Background Health recommender systems (HRSs) offer the potential to motivate and engage users to change their behavior by sharing better choices and actionable knowledge based on observed user behavior. Objective We aim to review HRSs targeting nonmedical professionals (laypersons) to better understand the current state of the art and identify both the main trends and the gaps with respect to current implementations. Methods We conducted a systematic literature review according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and synthesized the results. A total of 73 published studies that reported both an implementation and evaluation of an HRS targeted to laypersons were included and analyzed in this review. Results Recommended items were classified into four major categories: lifestyle, nutrition, general health care information, and specific health conditions. The majority of HRSs use hybrid recommendation algorithms. Evaluations of HRSs vary greatly; half of the studies only evaluated the algorithm with various metrics, whereas others performed full-scale randomized controlled trials or conducted in-the-wild studies to evaluate the impact of HRSs, thereby showing that the field is slowly maturing. On the basis of our review, we derived five reporting guidelines that can serve as a reference frame for future HRS studies. HRS studies should clarify who the target user is and to whom the recommendations apply, what is recommended and how the recommendations are presented to the user, where the data set can be found, what algorithms were used to calculate the recommendations, and what evaluation protocol was used. Conclusions There is significant opportunity for an HRS to inform and guide health actions. Through this review, we promote the discussion of ways to augment HRS research by recommending a reference frame with five design guidelines.

Much topical gamification research has focused on the application of personality trait models and the development of player typologies. These models are often applied under the assumption that personality or gamification user type reside as a stable construct within the individual. However, the preference for gamification strategies as well as their motivational impact, may vary in different contexts and situations. Therefore, our study aimed to disambiguate the different levels of motivation (global, contextual and situational) underlying preferences for gamification strategies, in the specific domain of pro-environmental behaviour. To this end, we developed a gamified mobile app to promote pro-environmental behaviour. Next, 56 participants interacted with the app during on average 22 days, while logs with various game elements were collected. Additionally, participants filled out the Hexad questionnaire to establish gamification user type, a survey polling for intrinsic versus extrinsic motivation towards the environment, and two questionnaires to assess pro-environmental behaviour before and after app usage. Our findings suggest that particularly intrinsic motivation towards the environment predicts preferences for gamification strategies whereas gamification user types fall short. In sum, our study lends support to measuring at different levels of motivation to understand and tailor gamification strategies for pro-environmental behaviour. CCS CONCEPTS• Human-centered computing → Empirical studies in HCI; User models.

BACKGROUND Health recommender systems (HRSs) offer the potential to motivate and engage users to change their behavior by sharing better choices and actionable knowledge based on observed user behavior. OBJECTIVE We aim to review HRSs targeting nonmedical professionals (laypersons) to better understand the current state of the art and identify both the main trends and the gaps with respect to current implementations. METHODS We conducted a systematic literature review according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and synthesized the results. A total of 73 published studies that reported both an implementation and evaluation of an HRS targeted to laypersons were included and analyzed in this review. RESULTS Recommended items were classified into four major categories: lifestyle, nutrition, general health care information, and specific health conditions. The majority of HRSs use hybrid recommendation algorithms. Evaluations of HRSs vary greatly; half of the studies only evaluated the algorithm with various metrics, whereas others performed full-scale randomized controlled trials or conducted in-the-wild studies to evaluate the impact of HRSs, thereby showing that the field is slowly maturing. On the basis of our review, we derived five reporting guidelines that can serve as a reference frame for future HRS studies. HRS studies should clarify who the target user is and to whom the recommendations apply, what is recommended and how the recommendations are presented to the user, where the data set can be found, what algorithms were used to calculate the recommendations, and what evaluation protocol was used. CONCLUSIONS There is significant opportunity for an HRS to inform and guide health actions. Through this review, we promote the discussion of ways to augment HRS research by recommending a reference frame with five design guidelines.