|Year : 2015 | Volume
| Issue : 2 | Page : 145-153
Psychometrics properties of the Persian version of Beck Anxiety Inventory in North of Iranian adolescents
Mahnaz Fallahi Khesht-Masjedi1, Zoharah Omar2, Seyed Mousa Kafi Masoleh3
1 Department of Psychology, Shafa Hospital Psychiatric Research Center, Guilan University of Medical Scienses, Rasht, Iran
2 Faculty of Educational Studies, Universiti Putra Malaysia, Seri Kembangan, Malaysia
3 Faculty of Humanities, University of Guilan, Rasht, Iran
|Date of Web Publication||27-Feb-2015|
Dr. Mahnaz Fallahi Khesht-Masjedi
Guilan University of Medical Scienses, Shafa Hospital Psychiatric Research Center, 15 Khordad Avenue, Rasht
Source of Support: None, Conflict of Interest: None
Aim: This study investigated the psychometric properties of the Persian Version of the Beck Anxiety Inventory (BAI) for adolescents. Materials and Methods: This research examined the validity and reliability of BAI in North of Iranian normal population. After psychologists had been sufficiently prepared, they were dispatched to different regions of the Guilan (Guilan Province of Iran), referring to residential places for boys and girls in the research. At the end, 783 respondents were randomly recruited and tested using BAI. Two hundred and thirty-two respondents were randomly selected and re-tested in order to measure test-retest reliability with a 1-week interval time between first and second tests. To assess validity; we performed a principal component exploratory factor analysis to explore the factor structure of the BAI and Pearson's correlation coefficient performed for convergent validity between the BAI, self-rating anxiety scale, symptom check list-90-R, sexual abuse trauma index and divergent validity with Beck Depression Inventory (BDI)-II. For data reduction and analysis, the SPSS 22 and Amos 18 were conducted. Result: Findings showed that the Persian version of BAI proved an acceptable test-retest reliability (r = 0.67), an internal consistency (α =0.88), convergent validity (0.40-0.44), and divergent validity (r = 0.216) with BDI-II. We found a clear cut point for our society and these findings confirmed the confirmatory factor analysis results and suggested that the factor structure for the BAI-Iranian is valid and stable. The indices were the Chi-square statistics (χ2 df =547.234), the comparative fit index =0.91), the standardized root-mean-square (0.05), the root-mean-square error of approximation (0.04), and the Akaike Information Criteria (694) a good model fit is indicated. Conclusion: The results support the applicability of BAI in adolescents and suggest the use of this inventory for screening general anxiety by school counselors and psychologists adolescents and research aims.
Keywords: Adolescents, anxiety, Beck Anxiety Inventory, psychometrics
|How to cite this article:|
Khesht-Masjedi MF, Omar Z, Kafi Masoleh SM. Psychometrics properties of the Persian version of Beck Anxiety Inventory in North of Iranian adolescents. Int J Educ Psychol Res 2015;1:145-53
|How to cite this URL:|
Khesht-Masjedi MF, Omar Z, Kafi Masoleh SM. Psychometrics properties of the Persian version of Beck Anxiety Inventory in North of Iranian adolescents. Int J Educ Psychol Res [serial online] 2015 [cited 2019 Dec 12];1:145-53. Available from: http://www.ijeprjournal.org/text.asp?2015/1/2/145/152233
| Introduction|| |
Anxiety is an emotional state characterized by physiological arousal, unpleasant feelings of tension, and a sense of apprehension.  Anxiety has been recognized as one of the most common disorders among adolescents. , If the anxiety is left untreated, it may lead to other psychological problems such as depression, suicidal thoughts, behavioral problems and drug abuse. ,,, Anxiety is a prevalent problem among adolescent in Iran especially among girls. ,, Hence, with the prevalence of anxiety disorders among adolescents it is important to make a systematic evaluation to assess anxiety disorder using a valid and reliable instrument.
The Beck Anxiety Inventory (BAI) is one of the most frequently used self-report instruments to assess anxious symptomatology in patients with psychological disorders and in the normal population, both in clinical practice and research. 
In Iran, the BAI has become increasingly popular as an instrument to assess anxiety both in basic and applied research. In fact, the first various translations of the BAI have been published by Dr. Mahmuod Mansour and BAI was introduced to Iranian psychologist. Although BAI examined the psychometric in 2008 by Kaviani and Mosavi was entitled "psychometric properties of the Persian version of BAI",  we have not found any study that specifically analyzes the psychometric properties of any adolescents samples in Iran. The purpose of this study was to examine the psychometric properties of the BAI for Adolescents in Northern Iran.
