Frontiers in Public Health (Oct 2015)
Consumer Perceptions of Digital Health Coaching
Abstract
Background As digital technology and cognitive computing develop, the solutions they offer can be capitalised on by healthcare. In the scope of behavioural change, these solutions can range from activity tracking applications to complex artificial intelligence powered platforms, capable of answering health-related questions, becoming virtual assistants in health management and disease prevention. Our current research focuses on digital coaching in the context of health and well-being. Traditionally, health coaching denotes a set of methods to help an individual manage or prevent health conditions. A health coach uses a range of techniques to assist the individual in health-promoting behaviour change. We define a digital coach as a set of digital programs that can pro-actively help an individual to manage their health. A digital coach analyses health-related data submitted by the user and provides feedback, answers, encouragements, and warnings, when user’s behaviour or requests prompt it to do so. Unlike activity tracking applications for fitness, comprehensive digital solutions for health, based on solid research, are only beginning to gain their momentum. Thus it is important to form a detailed picture of the potential users of digital coaching, their expectations, demands, and apprehensions. This would make future designs well-informed and lead to better customer satisfaction and intervention effectiveness. Aim Our research objective is to understand consumer perception of digital coaching, and how various factors influence this perception and willingness to engage with a digital coach. We analyse not only the more classical factors of age, gender, and income, but such characteristics as consumers’ preferred health network, the level of trust they put into technology, previous coaching experience, preferred types of digital services, and favoured features and methods of interaction with these services. Careful analysis of how these factors influence consumer perception of digital coaching allows us to gain insight into the major characteristics of populations who are currently receptive to the idea of digital coaching and to identify factors that make other populations resist it. Methods In August-September 2015, we conducted an on-line quantitative survey of 5000 consumers across Spain, UK, Australia, China (Tier 1 cities) and the United States in their native languages. We recruited population samples, balanced across the five countries, genders and age ranges. Each recruited consumer had at least one of the following attributes: - Had received face-to-face health/lifestyle coaching - Currently managed a condition - Previously had or are recovering from a condition Participants were asked 37 questions relating to their demographics, general health management, use of digital technology, experience with various types of coaching, and a series of questions about digital coaching. The questions ranged from Likert scales to multiple choice questions to free text. Each participant provided over 180 data points. Due to the space limit we report on the analysis results of one question of special interest, relating directly to participants’ opinion on digital coaching: “How useful do you think this type of solution (digital coaching) would be as a purely digital, computer based service?” This question directly followed a series of questions about coaching in general and digital coaching in particular, their potential usefulness and possible features. The response to the question in focus was represented by a 5-point Likert scale (1 - Not at all useful, 5 – Extremely useful). Results To investigate the influence of different independent factors on the outcomes of the question we have performed several ANOVA analyses. Since our sample size is large (5000), we emphasise the importance of the effect size (η^2) in our analysis, which allows us to quantitatively measure the strength of a phenomenon, e.g., the effect of age on the perceived usefulness of digital coaching. The following independent factors that had medium to strong effect on the perceived usefulness of digital coaching: - The role of technology a participant is willing to consider for health management with different roles being “coach”, “companion”, “concierge”, “supporter”, “therapist”, and “none”. - The perceived level of new technology adopter, rated by the participant on a 5-point Likert scale from 1– “the last” to 5 – “the first”. - The likelihood of the participant to consider general coaching for health and wellness on a 5-point Likert scale from 1- “extremely unlikely” to 5 – “extremely likely”, where 20.72% chose the “extremely likely” option. - The likelihood of the participant to consider general coaching for health and wellness, designed and tailored for them, on a 5-point Likert scale from 1- “extremely unlikely” to 5 – “extremely likely”, where 24.72% chose the “extremely likely” option. The perceived role of technology accounted for 13.5% (F(5,4880)=152.86,p<.001) of the variance in the perceived usefulness of a digital coach. Post-hoc Tukey's HSD tests showed that participants who saw the role of technology as “coach” were significantly more likely to perceive digital coaching as useful (p<.01 for all group comparisons). New technology adopter levels accounted for 9.9% (F(4, 4878) = 134.70, p <.001) of the variance in the perceived usefulness of a digital coach. Post-hoc Tukey’s HSD tests showed that participants who reported to be “first adopters” were more likely to perceive digital coaching as useful (p<.001 for all group comparisons). Willingness to receive general health and wellness coaching, including programs tailored and designed for each specific user accounted for 25.3% (F(4, 4887) = 414.49, p<.001) and 22.1% (F(4, 4881) = 346.52, p<.001) respectively. For both factors, participants who ranked highest in their willingness to consider general health coaching found digital coaching more useful than other groups (p<.001 for all group comparisons). Gender, age, country of origin, income, reported state of general health, and other factors had negligible to no effect. Conclusions Our research shows that the perception of digital coaching does not vary between clean cut demographic groups, defined by gender or country of origin. Neither does the general health state pay a decisive factor. The factors that do impact user perception on digital coaching are mostly related to their attitude towards health coaching in general. Another set of influential factors are their opinion in digital technology and their readiness to explore new technological solutions.
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