Patient perceptions of three-dimensional (3D) surface imaging technology and traditional methods used to assess anthropometry.

3D surface imaging Body image Body morphology Obesity Weight management

Journal

Obesity Pillars (Online)
ISSN: 2667-3681
Titre abrégé: Obes Pillars
Pays: United States
ID NLM: 9918697364706676

Informations de publication

Date de publication:
Mar 2024
Historique:
received: 17 11 2023
revised: 16 01 2024
accepted: 17 01 2024
medline: 15 2 2024
pubmed: 15 2 2024
entrez: 15 2 2024
Statut: epublish

Résumé

Obesity and overweight are commonplace, yet attrition rates in weight management clinics are high. Traditional methods of body measurement may be a deterrent due to invasive and time-consuming measurements and negative experiences of how data are presented back to individuals. Emerging new technologies, such as three-dimensional (3D) surface imaging technology, might provide a suitable alternative. This study aimed to understand acceptability of traditional and 3D surface imaging-based body measures, and whether perceptions differ between population groups. This study used a questionnaire to explore body image, body measurement and shape, followed by a qualitative semi-structured interview and first-hand experience of traditional and 3D surface imaging-based body measures. 49 participants responded to the questionnaire and 26 participants attended for the body measurements and interview over a 2-month period. There were 3 main themes from the qualitative data 1) Use of technology, 2) Participant experience, expectations and perceptions and 3) Perceived benefits and uses. From this study, 3D-surface imaging appeared to be acceptable to patients as a method for anthropometric measurements, which may reduce anxiety and improve attrition rates in some populations. Further work is required to understand the scalability, and the role and implications of these technologies in weight management practice. (University Research Ethics Committee reference number ER41719941).

Sections du résumé

Background UNASSIGNED
Obesity and overweight are commonplace, yet attrition rates in weight management clinics are high. Traditional methods of body measurement may be a deterrent due to invasive and time-consuming measurements and negative experiences of how data are presented back to individuals. Emerging new technologies, such as three-dimensional (3D) surface imaging technology, might provide a suitable alternative. This study aimed to understand acceptability of traditional and 3D surface imaging-based body measures, and whether perceptions differ between population groups.
Methods UNASSIGNED
This study used a questionnaire to explore body image, body measurement and shape, followed by a qualitative semi-structured interview and first-hand experience of traditional and 3D surface imaging-based body measures.
Results UNASSIGNED
49 participants responded to the questionnaire and 26 participants attended for the body measurements and interview over a 2-month period. There were 3 main themes from the qualitative data 1) Use of technology, 2) Participant experience, expectations and perceptions and 3) Perceived benefits and uses.
Conclusion UNASSIGNED
From this study, 3D-surface imaging appeared to be acceptable to patients as a method for anthropometric measurements, which may reduce anxiety and improve attrition rates in some populations. Further work is required to understand the scalability, and the role and implications of these technologies in weight management practice. (University Research Ethics Committee reference number ER41719941).

Identifiants

pubmed: 38357215
doi: 10.1016/j.obpill.2024.100100
pii: S2667-3681(24)00002-0
pmc: PMC10865393
doi:

Types de publication

Journal Article

Langues

eng

Pagination

100100

Informations de copyright

© 2024 The Authors.

Déclaration de conflit d'intérêts

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Lucie Nield (L)

Advanced Wellbeing Research Centre, Sheffield Hallam University, Olympic Legacy Park, Sheffield, S9 3TU, UK.

Michael Thelwell (M)

Advanced Wellbeing Research Centre, Sheffield Hallam University, Olympic Legacy Park, Sheffield, S9 3TU, UK.

Audrey Chan (A)

Sheffield Business School, City Campus, Sheffield Hallam University, S1 1WB, UK.

Simon Choppin (S)

Advanced Wellbeing Research Centre, Sheffield Hallam University, Olympic Legacy Park, Sheffield, S9 3TU, UK.

Steven Marshall (S)

Sheffield Business School, City Campus, Sheffield Hallam University, S1 1WB, UK.

Classifications MeSH