The BAI is a 21-item self-report questionnaire, used to judge the severity anxiety. BAI is quite heavily loaded with somatic and panic-like symptom of anxiety rather than the stress-like symptoms of general anxiety.  Past research has established the validity and reliability of item scores of BAI. However, there has been continued controversy over the factor structure of the scale. Although BAI has been used mainly as a unitary measure of anxiety, numerous factor-analytic studies of BAI have revealed factor structures of one to six factors.  In the original study, Beck et al. tested BAI validity using exploratory factor analysis (EFA) on psychiatric outpatients.  Beck reported two-factor structures, the first factor comprised of somatic symptoms (12 items) and the second factor comprised of subjective anxiety and panic symptoms (9 items). They also reported that the factor structure of the BAI scale was distinct from that of the Beck Depression Inventory (BDI) with a moderately high correlation r = 0.48). , Several other studies also found support for the two-factor structures. ,, Kumar et al. also found support for two-factor structure when they tested the psychometric properties of BAI in the adolescent population.  Chapman et al. (2009) investigated the original two-factor structure of the BAI in a nonclinical sample of African-American and European American young adults using confirmatory factor analysis (CFA). They found that the previous factor structures of the BAI did not provide the best fit for either the African-American or the European American sample. Instead, their study revealed that an alternative, two-factor model that provided the best fit for the sample, particularly for the African-American sample.  Morin et al. examined the psychometric properties of the BAI in a nonclinical sample of 281 older adults using EFA. Their study revealed a six-factor solution of the BAI, which comprised of: Somatic (6 items), fear (3 items), and autonomic hyperactivity (3 items), panic (4 items), nervousness (3 items), and motor tension (2 items).  Osman et al. tested the BAI on adolescent sample and found that the existing factor structure in their samples was inadequate. A subsequent EFA (principal axis factoring) with orthogonal and oblique rotations supported a four-factor solution for both samples that included neurophysiological, subjective, autonomic, and panic factors. However, because of moderate intercorrelations among these factors (ranging from 0.31 to 0.55) further analyses of the principal factors revealed the support for a higher order, single factor structure of the BAI, which they labeled as anxious arousal.  Sæmundsson et al., tested the Icelandic version of BAI in a patient and a student population using CFA. Their findings revealed that a one-factor structure was superior to the alternative two-factor and four-factor models for the student population. Meanwhile, for the patient population, a four-factor model was the best model.  Sanford et al. tested the psychometric properties of the BAI within the adult population with sleep-disordered breathing and reported a single factor structure of the BAI scale. 
Empirical evidence has showed that BAI has the ability to discriminate the anxiety from depression.  Items from the BAI and BDI were reported to have a strong tendency to load on separate factors.  Sanford et al., reported that a high correlation between the BAI and BDI-II, but the combined factor analysis revealed two distinct factors. Hence, Sanford et al., suggest that the correlation is a function of the relation between the two constructs (anxiety and depression) rather than poor discriminant validity of the two measures. Nevertheless, studies have also reported substantial overlap of BAI with depressive symptoms particularly in a clinically depressed sample.  For instance, study conducted by Clara et al. supported the notion that anxiety and depression as two distinct phenomenon only to a limited extent when used in a clinically depressed sample.  Lahey et al. study on 4-17 year olds revealed that depressive symptoms were loaded on a different factor from worry-related symptoms in anxiety symptoms involving worry and social anxiety are loaded on the same factor as depressive symptoms.  Studies have also shown that this problem is not simply confined to self-report data. Considerable overlap also has been found in clinicians', parents', and teachers' ratings of depression and anxiety. 
In the current study, we examined the reliability and validity of scores on the BAI with adolescents North of Iranian. The mixed findings on the psychometric properties found past studies signify the need to test the psychometric properties of BAI when used on different samples. Furthermore, many studies testing the psychometric properties of the BAI have used EFA. The use of EFA has its limitations as this analysis cannot make distinctions between competing factor structures and also accounts the measurement error in the scores.  Hence, the use of CFA has been suggested as more appropriate to address these limitations. There have been considerably not many studies that have used CFA in testing the psychometric properties and validity of BAI. Three studies have employed CFA, namely Osman et al., Sæmundsson, et al., and Chapman et al. reported different BAI factor structures. ,, Osman et al. reported a two-factor structure, Sæmundsson, et al. reported a one-factor structure as the best model, meanwhile Chapman et al. suggested an alternative two-factor model for African-American sample. Furthermore, since the BAI is now being used on Iranian population, it is also important to test the convergent and discriminant validity of the BAI due to different cultural background.
