Separation anxiety in adulthood: dimensional or categorical?

Comprehensive Psychiatry 48 (2007) 546 – 553 www.elsevier.com/locate/comppsych

Separation anxiety in adulthood: dimensional or categorical? Derrick Silove a,b,⁎, Tim Slade c,d , Claire Marnane c,e , Renate Wagner c,e , Robert Brooks a,b , Vijaya Manicavasagar f a

Psychiatry Research and Teaching Unit, School of Psychiatry, University of New South Wales, Randwick NSW, 2031, Australia b Centre for Population Mental Health Research, Sydney South West Area Health Service, Liverpool NSW, 2170, Australia c School of Psychiatry, University of New South Wales, Randwick NSW, 2031, Australia d Clinical Research Unit for Anxiety and Depression at St Vincent's Hospital, Darlinghurst NSW, 2010, Australia e Clinic for Anxiety and Traumatic Stress, Bankstown Hospital, Bankstown NSW, 2200, Australia f The Black Dog Institute, Randwick NSW, 2031, Australia

Abstract Recent evidence suggests that a clinical form of separation anxiety can be observed in adults. An important question of relevance to defining the construct of adult separation anxiety is whether there is discontinuity between that constellation and other forms of anxiety. In the present study, 2 taxometric procedures—Mean Above Minus Below a Cut and Maximum Eigenvalue—were used to assess whether adult separation anxiety conformed primarily to a categorical or a dimensional pattern. The data were derived from a separation anxiety symptom questionnaire completed by 840 consecutive adult patients attending an anxiety disorders clinic. Although some results of the analysis were ambiguous, the overall findings suggested a dimensional pattern. The relevance of the finding to the status of adult separation anxiety is discussed. © 2007 Elsevier Inc. All rights reserved.

1. Introduction Extensive research has been devoted to the study of juvenile-onset separation anxiety disorder (JSAD) [1,2], a common disorder in the community [3,4] and the most prevalent diagnosis presenting to childhood anxiety clinics [5]. The developmental trajectory of JSAD however remains unclear [6-8], with some investigations suggesting that it creates risk specifically to panic disorder in adulthood [9], whereas more recent studies have indicated that JSAD may be a generic risk factor to a range of adult anxiety subcategories [10]. A third possibility, suggested by Manicavasagar and Silove [11], is that JSAD may persist, manifesting as an adult form of the disorder (the continuity hypothesis). That trajectory would be analogous to that of other early-onset anxiety disorders, such as social phobia, that commonly extend from adolescence into adulthood. The Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, ⁎ Corresponding author. Psychiatry Research and Teaching Unit, Level 1 Mental Health Centre, Liverpool Hospital, Liverpool NSW 2170, Australia. Tel.: +61 2 9616 4311; fax: +61 2 9602 5917. E-mail address: [email protected] (D. Silove). 0010-440X/$ – see front matter © 2007 Elsevier Inc. All rights reserved. doi:10.1016/j.comppsych.2007.05.011

Text Revision (DSM-IV-TR) [12], although classifying JSAD as a disorder of childhood and stipulating onset before 18 years of age, allows for the disorder to continue into later life. Nevertheless, until recently [13], the custom has been to exclude the putative subcategory of adult separation anxiety disorder (ASAD) from consideration in both epidemiologic [14,15] and clinical [16] studies focusing on the adult subtypes of anxiety. Yet there is growing evidence suggesting that separation anxiety can occur in later life in a form that seems equivalent to JSAD, although symptoms are modified somewhat by development [17]. The primary anxiety associated with ASAD is the fear of actual or possible separation from close attachment figures and a consequent preoccupation with the safety and whereabouts of those persons. Anxieties extend beyond parents to include intimate partners and children [11,17]. Whereas the criteria for JSAD highlight somatic symptoms such as nausea and stomachaches [12], such physical complaints seem to be less prominent in adults who instead exhibit more cognitive and emotional symptoms [11]. Moreover, adulthood presents different opportunities for those with separation anxiety to deal with their fears, for example, by making frequent phone calls, by adhering to rigid routines that ensure frequent contact with attachment

