Introduction

As indicated by ^{Fernández-Montalvo and Echeburúa (2006)}, it is increasingly difficult to find so-called “pure” clinical cases, i.e., patients who are afflicted by only one psychopathological disorder, as new research is showing that there is comorbidity between the different disorders. This fact implies a new approach to the evaluation and explanation of such disorders, and, consequently, the need to analyse and adapt the tools used for evaluating and explaining them. It further indicates the need for the creation of new tools that enable the gathering of more accurate information about the patient's disorders and its possible treatment.

Despite the fact that numerous measures have been developed to evaluate personality disorders in recent years, and against the opinions of some authors (^{Dutton, 2003}; ^{Gondolf, 2003}, among others), self-report methods (questionnaires, inventories, scales) remain the most commonly used measurement tools. These methods can produce skewed results because of the ease of manipulating, simulating or even hiding symptoms. Because of this, the reliability of the results and the validity of any inferences made are subject to serious questioning (^{Calcedo, 2000}; ^{Echeburúa, Amor, & Corral, 2003}).

On the other hand, the results obtained from different measurement instruments used in the diagnosis of these types of disorders often show low levels of agreement, which means that inferences and conclusions drawn from these data are also questionable (^{Hyler et al., 1989}; ^{Zimmerman & Coryell, 1990}). In any case, a clinical diagnosis must be based on information obtained by various means: self-reporting, interviews, etc.

In the field of psychopathology, self-reporting has been used for both the evaluation of specific disorders (^{Fernández-Montalvo & Echeburúa, 2006}) and the exploration of symptomatology, being it general or specific to an individual. One of the self-reporting methods most commonly used for the latter is the SCL-90 (^{Derogatis, 1977}; ^{Derogatis & Cleary, 1977}; ^{Derogatis, Lipman, & Covi, 1973}), composed of 90 items across nine different scales that seek to measure nine basic dimensions: somatisation, obsessive compulsion, interpersonal sensitivity, depression, anxiety, hostility, phobic anxiety, paranoid ideation and psychoticism. ^{Derogatis and Savitz (1999)} developed an updated version of the scale (SCL90-R) 90-item, multidimensional self-report symptom inventory which measures symptomatic psychological distress. The SCL-90-R results in three global measures of distress as well as the nine primary symptom dimensions defined before and did not represent a significant change respect to the SCL-90 since only two items were modified. However, the SCL-90 as well as the updated version, presents a few problems that complicate its use: the large number of items, the overlap in items, the high correlation among the nine scales, the low degree of discriminant validity, the instability of its structure, and the lack of factorial validity, indicated by the fact that factorial structures that varied from one to ten factors were proposed in various studies of the questionnaire (^{Davison et al., 1997}; ^{Sandín et al., 2008}; ^{Vassend & Skrondal, 1999}). In order to avoid some of these inconveniences, ^{Davison et al. (1997)} developed a questionnaire, the Symptom Assessment-45 Questionnaire (SA-45), that (a) maintained the advantages of the SCL-90; (b) required only half the number of items used in the SCL-90 (45 items); (c) contained the same number of items for each scale, in order to retain their reliability; and (d) avoided item overlap, thus minimising correlations among the different scales by increasing its discriminant validity and favouring the utility and usability of the instrument. This last improvement is especially important given the existing efforts to integrate the treatment of behavioural problems into primary care services, in order to offer more efficient and effective service to individuals with psychological and emotional problems.

Maruish, Bershadsky, & Goldstein (1998) carried out a project designed to demonstrate the benefits of integrating behavioral healthcare services in primary medical care settings providing an opportunity to further investigate the psychometric properties of the SA45 using data from a sample of 126 adults. Specifically, the appropriateness of the SA45's adult nonpatient norms, as well as cross-validation of its test-retest reliability and construct validity, was investigated. The results suggested that use of the SA45 nonpatient norms with primary care populations is appropriate. The use of the SA-45 has demonstrated its utility in (a) identifying and classifying psychiatric patients, although accurate classification of patients requires further evaluation for behavioral health problems, (b) evaluating psychopathological changes in patients with health problems, and (c) highlighting the effects of psychological treatment in psychiatric patients.

The psychometric properties of the Spanish version of the SA-45 have been studied by ^{Sandín et al. (2008)} using a sample of 420 students from various public universities in Madrid. The main objective of his work was the study of the factorial structure of the questionnaire through the implementation of a series of factor analyses, both exploratory and confirmatory. The results of the exploratory factor analyses suggest a factorial structure of nine factors, which was later corroborated through a confirmatory factor analysis. A similar study was carried out by ^{Alvarado, Sandín, Valdez-Medina, González-Arraia, & Rivera (2012)} using a sample of 418 university students from the Universidad Autónoma del Estado de México. The results showed that the psychometric characteristics of the questionnaire were very similar even when dealing with samples from diverse cultural backgrounds. However, factorial solutions are difficult to replicate, even under exceptionally favourable circumstances as the exploratory factor analysis is sensitive to the characteristics and size of the sample group used (^{Costello & Osborne, 2005}; ^{Osborne, Costello, & Kellow, 2008}; ^{Osborne & Fitzpatrick, 2012}).

