Search

Aims To report a systematic review of the psychometric properties of self-report instruments to identify the symptoms of anxiety in pregnancy to help clinicians and researchers select the most suitable instrument. Background Excessive anxiety in pregnancy is associated with adverse birth outcomes, developmental and behavioural problems in infants and postnatal depression. Despite recommendations for routine psychological assessment in pregnancy, the optimal methods to identify anxiety in pregnancy have not been confirmed. Design Psychometric systematic review. Data sources A systematic literature search of the multiple databases (1990-September 2014). Review methods Identification of self-report instruments to measure anxiety in pregnancy using COSMIN guidelines to assess studies reporting a psychometric evaluation of validity and reliability. Results Thirty-two studies were included. Studies took place in the UK, Australia, Belgium, Canada, Germany, Italy, Scandinavia, Spain and the Netherlands. Seventeen different instruments were identified. Measures of validity were reported in 19 papers and reliability in 16. The overall quality of the papers was rated as fair to excellent using the COSMIN checklist. Only one paper scored excellent in more than one category. Conclusion Many instruments have been adapted for use in different populations to those for which they were designed. The State Trait Anxiety Inventory, Edinburgh Postnatal Depression Scale and the Hospital Anxiety and Depression Scale have been tested more frequently than other instruments, yet require further assessment to confirm their value for use in pregnancy. [ABSTRACT FROM AUTHOR]

Childhood aggression and its resulting consequences inflict a huge burden on affected children, their relatives, teachers, peers and society as a whole. Aggression during childhood rarely occurs in isolation and is correlated with other symptoms of childhood psychopathology. In this paper, we aim to describe and improve the understanding of the co-occurrence of aggression with other forms of childhood psychopathology. We focus on the co-occurrence of aggression and other childhood behavioural and emotional problems, including other externalising problems, attention problems and anxiety-depression. The data were brought together within the EU-ACTION (Aggression in Children: unravelling gene-environment interplay to inform Treatment and InterventiON strategies) project. We analysed the co-occurrence of aggression and other childhood behavioural and emotional problems as a function of the child’s age (ages 3 through 16 years), gender, the person rating the behaviour (father, mother or self) and assessment instrument. The data came from six large population-based European cohort studies from the Netherlands (2x), the UK, Finland and Sweden (2x). Multiple assessment instruments, including the Child Behaviour Checklist (CBCL), the Strengths and Difficulties Questionnaire (SDQ) and Multidimensional Peer Nomination Inventory (MPNI), were used. There was a good representation of boys and girls in each age category, with data for 30,523 3- to 4-year-olds (49.5% boys), 20,958 5- to 6-year-olds (49.6% boys), 18,291 7- to 8-year-olds (49.0% boys), 27,218 9- to 10-year-olds (49.4% boys), 18,543 12- to 13-year-olds (48.9% boys) and 10,088 15- to 16-year-olds (46.6% boys). We replicated the well-established gender differences in average aggression scores at most ages for parental ratings. The gender differences decreased with age and were not present for self-reports. Aggression co-occurred with the majority of other behavioural and social problems, from both externalising and internalising domains. At each age, the co-occurrence was particularly prevalent for aggression and oppositional and ADHD-related problems, with correlations of around 0.5 in general. Aggression also showed substantial associations with anxiety-depression and other internalizing symptoms (correlations around 0.4). Co-occurrence for self-reported problems was somewhat higher than for parental reports, but we found neither rater differences, nor differences across assessment instruments in co-occurrence patterns. There were large similarities in co-occurrence patterns across the different European countries. Finally, co-occurrence was generally stable across age and sex, and if any change was observed, it indicated stronger correlations when children grew older. We present an online tool to visualise these associations as a function of rater, gender, instrument and cohort. In addition, we present a description of the full EU-ACTION projects, its first results and the future perspectives. [ABSTRACT FROM AUTHOR]

Objectives Chronic widespread musculoskeletal pain (CWP) is a characteristic symptom of fibromyalgia, which has been shown to be associated with an altered gut microbiome. Microbiome studies to date have not examined the milder CWP phenotype specifically nor have they explored the role of raised BMI. The aim of this study was to investigate whether the microbiome is abnormal in CWP. Methods CWP was assessed using a standardized screening questionnaire in female volunteers from the TwinsUK cohort including 113 CWP cases and 1623 controls. The stool microbiome was characterized using 16S rRNA amplicon sequencing and amplicon sequence variants, and associations with CWP examined using linear mixed-effects models adjusting for BMI, age, diet, family relatedness and technical factors. Results Alpha diversity was significantly lower in CWP cases than controls (Mann–Whitney test, P -values 2.3e-04 and 1.2e-02, for Shannon and Simpson indices respectively). The species Coprococcus comes was significantly depleted in CWP cases (P adj = 3.04e-03). A genome-wide association study (GWAS) performed for C. comes in TwinsUK followed by meta-analysis with three Dutch cohorts (total n  = 3521) resulted in nine suggestive regions, with the most convincing on chromosome 4 near the TRAM1L1 gene (rs76957229, P  = 7.4e-8). A Mendelian randomization study based on the results of the GWAS did not support a causal role for C. comes on the development of CWP. Conclusions We have demonstrated reduced diversity in the microbiome in CWP, indicating an involvement of the gut microbiota in CWP; prospectively the microbiome may offer therapeutic opportunities for this condition. [ABSTRACT FROM AUTHOR]