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figures, or by talking excessively as a means of lengthening contact time with key others [17]. An important question, nevertheless, is whether the proposed novel category of ASAD should be accorded a separate status equivalent to established subtypes of anxiety such as panic disorder and social phobia. Several factors determine the addition of disorders to the classification system, including inter alia, the consistent clustering of symptoms, a discriminating risk factor profile, family aggregation, a distinct period of onset, a predictable course and outcome, and a demonstrated response to specific interventions [18,19]. If the putative disorder is clearly demarcated from related symptom patterns by conforming to a categorical construct, that observation may add to other evidence supporting the distinctiveness of the syndrome (although the converse is not the case, that is, a dimensional pattern does not on its own preclude recognition of a disorder as warranting a separate status in the diagnostic system). The present study aims to examine whether symptoms of adult separation anxiety conform to a categorical or dimensional pattern. The present study builds on existing research undertaken by our group [17,20-22] that has sought to examine the phenomenology, developmental trajectory, and familial clustering of adult separation anxiety. In pursuing these investigations [8,11,17], we have established 2 methods for assessing the putative category of ASAD: a structured interview [17] and a self-report questionnaire [23], each containing the same items. Items were derived from modified JSAD criteria and from clinical observations of patients thought to have the adult disorder. The structured interview allows trained clinicians to make a global clinical judgment about the presence or absence of ASAD, with past studies yielding high levels of interrater reliability [17,22]. The Adult Separation Anxiety Self-Report Questionnaire (ASA-27), previously called the Adult Separation Anxiety Self-Report Checklist [21], is rated directly by respondents on a 4-point symptom frequency scale. Receiver operation characteristic analysis has shown a close concordance between the structured interview and the checklist [23]. Demonstrating continuities between a recognized childhood disorder (JSAD) and a putative adult form (ASAD) offers support for the nosologic status of the latter. In a community sample, Manicavasagar et al [17] found that most persons with ASAD reported high levels of separation anxiety in their early years. A subsequent study undertaken at an anxiety clinic (N = 70) [21] confirmed this developmental association, with those classified as having ASAD reporting differentially high levels of early separation anxiety compared with other anxiety patients. A third, community-based study of adults with histories of school anxiety [8] showed a close association between ASAD and past JSAD. Those reporting past JSAD had an 8-fold risk of being assigned a current diagnosis of ASAD. Since psychiatric disorders often cluster within families, demonstrating a pattern of aggregation adds indirect evidence in support of the status of a disorder. A study undertaken at a

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juvenile anxiety clinic [22] found that parents of children with JSAD had an 11-fold increased risk of ASAD but no higher rate of other anxiety disorders when compared with parents of children with other juvenile anxiety disorders. The results suggest a high level of specificity in the family clustering of adult and juvenile separation anxiety. As yet, however, no studies have assessed whether adult separation anxiety conforms to a categorical or dimensional pattern, that is, whether there is a “point of rarity” demarcating that pattern from other forms of anxiety. The present study aimed to examine this issue by applying taxometric analyses to a large data set obtained from an anxiety clinic. Taxometric techniques were formulated by Meehl and colleagues [24-26] to determine the latent structure of a particular phenomenon. Specifically, the analysis applied herein aimed to assess whether the latent structure of ASAD is best represented as an extreme point on a continuum of separation anxiety (ie, a continuous/ dimensional structure) or whether the symptom pattern clearly polarized respondents into 2 groups, hence indicating a taxonic structure. 2. Methods 2.1. Participants Participants comprised 840 consecutive patients attending a public outpatient anxiety disorders clinic covering a defined catchment area in Sydney, Australia. Services are provided free of charge, and there are no other specialist clinics for anxiety in the geographical area. Previous studies [27] undertaken at the clinic have shown that the diagnostic and demographic profile of attending patients are typical of those documented in similar anxiety clinics worldwide [28]. The South Western Sydney Area Health Service Ethics Committee provided ethics approval for the study, and respondents completed signed consent forms. 2.2. Measures Participants completed the ASA-27 [23]. The instrument contains 27 questions assessing separation anxiety symptoms occurring after the age of 18 years. Each item is rated on a 4point frequency scale: “This happens very often,” “This happens often,” “This happens occasionally,” and “This has never happened.” Items are assigned ratings of 3, 2, 1 and 0, respectively, yielding total scores ranging from 0 to 81. Questionnaire items have shown high levels of internal consistency (Cronbach α = .89) and test-retest reliability (r = .86, P b .001) [17]. In a comparison with the structured interview, receiver operation characteristic analysis yielded a high area under the curve coefficient (0.9), indicating a close correspondence for the construct measured by the 2 instruments [23]. Another team has since validated a separate measure against the ASA-27, reporting a correlation coefficient of 0.84 [29].