As the study by ^{Sandín et al. (2008)} was the first study in which the Spanish version of the SA-45 was validated psychometrically, we have deemed it beneficial to carry out a new study. The main objectives of this new study are to analyse the internal structure of SA-45 and to evaluate its reliability in a non-clinical sample.

Method

Results

Discussion and Conclusions

One point that the results have highlighted is that the best solution found has nuances that differentiate it from the solutions proposed by other authors (^{Alvarado et al., 2012}; ^{Sandín et al., 2008}) who have replicated Maruish et al.'s (¹⁹⁹⁸) original model.

We understand that using a non-clinical population in the initial studies as opposed to a clinical one as in Maruish et al.'s study (¹⁹⁹⁸) will in large part determine the results that are obtained. One of the first points that stand out is that the majority of the responses fall into the 0 and 1 categories. For example, for the item “Hear voices that other people do not hear”, 97.8 % fell into category 0. This is not an isolated case; for as many as 7 items, over 90 % of the responses are concentrated in the 0 category. If we consider the first two response categories, 30 of the 45 items show over 90 % of responses falling into these two categories. This fact alone may show that the composition of these items is not appropriate for a “normal” population, or in this case, for participants without diagnosed psychopathological disorders.

In this study, we have not replicated the solution proposed by ^{Maruish et al. (1998)}, though other authors have in fact done so (^{Alvarado et al., 2012}; ^{Sandín et al., 2008}).

It is worth highlighting that in contrast to the previous studies, we discovered a factor in the EFA that explains one third of the total variability, which leads us to consider the existence of a factor of general character. This general character must have great specific weight in the configuration of any explanatory model on the dimensionality of the instrument.

Nevertheless, the intention in carrying out a CFA was to test Maruish et al's (¹⁹⁹⁸) original model (model 2); this model has also been replicated by ^{Sandín et al. (2008)}.

Specifically, we have discovered that the global fit indexes were acceptable for our data. Nonetheless, given that the sample used by ^{Maruish et al. (1998)} was of clinical subjects, that the response pattern of our study may be atypical for a non-clinical population, and that the results obtained in the EFA may suggest alternative factorial solutions, another two models were tested.

The first model, consistent with the results of the EFA, comprised nine dimensions, of which the majority contained a combination of items from Maruish et al.'s original dimensions. The first dimension, and the most explanatory, comprised a total of nine elements from three factors (paranoid ideation, interpersonal sensitivity and depression); the second factor had seven items related to phobic anxiety and anxiety. The global fit indexes of this solution are clearly better than those of the original model.

On the other hand, exploring the possibility that the model was one-dimensional, a third model was tested (model 3), with nine first-order factors and a general second-order factor. The fit indexes were also acceptable, but although they are better than those obtained for the original model, they are worse than those obtained for model 1.

We understand that if the SA-45 is applied to a nonclinical population, we must evaluate whether scores ought to be corrected by Maruish et al.'s solution due to reasonable doubts as to whether the questionnaire is the best option for a non-clinical population. In this sense, we understand that the solution presented is best used as a measurement of the general mental health of the subjects rather than as a purely diagnostic test to be used in a psychiatric context.

Factor 1 encompasses elements of paranoid ideation, interpersonal sensitivity and depression. All the elements of factor 2 have the word “fear” in common, which may lead to the belief that its elements are not understood in the same way as in a population of clinical subjects. In factor 3, there is a mixture of items from the categories of somatisation and obsessive compulsion. The fourth factor makes clear reference to hostility, while in the fifth, elements of depression and interpersonal sensitivity are combined again. In other words, a subject who is probably not depressed will not interpret the combined content of the items in the same way clinical subjects interpret them. Factor 6 is, again, interpreted as psychoticism. Factor 7 is saturated with only three items from the original scale of anxiety that make reference to tension or nervousness. The eighth dimension includes a mixture from the categories of depression, obsessive compulsion and psychoticism. Specifically, the items refer to feeling sad, alone, incapable of concentrating and having constant thoughts of selfpunishment. Finally, factor 9 refers to obsessive compulsion, and the items that make up this dimension are related to being indecisive and insecure.

The discrepant results obtained in this study suggest that there is a need to continue researching the factorial structure of the SA-45 in the non-clinical population. It could be concluded that the items are not understood in the same way when applied to this sample as when they are applied to a clinical sample group. In fact, different dimensions arise from those proposed by ^{Maruish et al. (1998)} in the studies carried out with non-clinical population that may be related to personality traits. For this reason, more empirical evidence must be obtained on the configuration and the significance of the constructs in the SA-45 for the non-clinical population. Furthermore, the items should be adapted to this type of the population as necessary.