Objective: In patients with velocardiofacial syndrome (VCFS), medial displacement of the internal carotid arteries (ICAs) may increase the risk of vascular injury during the surgical correction of velopharyngeal dysfunction (VPD). Some surgeons advocate the use of vascular imaging studies prior to surgery. Nevertheless, the role of preoperative imaging is still controversial. This study aimed to review the current practice of the UK cleft units and also examine our own practice at the Evelina London Children's Hospital in relation to children with VCFS undergoing speech surgery over the previous 7 years. Design: A questionnaire was sent to all UK cleft surgeons to enquire about the management and use of preoperative vascular imaging in patients with VPD and VCFS. A retrospective study was also conducted of the unit's 7-year series of patients with VPD and VCFS. Results: Thirty-four completed questionnaires were returned (response rate 100%). Most UK surgeons (73.5%) do not regularly order preoperative vascular imaging for patients with VCFS although some reportedly would consider it if a posterior pharyngeal wall pulsation was visible. In our unit, between 2013 and 2019, a total of 40 patients affected by VCFS have been assessed for VPD. A magnetic resonance angiography (MRA) was performed for 23 patients. Medial deviation of the ICAs was identified in 7 (30%) patients. Conclusions: The results of the national survey showed no consensus on routine use of preoperative vascular imaging. Our retrospective study showed a 30% prevalence of medialized ICAs in our patient cohort. In these patients, the MRA findings influenced the choice of speech surgery. [ABSTRACT FROM AUTHOR]

Purpose: As a component of thyroid hormones, adequate iodine intake is essential during pregnancy for fetal neurodevelopment. Across Europe, iodine deficiency is common in pregnancy, but data are lacking on the predictors of iodine status at this life stage. We, therefore, aimed to explore determinants of iodine status during pregnancy in three European populations of differing iodine status. Methods: Data were from 6566 pregnant women from three prospective population-based birth cohorts from the United Kingdom (ALSPAC, n = 2852), Spain (INMA, n = 1460), and The Netherlands (Generation R, n = 2254). Urinary iodine-to-creatinine ratio (UI/Creat, µg/g) was measured in spot-urine samples in pregnancy (≤ 18-weeks gestation). Maternal dietary intake, categorised by food groups (g/day), was estimated from food-frequency questionnaires (FFQs). Multivariable regression models used dietary variables (energy-adjusted) and maternal characteristics as predictors of iodine status. Results: Median UI/Creat in pregnant women of ALSPAC, INMA, and Generation R was 121, 151, and 210 µg/g, respectively. Maternal age was positively associated with UI/Creat in all cohorts (P < 0.001), while UI/Creat varied by ethnicity only in Generation R (P < 0.05). Of the dietary predictors, intake of milk and dairy products (per 100 g/day) was positively associated with UI/Creat in all cohorts [ALSPAC (B = 3.73, P < 0.0001); INMA (B = 6.92, P = 0.002); Generation R (B = 2.34, P = 0.001)]. Cohort-specific dietary determinants positively associated with UI/Creat included fish and shellfish in ALSPAC and INMA, and eggs and cereal/cereal products in Generation R. Conclusions: The cohort-specific dietary determinants probably reflect not only dietary habits but iodine-fortification policies; hence, public-health interventions to improve iodine intake in pregnancy need to be country-specific. [ABSTRACT FROM AUTHOR]