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2.3. Statistical analysis Taxometric techniques developed by Meehl and Yonce [24,30] were applied to the data. The output from the taxometric analyses is in the form of several graphs, the shapes of which indicate whether the structure of the underlying construct represents discontinuity (ie, suggests the identification of a taxon) or is dimensional. Two taxometric techniques were used in accordance with contemporary recommendations [31]: Mean Above Minus Below a Cut (MAMBAC) [30] and Maximum Eigenvalue (MAXEIG) [26]. The MAMBAC procedure calculates the difference in mean scores of one indicator above and below all possible cutoff points on a second indicator. These individual values are then plotted on a graph. Dish-shaped or monotonically rising graphs indicate a latent dimension, whereas peaked graphs indicate a latent taxon. For the MAXEIG procedure, the eigenvalues of the first factor derived from a factor analysis of 2 or more indicators are plotted in subsamples defined by scores on another indicator. The MAXEIG graphs that are indicative of a dimensional latent structure remain relatively flat or, in the case of skewed indicators, rise toward one extreme. A taxonic latent structure produces noticeably peaked MAXEIG graphs. Comparing the mean base rate

estimates derived from taxometric analyses to a base rate suggested either by the extant literature or clinical experience presents another source of data from which to derive conclusions about the likely latent structure. If the mean base rate contains little variation and is close to the proposed base rate, then this suggests evidence for taxonicity. If the mean base rate is highly variable and/or deviates markedly from the proposed base rate, then this is suggestive of dimensionality. One of the important features of the taxometric methodology is the use of multiple, semi-independent statistical procedures. Confidence in the underlying structure is achieved through consistent findings across these multiple taxometric analyses. Another innovation of a recent program designed to carry out taxometric analysis is the generation and analysis of simulated data sets that mirror all the properties of the research data but differ in their underlying structure [32]. If the research data are closer in structure to the simulated dimensional data, then greater confidence is placed on a dimensional solution. If, on the other hand, the research data are closer to the simulated taxonic data, then a taxon is supported. It has recently been shown that these sample-specific simulations do not perform optimally when the base rate of the construct is low (ie, b10%) [33]. However, as described below, the base rate for the current study is 15% and therefore is safe from interpretational

Table 1 Specification of ASA-27 questionnaire items and the indicator set to which they belong Theoretically derived indicator set (n = 8 indicators) 1. More secure at home when with people who are close 2. Difficulty staying away from home for several hours 3. Carrying around something that gives security or comfort 4. Extreme stress before leaving home to go on a trip 5. Nightmares or dreams about being separated from someone close 6. Extreme stress before leaving someone close to go on a trip 7. Upset when usual daily routines are disrupted 8. Worrying about the intensity of relationships with people close 9. Headaches, stomachaches, or nausea before leaving for work 10. Talk a lot to keep people close 11. Concerned about where people close to you are going 12. Difficulty in sleeping alone at night 13. Better able to go to sleep if hearing the voices of people close to you 14. Very distressed when thinking about being away from people close to you 15. Nightmares or dreams about being away from home 16. Worrying about people close to you coming to serious harm 17. Upset about changes to routine that interfere with contact with people close to you 18. Worrying a lot about people close to you leaving 19. Sleep better if the lights are on in the house or bedroom 20. Tried to avoid being at home alone 21. Sudden bouts of anxiety when thinking about being separated from those close to you 22. Get anxious if not speaking to people close to you on the telephone regularly 23. Would not be able to cope or go on if someone you cared about left you 24. Sudden bouts of anxiety when separated from people close to you 25. Worrying a lot about possible events that may cause separation from attachment figures 26. People said that you talk a lot 27. Worrying that relationships are so close that they cause problems

Empirically derived indicator set (n = 6 indicators)

Factor analysis–derived indicator set (n = 8 indicators)