We conducted a CFA of the BAI based upon the three previously described existing factor structures of the BAI. The BAI is a widely used self-report measure of anxiety in psychiatric research and practice, as well as in nonclinical research. , BAI has also received international acceptance and has been translated into several languages ,,,, and also translated into Persian language and validated in the adult population in Iran.  However, the psychometric properties of the BAI scale were not tested in Kaviani and Mosavi's study. Study has yet to be conducted to test the factor structure, validity and reliability of the Persian Version of the BAI among Iranian adolescents.
Osman and Augustine tested the factor structure, validity and reliability of the BAI English version in samples of adolescents ranging from 14 to 18 years old. They reported that the BAI showed acceptable psychometric properties in adolescents. Therefore, the purpose of this study is to test the factor structure, validity and reliability of the Persian version BAI in samples of Iranian adolescents. 
The convergent and discriminant validity BAI are contrasted with those of a widely used measure, The self-rating anxiety scale (SAS), State-Trait Anxiety Inventory (STAI), symptom check list-90-R (SCL-90-R) and BDI-II.
| Materials and Methods|| |
The research design in this study was a correlation. Correlational studies can suggest a relationship exists between variables. The target population of this study is teenagers in North of Iran (Guilan Province). Guilan is one of the provinces of Iran. It lies along the Caspian Sea. Participants in the study were a group of 783 teenagers, aged 15-19 years. Adolescents were school and nonschool from of north of Iran in 2011 to 2012, and who participate in the study. Average age of the sample was 17.93 years (standard deviation [SD] =1.64, range =15-19); 44.7% (N = 350) were female and 55.3% (N = 433) male.
Based on the previous studies, we assumed a prevalence of 5%. With a precision of 1-95% confidence interval, taking into account the multistage clustering sampling method, we calculated the minimum sample size, and finally selected 783 adolescents for our study. Assuming 18 adolescents in each cluster, we selected 44 clusters that were proportionally distributed among health center districts. At first, the list of adolescents was obtained from the Guilan University of Medical Sciences (health departments). The number of adolescents was added up cumulatively. Selecting the location of the first cluster was based on a random number table. Then, using a systematic sampling technique, knowing the inter cluster interval, we selected the subsequent clusters. Totally, our sample included 350 girls and 433 boys.
No history of psychiatric hospitalization, no serious organic disease, such as diabetes and having normal intelligence.
Incomplete completion of the questionnaires.
Initial evaluation was done by mental health professionals in Guilan University of Medical Sciences who have bachelor or master's degree in psychology.
- Beck Anxiety Inventory consists of 21 items, most of which closely represent diagnostic and statistical manual of mental disorders-III-R criteria for panic disorders. Clients' rate items according to how much they are bothered by the particular symptom; each item is on a four-point scale ranging from 0 (not at all) to 3 (severely, I could barely stand it). Thirteen items describe physical or physiological symptoms (e.g. Heart pounding), five represent as well as cognitive connotation. Beck (1988) reported internal consistency (Cronbach's alpha = 0.92) and a 1-week retest reliability coefficient of 0.75. The items of the BAI are as follows: (1) Numbness or tingling, (2) feeling hot, (3) wobbliness in legs, (4) unable to relax, (5) fear of the worst happening, (6) dizzy or lightheaded, (7) heart pounding or racing, (8) Unsteady, (9) terrified, (10) nervous, (11) feelings of choking, (12) hands trembling, (13) shaky, (14) Fear of losing control, (15) difficulty breathing, (16) fear of dying, (17) scared, (18) indigestion or discomfort in abdomen, (19) faint, (20) face flushed, and (21) sweating (not due to heat).  There are specific psychometric properties of the BAI that are worth noting. The BAI has demonstrated excellent internal consistency in psychiatric samples (a = 0.92) with adequate 1-week test - retest reliability (r = 0.83) in the original sample.  The BAI has a stronger correlation with measures of anxiety (r = 0.48) than measures of depression (r = 0.25) in the original sample,  although the BAI correlated significantly with measures of both anxiety (r = 0.51-0.69) and depression (r = 0.48-0.56) in a sample of college students. 
