3 research outputs found
Do baseline characteristics affect depressive symptoms treatment success? Posthoc subgroup analysis from the CONEMO trials
Objective: As a secondary trial plan analysis, we aim to examine whether participant characteristics, measured before randomization, modified the effect of a digital intervention designed to improve depressive symptoms (CONEMO – Emotional Control) on recovery from depression that has presented a substantive impact on previous research.Method: Mixed logistic regression was used to explore interactions between the treatment arm and subgroups of interest, including suicidal ideation, race/color, age, gender, income, type of mobile phone, alcohol misuse, tobacco use, and diabetes/hypertension). We estimated interaction effects between the treatment group and these subgroup factors for the secondary outcomes using linear mixed regression models.Results: Increased effects of the CONEMO intervention on the primary outcome (reduction of the scores of depressive symptoms in at least 50% at three-month follow-up) were observed amongst older and wealthier participants in Lima (p-values 0.030 and 0.001, respectively). At the same time, there was no evidence of such differential effects in São Paulo or any other secondary outcomes level in both countries.Conclusions: Digital intervention used in primary care settings needs to be accessible. We conclude that the technological intervention CONEMO has no heterogeneity effects on most subgroups studied, except income and age in the Lima trial
Do baseline characteristics affect depressive symptoms treatment success?:Posthoc subgroup analysis from the CONEMO
Objective: As a secondary trial plan analysis, we aim to examine whether participant characteristics, measured before randomization, modified the effect of a digital intervention designed to improve depressive symptoms (CONEMO - Emotional Control) on recovery from depression that has presented a substantive impact on previous research.Method:Mixed logistic regression was used to explore interactions between the treatment arm and subgroups of interest, including suicidal ideation, race/color, age, gender, income, type of mobile phone, alcohol misuse, tobacco use, and diabetes/hypertension). We estimated interaction effects between the treatment group and these subgroup factors for the secondary outcomes using linear mixed regression models.Results:Increased effects of the CONEMO intervention on the primary outcome (reduction of the scores of depressive symptoms in at least 50% at three-month follow-up) were observed amongst older and wealthier participants in Lima (p-values 0.030 and 0.001, respectively). At the same time, there was no evidence of such differential effects in São Paulo or any other secondary outcomes level in both countries.Conclusions:Digital intervention used in primary care settings needs to be accessible. We conclude that the technological intervention CONEMO has no heterogeneity effects on most subgroups studied, except income and age in the Lima trial