Objectives Because of fundamental differences in healthcare systems, US readmission data cannot be extrapolated to the European setting: To investigate the opinions of readmitted patients, their carers, nurses and physicians on predictability and preventability of readmissions and using majority consensus to determine contributing factors that could potentially foresee (preventable) readmissions. Design Prospective observational study. Readmitted patients, their carers, and treating professionals were surveyed during readmission to assess the discharge process and the predictability and preventability of the readmission. Cohen's Kappa measured pairwise agreement of considering readmission as predictable/preventable by patients, carers and professionals. Subsequently, multivariable logistic regressionidentified factors associated with predictability/preventability. Setting 15 hospitals in four European countries Participants 1398 medical patients readmitted unscheduled within 30 days Main Outcome(s) and Measure(s) (1) Agreement between the interviewed groups on considering readmissions likely predictable or preventable;® Factors distinguishing predictable from non-predictable and preventable from non-preventable readmissions. Results The majority deemed 27.8% readmissions potentially predictable and 14.4% potentially preventable. The consensus on predictability and preventability was poor, especially between patients and professionals (kappas ranged from 0.105 to 0.173). The interviewed selected different factors as potentially associated with predictability and preventability. When a patient reported that he was ready for discharge during index admission, the readmission was deemed less likely by the majority (predictability: OR 0.55; 95% CI 0.40 to 0.75; preventability: OR 0.35; 95% CI 0.24 to 0.49). Conclusions There is no consensus between readmitted patients, their carers and treating professionals about predictability and preventability of readmissions, nor associated risk factors. A readmitted patient reporting not feeling ready for discharge at index admission was strongly associated with preventability/predictability. Therefore, healthcare workers should question patients' readiness to go home timely before discharge. [ABSTRACT FROM AUTHOR]

BackgroundSeveral studies have reported weak associations between religious or spiritual belief and psychological health. However, most have been cross-sectional surveys in the USA, limiting inference about generalizability. An international longitudinal study of incidence of major depression gave us the opportunity to investigate this relationship further.MethodData were collected in a prospective cohort study of adult general practice attendees across seven countries. Participants were followed at 6 and 12 months. Spiritual and religious beliefs were assessed using a standardized questionnaire, and DSM-IV diagnosis of major depression was made using the Composite International Diagnostic Interview (CIDI). Logistic regression was used to estimate incidence rates and odds ratios (ORs), after multiple imputation of missing data.ResultsThe analyses included 8318 attendees. Of participants reporting a spiritual understanding of life at baseline, 10.5% had an episode of depression in the following year compared to 10.3% of religious participants and 7.0% of the secular group (p < 0.001). However, the findings varied significantly across countries, with the difference being significant only in the UK, where spiritual participants were nearly three times more likely to experience an episode of depression than the secular group [OR 2.73, 95% confidence interval (CI) 1.59–4.68]. The strength of belief also had an effect, with participants with strong belief having twice the risk of participants with weak belief. There was no evidence of religion acting as a buffer to prevent depression after a serious life event.ConclusionsThese results do not support the notion that religious and spiritual life views enhance psychological well-being. [ABSTRACT FROM PUBLISHER]

BackgroundPredictD is a risk algorithm that was developed to predict risk of onset of major depression over 12 months in general practice attendees in Europe and validated in a similar population in Chile. It was the first risk algorithm to be developed in the field of mental disorders. Our objective was to extend predictD as an algorithm to detect people at risk of major depression over 24 months.MethodParticipants were 4190 adult attendees to general practices in the UK, Spain, Slovenia and Portugal, who were not depressed at baseline and were followed up for 24 months. The original predictD risk algorithm for onset of DSM-IV major depression had already been developed in data arising from the first 12 months of follow-up. In this analysis we fitted predictD to the longer period of follow-up, first by examining only the second year (12–24 months) and then the whole period of follow-up (0–24 months).ResultsThe instrument performed well for prediction of major depression from 12 to 24 months [c-index 0.728, 95% confidence interval (CI) 0.675–0.781], or over the whole 24 months (c-index 0.783, 95% CI 0.757–0.809).ConclusionsThe predictD risk algorithm for major depression is accurate over 24 months, extending it current use of prediction over 12 months. This strengthens its use in prevention efforts in general medical settings. [ABSTRACT FROM AUTHOR]

Background Finite mixture models posit the existence of a latent categorical variable and can be used for probabilistic classification. The authors illustrate the use of mixture models for dietary pattern analysis. An advantage of this approach is taking classification uncertainty into account. Methods Participants were a random sample of women from the European Prospective Investigation into Cancer. Food consumption was measured using dietary questionnaires. Mixture models identified latent classes in food consumption data, which were interpreted as dietary patterns. Results Among various assumptions examined, models allowing the variance of foods to vary within and between classes fit better than alternatives assuming constant variance (the K-means method of cluster analysis also makes the latter assumption). An eight-class model was best fitting and five patterns validated well in a second random sample. Patterns with lower classification uncertainty tended to be better validated. One pattern showed low consumption of foods despite being associated with moderate body mass index. Conclusion Mixture modelling for dietary pattern analysis has advantages over both factor and cluster analysis. In contrast to these other methods, it is easy to estimate pattern prevalence, to describe patterns and to use patterns to predict disease taking classification uncertainty into account. Owing to substantial error in food consumptions, any analysis will usually find some patterns that cannot be well validated. While knowledge of classification uncertainty may aid pattern evaluation, any method will better identify patterns from food consumptions measured with less error. Mixture models may be useful to identify individuals who under-report food consumption. [ABSTRACT FROM AUTHOR]