No abstract

Background: Baseline data is necessary for monitoring how a population perceives the threat of pandemic influenza, and perceives how it would behave in the event of pandemic influenza. Our aim was to develop a module of questions for use in telephone health surveys on perceptions of threat of pandemic influenza, and on preparedness to comply with specific public health behaviours in the event of pandemic influenza.

BackgroundResettled refugees are a particularly vulnerable group. They have very high levels of mental health problems, in particular, trauma-related disorders, but very low uptake of mental health care. Evidence suggests that poor “mental health literacy”, namely, poor knowledge and understanding of the nature and treatment of mental health problems is a major factor in low or inappropriate treatment-seeking among individuals with mental health problems. This study used a culturally adapted Mental Health Literacy Survey method to determine knowledge of, and beliefs about, helpfulness of treatment interventions and providers for posttraumatic stress disorder (PTSD) amongst resettled Iraqi refugees.Methods225 resettled Iraqi refugees in Western Sydney attending the Adult Migrant English Program (AMEP), federally funded English language tuition, were surveyed. A vignette of a fictional character meeting diagnostic criteria for PTSD was presented followed by the Mental Health Literacy Survey. PTSD symptomology was measured using the Harvard Trauma Questionnaire part IV (HTQ part IV), with Kessler Psychological Distress Scale (K10) used to measure levels of general psychological distress.ResultsOnly 14.2% of participants labelled the problem as PTSD, with “a problem with fear” being the modal response (41.8%). A total of 84.9% respondents indicated that seeing a psychiatrist would be helpful, followed by reading the Koran or Bible selected by 79.2% of those surveyed. There was some variation in problem recognition and helpfulness of treatment, most notably influenced by the length of resettlement in Australia of the respondents.ConclusionsThese findings have important implications for the design and implementation of mental health promotion and treatment programs for resettled refugees and those who work with them.Electronic supplementary materialThe online version of this article (doi:10.1186/s12888-014-0320-x) contains supplementary material, which is available to authorized users.

BackgroundEstimating multimorbidity (presence of two or more chronic conditions) using administrative data is becoming increasingly common. We investigated (1) the concordance of identification of chronic conditions and multimorbidity using self-report survey and administrative datasets; (2) characteristics of people with multimorbidity ascertained using different data sources; and (3) whether the same individuals are classified as multimorbid using different data sources.MethodsBaseline survey data for 90,352 participants of the 45 and Up Study—a cohort study of residents of New South Wales, Australia, aged 45 years and over—were linked to prior two-year pharmaceutical claims and hospital admission records. Concordance of eight self-report chronic conditions (reference) with claims and hospital data were examined using sensitivity (Sn), positive predictive value (PPV), and kappa (κ).The characteristics of people classified as multimorbid were compared using logistic regression modelling.ResultsAgreement was found to be highest for diabetes in both hospital and claims data (κ = 0.79, 0.78; Sn = 79%, 72%; PPV = 86%, 90%). The prevalence of multimorbidity was highest using self-report data (37.4%), followed by claims data (36.1%) and hospital data (19.3%). Combining all three datasets identified a total of 46 683 (52%) people with multimorbidity, with half of these identified using a single dataset only, and up to 20% identified on all three datasets. Characteristics of persons with and without multimorbidity were generally similar. However, the age gradient was more pronounced and people speaking a language other than English at home were more likely to be identified as multimorbid by administrative data.ConclusionsDifferent individuals, with different combinations of conditions, are identified as multimorbid when different data sources are used. As such, caution should be applied when ascertaining morbidity from a single data source as the agreement between self-report and administrative data is generally poor. Future multimorbidity research exploring specific disease combinations and clusters of diseases that commonly co-occur, rather than a simple disease count, is likely to provide more useful insights into the complex care needs of individuals with multiple chronic conditions.

The SQiD demonstrates potential as a simple clinical tool worthy or further investigation.