1 Introduction

From the ancient myth of Pandora to the current paradigm of positive psychology, hope has emerged as a central construct when discussing human psychological strengths. In positive psychology, research is centered on the scientific study of positive experiences, human positive traits and institutions that enhance human’s development (Duckworth et al. 2005), that is to say, in those conditions and processes that contribute to people, groups and institutions’ optimal functioning (Gable and Haidt 2005). Among these, constructs such as self-control, resiliency, benefit finding, spirituality, optimism and hope have been fore grounded (Snyder 2000).

Particularly, hope has gained increasing attention in positive psychological research (Marques et al. 2013; Snyder 2000). Several theories and models of hope based on affects and emotions have been developed (Averill et al. 1990; Farran et al. 1995; Scioli et al. 2011). The most popular model of hope has been developed by Charles R. Snyder, in which hope is conceived as “a positive motivational state that is based on an interactively derived sense of successful (a) agency (goal-directed energy) and (b) pathways (planning to meet goals)” (Snyder et al. 1991a, p. 287). That is, hope primarily is a cognitive process, consisting on the perception that individual’s goals can be met (Snyder et al. 1991b), and tapping three capacities: (1) the conceptualization of goals; (2) the development of strategies to reach these goals (pathways); and (3) the motivation for using those strategies (agency) (Lopez et al. 2000; Snyder 2000). Therefore, the two conceptual dimensions of hope would be pathways and agency. These two dimensions are not synonymous, but both are necessary in order to attain the original goals (Snyder 2000).

Since the very beginning of hope theory, several scales were developed to operationalize the construct. The first measurement instrument presented was the dispositional hope scale (DHS; Snyder et al. 1991b), a 12-item scale measuring pathways and agency, each with four items and the addition of, four filler items. The scale was designed for individuals from 15 years old. Later, Snyder and colleagues presented the State Hope Scale (Snyder et al. 1996), a 6-item measure of state hope. These authors finally added to the battery of hope measures the Children’s Hope Scale (Snyder et al. 1997), a scale that follows the original DHS. This shorter version is a six-item dispositional self-report index, assessing both pathways and agency in children aged 8–16. Among these measures, the DHS is the greatest exploited in hope research. DHS has been related to an extensive range of constructs, and has also been the subject of several psychometric studies, and it has been translated and validated in many languages such as Japanese (Kato and Snyder 2005), Dutch (Brouwer et al. 2008), Chinese (Chen et al. 2009), Turkish (Kemer and Atic 2012), or French (Gana et al. 2013). However, to our knowledge, DHS has neither been translated into Spanish nor validated for its use in Spanish speaking populations.

The research concerning DHS scale comes from its outstanding role as a predictor/criterion in many studies. Higher scores on hope have been positively related to problem solving abilities and academic achievement (Snyder et al. 2002), extraversion (Halama 2010), individualism and collectivism (Bernardo 2010), social support (Kemer and Atic 2012), well-being (Khan 2012), life satisfaction (Bailey and Snyder 2007; Halama 2010; Marques et al. 2013; O’Sullivan 2011; Wong and Lim 2009), adaptation to aging (Moraitou et al. 2006), or spirituality (Marques et al. 2013). Low hope punctuations, in turn, have been related to neuroticism (Halama 2010), procrastination, self-doubt and negative ruminations (Geiger and Kwon 2010). Newest literature points out the important benefits of hope in youth life satisfaction. For example, students with high scores on hope have shown higher levels of well-being and life satisfaction (Bailey and Snyder 2007; Gilman et al. 2006; Marques et al. 2013; Snyder 2000; Valle et al. 2004; Wong and Lim 2009). Recently, Marques et al. (2013) have found a strong relation between hope and life satisfaction in a sample of Portuguese students, a relation that is stable through time. Again with life satisfaction, Halama (2010) found a correlation between this construct and hope of 0.381, and Marques et al. (2013) found a relation quantified in 0.44, 0.51, and 0.55, in different periods of time. Other studies have studied the relation between hope and spirituality in sample of students. For example, Marques et al. (2013) found a correlation of 0.41, 0.39, and 0.40 between spirituality –measured by a single item- and hope, in a longitudinal study. In sum, the existent literature has systematically found evidence on the relationships among hope and other outcomes related to positive psychology, such as spirituality and life satisfaction, outcomes also measured in the current study.

