ReviewBundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz2020
[Digital public health-leverage for community capacity building in health promotion : Current situation, developmental issues and TEAviisari as a model implementation].
Review in Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- [Knowledge about human papillomaviruses among students in Germany-a cross-sectional study with a need for action].Urologie (Heidelberg, Germany) · 2025Article
- Mapping Digital Public Health Interventions Among Existing Digital Technologies and Internet-Based Interventions to Maintain and Improve Population Health in Practice: Scoping Review.Journal of medical Internet research · 2024Article
- The digitized chronic disease management model: scalable strategies for implementing standardized healthcare and big data analytics in Shanghai.Frontiers in big data · 2023Article
- Availability of open data for spatial public health research.German medical science : GMS e-journal · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In 1986, the Ottawa charter marked a paradigm shift for public health, putting the focus on strengthening community action and on creating supportive environments for health. A key to this is "capacity building" (CB), which we understand as the development and sustainable implementation of structural capacities, e.g. coordinated data collection, collaboration processes across sectors and reliable provision of basic resources in all areas of local health promotion.Many efforts and three and a half decades later we still envisage infrastructure deficits, scattered public health landscapes and restraints to intersectoral cooperation much too often. While agreement on the theoretical insights on what is needed appears to be broad, translating these insights into practice remains a challenge. In this situation, digital public health (DPH) can contribute to overcoming barriers and making knowledge for action more visible and more accessible. With DPH, data can be integrated, structured and disseminated in novel ways.We discuss why CB at the local level could benefit from technological advances and what DPH might do for the provision of information services on public health capacity. Our focus is on the web-based, interactive representation of public health data for use in information, governance or benchmarking processes. As an example from public health practice, the Finnish tool TEAviisari (National Institute for Health and Welfare, Finland) is presented.The 2020 EU Council Presidency of Germany - with the topics of digitalisation and the common European health data space - offers opportunities to decisively advance the development of CB in health promotion in this country.
Indexed as
Identifiers
32451594What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.