Depression among adolescents is a significant public health concern, with increasing global prevalence and substantial impact on quality of life, academic performance, and long-term mental health outcomes (1). The World Health Organization (WHO) estimates that depression is one of the leading causes of illness and disability among adolescents worldwide, often beginning during this critical developmental period and persisting into adulthood if left untreated (2). Traditional face-to-face Cognitive Behavioral Therapy (CBT) is recognized as an effective, evidence-based treatment for depression. However, barriers such as limited access to trained professionals, stigma, and time constraints often prevent adolescents from receiving timely and adequate mental health care (3).

In response to these limitations, Digital Cognitive Behavioral Therapy (dCBT) has emerged as a novel and accessible alternative. Delivered via internet platforms, mobile applications, or computer programs, dCBT incorporates the same core principles of CBT, such as cognitive restructuring, behavioral activation, and problem-solving, but offers the advantage of remote, flexible, and potentially anonymous participation (4). Studies have shown promising outcomes for dCBT in adult populations, but research focusing on its efficacy among adolescents remains limited, particularly in low-resource settings where digital interventions may bridge the treatment gap (5).

This study aims to assess the effectiveness of a structured dCBT intervention compared to standard counseling in reducing depressive symptoms among adolescents. By employing a randomized controlled trial design, this research seeks to provide robust evidence on the viability of digital mental health interventions for younger populations.

A total of 120 participants aged between 13 and 18 years were recruited from secondary schools and adolescent health clinics. Inclusion criteria were: a diagnosis of depression based on DSM-5 criteria, a PHQ-9 score ≥10, and access to a smartphone or computer. Exclusion criteria included current psychiatric medication use, diagnosis of other major psychiatric disorders, or ongoing psychotherapy.

Randomization and Group Allocation

Participants were randomly assigned into two groups using a computer-generated random number table. The intervention group (n = 60) received an 8-week structured dCBT program delivered via a mobile application. The control group (n = 60) received standard counseling services provided by school counselors. Allocation was concealed using sealed opaque envelopes, and outcome assessors were blinded to group assignment.

Intervention Details

The digital CBT program consisted of weekly modules focusing on mood tracking, cognitive restructuring, behavioral activation, problem-solving skills, and relaxation techniques. Each module included interactive activities, quizzes, and audio-visual content to enhance engagement. Participants were encouraged to complete one module per week and received automated reminders.

Outcome Measures

The primary outcome was the change in depression severity, assessed using the Patient Health Questionnaire-9 (PHQ-9) and the Beck Depression Inventory-II (BDI-II), measured at baseline and post-intervention. Secondary outcomes included anxiety levels measured using the Generalized Anxiety Disorder-7 (GAD-7) scale and quality of life assessed by the KIDSCREEN-27 questionnaire.

Statistical Analysis

Data were analyzed using SPSS version 25. Descriptive statistics were used for demographic data. Paired t-tests were applied to compare within-group differences, and independent t-tests were used to compare between-group differences. A p-value of less than 0.05 was considered statistically significant. Missing data were handled using the intention-to-treat principle, with last observation carried forward (LOCF) method for imputation.

and the control group receiving standard counseling (n = 60). All participants completed the baseline assessments, and 112 (93.3%) completed the post-intervention follow-up. Demographic characteristics such as age, gender distribution, and baseline severity scores were comparable between both groups (Table 1).

Following the 8-week intervention, significant improvements were observed in the digital CBT group. The mean PHQ-9 score in the intervention group decreased from 15.4 ± 2.5 at baseline to 7.6 ± 2.2 post-intervention (p < 0.001). In contrast, the control group showed a smaller reduction from 15.1 ± 2.3 to 12.2 ± 2.0 (p = 0.04). The between-group difference was statistically significant (p < 0.001) (Table 2).

Similarly, BDI-II scores dropped significantly in the intervention group (27.3 ± 4.5 to 13.4 ± 3.1), while the control group showed a modest reduction (26.9 ± 4.7 to 21.8 ± 3.8). The intervention group also reported improved anxiety scores on the GAD-7 scale (13.5 ± 2.6 to 6.9 ± 2.3), compared to the control group (13.1 ± 2.4 to 10.2 ± 2.5) (Table 2). Quality of life, as assessed by KIDSCREEN-27, improved more significantly in the digital CBT group (mean score increase from 58.4 ± 6.1 to 72.3 ± 5.5) than in the control group (60.1 ± 5.8 to 64.2 ± 5.1) (p < 0.01).

Table 1. Baseline Characteristics of Participants

Table 2. Pre- and Post-Intervention Outcome Measures

These findings suggest that digital CBT significantly reduces depressive and anxiety symptoms and improves quality of life compared to standard counseling methods among adolescents (Table 2).

The findings of this study demonstrate that digital cognitive behavioral therapy (dCBT) is a significantly effective intervention for managing depressive symptoms among adolescents. Participants in the dCBT group exhibited notable reductions in depression and anxiety scores and reported enhanced quality of life compared to those receiving standard counseling. These results align with growing evidence supporting the utility of digital mental health interventions in youth populations (1,2).

Adolescent depression poses a unique challenge due to factors such as low mental health literacy, stigma, and limited access to qualified mental health professionals (3,4). Digital platforms can circumvent many of these barriers by providing private, flexible, and scalable modes of therapy delivery. Previous research has shown that dCBT programs can be as effective as face-to-face therapy, particularly when they include interactive elements and personalized feedback (5,6). Our study confirms similar outcomes, with significant improvements in PHQ-9 and BDI-II scores observed in the dCBT group.

The improvement in anxiety symptoms further supports the transdiagnostic nature of CBT, which addresses cognitive distortions and behavioral avoidance common to both depression and anxiety disorders (7). This dual efficacy is especially important given the high comorbidity of anxiety with adolescent depression (8). Moreover, the substantial improvement in KIDSCREEN-27 scores highlights the broader psychosocial benefits of digital therapy, including better self-perception, school engagement, and peer relationships (9).

Adherence and engagement remain critical concerns in digital interventions. In our study, high completion rates suggest that the use of gamification, weekly reminders, and user-friendly interfaces contributed positively to participation. These strategies are supported by literature indicating that engaging content and reinforcement mechanisms are key predictors of adherence in digital programs (10,11). However, it is important to recognize that digital interventions may not be suitable for all adolescents, particularly those with severe or complex mental health conditions requiring in-person evaluation (12).

The limitations of the present study include a relatively short follow-up duration and reliance on self-reported measures, which may be susceptible to response bias. Additionally, the intervention was conducted in a controlled trial setting, which may not fully reflect real-world implementation challenges such as internet access inequality or varying levels of digital literacy among adolescents and their caregivers (13,14). Future research should explore long-term outcomes, cost-effectiveness, and the impact of integrating digital CBT into school-based mental health systems (15).

In conclusion, digital CBT represents a promising and effective approach for addressing adolescent depression. Its potential for wide reach, personalization, and adaptability makes it a valuable tool in bridging the treatment gap in youth mental health care.

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