It remains unclear which individuals with subthreshold depression benefit most from psychological intervention, and what long-term effects this has on symptom deterioration, response and remission.

To synthesise psychological intervention benefits in adults with subthreshold depression up to 2 years, and explore participant-level effect-modifiers.

Randomised trials comparing psychological intervention with inactive control were identified via systematic search. Authors were contacted to obtain individual participant data (IPD), analysed using Bayesian one-stage meta-analysis. Treatment–covariate interactions were added to examine moderators. Hierarchical-additive models were used to explore treatment benefits conditional on baseline Patient Health Questionnaire 9 (PHQ-9) values.

IPD of 10 671 individuals (50 studies) could be included. We found significant effects on depressive symptom severity up to 12 months (standardised mean-difference [s.m.d.] = −0.48 to −0.27). Effects could not be ascertained up to 24 months (s.m.d. = −0.18). Similar findings emerged for 50% symptom reduction (relative risk = 1.27–2.79), reliable improvement (relative risk = 1.38–3.17), deterioration (relative risk = 0.67–0.54) and close-to-symptom-free status (relative risk = 1.41–2.80). Among participant-level moderators, only initial depression and anxiety severity were highly credible (P > 0.99). Predicted treatment benefits decreased with lower symptom severity but remained minimally important even for very mild symptoms (s.m.d. = −0.33 for PHQ-9 = 5).

Psychological intervention reduces the symptom burden in individuals with subthreshold depression up to 1 year, and protects against symptom deterioration. Benefits up to 2 years are less certain. We find strong support for intervention in subthreshold depression, particularly with PHQ-9 scores ≥ 10. For very mild symptoms, scalable treatments could be an attractive option.

Sample size planning (SSP) is vital for efficient studies that yield reliable outcomes. Hence, guidelines, emphasize the importance of SSP. The present study investigates the practice of SSP in current trials for depression.

Seventy-eight randomized controlled trials published between 2013 and 2017 were examined. Impact of study design (e.g. number of randomized conditions) and study context (e.g. funding) on sample size was analyzed using multiple regression.

Overall, sample size during pre-registration, during SSP, and in published articles was highly correlated (r's ≥ 0.887). Simultaneously, only 7–18% of explained variance related to study design (p = 0.055–0.155). This proportion increased to 30–42% by adding study context (p = 0.002–0.005). The median sample size was N = 106, with higher numbers for internet interventions (N = 181; p = 0.021) compared to face-to-face therapy. In total, 59% of studies included SSP, with 28% providing basic determinants and 8–10% providing information for comprehensible SSP. Expected effect sizes exhibited a sharp peak at d = 0.5. Depending on the definition, 10.2–20.4% implemented intense assessment to improve statistical power.

Findings suggest that investigators achieve their determined sample size and pre-registration rates are increasing. During study planning, however, study context appears more important than study design. Study context, therefore, needs to be emphasized in the present discussion, as it can help understand the relatively stable trial numbers of the past decades. Acknowledging this situation, indications exist that digital psychiatry (e.g. Internet interventions or intense assessment) can help to mitigate the challenge of underpowered studies. The article includes a short guide for efficient study planning.