Despite its relevance in the positive psychology research, the psychometric properties of the DHS have shown contradictory results. The factor structure of the DHS is still under controversy. Babyak et al. (1993) found, in a sample of undergraduate students, a second order model underlying the scale, in which agency and pathways were first order factors, and there was a higher-order latent construct overarching these two. In 2006, again in a sample of undergraduate students, Roesch and Vaughn tested the factorial structure of the DHS and their findings suggested that a non-hierarchical two-factor model with agency and pathways dimensions fitted the data significantly better than a unidimensional one. These authors did not test for a second order model. Nevertheless, they found a large correlation between the two factors. More recently, Brouwer et al. (2008) have tested the unidimensional model, the two-factor model, and a bifactor model for the DHS, in samples of students, psychiatric patients and delinquents. In the bifactor model proposed by Brouwer et al. (2008), items loaded on the general hope factor, but also on agency or pathways. The authors concluded that, although items of pathways explained some additional variance in the bifactor model, the best factor model for the DHS was the unidimensional (Brouwer et al. 2008). In Turkish population, Kemer and Atic (2012) have found a two-factor structure underlying the DHS, but they did not consider alternative models. Recently, the French version of the DHS has also been validated (Gana et al. 2013). The one-factor and two-factor models of the DHS were tested, with results that gave support to the bidimensional solution, although a strong correlation between agency and pathways was found. The authors concluded that the discriminant validity of the two factors was weakly supported. Thus, and up to date, unidimensional, non-hierarchical bidimensional, second-order and bifactor models have been considered in the DHS validations. Not a single work, however, has tested these four structures together.

It is important to note the substantive differences derived from the four factor models tested of the DHS. A two factor model with agency and pathways latent variables would support Snyder′s theoretical view (Snyder 2000), in which the two hope components are not synonymous but in order to attain goals, both are necessary, and should be correlated. A second order factor model would not contradict this view, as it would only add that there are two levels of generalizability. The choice of the unidimensional model, on the contrary, would indicate that agency and pathways are not distinguishable. The bifactor model would indicate that there are three constructs involved: a general hope factor that explains a part of the variance, and pathways and agency explaining additional variance. All correlation between agency and pathways is therefore due to the general hope dimension. This model is not directly related to the original hope theory, as Snyder proposed two distinct but related factors operating within Hope. Accordingly, there is still a gap in the literature with respect to which factorial structure better represents the DHS, and thus, a point this study aims to address.

There is a wealth of research pointing out the importance of hope in the positive psychology paradigm, and the DHS has been widely used in this research arena. Nevertheless, no translation into Spanish and, as a consequence, no validation of this scale is available. Current research translates the DHS into Spanish and offers evidence on its reliability and validity. Therefore, the aim of this research is to systematically test for competitive models based on previous evidence, offering for the first time evidence about the psychometric properties of the scale in a Spanish population.

2 Method

2.1 Design, Participants and Procedure

Data come from a cross-sectional survey of undergraduate students from the University of Valencia. The sampling scheme was incidental. The questionnaires were distributed during classes. Students volunteered to participate. The fulfillment of the survey took approximately 15 min. The students self-completed the survey, with the assistance of researchers, who only gave standard instructions. The sample was composed of 242 students. 51.7 % were women. Age ranged from 18 to 28 years old, with a mean age of 20.43 (SD = 2.09). 62.8 % of the students studied Health Sciences, 16.2 % Social Sciences, 9 % Technical Sciences, 8.5 % Arts, and 3.5 % Pure Sciences.

2.2 Instruments

The survey included socio-demographic information, as well as the following instruments:

  1. (a)

    Dispositional Hope Scale (DHS; Snyder et al. 1991b). The DHS is a 12- item instrument, with 4 pathways items, measuring abilities to identify feasible ways to goal, four agency items, attainment measuring motivations for pursuing goals, and four filler items, ignored in the present work. Items scored from 1(definitely false) to four (definitely true) (Snyder et al. 1991b). The scale was translated into Spanish applying the standard forward and back-translation procedure, from the original English version. First, a Spanish speaking translator, with knowledge of the English-speaking culture, translated the scale into Spanish, emphasizing conceptual rather than literal translations. No special problems were detected in this version. Then, the instrument was translated back to English by a new English speaking translator. As no problems were found, the first translation was retained as an adequate Spanish version of the scale. The Spanish version of the scale, together with the well-known English version, can be consulted in the “Appendix”.

