, 6, 8, 20 and 21) measure the extent to which one feels connected to others; such items are based on the idea that ʺrelationships can assuage a fundamental sense of isolation, and that ʹa terror of non-beingʹ may emerge in their absenceʺ (p. 1186). The item 9 (If I had the right relationship, I would never feel alone) refers to the crucial role of interpersonal relationships in confronting with loneliness. Also, items 10 (I stay in bad relationships too long in order not to be alone) and 11 (I immediately get involved in new relationships as soon as I break up) are directly related to interpersonal defences against the sense of existential loneliness. In addition, items 4 (I feel lonely), 7 (I feel I have people I can trust and rely on if I need them), 13 (I feel alone) and 22 (I feel hopeless about having a romantic relationship) are strongly associated with emotional aspects.

Here, one matter requiring attention is that these items are actually related to the basic conditions such as social and emotional isolation that can constitute existential loneliness. In other terms, it is often emotional and social isolation that underlies existential loneliness. Ultimately, if we consider existential loneliness to be a multifaceted phenomenon which has interpersonal and intrapersonal levels, the problem goes away.

As previously indicated, there was a strong and positive association between ELQ and DJGLS scores. This strong association reveals that the two scales have something in common, or each includes particular items pertaining to the same conceptual element (e.g. lack of intimacy, social support, and companionship). This explains similarities in the conceptualization of existential loneliness and other kinds of loneliness assessed by the DJGLS. Similarly, there was a strong negative association between the ELQ and MLQ, in a way that low scores in presence of meaning was strongly associated with high scores in existential loneliness. This indicates that both scales have several elements in common, or items addressing purpose, goals and meaning in life (e.g. items 1, 2, 17, 18, and 19 in the ELQ).

Additional theoretical developments and conceptual analyses regarding social, emotional, and existential loneliness will prove helpful, as these concepts are conflated and interrelated.

First, the fact that the data was collected via online survey using self-reporting questionnaires and that participants were recruited by social media platform, may have reduced the generalizability of the results. Second, the study on the structure, validity and reliability of the ELQ was conducted on two samples of university students, therefore, further studies needed to be performed on different populations with diverse demographic characteristics and larger sample sizes to settle with the issues of generalizability.

As a result, in this study the Persian ELQ was developed and its psychometric properties were examined. It was found that the ELQ is a unidimensional scale which has an adequate internal consistency and reliability. Also, analyses showed good convergent and discriminant validity. The ELQ scores was positively correlated with its relevant negative psychological constructs, i.e. general loneliness, depressive symptoms and existential anxiety, and was negatively correlated with positive and healthy psychological functioning, i.e. meaning in life and satisfaction with life. In conclusion, the Persian version of the ELQ is a psychometrically suitable instrument which can be applied by psychologists or mental healthcare professionals to study the incidence and intensity of existential loneliness among Iranian university students.

Authors' contributions

SH and MA have designed the study, collected and analyzed the data, and drafted the manuscript. Both authors read and approved the final manuscript.

Acknowledgements

Authors would like to thank all participants who contributed in this research.

Funding
None.

Data Availability

The raw data supporting the conclusions of this article will be made available on a reasonable request from the corresponding author (SH).

Ethics approval and consent to participate

This study was approved by the ethical committee of the Islamic Azad University-Central Tehran Branch (Code: IR.IAU.CTB.REC.162417304), and was performed in accordance with the Declaration of Helsinki.At first, participants were informed about the purpose and procedure of the study. They were also informed that the participation in this study is voluntary, and that they are free to leave the study whenever they want. They were assured of confidentiality and anonymity of their information. Informed consent was obtained from all participants electronically before answering any question.

Consent for publication

Not applicable.

Competing interests
the authors declare no conflict or competing of interest.

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No competing interests reported.

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Dimensional Structure and Psychometric Properties of the Persian Version of the Existential Loneliness Questionnaire (ELQ)

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Abstract

Figures

Background

Methods

Participants

Instruments

Existential Loneliness Questionnaire (ELQ)

Beck Depression Inventory (BDI-13)

Existential Anxiety Questionnaire (EAQ)

De Jong Gierveld Loneliness Scale (DJGLS)

Satisfaction with Life Scale (SWLS)

Meaning In Life Questionnaire (MLQ)

Procedure

Statistical Analyses

Results

Content validity

Descriptive Statistics

Explratory Factor Analysis

Confirmatory Factor Analysis

Reliability

Convergent and Discriminant Validity

Discussion

Limitations

Conclusion

Declarations

References

Additional Declarations

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