- Beck Depression Inventory-II Iranian version is a 21-item Likert self-report questionnaire, measuring the present severity of depression symptoms in clinical and nonclinical adults and adolescents >13 years old. Similar to the BAI, respondents indicate the degree to which they are bithered by each symptom, each symptom being rate on a four-point scale tanging from 0 to 3. The total scores can vary from 0 to 63, with higher scores corresponding to higher levels of depression. 
- The SAS was designed by Zung: The SAS scale is designed similar to a customer service survey questionnaire. It is a 20-items self-report assessment device, which include measures of state and trait anxiety. Answering the statements a person should indicate how much each statement applies to him or her. Each question is scored on a Likert-type scale of 1-4 (based on these replies: "A little of the time," "some of the time," "good part of the time," "most of the time"). Overall assessment is done by total score. The total scores range from 20 to 80. 
- Symptom check list-90-R: The SCL-90-R is a self-report clinical rating scale. Originally it consists of 90 questions answered on a five-point scale, ranging from 0 ("not at all") to 4 ("extremely"). For the purposes of this study the subscales "anxiety" was used as separate measures, with higher scores on each subscale reflecting higher levels of anxiety, depression and psychoticism, respectively. Cronbach's alpha ranged from 0.79 to 0.90. Stability coefficients have been adequate across a range of groups and test-retest interval: r = 0.68-0.80. 
- State-Trait Anxiety Inventory: The STAI is a widely used instrument for assessing state anxiety (A - state, 20 items), and trait anxiety (A trait, 20 items). Responses on the A - state are rated on a four-point scale: 1 (not at all) to 4 (very much so) to indicate the current level of anxiety. The A-trait uses a four-point scale ranging from 1 (almost never) to 4 (almost always) to express general level of anxiety. Ten of the A-state items, and 9 of the A-trait items are reverse-scored. A raw score is obtained for each scale by summing the ratings for each scale and STAI has an acceptancable reliability and validity. 
The factor structure of the BAI is less clear-cut. Steer et al., reported evidence for a four-factor model, while two different two-factor models have also been proposed.  As a preliminary phase of the present study, we examined the cut point, reliability and validity the BAI.
Reliability of the measuring instruments
(1) Cronbach's alpha for each measuring instrument (BAI and SAS, STAI and SCL-90-R was conducted to confirm internal consistency. (2) Test-retest reliability in this study was performed twice between 1 and 2 weeks after first stage.
Validity of the measuring instruments
(1) Exploratory factor analysis was conducted to identify the factor structure. (2) CFA was conducted using structural equation modeling to confirm the exploratory model in the main study. (3) Criterion-related validity was conducted to correlation "BAI" scores and BDI.
Data were analyzed using by SPSS-22 (IBM company) and Amos 18. All statistical tests were two-sided. P = 0.05 was considered as statistically significant. In order to evaluate the internal consistency and item homogeneity, Cranach's alpha coefficient and the mean inter-item correlation coefficient were calculated. The acceptable level of alpha coefficient is >0.70,  and the optimal level of inter-item correlation coefficient is between 0.2 and 0.4. The corrected item total correlation coefficient of all 21 items was also calculated.
| Results|| |
Demographic characteristics are shown in [Table 1].
The sample comprised a total of 783 participants. The age ranged from 15 to 19 years 44.7% (N = 350) were female and 55.3% (N = 433) male. About 24.4% was 15 years, 24.6% was 16 years, 25.8% was 17 years, 13.2% was 18 years, and the last 12% was 19 years.
First, we conducted an independent t-test to examine the gender difference for the total BAI score and also examined the correlation between age and the total BAI score. There is a nonlinear relationship between age and the total score of the BAI, (t = 4.339, df =781) [Table 2].
The means, SD and alpha-coefficients for BAl, BDI-II, SAS, SCL-90-R and STAI are reported in [Table 3] (N = 783). For the BAl the range of scores was 0-57 with a mean of 8.02 (SD = 5.86). The skewness (1.98) and kurtosis (4.91) exceed desired limits. Analyses of internal consistency reliability for the Bal revealed a Cronbach's alpha = 0.88.
|Table 3: Means SD, alpha‑coefficients and intercorrelations between BAI, SAS, SCL‑90‑R, STAI and BDI‑II (n=783)|
Click here to view
The correlations [Table 3] BAI with the SAS (0.44), SCL-90-R (0.40) and with STAI (0.42) were moderate. But the correlation with the BDI-II was 0.216 for divergent validity. This is comparable to results reported in prior studies.
