60% of patients with depression are attended in the Spanish Primary Care. Nevertheless, half of them, approximately, show low adherence to medication and psychotherapy presents difficulties in delivering interventions to the community because the lack of time and specialized resources. For these reasons, online interventions offer a valuable alternative to face-to-face therapy: they are effective and involve minimal cost and time-investment to the depression treatment.
Despite of the effectiveness, completion rate of the treatment is very low. To improve adherence, more information is needed about the characteristics of the participants and the adherence predictors of the online interventions.
The present study aimed to examine sociodemographic and clinical characteristics between who complete the intervention and who doesn’t and to analyze the predictors of adherence of this internet-based intervention program, named “Smiling is fun” (www.sonreiresdivertido.com).
A total of 194 depressive patients were randomized either to the “Smiling is fun” program with low intensity therapist-guided group (n=96), where patients could ask the psychotherapists questions or advice via email with a maximum of three contacts over the treatment period or to the “Smiling is fun” totally self-guided group, where patients had no contact with any therapist (n=98). Patients, at the same time, were classified according to the level of the treatment compliance: Actives (those who completed at least 8 modules at the post-test of the intervention and 10 modules at 12-month follow up) and Dropouts (those who did not complete at least 8 modules at the post-test and 10 modules at 12-month follow up).
Results of this study indicated that, when the participants has no contact with any therapist, higher age is associated with greater adherence and low and high income level is associated with lower adherence.
When predictors were studied, results show that that older people tend to adhere more that younger participants in guided and unguided interventions. When there was no support from the therapist, those participants that perceived their health worse at baseline assessment were more likely to adhere to the treatment, when in the post-treatment assessment improve their depressive symptomatology compared to those who did not improve. Nevertheless, when a support of a psychology is present, those who improve their depressive symptomatology at post-treatment assessment were more likely to adhere who did not.
It is important to take into account that there are clinical and sociodemographic differences between actives and dropouts in each condition. As well as, differences in adherence predictors in each group and conditions. These results allow us to understand better who may benefit of this type of intervention and how might treatments to be tailored to increase the adherence for non-completers group. Moreover, all these adherence predictors should be considered in future development of Internet interventions for depressive disorders.
Overall, it is important to continue researching to explore other possible patients and programs characteristics to improve adherence in these interventions.
Read the full paper: Castro, A., López-del-Hoyo, Y., Peake, C., Mayoral, F., Botella, C., García-Campayo, J., et al. (in press). Adherence predictors in an Internet-based Intervention program for depression. Cognitive Behaviour Therapy. doi:10.1080/16506073.2017.1366546
Photo by: Fernando Butcher