514284 research-article2013
HPQ0010.1177/1359105313514284Journal of Health PsychologyTerol et al.
Article
Adaptation and validation of the Spanish version of the Social Comparison Scale in chronic illness patients
Journal of Health Psychology 2015, Vol. 20(11) 1474–1482 © The Author(s) 2013 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/1359105313514284 hpq.sagepub.com
Carmen Terol, Ana Lledó, Yolanda Quiles and Maite Martín-Aragón
Abstract This study examined the Social Comparison Scale in Spanish chronic illness context and analyzed its psychometric properties. The article presented the results of two studies. The first explored the test’s dimensional structure in a sample of 202 patients in a range of several chronic illnesses. The second study examined the instrument’s structure in a sample of 186 patients with specific chronic illness. The results replicated the original structure of the scale and proved to be valid for use with optimum reliability.
Keywords chronic illness, coping, reliability, social cognition, validation
Introduction The Social Comparison (SC) Theory developed by Festinger (1954) still maintains its fundamental aspects, such as the tendency toward comparison, similarity, and the general comparison process (Buunk and Gibbons, 2006). However, advances have been made with the introduction of changes to its original concept. Originally, the SC concept referred to the comparison that individuals make about their opinions and skills in comparison to their peers (Festinger, 1954), and later, the concept was extended to include the search for information about others’ emotions (Schachter, 1959).Nowadays, it appears as a fundamental construct for understanding multiple aspects of an individual’s life (Buunk and Gibbons, 2007) and is considered a key process in the context of adaptation to illness, especially
chronic illness (Tennen et al., 2000; Buunk and Gibbons, 2006). Literature about the role of SC in chronic health problems is increasing (Brakel et al., 2012b; Buunk et al., 2006a, 2006b; Gibbons and Buunk, 1999; Suls, 2003; Tennen et al., 2000; Terol et al., 2009, 2012). However, for different reasons the limitations of these studies make it difficult to reach any definite conclusions. First, the high heterogeneity of the measures used to evaluate SC and the fact that there Miguel Hernández University, Spain Corresponding author: Carmen Terol, Department of Health Psychology, Miguel Hernández University, Avda de la Universidad, s/n. 03202, Elche, Spain. Email: [email protected]
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Terol et al. is no standard SC instrument makes it difficult to reproduce and contrast results. Second, it is also difficult to analyze the influence of SC and its relationships with other psychosocial variables and/or individuals’ state of health because of the diversity of the variables measured, which in many studies do not include the SC dimensions—orientation and interpretation. These limitations highlight the importance of creating an evaluation instrument for SC in the context of chronic illness which has good psychometric properties and contains all the dimensions and their combinations, leading to in-depth studies with reliable and valid results which can be applied to clinical practice. This need is met through the scale developed by Van der Zee et al. (2000) to evaluate the two comparison dimensions, orientation (rising or descending) and interpretation (identification or contrast), whose combinations determine its negative and positive emotional effects. This scale showed good psychometric properties in a Dutch sample and was presented as an instrument to be used specifically with people who were ill (Van der Zee et al., 2000). The aim of this study, therefore, was to adapt the SC Scale of Van der Zee et al. (1999) to a Spanish context and analyze its psychometric properties in patients with chronic illness. This article presents the results of two studies. In the first, there is a statistical analysis and an exploration of the test’s dimensional structure. The second study examines the instrument’s structure by confirmatory factor analysis. In order to produce this instrumental study, the guidelines proposed by Carretero-Dios and Pérez (2007) were followed according to Montero and León’s (2007) classification.
Method Participants The sample in the first study consisted of 202 participants—115 women and 87 men—with an average age of 66 years (standard deviation (SD) = 11.5 years, range = 29–89 years). The average age for women was 64.7 years (SD =
11.2 years) and for men 68.2 years (SD = 11.7 years). In all, 26.7 percent (n = 54) were housewives, 10.9 percent were active, 43.1 percent were retired, and 4 percent unemployed. In all, 15.4 percent (n = 31) were unemployed due to permanent or temporary employment disability, or were retired due to illness. Marital status was as follows: 64.9 percent married or living with a partner and 35.1 percent single or not living with a partner. In all, 67 of the patients were diagnosed with hypertension (33.2%), 35 were diabetics (17.3%), 30 had cardiovascular problems (14.9%), 17 arthrosis (8.4%), 10 osteoporosis (5%), and the rest had other health problems, such as arthritis, asthma, and cholesterol. A total of 186 women participated in the second study. The average was 51 (SD = 9.65, range = 22–77). Employment status of the sample was as follows: 36.6 percent housewives (n = 68), 24.2 percent active (n = 45), 32.8 percent were unemployed and had temporary or permanent employment disability due to their illness (n = 61), and the rest were retired, unemployed, or had temporary employment disability not due to their illness (n = 12). Marital status was as follows: 78.6 percent married or living with a partner and 21.6 percent were single or not living with a partner. Patients were diagnosed with breast cancer (50.5%) and fibromyalgia (49.5%).
