In this public sector sample treated with measurement-based care,20,26,51
nearly half of the patients dropped out of medication treatment within the first year. Of those who dropped out, 14% left in the first 3 months and 36% in the second 3 months. Response and remission rates were very low and did not differ between those who did and did not drop out. Younger age and fewer side effects at baseline were associated with attrition at 6 months. Younger age, better perceived physical functioning, and more negative attitudes about psychiatric medications were associated with attrition at 12 months. More clinic visits was also associated with greater attrition.
The overall attrition rate in the first 3 months (7%, 12/179) following initiation or change in antidepressant treatment was less than the 26% reported in our prior analysis of a mixed public and private sector sample in the first 12 weeks in the STAR*D trial.10
The 6-month attrition rate (23%, 42/179) was also lower than the 6 month 49% attrition rate reported in a community mental health center sample beginning algorithm-based pharmacotherapy care.17
It may be that the patient and family education program improved retention.
Since sustaining attendance at medication treatment visits is of substantial importance, it is encouraging that 93% of this public sector group remained in treatment for at least 3 months, and 77% did so for at least 6 months, allowing continuing opportunities to intervene to maximize ongoing retention. It is possible, however, that the patients who agreed to study participation were more highly motivated to remain in treatment than the general population of public sector patients.
The relationship between increased frequency of visits and attrition suggests that visit burden may play a role in patients' willingness to continue in treatment in algorithm-based care or perhaps reflects the difficulty of retaining the more seriously burdened or complicated cases. This is important since the number of visits required to ensure vigorous dosing and careful monitoring of efficacy and side effects is generally more than in standard clinical practice. Increased frequency of visits among dropouts may also have been related to the need for multiple changes in dosing or treatment strategy due to side effects or lack of efficacy, which in turn may have contributed to drop out.
It was a somewhat unexpected finding that the remission and response rates of dropouts and completers at both 6 and 12 months did not differ, although completers at 12 months had had a full year of treatment compared with a mean of approximately 6 months of treatment for dropouts. Modest expectations for remission are, however, consistent with the socioeconomic disadvantage, extensive history of depressive illness, and probable treatment-resistant illness characterizing this group.19,23
Given the very high relapse rate with MDD following both remission and especially response without remission,52
it is possible, however, that dropouts in this public sector group are at greater risk for relapse or symptom worsening when discontinuing medication.
Younger age was associated with attrition at both time points, consistent with previous reports.7,8,10
Older age has been similarly associated with an increase in perceived need for medications.53
Experience with side effects from previous or concurrent medication, as seen by reports of side effects at baseline, predicted retention at 6 months. Side effects and lack of efficacy are the most frequently reported reasons for dropout.54,55
The findings presented here, however, suggest that side effects related to medications at study entry may be a signal of perseverance in this population and may be associated with already having engaged in treatment.
Those with better perceived physical functioning were less likely to remain in treatment for a year. Higher perceived mental health functioning, although not higher physical functioning, was associated with discontinuation in the STAR*D study,10
as well as in a recent naturalistic study.56
Both findings may be related to decreased perception of need for help as a reason for treatment discontinuation.
Decision rules for identifying those at risk for dropping out of treatment by 6 months are driven primarily by younger age (under 49 years), increased monthly visit frequency, and MAST scores generally below the threshold that suggests alcohol abuse. Decision rules for those at risk for dropping out by 12 months are driven by younger age (under 40 years) and older age along with more negative perception of medications, especially among those with very low DAST scores suggesting no drug abuse.
It is of interest that greater likelihood of alcohol abuse and somewhat more risk of drug abuse are decision rules suggesting retention in the classification tree. It may be that prior experience with problems has taught participants that treatment is needed. In the STAR*D sample, prior experience with episodes of depression was similarly associated with retention.10
In this study, Hispanic ethnicity, depressive symptom severity, or years since first onset of depression were not related to attrition, although these predictors were present in the large STAR*D trial.10
These factors may be of less importance in a public sector population already burdened with comorbid conditions and issues related to lower socioeconomic status, or this sample may not have had sufficient power to identify them.
The finding that negative perception of medications is associated with attrition at 12 months and a trend toward attrition at 6 months is consistent with earlier findings concerning negative attitudes and nonadherence.13
This is a useful finding, since attitudes may be modifiable both at the inception of and during treatment. Specific items on the DAI predicted the likelihood of attrition with a reasonable level of sensitivity. The question that best predicted attrition at 6 and 12 months addressed the perception that medications do harm, which is consistent with an earlier report linking skepticism about antidepressants with attrition.14
The content of the five items that were most sensitive in predicting attrition at both time points focused on perceived negative effects or lack of positive effects of medications rather than broader attitudes about medication or treatment found in other DAI items. Since the DAI assessment was originally developed to evaluate adherence in patients with schizophrenia, however, its content may not be ideally targeted to the symptoms of depression or the effects of antidepressants. Other assessment tools that are shorter and easier to use, such as the Beliefs About Medicines Questionnaire,57
merit further investigation for their usefulness in predicting attrition during treatment of MDD.
Findings in this study have policy implications for guiding a personalized approach to minimizing attrition in public sector clinics and allocating scarce resources. All patients may benefit from basic education about depression, expectations about the timing and likelihood of improvement, the likelihood and management of side effects, as well as other basic activities that may assist with retention such as appointment reminders and ease of access. However, the most important choice for clinicians in considering an intervention is not whether it works for most
patients, but whether it works for a particular
Public sector clinics may therefore consider maximizing retention by conducting an individualized review with patients of their beliefs and attitudes about antidepressant treatment both when initiating treatment and again as treatment progresses. This may be especially important with younger patients and patients who require more frequent visits. Clinicians and researchers can easily ask simple questions about beliefs and then draw on the answers to focus personal or support staff resources on responding to specific fears, negative attitudes, and irrational or uninformed perceptions about treatment that the patient may have. Enhancing attitudes about medications has previously been found to be associated with greater adherence to antidepressant medication treatment59
and may be helpful in reducing attrition as well.
Ongoing objective self monitoring of symptoms and side effects with feedback from staff may also help all patients achieve a more realistic perception of functioning and self-management. Such education, support, and monitoring may help substitute for the learning that can come with age and may assist with retention.
Limitations of this study include the lack of randomization of either patients or physicians, lack of blinding of the research outcome assessors to treatment assignment, and likely variability in physician fidelity to the algorithm. Results are exploratory and need to be confirmed in additional studies. The size of the study sample was relatively small, resulting in decreased power to identify differences between groups and to construct more complex models to predict attrition. The study also did not assess whether dropouts and completers received non-medication services at their clinics during the study period, which could have had an impact on retention. It is possible that dropouts received treatment for depression from primary care or other clinicians. Reasons for discontinuation of medication treatment were not collected. Some discontinuations could have involved patient-clinician consensus about treatment completion and based on limited information available, some involved medical reasons for discontinuation. Factors related to clinicians (e.g., experience, race), the patient/clinician alliance, the healthcare system (e.g., appointment wait times) or treatment (e.g., side effects, efficacy) were also not assessed.
This study showed that attitudinal variables are important predictors of treatment attrition. Efforts to elicit attitudes about medications and to use resources to tailor educational or other retention interventions to patients with negative beliefs about antidepressants may be of use in public sector clinics when initiating a new medication and throughout treatment, with particular focus on younger patients and those requiring frequent visits.