Abstract
When considering subcultures, it is useful to identify if different program modalities appeal to different demographic segments of the population. In some cases, such as male-dominated technology workplaces, demographic characteristics such as female gender may define a subculture. In other cases, trends by demographics may exist within or external to a subculture. For example, different participation trends by age may manifest within the subculture of manufacturing populations. Alternatively, demographic trends can be analyzed for the population overall (external to subcultures). While demographics alone do not necessarily define a subculture, participation trends across different modalities can offer insights for strategies.
Participation data from 615 976 employees who were offered the program modalities sponsored by their employer and delivered via a third party well-being vendor were analyzed to look for differences in participation by demographic characteristics. The analysis was limited to those eligible during the 2017 calendar year. Logistic regression procedures controlling for incentive design were used to analyze the odds of participation across 3 types of programs (coaching, online modules, and device tracking).
Odds ratios are presented in Table 2, comparing each group to the same reference group, which is designated by missing data in the table. For example, the probability of female participation is compared to male participation. Results higher than 1.0 indicate greater likelihood compared to the reference group while results lower than 1.0 indicate lower likelihood to participate.
Odds of Participation by Demographic Characteristics.
a P < .001.
b P < .05.
Women were more likely to participate in well-being activities than men: 78% more likely to participate in online modules compared to men, followed by 64% in device tracking and 61% in coaching. The likelihood of engaging in technology-based modalities (online modules/tracking) to support well-being habits decreases with age. Coaching appealed similarly between Millennial, Generation X, Baby Boomer, and the Silent generations. Online Modules had similar appeal for those with incomes up to $75K and less appeal for those above that. Coaching participation is most likely among lower income households. Participation across all types of programs tends to be lower as income increases.
Individual preferences to participate in different types of programs underscore the need to provide a variety of modalities and program types to meet the needs of subgroups within a population. Additionally, understanding the needs of population subgroups can inform decisions about resource allocation and the tactics required to support participation strategies. For example, for a predominantly older male population, coaching is the modality most likely to be successful. Device tracking is more likely to have strong uptake among Millennials and Baby Boomer age groups. Coaching appealed universally across age groups and may be useful to encourage people to engage in modalities beyond their “comfort zone.” A possible method for maximizing uptake of technology among older individuals is to pair modalities such as coaching with technology-based resources such as apps, online modules, and tracking.
Both authors are affiliated with Virgin Pulse. Dr Mary Marzec, PhD is a Senior Researcher and Consultant and Nathan Barleen is Director of Research.