Test-retest reliability was estimated by Pearson r correlation coefficient (0.67, P < 0.01, N = 231) after 1 and 2 weeks after.
Means, SD and alpha-coefficients for the BAI, the BDI-II, SAS, the SCL-anxiety, the STAI are reported in [Table 3]. The Cronbach's alpha (0.88) of the BAI is slightly higher in these samples. On the other hand, the mean (8.1) is substantially higher in this sample, exceeding the SD (6.86). The item-total correlations of the BAI-items range from 0.49 to 0.88. Several of the items (2, 5, 15 and 20) reflecting physiological symptoms and item 16 "fear of dying" have low (0.35) item-total correlation. The distribution of each item is closer to normal in this sample; skewness and kurtosis are substantial for most of the items. Especially, item 15 difficulty breathing display substantial deviations from the normal distribution.
Anxiety levels were determined according to the manual of the BAI indicate, A grand sum between 0 and 21 indicates very low anxiety. A grand sum between 22 and 35 indicates moderate anxiety. A grand sum that exceeds 36 is a potential cause for concern. For Iranian adolescents, a grand sum between 0 and 23 indicates very low anxiety. A grand sum between 24 and 42 indicates moderate anxiety. A grand sum that exceeds 43 is a potential cause for concern [Table 4].
Second, we performed a principal component factor analysis to explore the factor structure of the BAI. The correlation matrix for the 21 items was computed first, and Kaiser-Meyer-Olkin's measure of sampling adequacy (minimum acceptable level >0.50) and Bartlett's test of sphericity were calculated to verify the appropriateness of using factor models. Screen test criteria were used to determine the number of factors to extract [Table 5].
A principal components factor analysis with warimax rotation was chosen because it was consistent with the factor analytic approach used in the development of the BAI and because it was assumed any factors would be inter correlated. We tested four models (subjective, somatic, panic, neurophysiological). The Beck and Steer four-factor model and the Osman et al., second-order four-factor model. The models are presented with factor loadings in ascending order in terms of complexity. Examination of Eigen values and screen plots suggested a three-factor solution for both groups (boys and girls) [Table 6].
|Table 6: Specific item loading comparisons for existing factor models and Iranians from the current sample on the BAI|
Click here to view
The first factor had an Eigen value of 6.36 and explained 30.29% of the variance for adolescents. The content of this factor suggested that items represented somatic symptoms. A second factor had an Eigen value of 4.56 and explained 70% of the variance for Iranian adolescents; this factor had an Eigen value of 1.77 and explained 8.46% of the variance.
In EFA the factor labeled "subjective" in all models tested during conformational analyses. However, in all these analyses item 16 "fear of dying" had its highest loading on this factor as opposed to what was reported in the manual.  Item 16 loading on the subjective factor is congenial with what was originally expected by Beck et al.  Therefore, we chose to allow this item to load on the "Subjective" factor instead of the "panic" factor. This substantially increased goodness-of-fit for the model. The items eight "unsteady", items 12 "hands trembling" and 13 "shaky", items six "Dizzy or light-headed" and 19 "Faint" and items 11 "feelings of choking" and 15 "difficulty breathing", were correlated. All changes had a theoretical rationale and were supported by the Modification Indices. Each of these changes made substantial increases in the goodness-of-fit measures [Table 6].
The CFA was used to confirm the exploratory model. The results provided evidence that the developed instrument achieved sound psychometric properties. The CFA model fit was evaluated using multiple fit indices. The indices elected were the Chi-square statistics (x2 df =547.234), the comparative fit index (CFI) (CFI = 0.91), the standardized root-mean-square (SRMR = 0.05), the root-mean-square error of approximation (RMSEA = 0.04), and the Akaike Information Criteria (AIC = 694). A good model fit is indicated by values of 0.90 or higher for the CFI and GFI. For the SRMR and RMSEA, values of 0.05 or lower indicate a close fit, while values <0.08 indicate an acceptable fit and the one with the lowest AIC is preferred in model comparison.
| Discussion|| |
A researched of the literature about the BAI showed that 66.3% of the articles examined reliability estimates for BAI scores. This figure is consistent with that reported by Willson 1999  and others. ,
This study focuses on investigating the factor structure and internal consistency of the instrument in adolescents. The available and translatable articles that did provide reliability estimates were subjected to a reliability study. The BAI scores showed good to very good internal consistency, with coefficient alpha values. Findings showed that the Persian version of BAI proved a good reliability (r = 0.88, P < 0.001), a very suitable validity (r = 0.59.6, P < 0.001), given that almost 92% of the studies reporting coefficient alphas and almost 75% of the studies calculating test-retest reliability estimates used participants of both genders. The test-retest reliability was satisfactory and readily comparable with those obtained in other studies.  The Iranian version of the BAI displays satisfactory reliability.
