Dataset Information

Sampling and weighting of the Austrian Psychiatric Prevalence Survey (APPS).

ABSTRACT: Mental disorders are common and have severe consequences for the patients, their relatives, and society. Mental health care planning requires precise knowledge of the prevalence of psychiatric disorders and details regarding the provided treatment. Because administrative data lack information on persons not in contact with health services, we need epidemiologic studies delivering nationwide information on the prevalence of psychiatric disorders. This requirement induces the need for adequate sampling procedures to collect reliable data, allowing for accurate estimations of mental health care needs, over- and underprovision. This is the purpose of the Austrian Psychiatric Prevalence Survey (APPS).The present technical report describes the exact procedure how a nationwide sample has been drawn, adopting a stratified cluster sampling scheme. Because such a complex sampling procedure requires an adequate weighting to obtain unbiased population estimates, this report also contains the exact steps to calculate the corresponding weights. This way, the report not only fosters the full disclosure of the sampling strategy of the APPS, it may also serve as a best practice example for similar endeavours.

SUBMITTER: Alexandrowicz RW

PROVIDER: S-EPMC6561988 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Sampling and weighting of the Austrian Psychiatric Prevalence Survey (APPS).

Alexandrowicz Rainer W RW Bacher Johann J Wancata Johannes J

Neuropsychiatrie : Klinik, Diagnostik, Therapie und Rehabilitation : Organ der Gesellschaft Osterreichischer Nervenarzte und Psychiater 20190403 2

Mental disorders are common and have severe consequences for the patients, their relatives, and society. Mental health care planning requires precise knowledge of the prevalence of psychiatric disorders and details regarding the provided treatment. Because administrative data lack information on persons not in contact with health services, we need epidemiologic studies delivering nationwide information on the prevalence of psychiatric disorders. This requirement induces the need for adequate sam ...[more]

PMID: 30945143

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Project description:BACKGROUND:The use of communication apps on mobile phones offers an efficient, unobtrusive, and portable mode of communication for medical staff. The potential enhancements in patient care and education appear significant, with clinical details able to be shared quickly within multidisciplinary teams, supporting rapid integration of disparate information, and more efficient patient care. However, sharing patient data in this way also raises legal and ethical issues. No data is currently available demonstrating how widespread the use of these apps are, doctor's attitudes towards them, or what guides clinician choice of app. OBJECTIVE:The objective of this study was to quantify and qualify the use of communication apps among medical staff in clinical situations, their role in patient care, and knowledge and attitudes towards safety, key benefits, potential disadvantages, and policy implications. METHODS:Medical staff in hospitals across Victoria (Australia) were invited to participate in an anonymous 33-question survey. The survey collected data on respondent's demographics, their use of communication apps in clinical settings, attitudes towards communication apps, perceptions of data "safety," and why one communication app was chosen over others. RESULTS:Communication apps in Victorian hospitals are in widespread use from students to consultants, with WhatsApp being the primary app used. The median number of messages shared per day was 12, encompassing a range of patient information. All respondents viewed these apps positively in quickly communicating patient information in a clinical setting; however, all had concerns about the privacy implications arising from sharing patient information in this way. In total, 67% (60/90) considered patient data "moderately safe" on these apps, and 50% (46/90) were concerned the use of these apps was inconsistent with current legislation and policy. Apps were more likely to be used if they were fast, easy to use, had an easy login process, and were already in widespread use. CONCLUSIONS:Communication app use by medical personnel in Victorian hospitals is pervasive. These apps contribute to enhanced communication between medical staff, but their use raises compliance issues, most notably with Australian privacy legislation. Development of privacy-compliant apps such as MedX needs to prioritize a user-friendly interface and market the product as a privacy-compliant comparator to apps previously adapted to health care settings.

Project description:BackgroundThe Behavioral Risk Factor Surveillance System (BRFSS) is an annual survey designed to identify trends in the public's health. In its 2019 field survey, the U.S. state of GA tested a new 3 - item module to measure the numbers of bereaved, resident adults aged 18 years and older. Participants were eligible if they answered 'Yes' to the item 'Have you experienced the death of a family member or close friend in the years 2018 or 2019?'. This analysis explores two research questions. Can estimates for bereavement prevalence be derived without large sampling errors, low precision, and small subsamples? Can multiple imputation techniques be applied to overcome non-response and missing data to support multivariate modeling?MethodsBRFSS is a non-institutionalized sample of adults aged 18 years and older living in the U.S. state of Georgia. Analyses in this study were conducted under two scenarios. Scenario 1 applies the complex sample weights created by the Centers for Disease Control and imputes values for missing responses. Scenario 2 treats the data as a panel - no weighting combined with removal of persons with missing data. Scenario 1 reflects the use of BRFSS data for public health and policy, while Scenario 2 reflects data as it is commonly used in social science research studies.ResultsThe bereavement screening item has a response rate (RR) of 69.1% (5206 of 7534 persons). Demographic subgroups and categories of health have RR of 55% or more. Under Scenario 1, the estimated prevalence of bereavement is 45.38%, meaning that 3,739,120 adults reported bereaved in 2018 or 2019. The estimated prevalence is 46.02% with Scenario 2 which removes persons with any missing data (4,289 persons). Scenario 2 overestimates the bereavement prevalence by 1.39%. An illustrative logistic model is presented to show the performance of exposure to bereavement under the two data scenarios.ConclusionsRecent bereavement can be ascertained in a surveillance survey accounting for biases in response. Estimating bereavement prevalence is needed for measuring population health. This survey is limited to one US state in a single year and excludes persons aged 17 years and younger.

Dataset Information

Sampling and weighting of the Austrian Psychiatric Prevalence Survey (APPS).

Publications

Sampling and weighting of the Austrian Psychiatric Prevalence Survey (APPS).

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