Limitations and Strengths
PD, Depression, Anxiety
SENSITIVITY
This study had several limitations. First, since R package Lavaan gave a warning for all growth models using both MLR estimation and other robust estimators, ML estimation was used to fit the model. Presumably, the model with several hundred parameters was too large for our data. The ML estimator is not robust against deviations from normally distributed data, which can lead to biased model parameters. This should be considered when interpreting significant results. However, (full information) ML is a good estimator to handle missing data and to use as much data as possible in longitudinal analyses. Second, the high percentage of nonusers may have distorted the results, although this shows probably a realistic picture of usage of online self-help interventions. Sensitivity analyses showed that the nonusers did probably not influence the treatment effect of the intervention: when leaving the participants who did not actually follow the online self-help training out of the analyses, also no significant treatment effect was found for the intervention group compared to CAU. Third, we used a subscale of the FCRI to measure PD, while most other studies used different questionnaires for PD, such as the Hospital Anxiety and Depression Scale (HADS) [An important strength of our study design is the long follow-up period of 24 months. The effect studies mentioned above, reported follow-up periods ranging from immediately after intervention to 12 months after baseline [