  2. (b)

    Satisfaction With Life Scale (SWLS; Diener et al. 1985). The SWLS is composed of five items assessing global life satisfaction. The Spanish version was validated by Atienza et al. (2000), with five items scoring from 1(totally disagree) to 5 (totally agree). Alpha was 0.85 in this study. A confirmatory factor analysis (CFA) of the satisfaction with life items was estimated in order to test for factorial validity. A single factor structure previously found (Diener et al. 1985; Pavot et al. 1991; Sancho et al. 2014; Shevlin et al. 1998) was estimated and resulted in excellent fit indices (χ 2 5  = 13.6391, p = 0.01, CFI = 0.979, GFI = 0.973, SRMR = 0.032 and RMSEA = 0.085).

  3. (c)

    Meaning and Peace subscales from the 12-item Functional Assessment of Chronic Illness Therapy-Spiritual (FACIT-Sp-12; Brady et al. 1999). These subscales measure two dimensions of spirituality: meaning, with 4 items, and peace, also with four items, scoring from 0 (not at all) to 4 (very much). Examples of items of the meaning subscale are “I have a reason for living” or “I feel a sense of purpose in my life”. Examples of peace items are “I feel peaceful” or “I feel a sense of harmony within myself”. Alphas were 0.70 and 0.61 for meaning and peace, respectively. A CFA was estimated for the two factors of spirituality, with a non-hierarchical two-factor structure, the theoretical and validated structure for the original scale (Canada, Murphy, Fitchett, Peterman and Schover 2008). This model adequately fitted the data (χ 2 19  = 62.033, p < 0.01, CFI = 0.851, GFI = 0.911, SRMR = 0.076 and RMSEA = 0.099).

2.3 Data Analysis

Factorial validity was assessed via CFA. The models plausibility was assessed using several fit criteria, as recommended in the literature (for example, Hu and Bentler 1999; Tanaka 1993): (a) Chi square statistic (Kline 1998); (b) the comparative fit index (CFI; Bentler 1990), with values of more than 0.90 indicating a good representation of the data (and, ideally, >0.95; Hu and Bentler 1999); (c) the root mean squared error of approximation (RMSEA; Steiger and Lind 1980), with values of 0.05 or less for an excellent fit (the RMSEA uses errors of prediction and measurement to assess the degree of match between the hypothesized and true models); (d) the GFI as a measure of proportion of variance–covariance explained for the model, with values of more than 0.90 as indicative of adequate fit (Hoyle and Panter 1995); and (e) the standardized root mean squared residuals (SRMR), with values of 0.08 or less as indicative of appropriate fit (Hu and Bentler 1999). Hu and Bentler (1999) suggested that a CFI of at least 0.95, a RMSEA less than 0.06 and a SRMR less than 0.08 together would indicate a good fit between the hypothesized model and the data. Additionally, and in order to compare the models, differences between models’ CFI and the consistent akaike information criterion (CAIC) were estimated. There is an increasing tendency to use subjective criteria to make inferences on the differences between models, especially differences between CFI. Little (1997) argued that a CFI difference of 0.05 or less could be considered negligible, whereas other authors suggested that this difference should not exceed 0.01 (Cheung and Rensvold 2002). CAIC is a measure of information theory goodness of fit—applicable when ML estimation is used-, similar to Akaike’s information Criterion, but adding a penalty function for small sample sizes. Models with the lowest CAIC are preferred optimal. Structural models were estimated using EQS 6.1.

The statistical analyses also included estimations of the DHS internal consistency (Cronbach’s alpha and items’ homogeneity); nomological validity, estimated relating hope, agency and pathways to life satisfaction and two dimensions of spirituality, meaning and peace; and discriminant validity of agency and pathways, that was assessed by z-tests for paired correlations. These analyses were conducted with SPSS 20.

