ReviewFrontiers in veterinary science2024
An overview of the literature on assistance dogs using text mining and topic analysis.
Review in Frontiers in veterinary science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Development and Validation of an IMU Sensor-Based Behaviour-Alert Detection Collar for Assistance Dogs: A Proof-of-Concept Study.Animals : an open access journal from MDPI · 2025Article
- Low Vision Rehabilitation and Eye Exercises: A Comprehensive Guide to Tertiary Prevention of Diabetic Retinopathy.Life (Basel, Switzerland) · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
It is said that dogs are human's best friend. On occasion, dogs can be raised and trained to provide additional specific benefits to humans suffering from a range of physical or mental conditions, working as assistance dogs. In this article, we employed innovative techniques to review the vast and constantly expanding literature on the subject, which covers a multitude of aspects. The 450 articles obtained through keyword search on Scopus were initially described in terms of year of publication, geographical context and publication destination, and were subsequently analysed through automated text mining to detect the most important words contained within them. Lastly, a generative model of topic analysis (Latent Dirichlet Allocation-LDA) described the content of the collection of documents, dividing it into the appropriate number of topics. The results yielded interesting insights across all domains, demonstrating the potential of automated text mining and topic analysis as a useful tool to support the researchers in dealing with complex and time-consuming subjects' reviews, integrating the work done with traditional reviewing methods.
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.