4

2 1 2 3 8

5 4

7 4

5 8 1 6 6 1 7 2 1

5 3 3

6 2

5 8 1 3

1 6 2 1 4

4 5 6 6 7 1 5 3 7 6 6 7 7 7 7 7 4 8

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difficulties brought about by examination of low base rate constructs. A relative fit statistic can also be calculated that is represented as a positive value when the research data are closer to the simulated dimensional data and as negative values when the research data are closer to the simulated taxonic data. Hence, traditional MAXEIG and MAMBAC graphs and the calculation of mean base rate estimates, along with the analysis of simulated data sets, provide a comprehensive suite of interpretative tools for the determination of latent structure. The MAMBAC and MAXEIG analyses of the research data, the simulated taxonic data, and the simulated dimensional data along with estimation of base rates were all generated using programs developed by Ruscio [31]. 2.4. Selection and construction of indicator sets In accordance with contemporary guidelines for conducting taxometric analysis [34], 3 sets of indicators were constructed using different combinations of items from the ASA-27. The first set of indicators was theoretically derived, being based on the structure of DSM-IV diagnostic criteria for JSAD. Because formal diagnostic criteria for a putative category of ASAD currently do not exist and there is the foregoing evidence that the juvenile form extends into adulthood, the 8 diagnostic criteria for JSAD were matched to relevant items in the ASA-27 (see Table 1 for specification of items and the indicator sets to which they belong). Indicator validity, as measured by the separation in standard deviation units between the taxon and complement groups, ranged from 1.41 to 2.47, with all indicator validities being above the recommended cutoff score of 1.25 [25]. Two empirically based approaches were applied to construct the second and third sets of indicators. The second indicator set identified items that correlated most highly with the total ASA-27 questionnaire score, assuming that those items would be the most discriminating. The 12 items with the greatest correlations were selected and then paired according to the largest correlations between items within a pair, yielding a set of 6 indicators (see Table 1 for item specification). Indicator validities for this second set of indicators ranged from 1.95 to 2.28, again all above the recommended cutoff of 1.25. The third set of indicators was based on the results of an exploratory factor analysis of all ASAD items. A principalcomponents analysis indicated that between 5 and 11 factors accounted for the structure of the item pool. The large sample size and number of factors examined made χ2 analysis an unreliable measure of fit for this model [35]. Instead, confirmatory factor analysis was applied that supported an 8-factor model (see Table 1 for item specification) with a single second-order factor producing a root mean squared error of approximation of .047 [35]. Indicator validities for this third set of indicators ranged from 1.31 to 2.25, once again all above the recommended cutoff of 1.25.

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3. Results The average age of the sample was 37 years (SD = 12.9). Most subjects were female (70%, n = 629) and born in Australia (73%, n = 658), and approximately half were employed (51%, n = 463). Almost half were cohabiting with an intimate partner (49%, n = 442), with 36% being single (n = 320), 12% divorced or separated (n = 112), and 3% widowed (n = 27). Psychologists assigned the following DSM-IV adult subcategories for anxiety (excluding ASAD): 229 (26%) panic disorder with agoraphobia; 178 (20%) generalized anxiety disorder; 159 (18%) panic disorder; 118 (13%) social phobia; and 28 (3%) each for posttraumatic stress disorder, obsessive compulsive disorder, and specific phobia. The remaining 14% comprised a broad range of assignments including subthreshold anxiety disorders, mood disorders, and anxiety disorder not otherwise specified. In addition to these conventional diagnoses, a clinical diagnosis of ASAD was made where 2 psychologists (one of whom was the director of the clinic) concurred about its presence. The overall prevalence estimate for ASAD at the clinic was 15%, the figure used in the taxometric analysis. 3.1. MAXEIG analyses The MAXEIG analyses were carried out on all 3 sets of indicators. The 3 panels in Fig. 1 show the average MAXEIG graphs using each of the 3 sets of indicators for the research data (left graphs), the simulated taxonic data (middle graphs), and the simulated categorical data (right graphs) (individual MAXEIG and MAMBAC graphs are available upon request). Average graphs for the theoretically derived and the empirically paired indicator sets all showed clear concordance in structure between the research data and the simulated dimensional data. Average graphs for the factor analysis–derived indicator set demonstrated less clear, yet still evident, concordance between the research data and the simulated dimensional data. The relative fit statistics were +3.76 for the theoretically derived indicator set, +4.81 for the empirically paired indicator set, and +0.92 for the factor-analyzed indicator set. The fit statistics for the empirically derived and theoretically derived indicator sets were strongly positive, supporting the concordance between the research data and the simulated dimensional data. The fit statistic for the factor-analyzed indicator set was more ambiguous, precluding a definitive conclusion being drawn about whether a dimensional or taxonic structure was preferred. The overall results, however, favored a dimensional latent structure. A dimensional latent structure was further supported by the highly variable mean (and SD) estimates of the base rate (theoretically derived, 0.33 [0.23]; empirically derived, 0.28 [0.12]; and factor analysis derived, 0.21 [0.11]). The base rates produced by the analysis diverged substantially from the actual base rate of 15%, adding further evidence in favor of a dimensional latent structure.

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Fig. 1. Average MAXEIG graphs for research data, simulated taxonic data, and simulated dimensional data from theoretically derived indicators (top panel), empirically paired indicators (middle panel), and factor-analyzed indicators (bottom panel).

