When numbers make you feel: Impact of round versus precise numbers on preventive health behaviors

Wadhwa, Monica; Zhang, Kuangjie

doi:10.1016/j.obhdp.2018.08.005

Cited by 12 publications

(9 citation statements)

References 52 publications

(69 reference statements)

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“…We also contribute to the broader literature on the effects of numerical roundness and precision. These characteristics of numerical information can affect how numbers are processed ( Wadhwa and Zhang, 2015 , 2019 ), how different targets are evaluated ( Pena-Marin and Bhargave, 2016 ; Gunasti and Ozcan, 2019 ), and behavioral outcomes including financial decision-making ( Isaac et al, 2020 ), responses to health messages ( Wadhwa and Zhang, 2019 ), and consumer preferences ( Santana et al, 2020 ). We show that numerical information can affect a novel outcome: whether to engage in self-temporal or other-focused comparisons.…”

Section: Discussionmentioning

confidence: 99%

Numerical Feedback Roundness Affects the Choice of the Self vs. Others as a Reference Point

Shoham

Munichor

2021

Front. Psychol.

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People can use social or personal information as a reference point against which they compare their performance. While previous research has shown that reference point choice can be affected by individual characteristics, situational factors, and goals, we suggest that properties of the performance feedback itself can also play a role in this choice. We focus on the effects of round vs. precise numerical feedback on reference point preferences. In three studies, we show that people are more likely to use themselves as a reference point to evaluate their performance following a feedback in the form of a round score (e.g., a score of 70 in a task) and to use others as a reference point following a precise score (e.g., a score of 71). Study 1 shows decreased interest in comparisons with others following round rather than precise feedback. Study 2 shows that round (vs. precise) feedback also increases actual choice of the self (vs. others) as a reference point. Study 3 demonstrates that the effect of the numerical feedback on reference point preferences extends to the choice of a benchmark for future comparisons. We discuss the implications of our results for the literature and practice, including how this can be used to encourage desirable behaviors.

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Section: Discussionmentioning

confidence: 99%

Numerical Feedback Roundness Affects the Choice of the Self vs. Others as a Reference Point

Shoham

Munichor

2021

Front. Psychol.

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“…Some of these factors studied were health information seeking (Bagherzadeh et al, 2021;Chew & Chng, 2021;Stewart et al, 2004), health knowledge, health education, health information search, and informational experience (Ben Ayed & El Aoud, 2021;Noor et al, 2014), health communication (Han et al, 2014;J. Liu et al, 2020;Seiter & Brophy, 2020;Son et al, 2017), message framing (Bahety et al, 2021;Luoto et al, 2014;Siu, 2007;Wadhwa & Zhang, 2019), virtual reality technology (Choi & Noh, 2020), e-health literacy (Suanrueang et al, 2022), and nudge (Bronchetti et al, 2015). These factors were related to the information search carried out by consumers to make an informed PHB adoption decision.…”

Section: Theory References Amentioning

confidence: 99%

“…Cost-effectiveness analysis can help identify opportunities that are sometimes neglected and possess gains in health at a relatively lower cost. (Jayanti & Burns, 1998;Yap et al, 2014), health value (Hurdle, 1998), risk perception (Dao & Lim, 2022;Dinoff & Kowalski, 1999;Fish, 2009;Lobello & Underhill, 2012;Meischke et al, 2000;Samadipour et al, 2022), message framing (Siu, 2007;Wadhwa & Zhang, 2019), attitude, health knowledge (Goodwin et al, 2019;Roters et al, 2010;Zhang et al, 2017), and health literacy (Joseph & Fleary, 2021;Suanrueang et al, 2022). Other critical personal factors also came under the characteristics section of the TCCM framework-based analysis performed in Study-2.…”