The correlations with other self-report scales used to measure the severity of anxiety ranges from low moderate to moderate. The BAI has its highest correlation with the anxiety-subscale of the SCL-90 and a bit lower with the STAI. The results are comparable to those found in other studies , and strengthen the impression that the Iranian version is representative of the original version. A correlation with BDI-II at 0.21, is relatively high given the explicit aim of using the BAl as a tool for separating anxiety from depression.  Even though the correlation with the BDI-II was higher in the teenagers sample than in the community sample, the moderate correlations with the two SCL-90 subscales and ASA provide further support for the divergent validity of the BAl. And Beck and Steer point out, given the high level of correlation generally found between anxiety and depression over the years, a substantial correlation between measures of anxiety and depression should be expected. The high correlation between the Beck anxiety and depression inventories might also be due to elevated levels of general distress or negative affectivity (NA; Watson and Clark, 1994) The BAI discriminates better from depression as measured by the BDl-II than does the other anxiety measures included in this study. ,, The BAI's superiority over the STAI as a divergent measure is supported by this study. The correlation with other anxiety measures is within the same range as the correlation with the depression measures. Due to high level of concurrence of anxiety and depression symptoms, this may not be a problem. However, the emphasis in the BAI on physiological components as 15 of 21 items relate to physiological symptoms, perhaps facilitates better discrimination from depression than do other scales, but may be at the expense of convergent validity. ,,,,,,,,,,,,, The reported studies so far also indicate that the BAI functions best measuring anxiety disorders having strong physiological components, such as panic disorder. ,,
To achieve an acceptable fit as measured by the CFI-index, some changes were made modifying the Beck and Steer model. The theoretically most interesting change was letting item 16 fear of dying regress on the "subjective" factor instead of the "panic" factor. This is consistent with the two-factor Kabacoff et al. This concurs with the fact that this is the only item not reporting physiological symptoms as well. 
Generally, there seems to be the reason to connect this item to a subjective or cognitive factor, instead of the other factors related to physiological items. Due to the difficulties in achieving satisfactory fit on the models examinated, explorative factor analyses were conducted. Results from these analyses slightly favored a four-factor model in the population sample as well as in the Iranian teenagers samples. The results from confirmatory as well as exploratory factor analyses support the validity of the Iranian version of the BAl, as it displays psychometric properties within a reasonable range of what has been obtained on the original version. Thus, the results in this study sustain the validity of the Iranian translation.
| Recommendation|| |
In conclusion, the findings show that the BAI-Iranian has sound psychometric properties and is a reliable instrument for measuring levels of depression among adolescents in Iranian. Therefore, it can be used with confidence in the future.
| Acknowledgments|| |
We specially thank to all the teenagers who participated in this study. We would also like particularly to acknowledge the contribution of coworkers (Psychologists) in Guilan University of Medical Science for helping us with the data collection for this study.
| References|| |
Davison GC, Neale JM, Kring AM. Abnormal Psychology. 9 th
ed. Hoboken, NJ: John Wiley and Sons, Inc.; 2003.
Rapee RM, Kennedy S, Ingram M, Edwards S, Sweeney L. Prevention and early intervention of anxiety disorders in inhibited preschool children. J Consult Clin Psychol 2005;73:488-97.
Barrett PM, Duffy AL, Dadds MR, Rapee RM. Cognitive-behavioral treatment of anxiety disorders in children: Long-term (6-year) follow-up. J Consult Clin Psychol 2001;69:135-41.
Boland RJ, Keller MB. Course and outcome of depression. In Gotlib I, Hammen C, editors. Handbook of Depression. 3 rd
ed. New York: Guilford; 2002. p. 43-60.
Nordhagen T, Pallesen S, Nordhus H. Norwegian Version of the BAl. Unpublished Manuscript. Institute for Clinical Psychology, University of Bergen; 2000.
Keenan K, Hipwell AE. Preadolescent clues to understanding depression in girls. Clin Child Fam Psychol Rev 2005;8:89-105.