Instruments Sociodemographic and clinical questionnaire. This questionnaire collected information about age, gender, employment situation, marital status, treatment, time, and type of diagnosis. Scale for Social Comparison processes in illness (Van der Zee et al., 1999) was adapted for this study through a forward–backward translation procedure and two pilot tests: the first one is about comprehension and validity; the second one is to confirm the adaptation and comprehension of the final scale. The final version of the scale includes 12 items as in the original version keeping to the same format with a Likert response of 1–5 which indicates
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comparison frequencies (1 = never, 2 = rarely, 3 = now and again, 4 = often, and 5 = very often). The General Social Comparison Orientation Scale. The General Social Comparison Orientation Scale (Buunk et al., 2005; Gibbons and Buunk, 1999) consisted of 11 items, 7 expressed positively and 2 negatively, with 5-point Likert responses. Reliability coefficients were higher than .80, test–retest stability was .57, and criteria validity was r = .43 with neuroticism and r = −.20 with self-esteem (Buunk et al., 2005). Chronic patients from our study sample showed .72 reliability. Neuroticism subscale from the Eysenck Personality Questionnaire–Revised. Neuroticism subscale from the Eysenck Personality Questionnaire– Revised (EPQ-R; Eysenck and Eysenck, 2001), Spanish adaptation, consisted of 23 items with a yes/no dichotomous response, an internal consistency of .86, and a reliability of .80 for the sample study. Rosenberg Self-Esteem Scale. The Rosenberg Self-Esteem Scale (Rosenberg, 1965) consisted of 10 items with a 4-point Likert response, adapted and validated in a Spanish clinical population, with reliability coefficients of .87 and test–retest correlations of .72 (Vázquez et al., 2004) and with a reliability between .62 and .78. General State of Health and Quality of Life. The General State of Health and Quality of Life evaluated with a measurement scale from the Impact of Illness in patients with rheumatic diseases (Meenan et al., 1980) consisted of two scales, a 10-point scale (0 = Very bad, 10 = Excellent) and a 10-cm visual analogue scale indicating “very bad” and “very well” at each end, which patients mark with an “X” to indicate how they feel.
Procedure Over a period of 1 year, health professionals from different Health Centres and Hospitals in
the province of Alicante (Spain) selected patients from the outpatients. The patients were informed about the study and the possibility of voluntary participation in the study. Once the patient agreed, a trained professional explained the aim of the study and asked for the patient’s consent by signing a “commitment to participate.” The instruments were randomly ordered to control a possible fatigue effect and bias in the answers by the patients. The sample was calculated following the minimum criteria required for making different programmed statistical analyses.
Data analysis For the exploratory analysis, we used Cronbach’s alpha reliability index to analyze the scales and we tested the characteristics of the items and the scale’s consistency variance using Pearson’s item-total correlation. In order to identify the original questionnaire’s dimensions, we made an exploratory factorial analysis of the principal components using the varimax rotation method, and analyses were made of the correlation matrix and Bartlett’s sphericity indices (Bartlett’s test = 878.66; p ≤ .001) and the Kaiser–Meyer–Olkin test (≥.76). All statistical analyses were made using the SPSS 11.5 statistical program. In order to confirm the questionnaire’s internal structure, factor analysis with structural equation models was used. The estimation of the models was carried out using the AMOS program, version 15.0. The test model was derived from the findings in the preceding study so it had a four-factor structure: Upward Identification Social Comparison (UISC), Upward Contrast Social Comparison (UCSC), Downward Identification Social Comparison (DISC), and Downward Contrast Social Comparison (DCSC), each with 3 items. The measurement model’s fit was assessed by the χ2 statistic of goodness of fit. The χ2/gl ratio was calculated. If this ratio is inferior to 6, it is assumed that the model fit is adequate. Carmines and McIver (1981) and Kline (1998) establish a value of 3 for an acceptable model.
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Terol et al. Furthermore, and following the recommendation to contrast various indices to ensure the fit of the proposed model, the following goodnessof-fit indices (GFIs) were kept in mind: (a) the GFI, (b) the comparative fit index (CFI), both of which require values equal to or higher than .90, and (c) the root mean square error of approximation (RMSEA). Values equal to or less than .05 indicate that the model based on the sample used represents the population, and when values are lower than .08, the fit is considered acceptable (Browne and Cudeck, 1992; Jöreskog and Sörbom, 1993). Factor loadings were used for individual fit or the fit of the model components. The previous section of this study aimed to provide evidence about the relations between the measures provided through the questionnaire and other external variables which are theoretically related to the SC dimensions. To make these analyses, we used the Pearson’s correlation coefficient.
Results Study 1: preliminary psychometric study of the SC scale Study of the instrument’s dimensionality. The factorial analysis showed that the four dimensions from the original scale by Van der Zee et al. (1999) explain 71.34 percent of the total variance. The first two, Upward Identification and Upward Contrast, include 6 items of comparison with other people who are in better circumstances. The first three (1, 2, and 3) refer to identification with that person and the last three (4, 5, and 6) to nonidentification or to contrast with the other person. The third and fourth dimensions, DISC and DCSC, include 6 items of comparison with another person with health problems who is in worse circumstances. Items 7, 8, and 9 refer to when the patient identifies with the subject of comparison and the other three to nonidentification. The highest explained variance is found in the Upward Contrast dimension (30.86%). All the items on the scale present factorial loadings
which fluctuate between .90 for item 2 and .57 for item 3 (see Table 1). Reliability and statistical analysis of the items. The reliability coefficient of the total scale has an optimum internal consistency (α = .76). Consistency is increased to .78 by eliminating item 3 (see Table 2). The reliability index for the subscales was higher than .76 in three of them and the lowest subscale was Upward Identification (α = .62).
Study 2: confirmatory factor analysis and external evidence of validity Confirmatory factor analysis. The results indicate that the global fit shown by the model is appropriate. The chi-square test was significant (χ2(48) = 78.92, p = .003) and the χ2/gl ratio was 1.68. The GFI and CFI adopted values of .93 and .98, respectively, while the RMSEA estimation was .059. The graphic representation of this model is shown in Figure 1. Correlation of factors and factor loadings of the items. Just as Figure 1 shows, only high correlations are observed between the UISC-DCSC factors and between UCSC-DISC factors. The correlations between the other factors are low. All the factor loadings are high, fluctuating between .80 and .97. Evidence of external validity. The Upward Contrast and Downward Contrast subscales show significant relations with the rest of the variables evaluated. They show negative correlations with perception of state of health, perception of quality of life, and positive self-esteem, and positive correlations with neuroticism, orientation toward SC, and negative self-esteem (see Table 3).
