Psychometric Properties of the Anxiety Attitude and Belief Scale in an Asian Community Group

Abstract

Background: This study examined the psychometric properties of the Anxiety Attitude and Belief Scale (AABS), a measure of attitudes and beliefs intended to index a psychological vulnerability to anxiety problems, in an Asian context.

Methods: Exploratory factor analysis was performed on sample of 434 community participants from Singapore, who were predominantly ethnic Chinese.

Results: A revised factor structure of the scale (AABS–A) comprising of three factors, namely Catastrophising, Vigilance/Avoidance, and Reasonable Anxiety–Related Beliefs, was found. Internal consistency was satisfactory for the total scale and the three factor scales derived. Concurrent and discriminate validity of the AABS–A were also good.

Conclusion: Study results suggest that the AABS–A is a valid and reliable instrument for assessing anxiety–related attitudes and beliefs in Asian, in particular Singaporean, community samples.

Keywords: Anxiety; Attitude; Belief; Reliability; Validity; Asia

Introduction

Psychometric Properties of the Anxiety Attitude and Belief Scale (AABS) in an Asian Sample. The role of cognition is underscored in the development and maintenance of anxiety problems, specifically pertaining to the chronic over–activity of schemas involving beliefs organized around themes of danger, harm to self, and personal vulnerability or inability to cope [1,2]. Despite playing a central role in cognitive theories of anxiety, anxiety–related beliefs⁄attitudes have remained less researched relative to alternative cognitive models of anxiety such asanxiety–related transitory situational automatic thoughts (e.g., Cognition Checklist, Scale A) and Agoraphobic Cognitions [3]. Also, few measures are available to assess enduring beliefs⁄attitudes that predispose individuals to anxiety reactions and symptoms [4]. Pinpointing predisposing anxious attitudes⁄beliefs may contribute towards current understanding of processes leading up to overt manifestations of anxiety symptoms [4].

In view of the above, Brown et al. [4] argued that a gross assessment of conscious verbal productions may overlook the contributions of anxiety–related cognitions in an individual’s presentation of anxiety symptoms such as fear and worry. Therefore, using Exploratory Factor Analysis (EFA), Brown and colleagues [4] developed the Anxiety Attitude and Belief Scale (AABS; with its 3 subscales: Catastrophising, Vigilance⁄Avoidance, and Reasonable Anxiety–Related Beliefs) to assess enduring attitudes⁄beliefs that potentially predisposes one to anxiety symptoms. Good psychometric properties and adequate reliability were demonstrated for the AABS [4].The psychometric properties of the AABS have yet to be replicated by other independent researchers or validated with other cultural populations. It is necessary to generalize the study findings to populations beyond that of the original research. Replication in support of findings from Brown et al. would strengthen confidence in the use of AABS in further research.

Previous studies have noted higher pessimism in Asians residing in western countries, which relate positively with self–reported anxiety and depression symptoms [5]. Studies have also noted higher self–reported mean scores on anxiety and depression measures, lower levels of global happiness and life satisfaction, and less frequencies of positive affect among East Asian than North American populations [6,7]. Some cross–cultural and social psychological theories have been proposed to explain these findings. For instance, the Japanese have been suggested to experience lower positive self–regard than western populations, possibly from the practice of self–criticism and perfectionism [6,8]. Considering these cross–cultural differences, the significance of identifying anxiety–related attitudes⁄beliefs as previously discussed, and also the importance of measurement equivalence in assessing psychological constructs across cultures, is critical [7]. Possibly, processes of change in the development and maintenance of anxiety symptoms that are unique to the Asian setting could be highlighted [7].

Based on the National Mental Health Survey of Adults in Singapore [9], prevalence rates of anxiety disorders in Singapore are higher than that of other Asian countries like China (1.2%) and Japan (1.2%) [10]. Considering this, as well as a potential risk for anxiety among Asian populations as highlighted above, the development of a reliable and valid instrument for assessing anxiety–related beliefs⁄ attitudes in an Asian–dominated population such as Singapore is useful and necessary [6,7]. Identifying a pattern of anxiety–related beliefs⁄attitudes in a sample of Singaporeans may reveal important cognitions and schemas unique to this group, which may also be helpful in therapeutic settings [4]. Thus, the present study sought to establish the psychometric properties of the AABS in a Singaporean community sample [11]. In view of possible cultural differences in the experiences and presentation of anxiety symptoms between Asian and western samples, a different factor structure of the AABS could emerge for the Singaporean sample [12]. However, as there have not been any past studies evaluating the AABS in the Singapore population, the study did not make any specific hypotheses on the factor structure and adopted an open–ended approach towards the examination of the factor structure of the AABS. In addition, the study also investigated the concurrent and discriminate validity of the AABS.

Methods

Participants

434 participants (age range = 21 to 74 years; M = 43.14; SD = 14.48) participated. The sample consisted of 157 males (M= 44.55 years, SD = 15.18) and 277 females (M= 42.32 years, SD = 14.04). Consistent with the multi–ethnic composition of Singapore, 85.7% of the participants were Chinese, 8.1% were Malays, 4.8% were Indians, and 0.9% was of other ethnic groups. The majority of the participants (53.2%) indicated that English was their first language, followed by Mandarin (37.1%), Malay (5.8%), Hindi⁄Tamil (0.9%), and other languages (2.5%).