3 Results

3.1 Factorial Validity

Four models with the a priori structures shown in Fig. 1 were specified, estimated and tested in the sample. These models were: one-factor model (hope); two correlated factors model (agency and pathways); second order model with hope underlying the two first order factors; a bifactor model with hope as a unidimensional construct underlying the eight items, and agency and pathways explaining additional variance. It is important to note that, in order to identify a second order model with two first order factors, these factor loadings were constrained to equality (Bollen 1989).

Fig. 1
figure 1

Four CFA models specified and tested for the dispositional hope scale validation

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Table 1 shows the standardized factor loadings and fit indexes for the aforementioned four models. Overall fit indices showed an adequate fit for the four models. Indeed, the fit indices of one-factor, two-factor and bifactor models were excellent. Second order model showed estimation problems. In particular, this model presented a second order factor loading constrained to one, which is not surprising given that only two indicators of the second order factor were posited, with their loadings constrained to equality for identification purposes. Bifactor model showed the unique variance explained by the subdomains (agency and pathways), when hope as a general factor is taken into account. Bifactor model fitted the data appropriately but as it is shown in Table 1, only one of the factor loadings was significant for this case. That is, when the common variance was split, factor loadings for agency and pathways factors were very low, and statistically non-significant (except for item 8, “I meet the goals that I set by myself”). Thus, the unique variance explained by agency over and above the general factor of hope was very little, and it was almost inexistent the one explained by pathways. The two-factor model adequately fitted the data, but the correlation was extremely high [r = 0.933, 95 %CI (0.817–1.049)], showing no discriminant validity. Differences between CFIs were not substantial, with the largest difference found between unidimensional and bifactor models (ΔCFI = 0.015), a difference much lower than the one recommended by Little (1997), and almost not exceeding the cut-off by Cheung and Rensvold (2002). Results of CAIC showed that the unidimensional model had a better fit, with the lowest value in this index.

Table 1 Standardized factor loadings and fit indexes for the four confirmatory models of the dispositional hope scale
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3.2 Internal Consistency

Evidence on the reliability and internal consistency of the Spanish version of the DHS is provided, both at scale and item levels. Descriptive statistics, item homogeneity, alpha if-item-deleted and inter-item correlations for the unidimensional model are presented in Table 2. Although the unidimensional model was the best fitting one, internal consistency was calculated for the hope factor, and also for agency and pathways. Cronbach’s alphas were 0.826 for the hope, 0.750 for agency and 0.668 for pathways.

Table 2 Means, standard deviations, item-adjusted total correlation (rit), alpha if item deleted (αid), and inter-item correlations for the one-factor model of the dispositional hope scale
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3.3 Nomological Validity

As mention in the introduction, life satisfaction and spirituality provide evidence of nomological validity, understood as the degree to which a construct behaves as it should, within a system of related constructs called a nomological net (Campbell 1960).

Nomological validity was therefore obtained correlating hope, agency and pathways with satisfaction with life and the two dimensions of spirituality measured in the study. The overall hope factor correlated 0.706 (p < 0.01) with life satisfaction, 0.563 (p < 0.01) with meaning and 0.600 (p < 0.01) with peace. When hope was measured with the two theoretical dimensions, agency correlated 0.685 (p < 0.01) with life satisfaction, 0.519 (p < 0.01) with meaning and 0.484 (p < 0.01) with peace. Finally, pathways correlated 0.614 (p < 0.01) with life satisfaction, 0.513 (p < 0.01) with meaning and 0.610 (p < 0.01) with peace.

In order to compare the discriminant power of agency and pathways subdomains, their correlations with the mentioned constructs were statistically compared. Agency and pathways correlations with life satisfaction and meaning were not statistically different (z = 1.95 and z = 0.14, respectively, p > 0.05) although there existed statistically significant differences between the correlation of the subdomains with peace (z = −3.08, p < 0.01), indicating some discriminant validity for the two subscales just for the peace construct.

4 Discussion

This study presents the first translation and validation of the Spanish version of the DHS. This research aims to clarify DHS dimensionality, a profusely used measure of hope. Most studies on factorial validity of the scale have not tested the full range of models found in the literature. The current research tests all the proposed factorial models, also studying internal consistency and nomological validity of the Spanish version of the DHS.