Discussion The adaptation of the items and the analysis of the psychometric properties for estimating their reliability, the dimensionality of the instrument,
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Table 1. Factor analysis: dimensions of Social Comparison. Social Comparison
When I think or see others who are better than me …
Factor loading
Upward Identification (UISC)
1. I guess I can also improve 2. I am glad that I can also improve 3. I have hope that I will also be able to improve 4. I feel scared to notice that I am not so well 5. I feel disgusted by my own situation 6. I realize I am not so well and it makes me sad
.86 .90 .57
8.89
.79
30.86
Social Comparison
When I think or see others who are worse than me …
Factor loading
% VE
Downward Identification (DISC)
7. I have fear that I will get worse 8. I think I will be so in the future 9. I have fear that I may be so 10. I am glad I am not so bad 11. I feel relieved to not be so bad 12. I realize that I am pretty good
.77 .85 .85 .83 .80 .79
17.66
Upward Contrast (UCSC)
Downward Contrast (DCSC)
% VE
.82 .84
13.92
VE: variance explained; UISC: Upward Identification Social Comparison; UCSC: Upward Contrast Social Comparison; DISC: Downward Identification Social Comparison; DCSC: Downward Contrast Social Comparison. Total VE = 71.33%.
and obtaining external validity evidence have all been covered in this study. The results from the different analyses with respect to construct validity support the factorial structure of the original version of SC with four factors: UISC, UCSC, DCSC, and DISC (Van der Zee et al., 1999). This was tested in both the exploratory analysis and the confirmatory analysis, which show values within the ranges established as adequate. The reliability of the four subscales which make up this instrument, calculated with Cronbach’s alpha coefficient and in the confirmatory study, showed adequate internal consistency at the initial stage. In the confirmatory study, all factors loaded high, and according to the SC theory, high correlations were obtained between UISC-DCSC and UCSCDISC and in the expected theoretical sense (Buunk et al., 2005; Buunk and Gibbons, 2006). With respect to criteria validity, in literature, the use of the UCSC and DISC is seen to be less adaptive as they produce negative consequences
(Buunk and Gibbons, 2006). Our results provide criteria validity because the high use of this type of comparison was related to a poor state of health, a higher degree of “neuroticism” and “negative self-esteem.” These results coincide with those obtained in other studies (Buunk et al., 2006a, 2006b; Petersen et al., 2012). Similarly, a higher “orientation towards social comparison” was also related to a higher use of this type of “unfavourable” comparison. From the perspective that these factors (orientation, self-esteem, and neuroticism) are understood as personal predispositions which influence the frequency and use of SC (Van der Zee et al., 1999), the results obtained indicate that these characteristics, which tend toward pessimism, could act as a risk factor for the use of nonadaptive SCs. Although there is little consistency in literature about self-esteem in relation to SC, a greater use of unfavourable comparisons in relation to neuroticism and orientation is evident (Buunk et al., 2009; Terol et al., 2012). Therefore, with respect to unfavourable
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Terol et al. Table 2. Reliability analysis. Cronbach’s alpha When I think or see others who are better than me … 1. I guess I can also improve UISC = .62 2. I am glad that I can also improve 3. I have hope that I will also be able to improve 4. I feel scared to notice that I am UCSC = .83 not so well 5. I feel disgusted by my own situation 6. I realize I am not so well and it makes me sad When I think or see others who are worse than me … 7. I have fear that I will get worse DISC = .84 8. I think I will be so in the future 9. I have fear that I may be so 10. I am glad I am not so bad DCSC = .76 11. I feel relieved to not be so bad 12. I realize that I am pretty good
“r” item-total
Alpha without item
.30 .35 .30
.75 .75 .78
.54
.73
.52
.73
.56
.73
.51 .44 .44 .33 .42 .22
.73 .74 .74 .75 .74 .76
UISC: Upward Identification Social Comparison; UCSC: Upward Contrast Social Comparison; DISC: Downward Identification Social Comparison; DCSC: Downward Contrast Social Comparison.
comparisons, our results coincide with those obtained in other studies, and consequently validate the scale criteria (Petersen et al., 2012). The application of these results to clinical practice implies that in group intervention programs with chronic patients, not only would it be necessary to include comparison management as a strategy for coping with adaptation objectives but also to control the influence of other personal variables that can prejudice the use of SC in a disadaptive sense. On the other hand, it is important to point out that we did not obtain the positive effect of the use of UISC and DCSC in the perception of health and quality of life, as shown in other studies (Buunk et al., 2006b; Buunk and Gibbons, 2006). The lack of significant relations between these two dimensions of SC and health results is important if we consider the fact that theoretically they would be more adaptive comparisons for these patients (Buunk et al., 2006; Terol et al., 2012). That is to say, the comparisons that are related to thinking that “I will get better when I see others who are
better” (UISC) and “feeling relieved when I realize I am not so ill” (DCSC) are not related with a perceived better state of health. One possible explanation could be due to the characteristics of the samples studied—patients with long-term chronic illness—in which case it becomes difficult to maintain the positive effect of the use of the UISC and DCSC since deterioration and the daily impact of the illness predominate. The situation of chronic illness generates multiple threats, so the use of “favourable” SC may act rather to maintain results and minimize the adverse effects of the illness. Consequently, another aspect to be researched would be the importance of measuring the content or motivation behind SC in the context of what is compared (physical function, emotional impact, coping, and other aspects) since in other studies the effect of SC on the state of health has depended on the type of information and on the different dimensions of the quality of life they were compared with (Brakel et al., 2012; Buunk et al., 2006; Taylor and Lobel, 1989). It is also important to point
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Figure 1. Confirmatory analysis.
