Utility of the Mild Brain Injury Atypical Symptoms Scale to detect symptom exaggeration : an analogue simulation study

Brief self-report symptom checklists are often used to screen for postconcussional disorder (PCD) and posttraumatic stress disorder (PTSD) and are highly susceptible to symptom exaggeration. This study examined the utility of the five-item Mild Brain Injury Atypical Symptoms Scale (mBIAS) designed for use with the Neurobehavioral Symptom Inventory (NSI) and the PTSD Checklist–Civilian (PCL–C). Participants were 85 Australian undergraduate students who completed a battery of self-report measures under one of three experimental conditions: control (i.e., honest responding, n = 24), feign PCD (n = 29), and feign PTSD (n = 32). Measures were the mBIAS, NSI, PCL–C, Minnesota Multiphasic Personality Inventory–2, Restructured Form (MMPI–2–RF), and the Structured Inventory of Malingered Symptomatology (SIMS). Participants instructed to feign PTSD and PCD had significantly higher scores on the mBIAS, NSI, PCL–C, and MMPI–2–RF than did controls. Few differences were found between the feign PCD and feign PTSD groups, with the exception of scores on the NSI (feign PCD > feign PTSD) and PCL–C (feign PTSD > feign PCD). Optimal cutoff scores on the mBIAS of ≥8 and ≥6 were found to reflect “probable exaggeration” (sensitivity = .34; specificity = 1.0; positive predictive power, PPP = 1.0; negative predictive power, NPP = .74) and “possible exaggeration” (sensitivity = .72; specificity = .88; PPP = .76; NPP = .85), respectively. Findings provide preliminary support for the use of the mBIAS as a tool to detect symptom exaggeration when administering the NSI and PCL–C.

Method of symptom assessment influences cognitive, affective and somatic post-concussion-like symptom base rates

Primary objective: To investigate whether assessment method influences the type of post-concussion-like symptoms. Methods and procedures: Participants were 73 Australian undergraduate students (Mage = 24.14, SD = 8.84; 75.3% female) with no history of mild traumatic brain injury (mTBI). Participants reported symptoms experienced over the previous 2 weeks in response to an open-ended question (free report), mock interview and standardized checklist (British Columbia Post-concussion Symptom Inventory; BC-PSI). Main outcomes and results: In the free report and checklist conditions, cognitive symptoms were reported significantly less frequently than affective (free report: p < 0.001; checklist: p < 0.001) or somatic symptoms (free report: p < 0.001; checklist: p = 0.004). However, in the mock structured interview condition, cognitive and somatic symptoms were reported significantly less frequently than affective symptoms (both p < 0.001). No participants reported at least one symptom from all three domains when assessed by free report, whereas most participants did so when symptoms were assessed by a mock structured interview (75%) or checklist (90%). Conclusions: Previous studies have shown that the method used to assess symptoms affects the number reported. This study shows that the assessment method also affects the type of reported symptoms.

Development of an evidence-based symptom checklist for symptoms of recurrence in women with endometrial cancer

Objective Women treated for endometrial cancer currently commonly attend clinic-based follow-up examinations for up to five years. This is based on little evidence and alternative models need to be investigated. This study aimed to identify currently available symptom checklists, determine the comprehensiveness of identified checklists, and generate an updated list of symptoms potentially associated with a recurrence of endometrial cancer for future testing within a prospective study. Methods/materials We conducted a systematic review of the literature extracting; routine follow-up schedules; proportion of patients with symptomatic or asymptomatic recurrence; symptoms of recurrence; prevalence of these symptoms at recurrence. Results Overall, three previous checklists, and 12 retrospective studies were identified meeting the selection criteria. The average rate of recurrence across the studies was 13% (range 3%-19%). The proportion of patients identified with a symptomatic recurrence varied widely (overall average 67%;range 41% to 91%). The most commonly reported symptoms were vaginal bleeding (25%), pain [not further described] (16%) and abdominal pain and/or discomfort and swelling (15%) which combined, represented 56% of the total reported symptoms. The three previous checklists listed 14 and this review identified an additional 24 symptoms (e.g. vaginal discharge, leg pain, constipation, headache and self-detected mass) not previously identified. Conclusion The newly developed symptom checklist expands previous ones, by an additional 24 symptoms. It will be used in a prospective cohort study to assess whether it is sensitive and specific enough to identify recurrence compared to current standard follow-up examinations.