Emami H. Epidemiological Studies on Mental Health in Tehran-Iran. UMEÅ UNI VERSI-TY Medical Dissertaion from Department of Clinical Science. Umeå, Sweden: Division of Psychiatry Umeå University; 2008. p. 901-85.
Hossinifard SM, Birashk B, Atef Vahid MK. Epidemiology of mental disorders in high-school students in Rafsanjan. Iran J Psychiatry Clin Psychol 2005;11:71-80.
Mohebi S, Sharifirad GH, Shahsiah M, Botlani S, Matlabi M, Rezaeian M. The effect of assertiveness training on student′s academic anxiety. J Pak Med Assoc 2012;62:S37-41.
Magán I, Sanz J, García-Vera MP. Psychometric properties of a Spanish version of the Beck Anxiety Inventory (BAI) in general population. Span J Psychol 2008;11:626-40.
Kaviani H, Mosavi AS. Psychometric properties of the persion version of Beck Anxiety Inventory. Tehran Univ Med J 2008;65:136-40.
Beck AT, Epstein N, Brown G, Steer RA. An inventory for measuring clinical anxiety: Psychometric properties. Journal of Consulting and Clinical Psychology 1988;56:893-7.
Beck AT, Steer RA, Beck JS. Types of self-reported anxiety in outpatients with DSM-III-R anxiety disorders. Anxiety Stress Coping Int J 1993;6:43-55.
Hewitt PL, Norton GR. The Beck Anxiety Inventory: A psychometric analysis. Psychol Assess 1993;5:408-12.
Contreras S, Fernandez S, Malcarne VL, Ingram RE, Vaccarino VR. Reliability and validity of the beck depression and anxiety inventories in Caucasian Americans and Latinos. Hisp J Behav Sci 2004;26:446-62.
Creamer M, Foran J, Bell R. The beck anxiety inventory in a non-clinical sample. Behav Res Ther 1995;33:477-85.
Kumar G, Steer RA, Beck AT. Factor structure of the Beck Anxiety Inventory with adolescent psychiatric inpatients. Anxiety Stress Coping 1993;6:125-31.
Chapman LK, Williams SR, Mast BT, Woodruff-Borden J. A confirmatory factor analysis of the beck anxiety inventory in African American and European American young adults. J Anxiety Disord 2009;23:387-92.
Morin CM, Landreville P, Colecchi C, McDonald K, Stone J, Ling W. The Beck Anxiety Inventory: Psychometric properties with older adults. J Clin Geropsychology 1999;5:19-29.
Osman A, Hoffman J, Barrios FX, Kopper BA, Breitenstein JL, Hahn SK. Factor structure, reliability, and validity of the Beck Anxiety Inventory in adolescent psychiatric inpatients. J Clin Psychol 2002;58:443-56.
Muntingh AD, van der Feltz-Cornelis CM, van Marwijk HW, Spinhoven P, Penninx BW, van Balkom AJ. Is the Beck Anxiety Inventory a good tool to assess the severity of anxiety? A primary care study in the Netherlands Study of Depression and Anxiety (NESDA). BMC Fam Pract 2011;12:66.
24 . Beck AT, Steer RA, Gabin M. Psychometric properties of the BDI: Twenty-five years of evaluation. Clin Psychol Rev 1988;8:77-100.
Sanford SD, Bush AJ, Stone KC, Lichstein KL, Aguillard N. Psychometric evaluation of the Beck Anxiety Inventory: A sample with sleep-disordered breathing. Behav Sleep Med 2008;6:193-205.
Clara IP, Cox BJ, Enns MW. Confirmatory factor analysis of the depression-anxiety-stress scales in depressed and anxious patients. J Psychopathol Behav Assess 2001;23:61-7.
Lahey BB, Applegate B, Waldman ID, Loft JD, Hankin BL, Rick J. The structure of child and adolescent psychopathology: Generating new hypotheses. J Abnorm Psychol 2004;113:358-85.
Watson D, O′Hara MW, Simms LJ, Kotov R, Chmielewski M, McDade-Montez EA, et al.
Development and validation of the Inventory of Depression and Anxiety Symptoms (IDAS). Psychol Assess 2007;19:253-68.
Kjaergaard M, Arfwedson Wang CE, Waterloo K, Jorde R. A study of the psychometric properties of the beck depression inventory-II, the montgomery and åsberg depression rating scale, and the hospital anxiety and depression scale in a sample from a healthy population. Scand J Psychol 2014;55:83-9.
