Title |
An Ethical Framework for Automated, Wearable Cameras in Health Behavior Research
|
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Published in |
American Journal of Preventive Medicine, March 2013
|
DOI | 10.1016/j.amepre.2012.11.006 |
Pubmed ID | |
Authors |
Paul Kelly, Simon J. Marshall, Hannah Badland, Jacqueline Kerr, Melody Oliver, Aiden R. Doherty, Charlie Foster |
Abstract |
Technologic advances mean automated, wearable cameras are now feasible for investigating health behaviors in a public health context. This paper attempts to identify and discuss the ethical implications of such research, in relation to existing guidelines for ethical research in traditional visual methodologies. Research using automated, wearable cameras can be very intrusive, generating unprecedented levels of image data, some of it potentially unflattering or unwanted. Participants and third parties they encounter may feel uncomfortable or that their privacy has been affected negatively. This paper attempts to formalize the protection of all according to best ethical principles through the development of an ethical framework. Respect for autonomy, through appropriate approaches to informed consent and adequate privacy and confidentiality controls, allows for ethical research, which has the potential to confer substantial benefits on the field of health behavior research. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 2 | 29% |
New Zealand | 1 | 14% |
Austria | 1 | 14% |
United States | 1 | 14% |
Unknown | 2 | 29% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 6 | 86% |
Scientists | 1 | 14% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 4 | 2% |
United Kingdom | 4 | 2% |
Spain | 2 | <1% |
France | 1 | <1% |
Saudi Arabia | 1 | <1% |
Unknown | 193 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 39 | 19% |
Researcher | 37 | 18% |
Student > Master | 25 | 12% |
Professor > Associate Professor | 14 | 7% |
Professor | 13 | 6% |
Other | 45 | 22% |
Unknown | 32 | 16% |
Readers by discipline | Count | As % |
---|---|---|
Social Sciences | 29 | 14% |
Computer Science | 25 | 12% |
Medicine and Dentistry | 25 | 12% |
Psychology | 17 | 8% |
Nursing and Health Professions | 12 | 6% |
Other | 48 | 23% |
Unknown | 49 | 24% |