Strengths and Limitations
LBP
Our study has a number of strengths. The application of multiple imputation by chained equations for missing data helped to reduce bias introduced by missing data. Since a large number of cases had at least 1 missing data point due to illegible reporting by the therapist, no reporting by the therapist or other problems not related to the patient, performing a complete case analysis would have significantly reduced the number of cases available for the analysis. Imputing missing data allowed optimal use of the available data and therefore provide more robust results. Another strength of the study is the use of the EXAS for the measurement of adherence during every treatment session. The detailed information on patient adherence provided by the EXAS allowed the use of LCGA to determine different groups of patients with distinct adherence trajectories.Limitations of the study should also be discussed. The first limitation is the introduction of missing data through the way data on adherence was collected. To keep the added workload for the physical therapists participating in the study low, we chose a method that allowed the physical therapists to write down the data on a form they could keep on their desk. Although this methodology requires little effort from the therapist, it introduced more room for errors in reporting (illegible handwriting, forgetting to complete part of the form, etc.) than for example digital reporting through a web–based application. Although imputation was used to minimize the effects of missing data on the results, the best way to handle missing data is to prevent it. A second limitation is that there are currently no existing rules or conventions for the pooling of estimates from LCGA on imputed datasets. Imputation of missing data and analysis of the imputed data generally consists of 3 steps.Although no differences between baseline characteristics of the identified trajectory groups were found, the results show that there is no single trajectory of adherence for all patients and that it might not be possible to distinguish different subgroups based on baseline characteristics alone. Therefore, when planning patient treatment, clinicians should not attempt to determine adherence of their patients at the start of treatment and base interventions on that assessment. Instead, monitoring adherence during treatment using an instrument such as the EXAS and intervening when adherence is too low appears to be the optimal strategy.Future research should incorporate the patient–therapist interaction, the patient’s social environment, and patient characteristics when studying patient adherence to better understand how patient adherence can be supported during physical therapist treatment. Another important next step in the research on patient adherence in patients with LBP is to study the association between trajectories of adherence to HBE and clinical outcomes to assess the effects of adherence on clinical outcomes.