With respect to factorial validity, the best fitting model was the simplest structure: a one factor solution of hope. This is in line with the results of Brouwer et al. (2008), who found that although pathways items explained some additional variance in the bifactor model, the best choice for the DHS structure was unidimensionality. However, whereas these authors found that item three had a higher loading on pathways compared to the loading on the general factor, this is not the case in this study, in which every factor loading was higher for the hope general factor. Moreover, in the unidimensional model tested, minimum factor loading was 0.521, a higher value than the one obtained in the same model by Brouwer et al. (2008). On the contrary, Gana et al. (2013) found support for the two-factor model, but with a strong correlation between the factors and weak evidence of their discriminant validity. Results in this study also showed a high correlation between pathways and agency. Thus, and taking into account differences on fit indices, especially those found in CAIC, current research advocates for the unidimensional structure of the DHS.

As regards internal consistency, results found for the general hope factor were similar to other studies. For example, Snyder et al. (2002) found an alpha of 0.86 in a student’s sample. However, the alphas of the two dimensions of hope were lower, as these authors found an alpha of 0.81 for agency and 0.74 for pathways. In the study by Roesch and Vaughn (2006), alpha for the two dimensions of the scale were 0.82 for agency and 0.79 for pathways, again higher estimates than those found in these results. As in previous research, and probably because of the larger number of items, internal consistency was better when the scale was treated as unidimensional. This is another point that supports the use of the scale as a unidimensional one.

Regarding evidence of nomological validity, all correlations were in the expected direction and consistent with the estimates found in previous literature (Halama 2010; Marques et al. 2013). For example, Marques et al. (2013) found a correlation of 0.55 between hope and life satisfaction, and 0.39 between hope and spirituality. Halama (2010), in turn, found a correlation between hope and life satisfaction of 0.38. In this study, values were above the ones found previously, with a maximum of 0.706 for the relationship between hope and life satisfaction, and a minimum of 0.563 for the relation between hope and meaning, one of the dimensions of spirituality tested. Therefore, it can be concluded that all relationships offer evidence of the nomological validity of the DHS.

When discriminant validity of agency and pathways was studied, results were complex. When life satisfaction and meaning correlations with agency and pathways were contrasted, results showed no statistical differences between them. However, this was not the case for the correlations of agency and pathways with peace, which were statistically different. Thus, no systematic information about the relation between hope and life satisfaction and meaning seems to be lost when hope is treated as a general factor in the Spanish context. Nevertheless, when the relation studied is the one between hope and peace, results showed different relations between peace and the different subdomains, agency and pathways, and thereby, not taking into account the different subdomains could lead to obviate additional information. However, it must be borne in mind that both correlations were positive and large (0.484 for agency and 0.610 for pathways), and these are sample-based results. Therefore, this result needs further investigation.

To put the whole thing in a nut shell, factorial results of the Spanish version of the DHS offer evidence for a basic unidimensional structure, as items measured the same construct, being very little the unique variance that was explained by agency over and above the general factor of hope, and irrelevant the one explained by pathways. On one hand, and as regards the first aim of the study, among the four different structures for the Spanish version of the DHS collected along the literature and tested in this research, a unidimensional structure has been found as the best structure to represent the scale. On the other hand, this study offers the first presentation and validation of a Spanish version of the DHS, giving evidence of its adequate psychometric properties.

The main strength of the present paper is that DHS is a brief and broadly used measure of hope, that has been proved to have appropriate psychometric properties, both validity and reliability. Because of its short length, the DHS is particularly suitable for large batteries of assessments as an initial measure of hope (Lopez et al. 2000), not only for English speaking populations, but also for Spanish ones. A second strength is that it is the first validation of the DHS, in any language, which has tested the four different factor models presented along the literature, presenting findings consistent with previous ones (Brouwer et al. 2008). Finally, the third contribution of this paper is that it is the first validation, as far as we know, of the Spanish version of the DHS. Among the drawbacks, as the sample was assessed only once, no estimates of test–retest reliability could be provided in the current study. Another limitation is the few constructs measured to establish the criterion-related validity. Such information could give additional insight into the scale reliability. Last, but not least, there is the incidental nature of the sample, which is both a benefit, as the undergraduate samples are the ones used in the studies gathered on this topic, so that results of this research enable a better comparability between studies, and a liability, because of generalization restrictions. Thus, future research on different Spanish samples is needed.