Aasen H. An empirical investigation of depression symptoms: Norms, psychometric characteristics and factor structure of the beck depression inventory-II. University of Bergen; 2001. Available from: http://www.ub.uib.no/elpub/2001/h/308003/Hovedoppgave.pdf
[Last accessed on 2012 Dec 11].
Ayers CR, Sorrell JT, Thorp SR, Wetherell JL. Evidence-based psychological treatments for late-life anxiety. Psychol Aging 2007;22:8-17.
De Ayala RJ, Vonderharr-Carlson DJ, Kim D. Assessing the reliability of the Beck Anxiety Inventory scores. Educ Psychol Meas 2005;65:742-56.
Jylhä P, Isometsä E. The relationship of neuroticism and extraversion to symptoms of anxiety and depression in the general population. Depress Anxiety 2006;23:281-9.
Gregory RJ. Psychological Testing: History, Principles, and Applications. 5 th
ed. Boston: Pearson Education, Inc.; 2007.
Modabernia MJ, Shodjai Tehrani H, Fallahi M, Faghirpour M. Normalizing SCL-90-R inventory in Gilan high-school students. J Gilan Univ Med Sci 2010;75:58-65.
Steer RA, Ranieri WF, Beck AT, Clark DA. Further evidence for the validity of the Beck Anxiety Inventory with psychiatric outpatients. J Anxiety Disord 1993;7:195-205.
Hair JF, Anderson RE, Tatham RL, Black WC. Multivariate data analysis. 4 th
ed. Saddle River, NJ: Prentice Hall; 2010.
Beck AT, Steer RA. Manualfor the Beck Anxiety Inventory. San Antonio, TX: Psychological Corporation; 1990.
Ayala RJ, Vonderharr-Carolson DJ, Kim D. Assessing the reliability of the Beck Anxiety Inventory scores. J Educ Psychol Meas 2005;65:742-56.
Willson K, de Beurs E, Palmer C, Chambless D. Beck Anxiety Inventory. In Maruish ME, editor. The Use of Psychological Testing for Treatment Planning and Outcomes Assessment. 2 nd
ed. Mahwah, NJ: Lawrence Erlbaum; 1999. p. 971-93.
Vacha-Haase T, Henson RK, Caruso J. Reliability generalization: Moving toward improved understanding and use of score reliability. Educ Psychol Meas 2002;62:562-9.
Ferguson R. Using the Beck Anxiety Inventory in primary care. In: Maruish M, editor. Handbook of Psychological Assessment in Primary Care Settings. 1 st
ed. Mahwah, New Jersey: Lawrence Erlbaum Associates, Inc., Publishers; 2000.
Fydrich T, Dowdall D, Chambless DL. Reliability and validity of the Beck Anxiety Inventory. J Anxiety Disord 1992;6:55-61.
Cox BJ, Cohen E, Direnfeld DM, Swinson RP. Does the Beck Anxiety Inventory measure anything beyond panic attack symptoms. Behav Res Ther 1996;34:949-54.
Cox BJ, Cohen E, Direnfeld DM, Swinson RP. Reply to steer and beck: Panic disorder, generalized anxiety disorder, and quantitative versus qualitative differences in anxiety assessment. Behav Res Ther 1996;34:11-2.
Kabacoff RI, Segal DL, Hersen M, Van-Hasselt VB. Psychometric properties and diagnostic utility of the Beck Anxiety Inventory and the state-trait anxiety inventory with older adult psychiatric outpatients. J Anxiety Disord 1997;11:33-47.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]
|This article has been cited by|
||Mental Consequences and Behavioral Health 18 Month after Outpatient Cardiac Rehabilitation in Three Separated Profiles at Baseline
| ||Mozhgan Saeidi,Hadis Rezaeeyan,Delaram Bagherirad,Mahdieh Saeidi,Mahbobeh Sharyatmadari,Nahid Amani,Saeid Komasi |
| ||Clinical Epidemiology and Global Health. 2019; |
|[Pubmed] | [DOI]|
||Aggregation Partitioning and Study of Demographic, Medical, and Psychological Predictors Related to Derived Clusters in Cardiac Rehabilitation Patients: A Cross-Sectional Study
| ||Mozhgan Saeidi,Kodamorad Momeni,Keivan Kakabraee |
| ||Middle East Journal of Rehabilitation and Health. 2019; 6(2) |
|[Pubmed] | [DOI]|