Mental health problems are one of the main causes of the overall disease burden worldwide. Depression is a driver of disability in adults and in people aged 18-44 years, depression is the leading cause of disability and premature death. Many risk factors for depression are modifiable and mild to moderate depression can be brought into remission (i.e. symptoms decrease) through non-pharmaceutical interventions such as talking therapy or engaging in moderate to vigorous physical activity. Many non-pharmaceutical interventions under the umbrella of social prescriptions have been developed to help people who have or are at risk of mild to moderate depression. While clinical trials have pointed towards beneficial effects of these interventions, they may not fully capture real life and longitudinal effects of these interventions. It is also important to determine whether different patient groups (by sex, age, socioeconomic status and underlying health conditions) benefit from these intervention programmes to the same extent. Finally, it is not known how often non-pharmaceutical interventions are used as a first line option in practice by GPs. This study focusses on the use and real-life effectiveness of non-pharmaceutical interventions in UK primary care. Because of the large number of patients included in CPRD (Clinical Practice Research Datalink) and the extensive time horizon during which these patients were observed, we will be able to study immediate benefits and long-run effects for both men and women. Given the promising use of non-pharmaceutical interventions, the results of this study have direct implications for clinical care and population health.
This study focuses on the patterns of use and real-life effectiveness of non-pharmaceutical interventions in UK primary care. Previous studies investigating the health effects of non-pharmaceutical interventions administered to people diagnosed with non-severe depression are largely limited to controlled clinical trials and small-scale observational studies. First, this study explores the use of non-pharmaceutical interventions in UK primary care in adherence to current guidelines for non-severe depression, for which they are recommended as a first line option, by studying the proportion of patients who received a non-pharmaceutical intervention upon being diagnosed with non-severe depression. Second, while previous studies have pointed towards the efficacy of non-pharmaceutical interventions in improving key outcomes, they might not be able to fully capture treatment effectiveness during routine care and frequently lack the time horizon to study long-run benefits and risks. Thus, we aim to explore the use of non-pharmaceutical interventions on short-, mid-, and long-term physical and behavioural outcomes in a routine care set-up. For these analyses, we apply an advanced matching technique relying on machine learning - DAME (developed by the Duke Almost Matching Exactly Lab) - which is built to learn the proper metric to be used by weighting those covariates more which directly contribute towards the treatment effect more. Upon matching our treatment and control groups and to determine whether outcomes of patients differ between patients in each subgroup, we apply mean comparison tests. Finally, we test for heterogenous treatment effects by stratifying our sample by sex, age, socioeconomic status, ethnicity and comorbidities. Multiple testing is accounted for using the Benjamini-Hochberg method to take into consideration the number of subgroups and primary outcomes. The findings of this study are expected to provide novel insights into the use and effectiveness of non-pharmaceutical interventions in a real-life setting and can directly inform clinical practice.
We will explore the effects on the following primary outcome:
- Persistence of non-severe depression (i.e., repeated depression diagnosis and/or uptake of medication, see section ‘Exposures, outcomes and covariates’)
We will also explore the following secondary outcomes
- Number of all-cause emergency hospitalizations
- Number of severe adverse health events (stroke, heart attack [myocardial infarction] – each event type evaluated separately)
- All-cause mortality
- Suicide
- Number of GP visits
- Number of medications
- BMI
- Blood pressure
- Smoking status
- Recorded hazardous alcohol consumption
To address missingness of data, we will use multiple imputation for missingness in the covariates and pairwise deletion for the outcome variables (see relevant section below for more detail).
Till Bärnighausen - Chief Investigator - University of Heidelberg
Julia Lemp - Corresponding Applicant - University of Heidelberg
Anant Jani - Collaborator - University of Oxford
Justine Davies - Collaborator - University of Birmingham
Maximilian Schuessler - Collaborator - University of Heidelberg
Pascal Geldsetzer - Collaborator - University of Heidelberg
2011 Rural-Urban Classification at LSOA level;HES Admitted Patient Care;ONS Death Registration Data;Patient Level Index of Multiple Deprivation