Challenging the myth of an "epidemic" of common mental disorders : trends in the global prevalence of anxiety and depression between 1990 and 2010

Background Anxiety disorders and major depressive disorder (MDD) are common and disabling mental disorders. This paper aims to test the hypothesis that common mental disorders have become more prevalent over the past two decades. Methods We conducted a systematic review of prevalence, remission, duration, and excess mortality studies for anxiety disorders and MDD and then used a Bayesian meta-regression approach to estimate point prevalence for 1990, 2005, and 2010. We also conducted a post-hoc search for studies that used the General Health Questionnaire (GHQ) as a measure of psychological distress and tested for trends to present a qualitative comparison of study findings. Results This study found no evidence for an increased prevalence of anxiety disorders or MDD. While the crude number of cases increased by 36%, this was explained by population growth and changing age structures. Point prevalence of anxiety disorders was estimated at 3.8% (3.6-4.1%) in 1990 and 4.0% (3.7-4.2%) in 2010. The prevalence of MDD was unchanged at 4.4% in 1990 (4.2-4.7%) and 2010 (4.1-4.7%). However, 8 of the 11 GHQ studies found a significant increase in psychological distress over time. Conclusions The perceived "epidemic" of common mental disorders is most likely explained by the increasing numbers of affected patients driven by increasing population sizes. Additional factors that may explain this perception include the higher rates of psychological distress as measured using symptom checklists, greater public awareness, and the use of terms such as anxiety and depression in a context where they do not represent clinical disorders.

Targeting medication non-adherence behavior in selected autoimmune diseases: a systematic approach to digital health program development

Background 29 autoimmune diseases, including Rheumatoid Arthritis, gout, Crohn’s Disease, and Systematic Lupus Erythematosus affect 7.6-9.4% of the population. While effective therapy is available, many patients do not follow treatment or use medications as directed. Digital health and Web 2.0 interventions have demonstrated much promise in increasing medication and treatment adherence, but to date many Internet tools have proven disappointing. In fact, most digital interventions continue to suffer from high attrition in patient populations, are burdensome for healthcare professionals, and have relatively short life spans. Objective Digital health tools have traditionally centered on the transformation of existing interventions (such as diaries, trackers, stage-based or cognitive behavioral therapy programs, coupons, or symptom checklists) to electronic format. Advanced digital interventions have also incorporated attributes of Web 2.0 such as social networking, text messaging, and the use of video. Despite these efforts, there has not been little measurable impact in non-adherence for illnesses that require medical interventions, and research must look to other strategies or development methodologies. As a first step in investigating the feasibility of developing such a tool, the objective of the current study is to systematically rate factors of non-adherence that have been reported in past research studies. Methods Grounded Theory, recognized as a rigorous method that facilitates the emergence of new themes through systematic analysis, data collection and coding, was used to analyze quantitative, qualitative and mixed method studies addressing the following autoimmune diseases: Rheumatoid Arthritis, gout, Crohn’s Disease, Systematic Lupus Erythematosus, and inflammatory bowel disease. Studies were only included if they contained primary data addressing the relationship with non-adherence. Results Out of the 27 studies, four non-modifiable and 11 modifiable risk factors were discovered. Over one third of articles identified the following risk factors as common contributors to medication non-adherence (percent of studies reporting): patients not understanding treatment (44%), side effects (41%), age (37%), dose regimen (33%), and perceived medication ineffectiveness (33%). An unanticipated finding that emerged was the need for risk stratification tools (81%) with patient-centric approaches (67%). Conclusions This study systematically identifies and categorizes medication non-adherence risk factors in select autoimmune diseases. Findings indicate that patients understanding of their disease and the role of medication are paramount. An unexpected finding was that the majority of research articles called for the creation of tailored, patient-centric interventions that dispel personal misconceptions about disease, pharmacotherapy, and how the body responds to treatment. To our knowledge, these interventions do not yet exist in digital format. Rather than adopting a systems level approach, digital health programs should focus on cohorts with heterogeneous needs, and develop tailored interventions based on individual non-adherence patterns.

