We used data from a previously conducted randomised controlled trial (HAP) that took place between October 2013 and July 2015 in primary health care centres in Goa, India, that included information on symptoms of depression and important mediators at three and 12 months after the trial started. Details of the original trial can be found in previous publications.(12, 16) The original trial was registered with the ISRCTN registry, number ISRCTN95149997.
Design
HAP was a parallel arm, individually randomised controlled trial with equal allocation of participants between arms. Participants aged between 18-65 years were recruited from 10 primary health centres. Eligibility criteria included a probable diagnosis of moderately to severe depression determined with a PHQ-9 score greater than 14. Pregnant women and participants who needed urgent medical attention or who were unable to communicate were excluded.
The intervention
The intervention (HAP) was a manualised psychological intervention based on behavioural activation for depression that primarily involved strategies to increase the number of enjoyable activities a person engaged with.(12, 18) Other strategies were also included after exploring their acceptability, appropriateness and feasibility in the local context including need-based strategies that addressed interpersonal triggers, problem-solving, relaxation and enlisting social support tailored to the specific need of the individuals.(19)
The experimental arm received up to eight sessions (described below) that lasted between 30 and 40 minutes at weekly intervals over a 3-month period. The sessions were usually face to face at the Primary Health Centre, or the patient’s home. Telephone sessions were used only when strictly necessary. The intervention was organized in three phases. The first phase (sessions 1-2) was primarily used to engage the participant, establish an effective relationship, explain the objectives of the sessions including behavioural activation, and to elicit a commitment for the HAP intervention. The middle phase (sessions 3-4) assessed activation targets and encouraged activation, identifying barriers to activation, and learning to overcome these and how to solve or cope with life problems. The ending phase (sessions 5-6) reviewed and strengthened gains the patient made during treatment in order to prevent relapse. If a participant did not respond to treatment by the third or fourth session, two additional middle-phase sessions were offered resulting in these patients attending a total of seven to eight sessions.
HAP was delivered by lay counsellors who had completed at least the 10th grade of education and were fluent in local languages. Counsellors were also required to meet pre-defined competency standards.(20) Training took place over a three-week period. Counsellors received weekly peer-led supervision in groups and individual supervision twice a month.
Enhanced usual care (EUC) was offered to participants in both arms of the trial.(12) EUC involved screening results for depression being shared with both patients and physician. Physicians were also trained on how to use a contextualised version of the mhGAP guidelines, including when and where to refer for psychiatric care.
Measures
Exposure
Our exposure of interest was the HAP intervention that was offered to participants in the experimental arm of the trial only.
Outcome
For our analysis, our primary outcome was the PHQ-9 score at 12 months. Response options generate a continuous score ranging from 0-27 since each of the nine items can be scored from zero (no symptoms) to three (nearly every day). Scores between ten and 14 represent moderate depression, and scores between 15 and 27 moderately severe to severe depression symptoms.(21)
Mediators
Causal mediation analyses require obtaining estimates in both the exposed participants, as well as the unexposed (i.e. the counterfactual). Where mediators were measured in both the experimental and control arms, estimates from participants in the control arm can be treated as the unexposed. However, where a mediator was only measured in the experimental arm, it was necessary to create a separate category for participants who had not been exposed to the mediator of interest but were still in the experimental arm.
Therapeutic process indicators (M1)
Characteristics associated with the delivery of the sessions were measured for participants in the experimental arm only. The first characteristic that we accounted for is the number of sessions completed that are categorised to reflect the phases of the HAP intervention that a participant completed (M1a: no sessions (unexposed); sessions one and two (phase 1), sessions three and four (phase 2); sessions five through eight (phase 3).
The second characteristic of the sessions that we accounted for is a participant’s self-reported completion of assigned tasks outside of sessions (homework) to improve activity levels. At each session except for the first one, activity monitoring charts were completed indicating whether a participant completed homework outside of the sessions. These self-reported activity charts were scored using the following criteria: completely (scored 2), partially (scored 1), or not at all (scored 0). Based on this variable, we calculated a score representing the proportion of homework completed (M1b: 0= none (unexposed); 1= > 0% and ≤ 50%; 2=> 50%).
Level of behavioural activation (M2)
Behavioural activation was measured for participants in both the experimental (exposed) and control arms (unexposed) at three months after the trial started. An adapted version of the Behavioural Activation for Depression Scale Short Form (BADS-SF) was used to capture activity levels that reflect the level of behavioural activation due to the HAP intervention.(22)
Extra sessions received in instances of non-response to the intervention (M3)
Adding extra sessions for participants who do not respond to the intervention may help to improve symptoms of depression. Therefore, if a participant did not respond to the intervention by session five, they were offered two additional sessions. Estimating this indirect effect via the additional sessions involves two variables including non-response to treatment (M3a: 0=non-response (unexposed); 1=responded to treatment) and the number of extra sessions received (M3b: 0=no extra sessions (unexposed); 1=one extra session; 2=two extra sessions). Appendix 1 details how non-response to the sessions was determined.
Mediator-outcome confounders
Due to the randomised nature of the exposure, it was not necessary to account for confounders for the association between the exposure and the outcome, or between the exposure and the mediators. However, it was necessary to account for confounders potentially distorting the association between the mediator and the outcome (mediator-outcome confounders). We considered all demographic characteristics as potential mediator–outcome confounders. The selection process for these confounders is described in the section on statistical methods.