UISC: Upward Identification Social Comparison; UCSC: Upward Contrast Social Comparison; DISC: Downward Identification Social Comparison; DCSC: Downward Contrast Social Comparison.
Table 3. Correlations between the factors and criteria variables. M ± dt Psychosocial Comparison orientation Neuroticism Positive self-esteem Negative self-esteem General self-esteem Health status Perceived health status Perceived quality of life
Upward Social Comparison
Downward Social Comparison
Identification
Contrast
Identification
Contrast
53.7 ± 16.49 52.32 ± 22.08 72.76 ± 15.15 38.01 ± 20.01 72.1 ± 9.35
.06 −.04 .10 −.07 .10
.15* .42** −.19** .39** .16*
.24** .32** −.18** .32** .10
.14 .10 .09 .07 .02
5.9 ± 2.4 6.8 ± 2.37
−.12 −.06
−.38** −.45**
−.30** −.21**
.01 .06
*p < .05; **p < .01.
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Terol et al. out that perhaps a previous emotional state and perceived control of the situation can influence and mediate in relation to favourable comparisons and perceived state of health, as shown in some studies (Stewart et al., 2013). On the other hand, the use of the (“favourable”) UISC and the DCSC was not related to any of these personal factors, so it is possible that its use is facilitated or not according to context factors (characteristics of the illness, health centres, hospitals or associations, etc.), which would have to be specified in future research. Finally, we should point out that although in our group of patients no significant relations were found in how certain forms of SC benefit health, this group could find indirect positive effects which specifically derive from avoiding the negative effects produced by comparing themselves with those who are worse and which remind them of their possible evolution (Downward Identification), or by comparing themselves with those who are better but are not useful as an example to be followed (Upward Contrast), which is what the results for perception of health and quality of life show. In this sense, it would be an adequate model of focused adaptation, especially in “avoiding” certain forms of comparison. Future long-term studies, besides including variables like perception of control and the content of comparison, would more specifically evaluate the use of “favourable” comparisons (Upward Identification and Downward Contrast) which would enable us to clarify their long-term function in the adaptation and health processes of different chronic patients. In conclusion, first, the results of this study allow us to obtain an adapted version of an evaluation instrument for SC in the context of chronic illness for the Spanish population, which replicates the original structure of the scale and proves to be valid for use with optimum reliability. Second, this study highlights how important it is for future research on SC with chronic patients to deal with the characteristics of the illness, personal characteristics, social context, and the participant’s relations so as to determine the development of the
comparison processes in the adaptation of these patients. Funding This research received no specific grant from any funding agency in the public, commercial, or not-forprofit sectors.
References Brakel TM, Dijkstra A and Buunk BP (2012a) Effects of the source of social comparison information on former cancer patients’ quality of life. British Journal of Health Psychology 17: 667–681. Brakel TM, Dijkstra A, Buunk BP, et al. (2012b) Impact of social comparison on cancer survivors’ quality of life: An experimental field study. Health Psychology 31(5): 660–670. Browne MW and Cudeck R (1992) Alternative ways of assessing model fit. Sociological Methods & Research 21: 230–258. Buunk BP and Gibbons FX (2006) Social comparison orientation: A new perspective on those who do and those who don’t compare with others. In: Guimond S (ed.) Social Comparison and Social Psychology: Understanding Cognition, Intergroup Relations and Culture. Cambridge: Cambridge University Press, pp. 15–33. Buunk BP, Belmonte J, Peiró J, et al. (2005) Diferencias individuales en la comparación social: Propiedades de la escala española de orientación hacia la comparación social. Revista Latinoamericana de Psicología 37: 561–579 Buunk BP, Brakel TM, Bennenbroek FC, et al. (2009) Neuroticism and responses to social comparison among cancer patients. European Journal of Personality 23(6): 475–487. Buunk BP, Terol MC and Lledó A (2006a) El papel de la comparación social en la adaptación a la enfermedad crónica: un estudio en cáncer. Revista de Psicología de la Salud 18(2): 27– 48. Buunk BP, Zurriaga R, Gonzalez P, et al. (2006b) Targets and dimensions of social comparison among people with spinal cord injury and other health problems. British Journal of Health Psychology 11: 677–693. Carmines EG and McIver JP (1981) Analyzing models with unobserved variables: Analysis of covariance structures. In: Bohrnstedt GW and
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Borgatta EF (eds) Social Measurement: Current Issues. Beverly Hills, CA: SAGE, pp. 65–115. Carretero-Dios H and y Pérez C (2007) Standards for the development and review of instrumental studies: Considerations about test selection in psychological research. International Journal of Clinical and Health Psychology 7: 863–882. Eysenck HJ and Eysenck SBG (2001) EPQ-R Cuestionario de personalidad de Eysenck revisado (10º Edicion). Madrid: TEA Ediciones. Festinger L (1954) A theory of social comparison processes. Human Relations 7(2): 117–140. Gibbons FX and Buunk BP (1999) Individual differences in social comparison: Development of a scale of social comparison orientation. Journal of Personality and Social Psychology 76: 129–142. Jöreskog K and Sörbom D (1993) LISREL 8: Structural Equation Modeling with the SIMPLIS Command Language. Hillsdale, NJ: Lawrence Erlbaum. Kline RB (1998) Principles and Practice of Structural Equation Modeling. New York: The Guilford Press. Meenan RF, Gertman PM and Mason JH (1980) Measuring health status in arthritis: The arthritis impact measurement scales. Arthritis and Rheumatism 23: 146–152. Montero I and León OG (2007) A guide for naming research studies in Psychology. International Journal of Clinical and Health Psychology 7: 847–862. Petersen S, Taube K, Lehmann K, et al. (2012) Social comparison and anxious mood in pulmonary rehabilitation: The role of cognitive focus. British Journal of Health Psychology 17: 463–476. Rosenberg M (1965) Society and the Adolescent Self-Image. Princeton, NJ: Princeton University Press. Stewart TL, Chipperfield JG, Ruthig JC, et al. (2013) Downward social comparison and subjective