Working memory correlates of three symptom clusters in schizophrenia

Examined whether discrete working memory deficits underlie positive, negative and disorganised symptoms of schizophrenia. 52 outpatients (mean age 37.5 yrs) with schizophrenia were studied using items drawn from the Positive and Negative Syndrome Scale (PANSS). Linear regression and correlational analyses were conducted to examine whether symptom dimension scores were related to performance on several tests of working memory function. Severity of negative symptoms correlated with reduced production of words during a verbal fluency task, impaired ability to hold letter and number sequences on-line and manipulate them simultaneously, reduced performance during a dual task, and compromised visuospatial working memory under distraction-free conditions. Severity of disorganisation symptoms correlated with impaired visuospatial working memory under conditions of distraction, failure of inhibition during a verbal fluency task, perseverative responding on a test of set-shifting ability, and impaired ability to judge the veracity of simple declarative statements. The present study provides evidence that the positive, negative and disorganised symptom dimensions of the PANSS constitute independent clusters, associated with unique patterns of working memory impairment.

Bayesian latent trait modeling of migraine symptom data

Definition of disease phenotype is a necessary preliminary to research into genetic causes of a complex disease. Clinical diagnosis of migraine is currently based on diagnostic criteria developed by the International Headache Society. Previously, we examined the natural clustering of these diagnostic symptoms using latent class analysis (LCA) and found that a four-class model was preferred. However, the classes can be ordered such that all symptoms progressively intensify, suggesting that a single continuous variable representing disease severity may provide a better model. Here, we compare two models: item response theory and LCA, each constructed within a Bayesian context. A deviance information criterion is used to assess model fit. We phenotyped our population sample using these models, estimated heritability and conducted genome-wide linkage analysis using Merlin-qtl. LCA with four classes was again preferred. After transformation, phenotypic trait values derived from both models are highly correlated (correlation = 0.99) and consequently results from subsequent genetic analyses were similar. Heritability was estimated at 0.37, while multipoint linkage analysis produced genome-wide significant linkage to chromosome 7q31-q33 and suggestive linkage to chromosomes 1 and 2. We argue that such continuous measures are a powerful tool for identifying genes contributing to migraine susceptibility.

Linkage and heritability analysis of migraine symptom groupings: A comparison of three different clustering methods on twin data

Migraine is a painful disorder for which the etiology remains obscure. Diagnosis is largely based on International Headache Society criteria. However, no feature occurs in all patients who meet these criteria, and no single symptom is required for diagnosis. Consequently, this definition may not accurately reflect the phenotypic heterogeneity or genetic basis of the disorder. Such phenotypic uncertainty is typical for complex genetic disorders and has encouraged interest in multivariate statistical methods for classifying disease phenotypes. We applied three popular statistical phenotyping methods—latent class analysis, grade of membership and grade of membership “fuzzy” clustering (Fanny)—to migraine symptom data, and compared heritability and genome-wide linkage results obtained using each approach. Our results demonstrate that different methodologies produce different clustering structures and non-negligible differences in subsequent analyses. We therefore urge caution in the use of any single approach and suggest that multiple phenotyping methods be used.

Multivariate methods to identify cancer-related symptom clusters

Multivariate methods are required to assess the interrelationships among multiple, concurrent symptoms. We examined the conceptual and contextual appropriateness of commonly used multivariate methods for cancer symptom cluster identification. From 178 publications identified in an online database search of Medline, CINAHL, and PsycINFO, limited to articles published in English, 10 years prior to March 2007, 13 cross-sectional studies met the inclusion criteria. Conceptually, common factor analysis (FA) and hierarchical cluster analysis (HCA) are appropriate for symptom cluster identification, not principal component analysis. As a basis for new directions in symptom management, FA methods are more appropriate than HCA. Principal axis factoring or maximum likelihood factoring, the scree plot, oblique rotation, and clinical interpretation are recommended approaches to symptom cluster identification.

