=Paper=
{{Paper
|id=Vol-2629/14_poster_robles.pdf
|storemode=property
|title=How Are We Measuring Persuasiveness on Health Interventions?
|pdfUrl=https://ceur-ws.org/Vol-2629/14_poster_robles.pdf
|volume=Vol-2629
|authors=Noemí Robles,Beni Gómez-Zúñiga,Modesta Pousada,Eulàlia Hernandez,Manuel Armayones
|dblpUrl=https://dblp.org/rec/conf/persuasive/RoblesGPHA20
}}
==How Are We Measuring Persuasiveness on Health Interventions?==
https://ceur-ws.org/Vol-2629/14_poster_robles.pdf
How Are We Measuring Persuasiveness on Health
Interventions?
Noemí Robles1, Beni Gómez-Zúñiga2, Modesta Pousada2, Eulàlia
Hernandez1, Manuel Armayones1
eHealth Center, Universitat Oberta de Catalunya
Faculty of Psychology and Education Sciences, Universitat Oberta de Catalunya
1 Introduction
One of the big challenges of health interventions is their capability of producing real
and sustained changes in health-related habits, such as reducing/eliminating certain un-
healthy behaviors (smoking and drinking patterns), increase others (physical activity)
or promoting new ones (adherence to treatment). Some authors highlight the relevance
of developing tailored
Interventions instead of generalists approaches for increasing the success in health
results. According to this thread, one of the aspects to consider could be the capability
of these interventions to persuade people to change their health-related behavior. Fol-
lowing this approach, it is crucial to count on validated tools that allows to evaluate the
potential persuasiveness of health interventions that could be useful for identifying the
strengths and weaknesses of health interventions and ensure their success.
2 Objective
The aim of this study was to review the existing validated tools for assessing persua-
siveness on health interventions.
3 Methodology
A literature review was conducted using peer-reviewed publication databases (Medline,
PsycInfo) and manual searches in search engines (Google Scholar, Google) and re-
search networks (Research Gate). The keywords for the search were “persuas*”,
“scale” or “questionnaire”, “health intervention” and “validation”. There were no re-
strictions in publication date and language. Only articles about scales/questionnaires
validation were considered. Those publications related to marketing and sales were ex-
cluded from the analysis.
Persuasive 2020, Adjunct proceedings of the 15th International conference on Persuasive Tech-
nology. Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons
License Attribution 4.0 International (CC BY 4.0)
4 Results
The results of the literature review showed a scarce number of validated question-
naires/scales for assessing persuasiveness, and only one specific tool focused on health
(Boster et al., 2011).
Three main areas of assessment were identified: Person Susceptibility to Persuasion,
Social Influence and Intervention Characteristics.
Regarding Person Susceptibility, assessment was centered on several personality
constructs such as assertiveness, self-control or need of unique choice. When assess-
ment focused on Social Influence, some of the elements considered were competition,
social comparison or social learning. Finally, those tools centered on Intervention/Tech-
nology Characteristics assessed aspects such as design aesthetics, unobtrusiveness,
quality or effectiveness. In this group of assessment tools, Letho et al. (2012) also in-
cluded in their scale the perceived persuasion of the product in terms of the capability
of the intervention to influence and promote changes.
Additionally, Meschtscherjakov et al. (2016) had developed the Persuasive Potential
Questionnaire (PPQ) which considered both Person Susceptibility and Interven-
tion/Technology Characteristics but focusing not specifically in design and usability
but in its persuasibility elements (named as System Persuasive Potential).
Next step will be a more in depth analysis of the theoretical models for designing
these assessment tools. A preliminary analysis showed that some of them were based
on the Persuasive Systems Design Model by Oinas-Kukkionen & Harjumaa (2009) and
on Kaptein and colleagues works.
5 Conclusions
There is a lack of specific validated tools for assessing the persuasiveness of health
interventions. Reviewing literature, the assessment of health interventions for changing
habits is mainly carried out through qualitative techniques, ad hoc surveys or analyzing
health variables (engagement, reduction/increase of behavior, etc.).
According to the analysis of those validated tools identified in the study the assess-
ment focuses on three cornerstones: personality variables, intervention/technology
characteristics and social influence that usually are considered as independent elements.
Future directions could include a more comprehensive and specific research on how
to assess the potential persuasiveness of health interventions in order to increase their
success.
6 References
1. Boster, F. J., Kotowski, M. R., Andrews, K. R., & Serota, K. (2011). Identifying Influence:
Development and Validation of the Connectivity, Persuasiveness, and Maven Scales. Jour-
nal of Communication, 61(1), 178–196. https://doi.org/10.1111/j.1460-2466.2010.01531.x
2. Kaptein, M., & Eckles, D. (2012). Heterogeneity in the Effects of Online Persuasion. Jour-
nal of Interactive Marketing, 26(3), 176–188. https://doi.org/10.1016/j.intmar.2012.02.002
3. Lehto, T., Oinas-Kukkonen, H., & Drozd, F. (2012). Factors Affecting Perceived Persua-
siveness of a Behavior Change Support System. ICIS 2012 Proceedings. Retrieved from
https://aisel.aisnet.org/icis2012/proceedings/HumanBehavior/18
4. Meschtscherjakov, A., Gärtner, M., Mirnig, A., Rödel, C., & Tscheligi, M. (2016). The Per-
suasive Potential Questionnaire (PPQ): Challenges, drawbacks, and lessons learned. Lecture
Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and
Lecture Notes in Bioinformatics), 9638, 162–175. https://doi.org/10.1007/978-3-319-
31510-2_14
5. Oinas-Kukkonen, H., & Harjumaa, M. (2009). Persuasive Systems Design: Key Issues, Pro-
cess Model, and System Features. Communications of the Association for Information Sys-
tems, 24, 485–500. https://doi.org/10.17705/1CAIS.02428