A Systematic Review and Meta-Analysis of Research on Goals for Behavior Change

Research Background and Issues

• What problems or challenges did the authors identify?
  This study highlights that while goals and behavior change (particularly in the health domain) have become significant topics in HCI research, the literature has primarily focused on single-domain goals (e.g., physical activity), neglecting multi-domain goals, social goals, intrinsically motivated goals, and qualitative goals. Additionally, most technological designs lack theoretical support, and there is limited literature evaluating the effectiveness of goal-related technologies.

• Why is this issue important?
  Goals are critical motivational factors for behavior change. A deeper understanding of how goals support behavior change through technology and the evaluation of the actual effectiveness of these technologies can advance the HCI field. Furthermore, the widespread use of these technologies in the health domain has significant implications for individual and public health.

• Research motivation and related work:
  Previous literature reviews have primarily focused on health goals and quantitative goals, such as step tracking, with little exploration of how goals and technologies influence actual behavior change. Additionally, research on the social aspects of goals, intrinsic motivation, and theoretical support for technology design remains scarce in the literature.

Solutions

• What methods or solutions did the authors propose?
  This study conducted a systematic review and meta-analysis of 180 papers from SIGCHI-related journals and conferences over the past decade, further analyzing 37 of these papers that examined the effectiveness of technology interventions in real-world scenarios. The study addressed four key research questions:

  1. What types of goals are explored in HCI research? What are their characteristics?
  2. What research methods are used for studying goals? Who are the participants?
  3. What technologies are used in behavior change research in HCI? How are these technologies implemented and evaluated?
  4. How effective are technology interventions in real-world scenarios?

• What is innovative about this solution?
  This study provides a comprehensive perspective that was previously unexplored in research on goals and behavior change technologies. It examines the core mechanisms of technology effectiveness across multiple dimensions, including goal types, technology types, theoretical support, and intervention outcomes.

• What are the implementation steps? What key techniques were used?

  1. Retrieve and screen literature related to behavior change and goals;
  2. Conduct a meta-analysis of studies that include evaluations of interventions in real-world scenarios;
  3. Extract goal characteristics (single-domain or multi-domain, social aspects, intrinsic motivation), technology types (e.g., mobile applications, wearable devices), and whether theoretical support was used in the design;
  4. Calculate intervention effect sizes using Cohen’s d and Hedges’ g to quantitatively analyze the impact of interventions.

Research Findings

• What specific findings were obtained?

  1. In terms of goal domains, health goals dominated (80.4%), particularly physical activity (38.9%); multi-domain goals accounted for only 20% of the literature; social goals and intrinsically motivated goals received little attention.
  2. Regarding technology types, mobile applications were the most common, followed by wearable devices. Real-world scenario evaluations were primarily conducted in daily life settings, typically lasting 1-4 weeks.
  3. Most interventions used single or quantitative goals (e.g., step counts or screen time), with behavioral measurements dominating, while qualitative goals and psychological metrics were less frequently adopted.
  4. The meta-analysis found that goal-setting and feedback monitoring interventions had medium effect sizes (step count increase: 0.50, screen time reduction: 0.56).

• What advantages does it have compared to existing solutions?
  This study is the first to integrate goal types, technology design, and theoretical support into a framework for evaluating behavior change. By using meta-analysis, it quantifies the relative effectiveness of technology interventions. Additionally, the study identifies gaps in theoretical support in existing literature and provides recommendations for improving technology design.

• What are the experimental or evaluation results?
  The meta-analysis revealed that social support interventions had a significant effect on increasing step counts (effect size: 0.91), while digital rewards or threat mechanisms were most effective in reducing screen time (effect size: 1.22). These interventions demonstrated the importance of theory-driven design, such as goal-setting theory, social cognitive theory, and self-regulation theory.

• Limitations and future directions:

  1. This study primarily screened the ACM database, and other relevant databases (e.g., PubMed) were not covered, which may lead to partial results.
  2. Certain goal domains and populations (e.g., children and non-Western participants) are underrepresented, and future research should address more diverse and socially valuable goals.
  3. The duration of interventions remains relatively short. Future studies are encouraged to adopt longer longitudinal designs to explore the long-term effects of behavior change.

Conclusion

This study systematically analyzed the penetration of goal and behavior change technologies in the literature, identifying the current research focus and limitations. It provides constructive recommendations for future research on goal-related studies in the HCI field. Additionally, through meta-analysis, it quantified the effectiveness of technology interventions, revealing the critical role of theory-driven design in supporting goal setting and behavior change.