Zoekresultaten

Somatic symptoms, pain, catastrophizing and the association with disability among children with heritable connective tissue disorders

The aim of the present study was to investigate the nature and prevalence of nonspecific somatic symptoms, pain and catastrophizing in children with Heritable Connective Tissue Disorders (HCTD), and to determine their association with disability. This observational, multicenter study included 127 children, aged 4–18 years, with Marfan syndrome (MFS) (59%), Loeys-Dietz syndrome (LDS) (8%), Ehlers-Danlos syndromes (EDS) (12%) and hypermobile Ehlers-Danlos syndrome (hEDS) (23%). The assessments included the Children's Somatization Inventory or parent proxy (CSI, PCSI), pain visual-analogue scale (VAS), SUPERKIDZ body diagram, Pain Catastrophizing Scale Child or parent proxy (PCS-C, PCS-P) and Childhood Health Assessment Questionnaire (CHAQ-30). Data from children aged ≥8 years were compared to normative data. In children ≥ 8 years (n = 90), pain was present in 59%, with a median of 4 (IQR = 3–9) pain areas. Compared to normative data, the HCTD group reported significantly higher on the CSI (p ≤ 0.001, d = 0.85), VAS pain intensity (p ≤ 0.001, d = 1.22) and CHAQ-30 (p ≤ 0.001, d = 1.16) and lower on the PCS-C (p = 0.017, d = −0.82) and PCS-P (p ≤ 0.001, d = −0.49). The intensity of nonspecific somatic symptoms and pain explained 45% of the variance in disability (r2 = 0.45 F(2,48) = 19.70, p ≤ 0.001). In children ≤ 7 years (n = 37), pain was present in 35% with a median of 5(IQR = 1–13) pain areas. The mean(SD) VAS scores for pain intensity was 1.5(2.9). Functional disability was moderately correlated to the number of pain areas (r = 0.56, p ≤ 0.001), intensity of nonspecific somatic symptoms (r = 0.63, p ≤ 0.001) and pain (r = 0.83, p ≤ 0.001). In conclusion, this study supports the need for comprehensive assessment of nonspecific somatic symptoms, pain, and disability in children with HCTD to allow tailored treatment.

Pain catastrophizing predicts dropout of patients from an interdisciplinary chronic pain management programme: a prospective cohort study

Objective: To explore predictors of dropout of patients with chronic musculoskeletal pain from an interdisciplinary chronic pain management programme, and to develop and validate a multivariable prediction model, based on the Extended Common- Sense Model of Self-Regulation (E-CSM). Methods: In this prospective cohort study consecutive patients with chronic pain were recruited and followed up (July 2013 to May 2015). Possible associations between predictors and dropout were explored by univariate logistic regression analyses. Subsequently, multiple logistic regression analyses were executed to determine the model that best predicted dropout. Results: Of 188 patients who initiated treatment, 35 (19%) were classified as dropouts. The mean age of the dropout group was 47.9 years (standard deviation 9.9). Based on the univariate logistic regression analyses 7 predictors of the 18 potential predictors for dropout were eligible for entry into the multiple logistic regression analyses. Finally, only pain catastrophizing was identified as a significant predictor. Conclusion: Patients with chronic pain who catastrophize were more prone to dropout from this chronic pain management programme. However, due to the exploratory nature of this study no firm conclusions can be drawn about the predictive value of the E-CSM of Self-Regulation for dropout.

Psychosocial- and physical functioning in hypermobile Ehlers-Danlos Syndrome: a 5-year follow-up study

Using precision farming to improve animal welfare

Animal welfare is a multidimensional phenomenon and currently its on-farm assessment requires complex, multidimensional frameworks involving farm audits which are time-consuming, infrequent and expensive. The core principle of precision agriculture is to use sensor technologies to improve the efficiency of resource use by targeting resources to where they give a benefit. Precision livestock farming (PLF) enables farm animal management to move away from the group level to monitoring and managing individual animals. A range of precision livestock monitoring and control technologies have been developed, primarily to improve livestock production efficiency. Examples include using camera systems monitoring the movement of housed broiler chickens to detect problems with feeding systems or disease and leg-mounted accelerometers enabling the detection of the early stages of lameness in dairy cows. These systems are already improving farm animal welfare by, for example, improving the detection of health issues enabling more rapid treatment, or the detection of problems with feeding systems helping to reduce the risk of hunger. Environmental monitoring and control in buildings can improve animal comfort, and automatic milking systems facilitate animal choice and improve human-animal interactions. Although these precision livestock technologies monitor some parameters relevant to farm animal welfare (e.g. feeding, health), none of the systems yet provide the broad, multidimensional integration that is required to give a complete assessment of an animal’s welfare. However, data from PLF sensors could potentially be integrated into automated animal welfare assessment systems, although further research is needed to define and validate this approach.

Inaugurele rede lectoraat Dairy over : duurzame en zorgvuldige melkveehouderij met Smart Dairy Farming

Vanuit het lectoraat Dairy wil de lector ‘Herd Management en Smart Dairy Farming’ door middel van het gebruik van moderne (sensor)technieken en beslissingsondersteunende managementsystemen het veemanagement op het primaire melk-­veebedrijf verbeteren, om zo een beter rendement te behalen. Zowel financieel als op het gebied van duurzaamheid, diergezondheidszorg en dierenwelzijn. Daarbij sluit het naadloos aan op het werkgebied van de lector ‘Duurzame Melkveehouderij’, die zich richt op ontwikkeling en overdracht van kennis op het gebied van verduurzaming van de melkveehouderij. Daarbij staat de praktische uitrol van de afspraken in de Duurzame Zuivelketen centraal. Oftewel: hoe kunnen we, in een internationaal concurrerende markt, een rendabele en duurzame melkveehouderij creëren die maatschappelijk geaccepteerd wordt?

Is self reflection dangerous?

Reflection is considered necessary and beneficial within career learning and is deemed to be a condition for successful career-identity development. Indeed, reflection is generally seen as a key competency in learning how to respond effectively to a complex and dynamic post-modern world in which individuals are increasingly exposed to risk. Paradoxically however, reflection can itself form a risk when it results in rumination. It is therefore important to identify the conditions and personal (risk) factors that make reflection a detrimental or beneficial activity and to identify elements within career learning interventions that promote benefit. The purpose here is to increase awareness about reflective versus ruminative processes and promote responsible use of interventions that aim to stimulate reflection in the process of career-identity formation. Based on the “career writing” method, the authors conclude that a successful career intervention must especially provide good facilitation and a safe holding environment. https://doi.org/10.1177/1038416216670675 LinkedIn: https://www.linkedin.com/in/reinekke-lengelle-phd-767a4322/