[Population-based health monitoring via computer-assisted telephone interviews in Bavaria].

Gesundheitswesen

CATI-Projekt, Bayerischer Forschungsverbund Public Health - Offentliche Gesundheit, München.

Published: August 2001

From June 1999 until May 2000, 2051 computer-assisted telephone interviews concerning health and health related behaviours were assessed in Bavarian households. The aim of the study was the evaluation of the validity and representativity of this data by a comparison of selected variables from the Bavarian Mikrozensus-survey 1999. The distribution patterns of the marital status, the size of the households, the gainful employment, the household-netto-income, the school qualification and of the smoking status correspond well with those of the Mikrozensus 1999. As often found in questionnaire based surveys, a disproportionately high rate of participation of highly educated persons was observed. This led to an effect only in terms of a too small rate of persons with a low household-netto-income. Within the study, two different designs were compared. The commitment of the telephone numbers to a gender for an equal quotation of men and women led to an under-representation of single-households and therefore also of unmarried persons, but it had no effect on the other characteristics. The results of this study show, that the method of computer assisted-telephone interviews is a valid and cheap basis for the establishment of an exhaustive health surveillance system in Germany.

Download full-text PDF

Source
http://dx.doi.org/10.1055/s-2001-16423DOI Listing

Publication Analysis

Top Keywords

computer-assisted telephone
8
telephone interviews
8
[population-based health
4
health monitoring
4
monitoring computer-assisted
4
interviews bavaria]
4
bavaria] june
4
june 1999
4
1999 2000
4
2000 2051
4

Similar Publications

Objective: This study examines the national prevalence of mental health disorders and their associated factors in Lebanon, specifically in the aftermath of the 2020 events, including the catastrophic events of Beirut blast and the concurrent financial meltdown amid the global pandemic.

Methods: Conducted between July and September 2022, the study interviewed a nationally representative sample of 1,000 Lebanese via telephone, using the Computer Assisted Telephone Interview (CATI) system. Gender-specific bivariate and multivariate models were generated for probable posttraumatic stress disorder (PTSD), depression, and anxiety.

View Article and Find Full Text PDF

Background: Results on parental burden during the COVID-19 pandemic are predominantly available from nonrepresentative samples. Although sample selection can significantly influence results, the effects of sampling strategies have been largely underexplored.

Objective: This study aimed to investigate how sampling strategy may impact study results.

View Article and Find Full Text PDF

Machine Learning-Based Quantification of Lateral Flow Assay Using Smartphone-Captured Images.

Biosensors (Basel)

January 2025

Department of Computer and Information Sciences, University of Houston-Victoria, Victoria, TX 77904, USA.

Lateral flow assay has been extensively used for at-home testing and point-of-care diagnostics in rural areas. Despite its advantages as convenient and low-cost testing, it suffers from poor quantification capacity where only yes/no or positive/negative diagnostics are achieved. In this study, machine learning and deep learning models were developed to quantify the analyte load from smartphone-captured images of the lateral flow assay test.

View Article and Find Full Text PDF

Smartphone application-based augmented reality for pre-clinical dental implant placement training: a pilot study.

Oral Maxillofac Surg

January 2025

Research Center for Digital Technologies in Dentistry and CAD/CAM, Department of Dentistry, Faculty of Medicine and Dentistry, Danube Private University, Steiner Landstraße 123, Krems an der Donau, 3500, Austria.

Purpose: Precise implant placement is essential for optimal functional and aesthetic outcomes. Digital technologies, such as computer-assisted implant surgery (CAIS), have improved implant outcomes. However, conventional methods such as static and dynamic CAIS (dCAIS) require complex equipment.

View Article and Find Full Text PDF

In digital image diagnosis using medical displays, it is crucial to rigorously manage display devices to ensure appropriate image quality and diagnostic safety. The aim of this study was to develop a model for the efficient quality control (QC) of medical displays, specifically addressing the measurement items of contrast response and maximum luminance as part of constancy testing, and to evaluate its performance. In addition, the study focused on whether these tasks could be addressed using a multitasking strategy.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!