ArticleBMC infectious diseases2017
Prevention of tick bites: an evaluation of a smartphone app.
Article in BMC infectious diseases, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 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
15 citing papers in PubMed.
- Exploring stakeholder perceptions and priorities related to reducing tick-related public health risks in natural environments of the United Kingdom.BMC public health · 2025Article
- Seroprevalence of tick-borne infections in blood donors in Europe: a systematic review.New microbes and new infections · 2025Review
- Unveiling Misconceptions among Small-Scale Farmers Regarding Ticks and Tick-Borne Diseases in Balochistan, Pakistan.Veterinary sciences · 2024Article
- Perception of risk among children: Exploring the risk of TB-rickettsial disease based on the children's drawing pictures in a Mayan community of Yucatan.Health promotion perspectives · 2023Article
- A One Health Evaluation of the Surveillance Systems on Tick-Borne Diseases in the Netherlands, Spain and Italy.Veterinary sciences · 2022Article
- Comparison of national surveillance systems for Lyme disease in humans in Europe and North America: a policy review.BMC public health · 2022Review
- Personal protection measures to prevent tick bites in the United States: Knowledge gaps, challenges, and opportunities.Ticks and tick-borne diseases · 2022Review
- Behavioral risk factors associated with reported tick exposure in a Lyme disease high incidence region in Canada.BMC public health · 2022Article
- Community engaged tick surveillance and tickMAP as a public health tool to track the emergence of ticks and tick-borne diseases in New York.PLOS global public health · 2022Article
- Potential for online crowdsourced biological recording data to complement surveillance for arthropod vectors.PloS one · 2021Article
- Article
- Googling for Ticks and Borreliosis in Germany: Nationwide Google Search Analysis From 2015 to 2018.Journal of medical Internet research · 2020Article
- Mobile application-based guidelines to enhance patient care and provider education in trauma and acute care surgery.Trauma surgery & acute care open · 2020Article
- Usability and Feasibility of a Smartphone App to Assess Human Behavioral Factors Associated with Tick Exposure (The Tick App): Quantitative and Qualitative Study.JMIR mHealth and uHealth · 2019Article
- "Tekenscanner": a novel smartphone application for companion animal owners and veterinarians to engage in tick and tick-borne pathogen surveillance in the Netherlands.Parasites & vectors · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLyme borreliosis (LB) is the most common reported tick-borne infection in Europe, and involves transmission of Borrelia by ticks. As long as a vaccine is not available and effective measures for controlling tick populations are insufficient, LB control is focused on preventive measures to avoid tick bites. To inform citizens about the risk of ticks, motivate them to check for tick bites, and encourage them to remove any attached tick as quickly as possible, a mobile app called 'Tekenbeet' (Dutch for 'tick bite') was developed and released. The aim of this study was to evaluate the usage and user satisfaction of the 'Tekenbeet' app and to investigate whether it affects users' knowledge, perceived severity, perceived susceptibility, self-efficacy, response efficacy, current behavior and intention to comply with preventive measures.
methodsUsage of the app was evaluated with data obtained from Google Analytics. A survey among the Dutch general adult population with two data collection periods evaluated the usage, user satisfaction and its influence on abovementioned outcomes.
resultsData obtained from Google Analytics showed the app was downloaded almost 40,000 in the 20 months following the launch. The 'tick radar' and 'tick diary' screens were viewed most often. In addition, a total of 554 respondents completed an online survey. The mean user satisfaction score was 7.44 (on a scale of 1-10) and 90.9% of respondents would recommend the app to others. On average, survey respondents who downloaded the app (n = 243) recorded significantly more often higher knowledge scores (OR 3.37; 95% CI 2.02-5.09) and had a higher intention to comply with preventive measures (OR 2.47; 95% CI 1.22-5.85) compared to respondents who did not download the app (n = 311).
conclusionsThe 'Tekenbeet' app is a frequently used and well-appreciated educational tool to increase public knowledge of ticks and tick bites. It also helps to improve the user's intention to apply preventive measures. The use of smartphones and apps is now commonplace in the Netherlands; the 'Tekenbeet' app feeds into this trend and thereby offers a modern day alternative to established formats such as an information leaflet and information provision on the Internet.
Indexed as
Identifiers
What 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.