Systematic optimization and evaluation of a Dutch sexual health intervention: Role model stories for chlamydia prevention, testing, and treatment.

BACKGROUND

The rapidly evolving nature of eHealth necessitates regular optimization and subsequent evaluation. Within the Dutch sexual health intervention Sense.info, we utilized a mixed-methods cyclic evaluation process to assess and optimize the potential impact of the chlamydia page. This paper reports on the page's optimization through the development of role model stories for chlamydia prevention and the subsequent evaluation of these stories.

METHOD

The experiences of 10 young individuals served as the basis of role model stories using the behavior change principle modeling based on social cognitive theory. These stories aimed to motivate young individuals to undergo sexually transmitted infection testing, use condoms, and notify sexual partners. Once the stories were posted online, we tracked use data between July and September 2022 and investigated end-user perspectives through a think-aloud study combined with semistructured interviews (= 20, = 19.7, SD= 2.65). Template analyses were used for the analysis of the think-aloud study.

RESULTS

Use data revealed that all stories were accessed by website visitors, yet other page elements on the chlamydia page interacted with more. The exploration of end-user perspectives indicated a positive impact of the personal stories on normalization, self-efficacy, and skills related to chlamydia preventive behaviors. Mixed results were found regarding some conditions for the effectiveness of the behavior change principle modeling.

DISCUSSION AND CONCLUSION

This study provided valuable insights into the cyclic evaluation process for evaluating and optimizing web-based public health interventions, as well as the potential impact of role model stories on sexual health prevention. Also, aspects of the stories that could be optimized in future optimization rounds were identified. Overall, this research contributes to enhancing the impact of eHealth interventions through iterative evaluation and optimization processes.