well-being in late life: The moderating role of perceived control. Aging & Mental Health 17(3): 375–378. Suls J (2003) Contributions of social comparison to physical illness and wellbeing. In: Suls J and Wallston KA (eds) Social Psychological Foundations of Health and Illness. Ames, IA: Blackwell Publishing, pp. 226–255. Taylor SE and Lobel M (1989) Social comparison activity under threat: Downward evaluation and upward contacts. Psychology Review 96: 569–575. Tennen H, McKee TE and Affleck G (2000) Social comparison processes in health and illness. In: Suls J and Wheeler L (eds) Handbook of Social Comparison: Theory and Research. New York: Kluwer/Plenum Publishers, pp. 443–483. Terol MC, Neipp MC, Lledó A, et al. (2012) Comparación Social y variables psicosociales relacionadas: una revisión de cáncer y dolor crónico. Anales de Psicología 28(2): 327– 337. Terol MC, Rodríguez J and García del Castillo JA (2009) Utilización de la Comparación Social en la enferemedad oncológica. In: PSICOONCOLOGÍA: Intervenciones Psicológicas en Cáncer (pp: 110–119). Bogotá: PSICOM Editores. Van der Zee K, Buunk BP, Sanderman R, et al. (1999) The big five and identification-contrast processes in social comparison in adjustment to cancer treatment. European Journal of Personality 13: 307–326. Van der Zee K, Buunk BP, Sanderman R, et al. (2000) Social comparison and coping with cancer treatment. Personality and Individual Differences 28: 17–34. Vázquez AJ, Jiménez R and Vázquez-Morejon R (2004) Escala de autoestima de Rosenberg: fiabilidad y validez en población clínica española. Apuntes de Psicología 22(2): 247–255.
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HPQ0010.1177/1359105313514284Journal of Health PsychologyTerol et al.
Article
Adaptation and validation of the Spanish version of the Social Comparison Scale in chronic illness patients
Journal of Health Psychology 2015, Vol. 20(11) 1474–1482 © The Author(s) 2013 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/1359105313514284 hpq.sagepub.com
Carmen Terol, Ana Lledó, Yolanda Quiles and Maite Martín-Aragón
Abstract This study examined the Social Comparison Scale in Spanish chronic illness context and analyzed its psychometric properties. The article presented the results of two studies. The first explored the test’s dimensional structure in a sample of 202 patients in a range of several chronic illnesses. The second study examined the instrument’s structure in a sample of 186 patients with specific chronic illness. The results replicated the original structure of the scale and proved to be valid for use with optimum reliability.
Keywords chronic illness, coping, reliability, social cognition, validation
Introduction The Social Comparison (SC) Theory developed by Festinger (1954) still maintains its fundamental aspects, such as the tendency toward comparison, similarity, and the general comparison process (Buunk and Gibbons, 2006). However, advances have been made with the introduction of changes to its original concept. Originally, the SC concept referred to the comparison that individuals make about their opinions and skills in comparison to their peers (Festinger, 1954), and later, the concept was extended to include the search for information about others’ emotions (Schachter, 1959).Nowadays, it appears as a fundamental construct for understanding multiple aspects of an individual’s life (Buunk and Gibbons, 2007) and is considered a key process in the context of adaptation to illness, especially
chronic illness (Tennen et al., 2000; Buunk and Gibbons, 2006). Literature about the role of SC in chronic health problems is increasing (Brakel et al., 2012b; Buunk et al., 2006a, 2006b; Gibbons and Buunk, 1999; Suls, 2003; Tennen et al., 2000; Terol et al., 2009, 2012). However, for different reasons the limitations of these studies make it difficult to reach any definite conclusions. First, the high heterogeneity of the measures used to evaluate SC and the fact that there Miguel Hernández University, Spain Corresponding author: Carmen Terol, Department of Health Psychology, Miguel Hernández University, Avda de la Universidad, s/n. 03202, Elche, Spain. Email: [email protected]
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Terol et al. is no standard SC instrument makes it difficult to reproduce and contrast results. Second, it is also difficult to analyze the influence of SC and its relationships with other psychosocial variables and/or individuals’ state of health because of the diversity of the variables measured, which in many studies do not include the SC dimensions—orientation and interpretation. These limitations highlight the importance of creating an evaluation instrument for SC in the context of chronic illness which has good psychometric properties and contains all the dimensions and their combinations, leading to in-depth studies with reliable and valid results which can be applied to clinical practice. This need is met through the scale developed by Van der Zee et al. (2000) to evaluate the two comparison dimensions, orientation (rising or descending) and interpretation (identification or contrast), whose combinations determine its negative and positive emotional effects. This scale showed good psychometric properties in a Dutch sample and was presented as an instrument to be used specifically with people who were ill (Van der Zee et al., 2000). The aim of this study, therefore, was to adapt the SC Scale of Van der Zee et al. (1999) to a Spanish context and analyze its psychometric properties in patients with chronic illness. This article presents the results of two studies. In the first, there is a statistical analysis and an exploration of the test’s dimensional structure. The second study examines the instrument’s structure by confirmatory factor analysis. In order to produce this instrumental study, the guidelines proposed by Carretero-Dios and Pérez (2007) were followed according to Montero and León’s (2007) classification.
