Evidence map›Paper›PMID 39624374›Full record

ArticleFrontiers in psychology2024

Crowd-counting technology within the Smart City context: understanding, trust, and acceptance.

Theresa Waclawek, Angela Fiedler, Melissa Schütz, Astrid Schütz

Abstract read
In one paragraph

Article in Frontiers in psychology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Theresa WaclawekDepartment of Psychology, University of Bamberg, Bamberg, Germany.
Angela FiedlerDepartment of Psychology, University of Bamberg, Bamberg, Germany.
Melissa SchützDepartment of Psychology, University of Bamberg, Bamberg, Germany.
Astrid SchützDepartment of Psychology, University of Bamberg, Bamberg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In city centers worldwide, including the UNESCO World Heritage Site of Bamberg's old town in Germany, alleviating pedestrian overcrowding is a pressing concern. Leveraging crowd-counting technologies with real-time data collection offers promising solutions, yet poses challenges regarding data privacy and informed consent. This preregistered study examines public response to a Smart City Bamberg project aimed at addressing pedestrian congestion through crowd-counting methods. We investigate informed consent by looking at understanding and acceptance of the project, as well as influencing factors, such as effectiveness of project explanation and trust. Through a three-stage study comprising exploratory interviews, a field study, and an online study, we reveal that the focus of project explanations significantly impacts understanding: Functional explanations, emphasizing project purpose, enhance comprehension compared to mechanistic explanations detailing project components. Additionally, project trust positively correlates with acceptance. Notably, understanding impacts acceptance through increased project trust. These findings underscore the importance of fostering understanding to garner public acceptance of crowd-counting projects. It is important, especially in the case of projects which aim to improve quality of life while also prioritizing robust data protection, that decisions regarding informed consent are grounded in comprehension rather than on preconceived biases against data sharing. Efforts should prioritize effective explanations to bolster project trust and consequently, promote acceptance.

Indexed as

acceptanceanonymizationcrowd-counting technologyexplanationSmart Citytrustunderstandingurban overcrowding

Identifiers

PMID39624374
PMCPMC11608974

What OpenQuestion holds

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Registered trials

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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.