Depresión ansiedad y síntomas somáticos en atención primaria

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  Psychological Medicine (2012), 42, 15–28. f Cambridge University Press 2011 doi:10.1017/S0033291711000985 O R I G I N A L AR T I C LE The structure of depression, anxiety and somatic symptoms in primary care L. J. Simms1*, J. J. Prisciandaro2, R. F. Krueger3 and D. P. Goldberg4 1 2 University at Buffalo, The State University of New York, Buffalo, New York, USA Medical University of South Carolina, Charleston, SC, USA 3 University of Minnesota – Twin Cities, Minneapolis, MN, USA 4 Institute of P
  The structure of depression, anxiety and somaticsymptoms in primary care L. J. Simms 1 *, J. J. Prisciandaro 2  , R. F. Krueger 3 and D. P. Goldberg 4 1 University at Buffalo, The State University of New York, Buffalo, New York, USA 2  Medical University of South Carolina, Charleston, SC, USA 3 University of Minnesota – Twin Cities, Minneapolis, MN, USA 4 Institute of Psychiatry, King’s College London, UK  Background. Observed co-morbidity among the mood and anxiety disorders has led to the development of increasingly sophisticated dimensional models to represent the common and unique features of these disorders.Patients often present to primary care settings with a complex mixture of anxiety, depression and somatic symptoms.However, relatively little is known about how somatic symptoms fit into existing dimensional models. Method. We examined the structure of 91 anxiety, depression and somatic symptoms in a sample of 5433 primarycare patients drawn from 14 countries. One-, two- and three-factor lower-order models were considered; higher-order and hierarchical variants were studied for the best-fitting lower-order model. Results. A hierarchical, bifactor model with all symptoms loading simultaneously on a general factor, along withone of three specific anxiety, depression and somatic factors, was the best-fitting model. The general factor accountedfor the bulk of symptom variance and was associated with psychosocial dysfunction. Specific depression and somaticsymptom factors accounted for meaningful incremental variance in diagnosis and dysfunction, whereas anxietyvariance was associated primarily with the general factor. Conclusions. The results ( a ) are consistent with previous studies showing the presence and importance of a broadinternalizing or distress factor linking diverse emotional disorders, and ( b ) extend the bounds of internalizing toinclude somatic complaints with non-physical etiologies. Received 24 September 2010; Revised 6 May 2011; Accepted 14 May 2011; First published online 20 June 2011 Key words : Anxiety, bifactor model, depression, diagnosis, somatization. Introduction Substantial co-morbidity among the mood and anxietydisorders (e.g. Kessler et al . 2005) has led to questionsabout how these disorders should be organized andhas resulted in a push for new conceptual models.In particular, a series of increasingly sophisticateddimensional models has generated much interestand support in recent years (e.g. Krueger & Finger,2001; Krueger et al . 2003; Kupfer, 2005; Watson,2005; Helzer et al . 2006; Simms et al . 2008), largely be-cause they provide a compelling basis for describingthe common and distinct components of anxiousand depressive symptomatology in addition to thefull breadth of features observed clinically in psy-chiatric and primary care settings. However, de-spite mounting evidence supporting dimensionalconceptualizations, the fields of psychology and psy-chiatry have not yet reached a consensus on whetherand how to implement such models in the next re-vision of the Diagnostic and Statistical Manual of MentalDisorders (i.e. DSM-5) and the International Classifi-cation of Diseases (i.e. ICD-11).Moreover, work remainson understanding the optimal dimensional modelof emotional symptoms, including how and whethersomatization symptoms relate to such dimensionalmodels (e.g. Dimsdale et al . 2009; Goldberg et al . 2010). Dimensional models of internalizing symptoms Clark & Watson’s (1991) tripartite model proposedthat ( a ) anxiety and depression share a non-specificcomponent, negative affectivity (NA), that contributesto the co-morbidity between these disorder types,( b ) depression is characterized specifically byanhedonia, and ( c ) anxiety and fear are marked by aspecific component of anxious/somatic arousal. Thismodel generated much support (e.g. Phillips et al . *Address for correspondence: Dr L. J. Simms, Department of Psychology, Park Hall 218, University at Buffalo, The State Universityof New York, Buffalo, NY 14221, USA.