Method Participants The sample in the first study consisted of 202 participants—115 women and 87 men—with an average age of 66 years (standard deviation (SD) = 11.5 years, range = 29–89 years). The average age for women was 64.7 years (SD =
11.2 years) and for men 68.2 years (SD = 11.7 years). In all, 26.7 percent (n = 54) were housewives, 10.9 percent were active, 43.1 percent were retired, and 4 percent unemployed. In all, 15.4 percent (n = 31) were unemployed due to permanent or temporary employment disability, or were retired due to illness. Marital status was as follows: 64.9 percent married or living with a partner and 35.1 percent single or not living with a partner. In all, 67 of the patients were diagnosed with hypertension (33.2%), 35 were diabetics (17.3%), 30 had cardiovascular problems (14.9%), 17 arthrosis (8.4%), 10 osteoporosis (5%), and the rest had other health problems, such as arthritis, asthma, and cholesterol. A total of 186 women participated in the second study. The average was 51 (SD = 9.65, range = 22–77). Employment status of the sample was as follows: 36.6 percent housewives (n = 68), 24.2 percent active (n = 45), 32.8 percent were unemployed and had temporary or permanent employment disability due to their illness (n = 61), and the rest were retired, unemployed, or had temporary employment disability not due to their illness (n = 12). Marital status was as follows: 78.6 percent married or living with a partner and 21.6 percent were single or not living with a partner. Patients were diagnosed with breast cancer (50.5%) and fibromyalgia (49.5%).
Instruments Sociodemographic and clinical questionnaire. This questionnaire collected information about age, gender, employment situation, marital status, treatment, time, and type of diagnosis. Scale for Social Comparison processes in illness (Van der Zee et al., 1999) was adapted for this study through a forward–backward translation procedure and two pilot tests: the first one is about comprehension and validity; the second one is to confirm the adaptation and comprehension of the final scale. The final version of the scale includes 12 items as in the original version keeping to the same format with a Likert response of 1–5 which indicates
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comparison frequencies (1 = never, 2 = rarely, 3 = now and again, 4 = often, and 5 = very often). The General Social Comparison Orientation Scale. The General Social Comparison Orientation Scale (Buunk et al., 2005; Gibbons and Buunk, 1999) consisted of 11 items, 7 expressed positively and 2 negatively, with 5-point Likert responses. Reliability coefficients were higher than .80, test–retest stability was .57, and criteria validity was r = .43 with neuroticism and r = −.20 with self-esteem (Buunk et al., 2005). Chronic patients from our study sample showed .72 reliability. Neuroticism subscale from the Eysenck Personality Questionnaire–Revised. Neuroticism subscale from the Eysenck Personality Questionnaire– Revised (EPQ-R; Eysenck and Eysenck, 2001), Spanish adaptation, consisted of 23 items with a yes/no dichotomous response, an internal consistency of .86, and a reliability of .80 for the sample study. Rosenberg Self-Esteem Scale. The Rosenberg Self-Esteem Scale (Rosenberg, 1965) consisted of 10 items with a 4-point Likert response, adapted and validated in a Spanish clinical population, with reliability coefficients of .87 and test–retest correlations of .72 (Vázquez et al., 2004) and with a reliability between .62 and .78. General State of Health and Quality of Life. The General State of Health and Quality of Life evaluated with a measurement scale from the Impact of Illness in patients with rheumatic diseases (Meenan et al., 1980) consisted of two scales, a 10-point scale (0 = Very bad, 10 = Excellent) and a 10-cm visual analogue scale indicating “very bad” and “very well” at each end, which patients mark with an “X” to indicate how they feel.
Procedure Over a period of 1 year, health professionals from different Health Centres and Hospitals in
the province of Alicante (Spain) selected patients from the outpatients. The patients were informed about the study and the possibility of voluntary participation in the study. Once the patient agreed, a trained professional explained the aim of the study and asked for the patient’s consent by signing a “commitment to participate.” The instruments were randomly ordered to control a possible fatigue effect and bias in the answers by the patients. The sample was calculated following the minimum criteria required for making different programmed statistical analyses.
Data analysis For the exploratory analysis, we used Cronbach’s alpha reliability index to analyze the scales and we tested the characteristics of the items and the scale’s consistency variance using Pearson’s item-total correlation. In order to identify the original questionnaire’s dimensions, we made an exploratory factorial analysis of the principal components using the varimax rotation method, and analyses were made of the correlation matrix and Bartlett’s sphericity indices (Bartlett’s test = 878.66; p ≤ .001) and the Kaiser–Meyer–Olkin test (≥.76). All statistical analyses were made using the SPSS 11.5 statistical program. In order to confirm the questionnaire’s internal structure, factor analysis with structural equation models was used. The estimation of the models was carried out using the AMOS program, version 15.0. The test model was derived from the findings in the preceding study so it had a four-factor structure: Upward Identification Social Comparison (UISC), Upward Contrast Social Comparison (UCSC), Downward Identification Social Comparison (DISC), and Downward Contrast Social Comparison (DCSC), each with 3 items. The measurement model’s fit was assessed by the χ2 statistic of goodness of fit. The χ2/gl ratio was calculated. If this ratio is inferior to 6, it is assumed that the model fit is adequate. Carmines and McIver (1981) and Kline (1998) establish a value of 3 for an acceptable model.
