The Pannonian Plain as a Source of Ambrosia Pollen in the Balkans

This study aims to find likely sources of Ambrosia pollen recorded during 2007 at five pollen-monitoring sites in central Europe, Novi Sad, Ruma, Negotin and Nis (Serbia) and Skopje (Macedonia). Ambrosia plants start flowering early in the morning and so Ambrosia pollen grains recorded during the day are likely to be from a local source. Conversely, Ambrosia pollen grains recorded at night or very early in the morning may have arrived via long-range transport. Ambrosia pollen counts were analysed in an attempt to find possible sources of the pollen and to identify Ambrosia pollen episodes suitable for further investigation using back-trajectory analysis. Diurnal variations and the magnitude of Ambrosia pollen counts during the 2007 Ambrosia pollen season showed that Novi Sad and Ruma (Pannonian Plain) and to a lesser degree Negotin (Balkans) were located near to sources of Ambrosia pollen. Mean bi-hourly Ambrosia pollen concentrations peaked during the middle of the day and concentrations at these sites were notably higher than at Nis and Skopje. Three episodes were selected for further analysis using back-trajectory analysis. Back-trajectories showed that air masses brought Ambrosia pollen from the north to Nis and, on one occasion, to Skopje (Balkans) during the night and early morning after passing to the east of Novi Sad and Ruma during the previous day. The results of this study identified the Southern part of the Pannonian Plain around Novi Sad and Ruma as being a potential source region for Ambrosia pollen recorded at Nis and Skopje in the Balkans.

Using Workload Measurement Tools in Diverse Care Contexts: the Experience of Staff in Mental Health and Learning Disability Inpatient Settings

Introduction The critical challenge of determining the correct level and skill-mix of nursing staff required to deliver safe and effective healthcare has become an international concern. It is recommended that evidence-based staffing decisions are central to the development of future workforce plans. Workforce planning in mental health and learning disability nursing is largely under-researched with few tools available to aid the development of evidence-based staffing levels in these environments. Aim It was the aim of this study to explore the experience of staff using the Safer Nursing Care Tool (SNCT) and the Mental Health and Learning Disability Workload Tool (MHLDWT) in mental health and learning disability environments. Method Following a 4-week trial period of both tools a survey was distributed via Qualtrics on-line survey software to staff members who used the tools during this time. Results The results of the survey revealed that the tools were considered a useful resource to aid staffing decisions; however specific criticisms were highlighted regarding their suitability to psychiatric intensive care units (PICU) and learning disability wards. Discussion This study highlights that further development of workload measurement tools is required to support the implementation of effective workforce planning strategies within mental health and learning disability services. Implications for Practice With increasing fiscal pressures the need to provide cost-effective care is paramount within NHS services. Evidence-based workforce planning is therefore necessary to ensure that appropriate levels of staff are determined. This is of particular importance within mental health and learning disability services due to the reduction in the number of available beds and an increasing focus on purposeful admission and discharge.

Affective Instability, Childhood Trauma and Major Affective Disorders

BACKGROUND: Affective instability (AI), childhood trauma, and mental illness are linked, but evidence in affective disorders is limited, despite both AI and childhood trauma being associated with poorer outcomes. Aims were to compare AI levels in bipolar disorder I (BPI) and II (BPII), and major depressive disorder recurrent (MDDR), and to examine the association of AI and childhood trauma within each diagnostic group. METHODS: AI, measured using the Affective Lability Scale (ALS), was compared between people with DSM-IV BPI (n=923), BPII (n=363) and MDDR (n=207) accounting for confounders and current mood. Regression modelling was used to examine the association between AI and childhood traumas in each diagnostic group. RESULTS: ALS scores in descending order were BPII, BPI, MDDR, and differences between groups were significant (p<0.05). Within the BPI group any childhood abuse (p=0.021), childhood physical abuse (p=0.003) and the death of a close friend in childhood (p=0.002) were significantly associated with higher ALS score but no association was found between childhood trauma and AI in BPII and MDDR. LIMITATIONS: The ALS is a self-report scale and is subject to retrospective recall bias. CONCLUSIONS: AI is an important dimension in bipolar disorder independent of current mood state. There is a strong link between childhood traumatic events and AI levels in BPI and this may be one way in which exposure and disorder are linked. Clinical interventions targeting AI in people who have suffered significant childhood trauma could potentially change the clinical course of bipolar disorder.