(Email: Psychological Medicine (2012), 42 , 15–28. f Cambridge University Press 2011doi:10.1017/S0033291711000985 ORIGINAL ARTICLE  2002; Lambert et al . 2004; Watson et al . 1995 a , b ) butlater was deemed too limited to describe the full breadth of symptoms relevant to emotional disorders.As a result, more detailed models have been offered(e.g. Zinbarg & Barlow, 1996; Brown et al . 1998;Mineka et al . 1998; Krueger & Finger, 2001; Simms et al . 2008). For example, Simms et al . (2008) reportedevidence for a symptom-based model that ( a ) repli-cated the general NA component and ( b ) supporteda differentiated lower-order structure of mood andanxiety symptoms.Disorder-based models (i.e. models of disordercovariances rather than symptom covariances) havealso supported a dimensional reconceptualizationof the mood and anxiety disorders. For example, basedonlatenttraitanalysesonasampleoftreatment-seeking individuals, Krueger & Finger (2001) pro-posed an internalizing spectrum model of anxietyand depressive disorders in which disorders weremodeled as reflecting varying levels of severityalong the same internalizing dimension. McGlinchey& Zimmerman (2007) replicated these results in alarger sample of out-patients and showed that inter-nalizing is associated with several indicators of dys-function and social burden. Other disorder-basedstudies have not only replicated the presence of an overarching internalizing factor but also identifiedNA as the core of the internalizing spectrum (e.g.Hettema et al . 2006; Griffith et al . 2010). Unfortunately,disorder-based structural analyses can be problem-atic because of the low base rates associated withsome disorders, heterogeneity within disorders, andchanges in diagnostic criteria across different DSMversions (Watson, 2005). Symptom-based analysesameliorate many of these problems because they donot rely on rationally derived criterion sets or poly-thetic scoring rules.Although not identical, both symptom- anddisorder-based dimensional models share severalimportant features. First, most include non-specificfactors (e.g. NA) that have been shown to play a sig-nificant role in the mood and anxiety disorders.Second, most models include specific componentsthat are offered to more finely differentiate symptomphenotypes (e.g. post-traumatic intrusions, panic,depression) that share NA as a common factor. Third,the models generally include a higher-order or hier-archical structure characterized by a general factorthat subsumes multiple specific symptom factors.Higher-order factor models imply that the varianceshared by specific factors (e.g. anxiety and depression)can be accounted for parsimoniously by an over-arching dimension of severity (e.g. Krueger & Finger,2001; Krueger et al . 2003). Hierarchical modelsdescribe symptoms as loading simultaneously on ageneral factor along with one or more specific factors(e.g. Simms et al . 2008).Based on these symptom- and disorder-based find-ings, some have argued for an empirically basedclassification system that accounts for the knownpatterns of disorder/symptom covariation (e.g.Watson, 2005; Goldberg et al . 2009). Goldberg et al .(2009) argued that anxiety and mood disordersdefined primarily by NA [such as major depressivedisorder (MDD), generalized anxiety disorder (GAD),phobias, post-traumatic stress disorder (PTSD),obsessive–compulsive disorder (OCD) and panic dis-order] should be reclassified as falling into a single‘emotional disorders’ cluster in DSM-5 and ICD-11.Similarly, Watson (2005) argued for an overarchingcategory of emotional disorders and also three sub-classes: ( a ) distress disorders, ( b ) fear disorders, and( c ) bipolar mood disorders. Symptomatology in primary care settings The majority of individuals with mental disordersare seen by general practitioners, family physicians,and physicians in general hospitals (Regier et al . 