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Terol et al. Furthermore, and following the recommendation to contrast various indices to ensure the fit of the proposed model, the following goodnessof-fit indices (GFIs) were kept in mind: (a) the GFI, (b) the comparative fit index (CFI), both of which require values equal to or higher than .90, and (c) the root mean square error of approximation (RMSEA). Values equal to or less than .05 indicate that the model based on the sample used represents the population, and when values are lower than .08, the fit is considered acceptable (Browne and Cudeck, 1992; Jöreskog and Sörbom, 1993). Factor loadings were used for individual fit or the fit of the model components. The previous section of this study aimed to provide evidence about the relations between the measures provided through the questionnaire and other external variables which are theoretically related to the SC dimensions. To make these analyses, we used the Pearson’s correlation coefficient.
Results Study 1: preliminary psychometric study of the SC scale Study of the instrument’s dimensionality. The factorial analysis showed that the four dimensions from the original scale by Van der Zee et al. (1999) explain 71.34 percent of the total variance. The first two, Upward Identification and Upward Contrast, include 6 items of comparison with other people who are in better circumstances. The first three (1, 2, and 3) refer to identification with that person and the last three (4, 5, and 6) to nonidentification or to contrast with the other person. The third and fourth dimensions, DISC and DCSC, include 6 items of comparison with another person with health problems who is in worse circumstances. Items 7, 8, and 9 refer to when the patient identifies with the subject of comparison and the other three to nonidentification. The highest explained variance is found in the Upward Contrast dimension (30.86%). All the items on the scale present factorial loadings
which fluctuate between .90 for item 2 and .57 for item 3 (see Table 1). Reliability and statistical analysis of the items. The reliability coefficient of the total scale has an optimum internal consistency (α = .76). Consistency is increased to .78 by eliminating item 3 (see Table 2). The reliability index for the subscales was higher than .76 in three of them and the lowest subscale was Upward Identification (α = .62).
Study 2: confirmatory factor analysis and external evidence of validity Confirmatory factor analysis. The results indicate that the global fit shown by the model is appropriate. The chi-square test was significant (χ2(48) = 78.92, p = .003) and the χ2/gl ratio was 1.68. The GFI and CFI adopted values of .93 and .98, respectively, while the RMSEA estimation was .059. The graphic representation of this model is shown in Figure 1. Correlation of factors and factor loadings of the items. Just as Figure 1 shows, only high correlations are observed between the UISC-DCSC factors and between UCSC-DISC factors. The correlations between the other factors are low. All the factor loadings are high, fluctuating between .80 and .97. Evidence of external validity. The Upward Contrast and Downward Contrast subscales show significant relations with the rest of the variables evaluated. They show negative correlations with perception of state of health, perception of quality of life, and positive self-esteem, and positive correlations with neuroticism, orientation toward SC, and negative self-esteem (see Table 3).
Discussion The adaptation of the items and the analysis of the psychometric properties for estimating their reliability, the dimensionality of the instrument,
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Table 1. Factor analysis: dimensions of Social Comparison. Social Comparison
When I think or see others who are better than me …
Factor loading
Upward Identification (UISC)
1. I guess I can also improve 2. I am glad that I can also improve 3. I have hope that I will also be able to improve 4. I feel scared to notice that I am not so well 5. I feel disgusted by my own situation 6. I realize I am not so well and it makes me sad
.86 .90 .57
8.89
.79
30.86
Social Comparison
When I think or see others who are worse than me …
Factor loading
% VE
Downward Identification (DISC)
7. I have fear that I will get worse 8. I think I will be so in the future 9. I have fear that I may be so 10. I am glad I am not so bad 11. I feel relieved to not be so bad 12. I realize that I am pretty good
.77 .85 .85 .83 .80 .79
17.66
Upward Contrast (UCSC)
Downward Contrast (DCSC)
% VE
.82 .84
13.92
VE: variance explained; UISC: Upward Identification Social Comparison; UCSC: Upward Contrast Social Comparison; DISC: Downward Identification Social Comparison; DCSC: Downward Contrast Social Comparison. Total VE = 71.33%.
and obtaining external validity evidence have all been covered in this study. The results from the different analyses with respect to construct validity support the factorial structure of the original version of SC with four factors: UISC, UCSC, DCSC, and DISC (Van der Zee et al., 1999). This was tested in both the exploratory analysis and the confirmatory analysis, which show values within the ranges established as adequate. The reliability of the four subscales which make up this instrument, calculated with Cronbach’s alpha coefficient and in the confirmatory study, showed adequate internal consistency at the initial stage. In the confirmatory study, all factors loaded high, and according to the SC theory, high correlations were obtained between UISC-DCSC and UCSCDISC and in the expected theoretical sense (Buunk et al., 2005; Buunk and Gibbons, 2006). With respect to criteria validity, in literature, the use of the UCSC and DISC is seen to be less adaptive as they produce negative consequences
(Buunk and Gibbons, 2006). Our results provide criteria validity because the high use of this type of comparison was related to a poor state of health, a higher degree of “neuroticism” and “negative self-esteem.” These results coincide with those obtained in other studies (Buunk et al., 2006a, 2006b; Petersen et al., 2012). Similarly, a higher “orientation towards social comparison” was also related to a higher use of this type of “unfavourable” comparison. From the perspective that these factors (orientation, self-esteem, and neuroticism) are understood as personal predispositions which influence the frequency and use of SC (Van der Zee et al., 1999), the results obtained indicate that these characteristics, which tend toward pessimism, could act as a risk factor for the use of nonadaptive SCs. Although there is little consistency in literature about self-esteem in relation to SC, a greater use of unfavourable comparisons in relation to neuroticism and orientation is evident (Buunk et al., 2009; Terol et al., 2012). Therefore, with respect to unfavourable
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Terol et al. Table 2. Reliability analysis. Cronbach’s alpha When I think or see others who are better than me … 1. I guess I can also improve UISC = .62 2. I am glad that I can also improve 3. I have hope that I will also be able to improve 4. I feel scared to notice that I am UCSC = .83 not so well 5. I feel disgusted by my own situation 6. I realize I am not so well and it makes me sad When I think or see others who are worse than me … 7. I have fear that I will get worse DISC = .84 8. I think I will be so in the future 9. I have fear that I may be so 10. I am glad I am not so bad DCSC = .76 11. I feel relieved to not be so bad 12. I realize that I am pretty good
“r” item-total
Alpha without item
.30 .35 .30
.75 .75 .78
.54
.73
.52
.73
.56
.73
.51 .44 .44 .33 .42 .22
.73 .74 .74 .75 .74 .76
UISC: Upward Identification Social Comparison; UCSC: Upward Contrast Social Comparison; DISC: Downward Identification Social Comparison; DCSC: Downward Contrast Social Comparison.
