Measurement invariance and differential item functioning of the PHQ-9 and GAD-7 between working age and older adults seeking treatment for common mental disorders.

BACKGROUND: The nine-item Patient Health Questionnaire (PHQ-9) and seven-item Generalised Anxiety Disorder (GAD-7) scale are widely used clinically and within research, and so it is important to determine how the measures, and individual items within the measures, are answered by adults of differing ages. This study sought to evaluate measurement invariance and differential item functioning (DIF) of the PHQ-9 and GAD-7 between working age and older adults seeking routine psychological treatment. METHODS: Data of working age (18-64 years old) and older (≥65) adults in eight Improving Access to Psychological Therapies (IAPT) services were used. Confirmatory factor analysis (CFA) was used to establish unidimensionality of the PHQ-9 and GAD-7, with multiple-group CFA to test measurement invariance and The Multiple Indicators, Multiple Causes Models approach to assess DIF. The employed methods were applied to a propensity score matched (PSM) sample in sensitivity analyses to control for potential confounding. RESULTS: Data from 166,816 patients (159,325 working age, 7491 older) were used to show measurement invariance for the PHQ-9 and GAD-7, with limited evidence of DIF and similar results found with a PSM sample (n = 5868). LIMITATIONS: The localised sample creates an inability to detect geographical variance, and the potential effect of unmeasured confounders cannot be ruled out. CONCLUSIONS: The findings support the use of the PHQ-9 and GAD-7 measures for working age and older adults, both clinically and in research settings. This study validates using the measures for these age groups to assess clinically significant symptom thresholds, and monitor treatment outcomes between them.

Predicting post-treatment symptom severity for adults receiving psychological therapy in routine care for generalised anxiety disorder: a machine learning approach.

Approximately half of generalised anxiety disorder (GAD) patients do not recover from first-line treatments, and no validated prediction models exist to inform individuals or clinicians of potential treatment benefits. This study aimed to develop and validate an accurate and explainable prediction model of post-treatment GAD symptom severity. Data from adults receiving treatment for GAD in eight Improving Access to Psychological Therapies (IAPT) services (n=15,859) were separated into training, validation and holdout datasets. Thirteen machine learning algorithms were compared using 10-fold cross-validation, against two simple clinically relevant comparison models. The best-performing model was tested on the holdout dataset and model-specific explainability measures identified the most important predictors. A Bayesian Additive Regression Trees model out-performed all comparison models (MSE=16.54 [95 % CI=15.58; 17.51]; MAE=3.19; R²=0.33, including a single predictor linear regression model: MSE=20.70 [95 % CI=19.58; 21.82]; MAE=3.94; R²=0.14). The five most important predictors were: PHQ-9 anhedonia, GAD-7 annoyance/irritability, restlessness and fear items, then the referral-assessment waiting time. The best-performing model accurately predicted post-treatment GAD symptom severity using only pre-treatment data, outperforming comparison models that approximated clinical judgement and remaining within the GAD-7 error of measurement and minimal clinically important differences. This model could inform treatment decision-making and provide desired information to clinicians and patients receiving treatment for GAD.

Examining bi-directional change in sleep and depression symptoms in individuals receiving routine psychological treatment.

BACKGROUND: Sleep disturbance is a common symptom of depression. There is conflicting evidence whether improvements in sleep might impact depressive symptoms, or whether treating the core depressive symptoms might improve sleep disturbance. This study explored the bi-directional impact of sleep and depressive symptom change among individuals receiving psychological treatment. METHODS: Session-by-session change in sleep disturbance and depressive symptom severity scores were explored in patients receiving psychological therapy for depression from Improving Access to Psychological Therapies services in England. Bi-directional change in sleep disturbance and depressive symptoms was modelled using random-intercept cross-lagged panel models with items from the PHQ-9. RESULTS: The sample included 17,732 adults that had received three or more treatment sessions. Both depressive symptoms and sleep disturbance scores decreased. Between initial timepoints, higher sleep disturbance was associated with lower depression scores, but after this point positive cross-lagged effects were observed for both the impact of sleep disturbance on later depressive symptoms, and depressive symptoms on later sleep disturbance scores. The magnitude of effects suggested depressive symptoms may have more impact on sleep than the reverse, and this effect was larger in sensitivity analyses. CONCLUSIONS: Findings provide evidence that psychological therapy for depression results in improvements in core depressive symptoms and sleep disturbance. There was some evidence that depressive symptoms may have more impact on sleep disturbance scores at the next therapy session, than sleep disturbance does on later depressive symptoms. Targeting the core symptoms of depression initially may optimise outcomes, but further research is needed to elucidate these relationships.