Section: Future Research Agendamentioning

confidence: 99%

“…Perceived health competence and perceived risk (Charlson et al, 2008; Gallant & Dorn, 2001; Gebhardt et al, 2001; Matejic et al, 2011; Wright et al, 2009) are cognitive evaluations the consumers do for making a PHB decision. Information and knowledge‐seeking predictors : Among information and knowledge‐seeking predictors, studies examined the role of various predictors that could lead to PHB decisions. Some of these factors studied were health information seeking (Bagherzadeh et al, 2021; Chew & Chng, 2021; Stewart et al, 2004), health knowledge, health education, health information search, and informational experience (Ben Ayed & El Aoud, 2021; Noor et al, 2014), health communication (Han et al, 2014; J. Liu et al, 2020; Seiter & Brophy, 2020; Son et al, 2017), message framing (Bahety et al, 2021; Luoto et al, 2014; Siu, 2007; Wadhwa & Zhang, 2019), virtual reality technology (Choi & Noh, 2020), e‐health literacy (Suanrueang et al, 2022), and nudge (Bronchetti et al, 2015). These factors were related to the information search carried out by consumers to make an informed PHB adoption decision. Temporal predictors : Studies also examined the role of cognitive rational evaluations done by the consumers in the form of time preference (Chapman et al, 2001), time patterns, and delay discounting (Epstein et al, 2022) as factors impacting their PHB choices. Social factors : Among social factors, the widely researched constructs are social support (Baker & Silverstein, 2008; Mayne, 1999; Mo & Winnie, 2010; Sriyakul & Jermsittiparsert, 2021), avoidance of social conflict (Keresztes et al, 2015), social mobility (Missinne et al, 2015), structural and cognitive social capital (Limbu et al, 2018), social network (Becker et al, 2006; Kapadia‐Kundu et al, 2014; Marimuthu, 2019; Southwell et al, 2010), family support (Marinthe et al, 2022), and social liberation (Chang et al, 2003).…”

Section: Study Findingsmentioning

confidence: 99%

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Preventive healthcare behavior: A hybrid systematic literature review (1998–2023)

De,

Sondhi,

Bhattacharjee

et al. 2023

Int J Consumer Studies

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Preventive healthcare behavior (PHB) refers to actions taken by consumers to avert possible incidences of lifestyle diseases. Over the years, diverse approaches have been used to comprehend the complex nature of PHB. This paper follows a three‐step process to examine work done in the PHB domain. At the outset, past literature was examined. This review included PHB models and frameworks, followed by a root‐cause analysis to identify factors that impacted PHB adoption. A systematic literature review (SLR) using a domain‐based hybrid review approach was the study's third and most crucial part. The SPAR‐4‐SLR (scientific procedures and rationales for systematic literature reviews) protocol was used to conduct the hybrid review, involving two separate review studies. In the first study, a bibliometric analysis was carried out, wherein a trend analysis was conducted on an initial pool of 1011 primary peer‐reviewed publications (1998–2023). The trend analysis was followed by a co‐citation network analysis of 39,608 secondary articles, which validated the importance of primary articles as indicated by the co‐citations in these secondary articles. Further, a purification process based on reliability, validity, and replicability criteria resulted in a final pool of 190 relevant articles. These articles were subjected to a thematic analysis. Next, a framework‐based review based on the theories, contexts, characteristics, and methods (TCCM) framework was conducted on the 190 articles. This step validated the primary study findings. Additionally, it examined and reported the underlying theories, context (country level), characteristics, and methods adopted by previous PHB studies. This analysis helps in indicating the future research agenda regarding PHB. Furthermore, the inferences drawn from the two studies were used to propose a conceptual framework for understanding consumers' PHB decisions based on the antecedents, decisions, and outcomes (ADO) framework. The framework posits that specific personal, demographic, cultural, social and socioeconomic factors are precursors to PHB adoption. This PHB adoption, in turn, has positive outcomes such as enhanced quality of life, consumer wellbeing, health promotion, health behavior change, and planning. The comprehensive review and proposed framework will significantly help advance knowledge about PHB. Apart from contributing to the academic literature, learnings from this study hold value for practitioners at the global level for designing actionable strategies for preventive healthcare products and services.

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“…It is necessary to note that, despite the large number of methods for disseminating knowledge on the theory of healthy lifestyles among students, there is insufficient attention to such an important aspect as the development of their health-saving behavior (Demkina, 2016). Preventive behavior of people (Wadhwa & Zhang, 2019), which becomes a part of health-saving behavior is also of great importance. According to the World Health Organization, health is for 50-55% determined by the lifestyle of a person, for 20% dependent on heredity, for 20-25% on the environment and for 8-12% on the work of health system.…”

Section: Introductionmentioning

confidence: 99%

Formation Of Health-Saving Behavior Of Modern University Students

Goryunova¹

2019

The European Proceedings of Social and Behavioural Sciences

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When numbers make you feel: Impact of round versus precise numbers on preventive health behaviors

Cited by 12 publications

References 52 publications

Numerical Feedback Roundness Affects the Choice of the Self vs. Others as a Reference Point

Numerical Feedback Roundness Affects the Choice of the Self vs. Others as a Reference Point

Preventive healthcare behavior: A hybrid systematic literature review (1998–2023)

Formation Of Health-Saving Behavior Of Modern University Students

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