1978,1993; Goldberg & Goodyer, 2005). In such settings,patients often present with combinations of anxious,depressive and somatic symptoms, in addition tophysical health problems, and as a result they fre-quently satisfy the criteria for multiple diagnoses(U¨stu¨n & Sartorius, 1995). Somatic symptoms, bothphysical and psychological in srcin, are commonlythe reason for presentation to physicians in generalmedical settings (e.g. Kroenke, 2003). Because of this,Mayou et al . (2005) suggested that future versions of the diagnostic nosology adopt etiological neutralityabout those somatic symptoms that are not clearlyassociated with a general medical condition, and ar-gued for the abolition of the somatoform disorderscategory, with reassignment of specific somatoformsymptoms to other parts of the classification system,such that somatic symptoms with depression areclassified with depression and those associated withanxiety are classified with anxiety. However, rela-tively little is known about how somatic symptomsrelate to existing dimensional models of the mood andanxiety disorders. Thus, before implementing such amajor change, more work is needed to better under-stand how somatic symptoms behave psychom-etrically in the context of the emotional disorders. Current study Thus, although consensus is emerging on the basictenets of the dimensional structure of commonemotional disorders, less consensus exists on the exact16 L. J. Simms et al.  form of the higher-order/hierarchical structure of such disorders. Moreover, much less is known abouthow somatic symptoms fit within a comprehensivedimensional structure of emotional disorders. Canvariance in somatic symptoms be completely ac-counted for by the same overarching general factorcommon to the mood and anxiety disorders? Or aresomatic symptoms statistically independent of moodand anxiety symptoms? To answer these questionsand extend the structural literature, we examinedseveral viable lower- and higher-order structuralmodels of mood, anxiety and somatic symptoms in alarge, multi-national sample of primary care patients.Krueger et al . (2003) conducted disorder-based analy-ses using the same data set and found a structuresimilar to that reported in previous epidemiologicalstudies (i.e. internalizing spectra). The present studyextends previous work by Krueger and colleagues andothers by ( a ) modeling symptom data directly, ( b )studying the location of somatic symptoms in relationto other emotional symptoms, ( c ) examining thesestructural questions in primary care patients fromaround the world, and ( d ) including a range of viablelower- and higher-order models. Method Sample and measures The present study used data from the World HealthOrganization’s Collaborative Study of PsychologicalProblems in General Health Care (WHO/PPGHC;U¨stu¨n & Sartorius, 1995), consisting of 5438 patientsinterviewed with the Primary Care Version of theComposite International Diagnostic Interview(CIDI-PC; Sartorius et al . 1993) from 15 general healthcare clinics in 14 countries. 1 # Compared to the usualversion of the CIDI, the CIDI-PC used in the presentstudy coded whether symptoms were currently pres-ent and was adapted to minimize skip-outs (i.e. mostsymptoms were asked of all participants), which isideal for structural analyses and uncommon in stan-dard interviews. Other ratings included the mainreason for contact, chronic diseases and alcohol use;psychotic symptoms were excluded. Participants wereselected from 25916 consecutive patients by a strati-fied sampling procedure in each center using theGeneral Health Questionnaire (GHQ-12; Goldberg &Williams, 1988), in which all respondents in thetop 20% of scores for that center, 35% of those in thenext 20%, and 10% of the remaining scores wereselected for clinical interview with the CIDI-PC. Thus,the sample was weighted toward patients presentingwith current mental health concerns and related dys-function. This particular within-center stratificationscheme was adopted to account for variations in howreadily patients admit to psychological symptomsacross centers. The 14 centers included Ankara,Turkey ( n = 400); Athens, Greece ( n = 196); Bangalore,India ( n = 398); Berlin and Mainz, Germany ( n = 800);Groningen, The Netherlands ( n = 340); Ibadan,Nigeria ( n = 269); Paris, France ( n = 405); Manchester,UK ( n = 428); Nagasaki, Japan ( n = 336); Riode Janeiro, Brazil ( n = 393); Santiago, Chile ( n = 274);Shanghai, China ( n = 576); Seattle, USA ( n = 373); andVerona, Italy ( n = 250).Item-level psychiatric symptom data were usedfor the present study’s latent structure analyses. AllCIDI-PC symptoms related to depression, anxiety orsomatic problems were included, except for two itemswith extremely low base rates (‘amnesia’ and ‘suicideattempt’). In total, 38 somatization, 25 anxiety and 28depression symptom items were included. Symptomsthat were clearly due to medical illness, or that werenot currently present, were not counted as present inour analyses. 