Alternative analytical methods for the identification of cancer-related symptom clusters

Advances in symptom management strategies through a better understanding of cancer symptom clusters depend on the identification of symptom clusters that are valid and reliable. The purpose of this exploratory research was to investigate alternative analytical approaches to identify symptom clusters for patients with cancer, using readily accessible statistical methods, and to justify which methods of identification may be appropriate for this context. Three studies were undertaken: (1) a systematic review of the literature, to identify analytical methods commonly used for symptom cluster identification for cancer patients; (2) a secondary data analysis to identify symptom clusters and compare alternative methods, as a guide to best practice approaches in cross-sectional studies; and (3) a secondary data analysis to investigate the stability of symptom clusters over time. The systematic literature review identified, in 10 years prior to March 2007, 13 cross-sectional studies implementing multivariate methods to identify cancer related symptom clusters. The methods commonly used to group symptoms were exploratory factor analysis, hierarchical cluster analysis and principal components analysis. Common factor analysis methods were recommended as the best practice cross-sectional methods for cancer symptom cluster identification. A comparison of alternative common factor analysis methods was conducted, in a secondary analysis of a sample of 219 ambulatory cancer patients with mixed diagnoses, assessed within one month of commencing chemotherapy treatment. Principal axis factoring, unweighted least squares and image factor analysis identified five consistent symptom clusters, based on patient self-reported distress ratings of 42 physical symptoms. Extraction of an additional cluster was necessary when using alpha factor analysis to determine clinically relevant symptom clusters. The recommended approaches for symptom cluster identification using nonmultivariate normal data were: principal axis factoring or unweighted least squares for factor extraction, followed by oblique rotation; and use of the scree plot and Minimum Average Partial procedure to determine the number of factors. In contrast to other studies which typically interpret pattern coefficients alone, in these studies symptom clusters were determined on the basis of structure coefficients. This approach was adopted for the stability of the results as structure coefficients are correlations between factors and symptoms unaffected by the correlations between factors. Symptoms could be associated with multiple clusters as a foundation for investigating potential interventions. The stability of these five symptom clusters was investigated in separate common factor analyses, 6 and 12 months after chemotherapy commenced. Five qualitatively consistent symptom clusters were identified over time (Musculoskeletal-discomforts/lethargy, Oral-discomforts, Gastrointestinaldiscomforts, Vasomotor-symptoms, Gastrointestinal-toxicities), but at 12 months two additional clusters were determined (Lethargy and Gastrointestinal/digestive symptoms). Future studies should include physical, psychological, and cognitive symptoms. Further investigation of the identified symptom clusters is required for validation, to examine causality, and potentially to suggest interventions for symptom management. Future studies should use longitudinal analyses to investigate change in symptom clusters, the influence of patient related factors, and the impact on outcomes (e.g., daily functioning) over time.

Cancer-related symptom clusters for symptom management in outpatients after commencing adjuvant chemotherapy, at 6 months, and 12 months

Goals of work: The aim of this secondary data analysis was to investigate symptom clusters over time for symptom management of a patient group after commencing adjuvant chemotherapy. Materials and methods: A prospective longitudinal study of 219 cancer outpatients conducted within 1 month of commencing chemotherapy (T1), 6 months (T2), and 12 months (T3) later. Patients' distress levels were assessed for 42 physical symptoms on a clinician-modified Rotterdam Symptom Checklist. Symptom clusters were identified in exploratory factor analyses at each time. Symptom inclusion in clusters was determined from structure coefficients. Symptoms could be associated with multiple clusters. Stability over time was determined from symptom cluster composition and the proportion of symptoms in the initial symptom clusters replicated at later times. Main results Fatigue and daytime sleepiness were the most prevalent distressing symptoms over time. The median number of concurrent distressing symptoms approximated 7, over time. Five consistent clusters were identified at T1, 2, and T3. An additional two clusters were identified at 12 months, possibly due to less variation in distress levels. Weakness and fatigue were each associated with two, four, and five symptom clusters at T1, T2, and T3, respectively, potentially suggesting different causal mechanisms. Conclusion: Stability is a necessary attribute of symptom clusters, but definitional clarification is required. We propose that a core set of concurrent symptoms identifies each symptom cluster, signifying a common cause. Additional related symptoms may be included over time. Further longitudinal investigation is required to identify symptom clusters and the underlying causes.