Procedure

Participants were recruited through advertising in the local community and by word of mouth. Each participant provided written consent prior to study participation, and was assured of their confidentiality and right to withdraw from participation at any stage of the study. Study questionnaires were given by hand or mailed to each participant who returned the completed questionnaire anonymously using pre–paid envelopes. Instruments were administered to all participants. Each participant took an average of 30 minutes and received no incentives to complete the questionnaires. The study was cleared in accordance with the ethical review process of the University of Queensland. Study procedures conformed to the provisions of the Declaration of Helsinki in 1995 (as revised in Edinburgh 2000) [13].

Measures

Demographic information questionnaire: Data on gender, age, marital status, race, religion, first language, country of birth, highest education level attained, employment status, and occupation were gathered in a one–page questionnaire developed by the researcher.

Anxiety Attitude and Belief Scale (AABS): The AABS is a 36– item self–report inventory measuring attitudes and beliefs intended to index a psychological vulnerability to anxiety problems.Respondents indicate a score (from 1 to 7) on each item and the total score is the summation of item scores, with higher scores representing greater maladaptive thinking. Initial psychometric properties of the AABS, including reliability, and discriminant, concurrent and predictive validities were established in an undergraduate sample [4].

Dysfunctional Attitudes Scale (DAS): The DAS is a 40–item, self–report inventory designed to assess attitudes or beliefs (e.g., concerns about approval from others, prerequisites for happiness, and perfectionistic standards) associated with a vulnerability to depression [14,15]. Respondents indicate a score (from 1 to 7) on each item and the total score is the summation of item scores, with higher scores representing greater maladaptive thinking. The DAS demonstrated good reliability and validity in both clinical and community populations and has also been validated in different language and cultural samples [16]. A Chinese version of the DAS also demonstrated sound psychometric properties (i.e., test–retest r = .87; Cronbach’s alpha coefficient=.95) in an adult sample in HongKong [17].

Anxiety Control Questionnaire (ACQ): The ACQ is a 30–item, self–report inventory designed to assess perceptions of control over potentially threatening internal and external events. After reverse scoring 18 items, the total score is obtained by the summation of all items, with higher scores representing higher levels of perceived control. Good internal consistency has been demonstrated in clinical samples and an undergraduate sample [18–20].

Anxious Self–Statements Questionnaire (ASSQ): The ASSQ is a 32–item self–report inventory measuring the frequency of anxietyrelated, cognitive self–statements experienced by the respondent [21]. Respondents indicate a score choosing from 1(“Not at all”) to 5 (“All the time”) to rate the frequencies of anxious self–statements that occurred to them over the past week. The Asian version of the ASSQ (ASSQ–A) was used in this study, which has been shown to possess good internal consistency with Cronbach’s alpha coefficient of .91 [22].

Depression Anxiety and Stress Scales (DASS–21): The DASS– 21 is a 21–item self–report inventory measuring negative emotional states of depression, anxiety and stress [23]. Very good reliability estimates were found in psychiatric and non–clinical samples and good construct, convergent, and discriminant validities have also been demonstrated [24–26]. The DASS–21 is valid and reliable in Asian samples [27].

Results

Preliminary Data Analyses

Preliminary data screening was conducted with Statistical Package for the Social Sciences (SPSS) 15.0. Missing data (< 5%) were randomly scattered throughout the data set and was treated using the Expectation Maximization (EM) algorithm. Positive skewness was noted for the DASS total score, and the ASSQ total score. This was not unexpected given the use of non–clinical subjects. Transformation of the variables did not alter the interpretation of results significantly. Therefore, results of analyses with untransformed data were interpreted. An investigation of Mahalanobis’ distances revealed 15 multivariate outliers, which were removed for further analysis. Multicollinearity was not evinced in the data. Examination of the residuals scatter plot and the normal probability plot indicated normality, linearity, and homoscedasticity of the residuals.

Exploratory Factor Analysis

As the AABS has not been validated using an Asian sample previously, exploratory factor analysis was employed to establish the factor structure of the AABS appropriate for the current Singapore sample. The 36 items of the AABS were subjected to Principal Components Analysis (PCA) using SPSS 15.0. Prior to performing PCA, the suitability of data for factor analysis was assessed. Inspection of the correlation matrix revealed the presence of several coefficients of .3 and above. The Kaiser–Meyer–Oklin value was .86, exceeding the recommended value of .6, indicating sampling adequacy [28]. Barlett’s Test of Sphericity [29] reached statistical significance (p < .001), indicating that relationships existed between at least some of the items and thus, supporting the factorability of the data.

An investigation of the loading matrices suggested the removal of four items due to low factor loadings (minimum factor loading = 0.40). A number of criteria were used to determine the most appropriate number of factors to retain: (a) minimum eigen values of 1, (b) minimum factor loadings of 0.40, and (c) meaningful interpretation of individual factors. An investigation of the loading matrices suggested the removal of four items due to low factor loadings. The results indicated that the model most concordant with these criteria was a three–factor solution rotated to simple structure using the Varimax method with Kaiser normalization. The screen test and number of eigen values greater than one supported the decision to accept a three–factor solution. Together, the three factors explained 39% of the variance in the items, with factor 1 to factor 3 contributing 15.1% (eigen value = 6.86), 14.7% (eigen value=3.29), and 9.2% (Eigen value = 2.33), respectively. The factor loadings and communalities were good, suggesting that the items were satisfactorily explained by the three underlying factors (conceptual fit). Item content, factor loadings, and communalities of the remaining 32 items are shown in Table 1.