Statistical methods
General
To better understand the relationship between different mediators and depression outcomes, we compared characteristics of the sessions (i.e. M1a - number of sessions and M1b proportion of homework completed), behavioural activation (M2), non-response to the intervention (M3a), and the number of extra sessions attended for participants who did not respond to HAP (M3b), with the outcome remission from depression (determined by a PHQ-9 score less than 10) for participants in the experimental arm only. Differences in baseline characteristics between treatment arms can be found in previous publications.(12, 16)
Mediation analysis
We aimed to investigate the extent to which symptoms of depression measured at 12 months using the PHQ-9 questionnaire, were explained by the direct effect and indirect effects of the intervention (Figure 1). To achieve these objectives, we used the interventional (in)direct effects approach to mediation analysis to understand population level effects relevant to this analysis.(17) Findings for this analyses are reported according to guidelines for reporting mediation analyses (AGReMA statement).(23)
Decomposition of total effect of the HAP intervention into direct and indirect effects
The first step of the mediation analyses involved decomposing the total effect of the HAP intervention, into path-specific indirect effects and the direct effect. In order for the decomposition to be valid, the sum of the different path specific effects including the direct effect, through which the effects of the intervention is mediated, must be the same as the total effect of the intervention.(24)
With three mediators, the following decompositions are required to sum the total effect: an estimate that does not involve any mediators (level 0 - all mediators set to unexposed); an estimate that includes one mediator (level 1 – one mediator exposed, the rest unexposed); two mediators (level 2 – two mediators set to exposed, one to unexposed), and three mediators (level 3 – all three mediators set to exposed).
Setting a mediator at an exposed status indicates the pathway includes the effect of this mediator. Likewise, setting a mediator to an unexposed status, indicates the pathway excludes the effect of this mediator (i.e. setting M2 and M3 to unexposed indicted the pathway includes M1 only). Table 1 describes the total effect and decompositions for the direct and indirect effects of the HAP intervention that sum the total effect.
Table 1
Decompositions for the direct and indirect effects of the HAP intervention that sum the total effect
Estimate
|
Description
|
M1
|
M2
|
M3
|
Total effect
|
Difference between predicted PHQ-9 scores between the experimental and control arm
|
NA
|
NA
|
NA
|
Direct effect
|
Difference between predicted PHQ-9 scores in the intervention and control arms, whilst fixing mediators to unexposed status (level 0)
|
unexposed
|
unexposed
|
unexposed
|
M1 – characteristics of the sessions
|
Difference between predicted PHQ-9 scores when changing M1 from levels in the exposed, to levels in the unexposed, in the experimental arm (level one)
|
exposed to unexposed
|
unexposed
|
unexposed
|
M2 – levels of behavioural activation
|
Difference between predicted PHQ-9 scores when changing M2 from levels in the exposed, to levels in the unexposed, in the experimental arm (level 2)
|
exposed
|
exposed to unexposed
|
unexposed
|
M3 – additional sessions offered in instances of non-response
|
Difference between predicted PHQ-9 scores when changing M3 from levels in the unexposed, to levels in the exposed, in the experimental arm (level 3)
|
exposed
|
exposed
|
exposed to unexposed
|
Estimation
Estimation for the different effects was based on Monte Carlo integration using 1,000 fold expanded dataset. Estimates for the total, direct, and indirect effects were obtained by running regression models for the outcome of PHQ-9 score, separately in the exposed and unexposed, whilst setting the mediators at a random subject-specific distribution (Table 1). Further details of the estimation methods can be found in Appendix 1.
Model fit
Regression models used to estimate the total, direct and indirect effects, included any mediator-outcome confounder that improved model fit as indicated by the Akaike Information Criterion (AIC).(25) Results indicate that age, education, and baseline PHQ-9 scores are important confounders. These models also included mediators set to relevant exposed/unexposed status (Table 1).
The regression models used to set the mediators at random, subject-specific draws for the unexposed/exposed status, included any variable that improved model fit as indicated by the Akaike Information Criterion (AIC),(25) but not known to be potentially influenced by them. This ensured that mediator values drawn were more specific to the considered individual, thereby providing better insight into mechanism. Models for the different mediators used a combination of predictors including age, education, baseline PHQ-9 scores, participants expectations of treatment, and marital status. Any relevant non-linearities and interactions were included in all models if determined to be significant at the five percent level, using the post-estimation testparm command in Stata.
Assumptions
The interventional effects have important underlying assumptions that will influence the validity of our findings if violated. Reassuringly, due to the randomised nature of the HAP trial, many of the assumptions with the interventional effects are fulfilled. The interventional effects capture the components of the total effect mediated by the different mediators, even when the structural dependence between multiple mediators is unknown (i.e. direction of the causal effects between the multiple mediators is unknown, or if there is unmeasured common causes of the mediators (Figure 1)). The main assumption relevant to our study is that there are no unmeasured mediator-outcome confounders.
Missing data
There were missing data for the BADS-SF variable (measuring M2) at three months (n=28, 5.7%) and the PHQ-9 variable at 12 months (n=47, 9.3%). To account for this, we implemented single stochastic imputation using chained equations with 10 burn-in iterations, under the assumption that data was missing at random (MAR). Details of the missing data analysis can be found in Appendix 2.
Ethical approval and consent
The trial protocol received ethical approval from the Sangath and LSHTM Institutional Review Boards.(18) Written or witnessed verbal (if the participant is illiterate) informed consent was mandatory for enrolment. All consent procedures were audio-taped, with the patient’s approval, for quality assurance.
Patient public involvement
As this is a secondary data analysis of the original trial, patients and public were not involved