comparisons, our results coincide with those obtained in other studies, and consequently validate the scale criteria (Petersen et al., 2012). The application of these results to clinical practice implies that in group intervention programs with chronic patients, not only would it be necessary to include comparison management as a strategy for coping with adaptation objectives but also to control the influence of other personal variables that can prejudice the use of SC in a disadaptive sense. On the other hand, it is important to point out that we did not obtain the positive effect of the use of UISC and DCSC in the perception of health and quality of life, as shown in other studies (Buunk et al., 2006b; Buunk and Gibbons, 2006). The lack of significant relations between these two dimensions of SC and health results is important if we consider the fact that theoretically they would be more adaptive comparisons for these patients (Buunk et al., 2006; Terol et al., 2012). That is to say, the comparisons that are related to thinking that “I will get better when I see others who are
better” (UISC) and “feeling relieved when I realize I am not so ill” (DCSC) are not related with a perceived better state of health. One possible explanation could be due to the characteristics of the samples studied—patients with long-term chronic illness—in which case it becomes difficult to maintain the positive effect of the use of the UISC and DCSC since deterioration and the daily impact of the illness predominate. The situation of chronic illness generates multiple threats, so the use of “favourable” SC may act rather to maintain results and minimize the adverse effects of the illness. Consequently, another aspect to be researched would be the importance of measuring the content or motivation behind SC in the context of what is compared (physical function, emotional impact, coping, and other aspects) since in other studies the effect of SC on the state of health has depended on the type of information and on the different dimensions of the quality of life they were compared with (Brakel et al., 2012; Buunk et al., 2006; Taylor and Lobel, 1989). It is also important to point
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Figure 1. Confirmatory analysis.
UISC: Upward Identification Social Comparison; UCSC: Upward Contrast Social Comparison; DISC: Downward Identification Social Comparison; DCSC: Downward Contrast Social Comparison.
Table 3. Correlations between the factors and criteria variables. M ± dt Psychosocial Comparison orientation Neuroticism Positive self-esteem Negative self-esteem General self-esteem Health status Perceived health status Perceived quality of life
Upward Social Comparison
Downward Social Comparison
Identification
Contrast
Identification
Contrast
53.7 ± 16.49 52.32 ± 22.08 72.76 ± 15.15 38.01 ± 20.01 72.1 ± 9.35
.06 −.04 .10 −.07 .10
.15* .42** −.19** .39** .16*
.24** .32** −.18** .32** .10
.14 .10 .09 .07 .02
5.9 ± 2.4 6.8 ± 2.37
−.12 −.06
−.38** −.45**
−.30** −.21**
.01 .06
*p < .05; **p < .01.
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Terol et al. out that perhaps a previous emotional state and perceived control of the situation can influence and mediate in relation to favourable comparisons and perceived state of health, as shown in some studies (Stewart et al., 2013). On the other hand, the use of the (“favourable”) UISC and the DCSC was not related to any of these personal factors, so it is possible that its use is facilitated or not according to context factors (characteristics of the illness, health centres, hospitals or associations, etc.), which would have to be specified in future research. Finally, we should point out that although in our group of patients no significant relations were found in how certain forms of SC benefit health, this group could find indirect positive effects which specifically derive from avoiding the negative effects produced by comparing themselves with those who are worse and which remind them of their possible evolution (Downward Identification), or by comparing themselves with those who are better but are not useful as an example to be followed (Upward Contrast), which is what the results for perception of health and quality of life show. In this sense, it would be an adequate model of focused adaptation, especially in “avoiding” certain forms of comparison. Future long-term studies, besides including variables like perception of control and the content of comparison, would more specifically evaluate the use of “favourable” comparisons (Upward Identification and Downward Contrast) which would enable us to clarify their long-term function in the adaptation and health processes of different chronic patients. In conclusion, first, the results of this study allow us to obtain an adapted version of an evaluation instrument for SC in the context of chronic illness for the Spanish population, which replicates the original structure of the scale and proves to be valid for use with optimum reliability. Second, this study highlights how important it is for future research on SC with chronic patients to deal with the characteristics of the illness, personal characteristics, social context, and the participant’s relations so as to determine the development of the
comparison processes in the adaptation of these patients. Funding This research received no specific grant from any funding agency in the public, commercial, or not-forprofit sectors.
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