Narrative therapy for adults with major depressive disorder: Improved symptom and interpersonal outcomes

Abstract This study investigated depressive symptom and interpersonal relatedness outcomes from eight sessions of manualized narrative therapy for 47 adults with major depressive disorder. Post-therapy, depressive symptom improvement (d=1.36) and proportions of clients achieving reliable improvement (74%), movement to the functional population (61%), and clinically significant improvement (53%) were comparable to benchmark research outcomes. Post-therapy interpersonal relatedness improvement (d=.62) was less substantial than for symptoms. Three-month follow-up found maintenance of symptom, but not interpersonal gains. Benchmarking and clinical significance analyses mitigated repeated measure design limitations, providing empirical evidence to support narrative therapy for adults with major depressive disorder. RÉSUMÉ Cette étude a investigué les symptômes dépressifs et les relations interpersonnels d'une thérapie narrative en huit séances chez 47 adultes souffrant d'un trouble dépressif majeur. Après la thérapie, l'amélioration des symptômes dépressifs (d=1.36) et la proportion de clients atteignant un changement significatif (74%), le mouvement vers la population fonctionnelle (61%), enfin l'amélioration clinique significative (53%) étaient comparables aux performances des études de résultats. L'amélioration des relations interpersonnelles (d=0.62) était inférieure à l'amélioration symptomatique. Le suivi à trois mois montrait un maintien des gains symptomatiques mais pas pour les relations interpersonnelles. L’évaluation des performances et les analyses de significativité clinique modèrent les limitations du plan de recherche à mesures répétées et apportent une preuve empirique qui étaie l'efficacité des thérapies narratives pour des adultes avec un trouble dépressif majeur. Este estudo investigou sintomas depressivos e resultados interpessoais relacionados em oito sessões de terapia narrativa manualizada para 47 adultos com perturbação depressiva major. No pós terapia, melhoria de sintomas depressivos (d=1,36) e proporção de clientes que alcançam melhoria válida (74%), movimento para a população funcional (61%) e melhoria clinicamente significativa (53%) foram comparáveis com os resultados da investigação reportados. As melhorias pós terapia nos resultados interpessoais relacionados (d=.62) foi menos substancial do que para os sintomas. Aos três meses de seguimento houve a manutenção dos sintomas mas não dos ganhos interpessoais. As análises de benchemarking e de melhoria clinicamente significativas atenuam as limitações de um design de medidas repetidas, fornecendo evidência empírica para a terapia narrativa para adultos com perturbação depressiva major. Questo lavoro ha valutato i sintomi depressivi e gli outcome nella capacità di relazionarsi a livello interpersonale in 8 sedute di psicoterapia narrativa manualizzata in un gruppo di 47 adulti con depressione maggiore. I risultati ottenuti relativamente a: post terapy, miglioramento dei sintomi depressivi (d_1.36), proporzione di pazienti che hanno raggiunto un miglioramento affidabile e consistente (74%), movimento verso il funzionamento atteso nella popolazione (61%) e miglioramento clinicamente significativo (53%) sono paragonabili ai valori di riferimento della ricerca sull'outcome. I miglioramento della capacità di relazionarsi valutata alla fine del trattamento (d_.62) si è rivelata meno sostanziale rispetto ai sintomi. Un follow-up dopo 3 mesi ha dimostrato che il miglioramento sintomatologico è stato mantenuto, ma non quello degli obiettivi interpersonali. Valori di riferimento e analisi della significatività clinica hanno fatto fronte ai limiti del disegno a misure ripetute, offrendo prove empiriche sulla rilevanza della terapia narrativa in pazienti adulti con depressione maggiore