PubMed Health⌕ Search

PubMed · 16996299

Reducing depression stigma using a web-based program.

Abstract

OBJECTIVE: This study was designed to investigate the efficacy and feasibility of a web-based depression stigma education tool for healthcare professionals. METHODS: A web-based depression stigma program utilizing adult learning theories was developed. Forty-two consecutive subjects were enrolled from University of Maryland staff and graduate students. Primary outcomes were Bogardus Social Distance Scale with a vignette on major depression disorder (BSDS-MDD) and the Depression Stigma Scale (DSS) administered before and after the intervention. RESULTS: Internet-based education significantly decreased the level of depression stigma (BSDS-MDD 10.6+/-4.4 versus 7.2+/-4.4, p<0.001; DSS-personal 12.7+/-7.2 versus 7.8+/-5.3, p<0.001; DSS-perceived 21.7+/-5.5 versus 12.4+/-5.5, p<0.001). After the educational intervention the subjects' knowledge about depression significantly improved (pre-test DKS=18.2+/-8.2 versus post-test DKS=20.6+/-4.1, p<0.001). The program was very well accepted by participants. For 100% of participants, it was not difficult to operate the program. CONCLUSIONS: Computer-assisted education was effective in reducing the stigma of depression and increasing knowledge about depressive disorder. A web-based intervention has the potential to be used for educating graduate students and university staff about depression and for reducing depression stigmata. Healthcare professionals interacting with people with stigmatizing conditions can benefit from web-based computer education.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Joseph Finkelstein, Oleg Lapshin. 2006-09-20. Reducing depression stigma using a web-based program.. https://doi.org/10.1016/j.ijmedinf.2006.07.004

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Overview of informatics for high content screening.

With the growing use of high content screening (HCS) and analysis in drug discovery and systems biology, informatics has come to the forefront as a critical technology to effectively utilize the massive volumes of high content data and images being generated. Informatics technologies are required to transform HCS data and images into useful information and then into knowledge to drive decision making in an efficient and cost effective manner. In this chapter, we provide an overview of informatics tools and technologies for HCS, discuss some of the challenges of harnessing the huge and growing volumes of HCS data, and provide insight to help toward implementing or selecting, and utilizing a high content informatics solution to meet your organization's needs.

Computers↗

The Dutch neuromuscular database CRAMP (Computer Registry of All Myopathies and Polyneuropathies): development and preliminary data.

Each of the various neuromuscular diseases is rare. Consequently, solid epidemiological data are not available and it is often difficult to find sufficient patients for studies. For this reason, the Dutch neuromuscular database, CRAMP (Computer Registry of All Myopathies and Polyneuropathies), was developed in 2004 by the Dutch Neuromuscular Research Support Centre, to store information on patient characteristics and diagnoses (based on Rowland and McLeod's classification) in a uniform and easily retrievable manner. Care was taken to preserve data confidentiality. It is envisaged that CRAMP will prove particularly useful for studies in which multicentre collaboration is needed to recruit a sufficiently large number of patients. More than 10,000 patients with neuromuscular diseases (4,837 female, 5,476 male) have been registered since 2004, half of whom (n=5059) have peripheral nerve disorders.

Computers↗

Factors associated with improved completion of computerized clinical reminders across a large healthcare system.

OBJECTIVE: To analyze the relationship of completion rates for a standardized set of computerized clinical reminders across a large healthcare system to practice and provider characteristics. METHODS: The relationship between completion rate for 13 standardized reminders at 49 primary care practices in the VA New England Healthcare System for a 30-day period and practice characteristics, provider demographics and, via survey, provider attitudes was analyzed. RESULTS: There was no difference in clinical reminder completion rate between staff physicians versus nurse practitioners/physician assistants (87.6% versus 88.1%) but both were better than residents (76.6%, p<0.0001). With residents excluded, there were no differences between hospital and community-based clinics or between teaching and non-teaching sites. Clinical reminder completion rate was lower for sites that did not fully utilize support staff in completion process versus sites that did (82.4% versus 88.1%, p<0.0001). Analysis of survey results showed no correlation of completion rate with provider demographics or attitudes towards reminders. However there was significant correlation with frequency of receiving individual feedback on reminder completion (r=0.288, p=0.004). CONCLUSION: Completion of computerized clinical reminders was not affected by a variety of provider characteristics, including professional training, demographics and provider attitude, although was lower among residents than staff providers. However incorporation of support staff into clinic processes and individualized feedback to providers were strongly associated with improved completion. These findings demonstrate the importance of considering practice and provider factors and not just technical elements when implementing informatics tools.

Computers↗