3.2. MAMBAC analyses The MAMBAC analyses were carried out on all 3 sets of indicators. Average MAMBAC graphs for the research data, the simulated taxonic data, and the simulated dimensional data are shown in Fig. 2. As with the MAXEIG analyses, MAMBAC analyses based on the theoretically derived indicator set showed clear evidence of a dimensional structure, with the research data more closely resembling the simulated dimensional rather than the simulated taxonic model. The graphs from the empirically derived indicator set demonstrate a right-hand cusp at the very end of the distribution. This provides some evidence suggesting a categorical latent structure. Although the graphs from the

factor analysis–derived indicator set are more ambiguous, the research data showed greater similarity to the simulated dimensional data than the simulated taxonic data. The relative fit statistics were +11.05 for the theoretically derived indicator set, +7.48 for the empirically paired indicator set, and +6.63 for the factor-analyzed indicator set. As with the MAXEIG analysis, all the fit statistics were highly positive, thus providing additional support for the concordance between the research data and the simulated dimensional data. A dimensional latent structure was also suggested by the results of mean base rate estimation (theoretically derived, 0.44 [0.09]; empirically derived, 0.42 [0.04]; and factor analysis derived, 0.37 [0.06]). Although these mean base

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Fig. 2. Average MAMBAC graphs for research data, simulated taxonic data, and simulated dimensional data from theoretically derived indicators (top panel), empirically paired indicators (middle panel), and factor-analyzed indicators (bottom panel).

rates are less variable than those derived from the MAXEIG analysis, they are still highly divergent in relation to the proposed base rate of 15%.

4. Discussion The present study sought to investigate the putative construct of ASAD further by using taxometric analysis. Although some of the graphs from the MAXEIG and MAMBAC analyses were ambiguous with regard to latent structure, on balance, the results suggested that adult separation anxiety is best represented as dimensional rather than a categorical construct.

This finding is consistent with taxometric analyses undertaken on a range of psychiatric disorders that consistently reveal dimensional patterns to the underlying constructs. These include depression [36,37], obsessivecompulsive disorder [38], posttraumatic stress disorder [39], and pathological worry associated with generalized anxiety disorder [40]. Together with past research, the present findings support the view that the various forms of anxiety may be best conceptualized as interrelated dimensions [41]. Yet the categorical (present-absent) approach remains an entrenched tradition in psychiatric classification because it simplifies and facilitates clinical practice as well as the representation of prevalence estimates in epidemiologic studies [42,43]. Recognizing the true underlying dimen-

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sional structure of a disorder nevertheless may help guide a more nuanced study of several aspects of the phenomenon, for example, in trying to identify its etiology and its responsiveness to treatment [44]. For example, where a construct is dimensional, it may be more meaningful to measure improvement after treatment using continuous measures. Symptoms of ASAD may diminish with treatment but they may not disappear altogether. This treatment outcome might be obscured if a categorical approach is applied [45]. Similarly, in large-scale community studies, instruments producing a broad range of scores ranking people on severity may provide a more fine-grained representation of the phenomenon than would a present/ absent diagnostic approach [40]. The strengths of the study are the large sample size, the use of a psychometrically tested measure of adult separation anxiety, and the application of multiple taxonic indicators. In particular, a range of theoretically and empirically derived criteria was used, offering ample opportunity for one or more sets of criteria to emerge as a taxon if a categorical structure existed. Nevertheless, it needs to be conceded that the 3 indicator sets were derived from the same questionnaire so that they represent overlapping conceptualizations of ASAD. A stricter test of the latent structure of ASAD may be achieved through analysis of entirely independent sets of indicators derived from related yet distinct measures. Another limitation relates to the nature of the sample. All participants had high levels of anxiety, a factor that might have reduced the potential to distinguish a category of ASAD. As such, the test applied might be regarded as conservative when compared with applying a taxometric analysis to a general population study or a more heterogeneous clinical population not constituted entirely of anxiety patients. 5. Conclusions This study indicates that although there were ambiguities in a minority of the results, the predominant findings suggest that separation anxiety in adulthood may be best represented as a continuously distributed construct. The findings are consistent with those emerging from taxometric analyses of most other adult anxiety subcategories [38,39]. The results therefore suggest that the symptom pattern alone may not be sufficient to make a diagnosis of ASAD, but that other criteria such as onset, course, family history, salience of separation anxiety compared with other symptoms, and associated disability should all be taken into account in reaching a final diagnosis. References [1] Gittelman R, Klein DF. Relationship between separation anxiety and panic and agoraphobic disorders. Psychopathology 1984;17(Suppl 1): 56-65.

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