2 DSM-III-R (APA, 1987) diagnostic vari-ables generated using the CIDI diagnostic algorithmswere used as outcome variables in subsequent re-gression analyses; diagnoses representing current(as opposed to lifetime) psychopathology were usedwherever possible. Disability was assessed usingthe Social Disability Schedule (SDS; Wiersma et al .1988) and the Brief Disability Questionnaire (BDQ;VonKorff  et al . 1996). Scores from the SDS (i.e.interviewer-rated disability in the occupationalrole) and the BDQ (i.e. total score and number of disability days in the past month) were used asoutcome variables in regression analyses. Evidencesupporting the reliability and validity of thesemeasures has been presented in reports of the WHO/PPGHC (Ormel et al . 1994). Structural modeling and statistical analyses We adopted a two-stage procedure to evaluate severalcompeting latent variable models of the latent struc-ture of psychiatric symptoms. First, we evaluatedthe fit of three lower-order factor models: model 1,a one-factor model in which all mood, anxiety andsomatic symptoms were subsumed under a single in-ternalizing factor; model 2, a two-factor model com-posed of correlated somatic and anxiety–depressionfactors; and model 3, a three-factor model in whichsomatic, anxious anddepressive symptoms are loadedon three correlated factors. These lower-order modelsprovided a basis for understanding how many factorsunderlie the symptoms, but they did not provide anopportunity to study the higher-order or hierarchical # The notes appear after the main text. Structure of depression, anxiety and somatic symptoms 17  structure of the domain. Thus, second, we studiedtwo variations on the best-fitting lower-order model:model 3h, a higher-order model in which the threefactors from model 3 were subsumed under a generalinternalizing factor; and model 3b, a hierarchical(bifactor) model in which all symptoms were modeledas loading on a general internalizing factor alongwith one of three specific (i.e. residual) factors corre-sponding to depression, anxiety and somatic symp-toms respectively (e.g. Gibbons et al . 2007; Reise et al .2007; Simms et al . 2008). Graphical representations of all estimated models are presented in Fig. 1.CIDI items were assigned to symptom factors basedon the diagnostic category from which they weredrawn (i.e. anxiety CIDI items were assigned to theanxiety factor, etc.). Notably, this strategy resulted inseveral similar items loading on multiple factors (e.g.similarly worded items reflecting a ‘lump in throat’are included in the CIDI for both anxiety and soma-tization disorder). Piccinelli et al . (1999), who used thesame data set for a different grade-of-membershipanalysis of the symptoms, dealt with this potentialstructural confound by removing all similar itemsfrom their analyses. However, doing so necessarilychanged the underlying constructs and their inter-relationships by artificially removing the overlap thatis embodied inthe DSM. Thus, inthe present studyweused all items within each diagnostic category to Internalizing All depression, anxiety, &somatic symptoms Model 1 DepressionAnxiety Depression & anxietysymptoms Somatization Somatic symptoms Model 2 Depression Depression symptoms Anxiety Anxiety symptoms Somatization Somatic symptoms Model 3 Depression Depression symptoms Anxiety Anxiety symptoms Somatization Somatic symptoms Internalizing Model 3h: Higher-order Depression Depression symptomsAnxiety symptomsSomatic symptoms InternalizingAnxietySomatization Model 3b: Bifactor Fig. 1. Summary of  a priori structural models. Dotted rectangles represent collections of symptoms. Error terms on symptomsand intermediate factors are omitted for clarity. 18 L. J. Simms et al.
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