Mental health disorders such as depression, anxiety, and cognitive impairment are major contributors to global disability and reduced quality of life (1). The World Health Organization estimates that one in eight individuals worldwide is affected by a mental disorder, with depression and anxiety being the most prevalent (2). Despite their burden, mental health conditions often remain underdiagnosed and undertreated, particularly in primary care settings where time constraints, limited training, and social stigma may hinder detection and management (3,4).

Primary care plays a critical role in the early identification and treatment of mental health disorders due to its accessibility and patient continuity. However, standard mental health screening in these settings is inconsistently applied and often relies on subjective clinical judgment (5). Traditional paper-based screening methods are not only time-consuming but may also fail to engage patients effectively or integrate seamlessly into clinical workflows (6).

The emergence of digital cognitive tools and e-screening platforms has opened new opportunities for improving mental health assessment in primary care. These technologies offer standardized, rapid, and user-friendly methods for screening multiple domains—including mood, anxiety, and cognition—through validated instruments such as the PHQ-9 for depression, GAD-7 for anxiety, and Montreal Cognitive Assessment (MoCA) for cognitive impairment (7–9). By embedding these tools into routine primary care visits, clinicians can be alerted to potential mental health issues in real-time, thereby enhancing referral rates, diagnosis accuracy, and timely intervention (10,11).

Preliminary studies suggest that digital screening tools may improve patient engagement, reduce stigma, and facilitate integration of mental health into general health services (12,13). Additionally, patient satisfaction and adherence appear to be higher when digital technologies are used, especially in busy urban clinics with high patient volume (14). However, evidence from real-world pilot implementations remains limited, particularly in low-resource primary care environments.

This pilot study was undertaken to assess the feasibility, utility, and preliminary outcomes of integrating a digital mental health screening tool into a primary care workflow. The study specifically evaluated screening rates, identification of at-risk individuals, follow-up adherence by primary care providers, and patient satisfaction with the digital process.

Adult patients aged 18 to 65 years presenting for scheduled general medical consultations were considered eligible. Patients were excluded if they had previously diagnosed psychiatric illness requiring ongoing psychiatric management, cognitive disabilities preventing self-administered assessments, or were unwilling to provide informed consent. A total of 250 participants were enrolled through convenience sampling.

Screening Tool and Procedure

The digital mental health screening tool was designed as a tablet-based application and integrated into the patient check-in process. It consisted of the following validated instruments:

PHQ-9: A 9-item questionnaire for screening and assessing the severity of depressive symptoms.

GAD-7: A 7-item instrument for evaluating anxiety symptoms.

MoCA-short: A brief version of the Montreal Cognitive Assessment used to screen for mild cognitive impairment.

Patients completed the digital screening independently in the waiting area prior to meeting the physician. On average, the screening process took approximately 7 to 10 minutes. Immediate automated scoring was generated and securely sent to the consulting physician’s terminal before the appointment.

Outcome Measures

The primary outcomes included:

• Screening completion rate
• Prevalence of positive cases for depression (PHQ-9 ≥10), anxiety (GAD-7 ≥10), and cognitive impairment (MoCA-short <22)
• Average time taken to complete screening
• Physician adherence to follow-up (referrals or in-clinic management documented in medical records)
• Patient satisfaction (measured through a brief post-screening survey using a 5-point Likert scale)

Data Collection and Analysis

Demographic data, screening outcomes, and physician follow-up actions were documented using the clinic’s electronic health records. Descriptive statistics were applied to summarize participant characteristics and screening results. Group comparisons (e.g., follow-up adherence between demographic subgroups) were analyzed using Chi-square tests for categorical data and t-tests for continuous variables. A p-value of <0.05 was considered statistically significant. All analyses were conducted using SPSS version 25.0.

Participant Demographics

Out of 250 patients approached, 230 individuals (92%) completed the digital screening tool. The mean age of the participants was 38.4 ± 12.6 years. Females comprised 54.3% of the sample, and the majority of participants (71.7%) had completed at least secondary education. Demographic characteristics are summarized in Table 1.

Table 1: Demographic Characteristics of Study Participants (n = 230)

Screening Outcomes

Among the 230 respondents, 60 (26.1%) screened positive for moderate to severe depression (PHQ-9 ≥10), 42 (18.3%) for clinically significant anxiety (GAD-7 ≥10), and 28 (12.2%) showed indications of mild cognitive impairment (MoCA-short <22). The average time to complete the screening was 7.2 ± 2.1 minutes. These outcomes are presented in Table 2.

Table 2: Mental Health Screening Outcomes

Physician Follow-up and Referrals

Out of the patients with positive screening results (n = 102), 86 (84.3%) received documented follow-up actions from primary care providers, including referrals to mental health specialists or initiation of counseling. Follow-up adherence by condition is shown in Table 3.

Table 3: Follow-up Actions by Primary Care Providers for Positive Screens (n = 102)

Patient Satisfaction

Among participants, 202 (87.8%) rated the digital tool as helpful, and 210 (91.3%) found it easy to use. Satisfaction results are summarized in Table 4.

Table 4: Patient Satisfaction with Digital Screening Tool

This pilot study assessed the integration of a digital cognitive screening tool for mental health assessment in a primary care setting and found it to be both feasible and effective. High completion rates (92%) and positive patient feedback suggest that digital tools can be smoothly incorporated into clinical workflows without disrupting consultation times. The observed prevalence of depression (26.1%), anxiety (18.3%), and cognitive decline (12.2%) is consistent with global estimates for primary care populations, where many cases remain undetected and untreated (1,2).

Primary care serves as a critical frontline for early detection of mental health conditions, yet various barriers—such as limited time, lack of mental health training, and stigma—often hinder the identification of these disorders (3,4). Traditional paper-based assessments have limited reach and practicality, especially in high-volume settings. In contrast, digital tools like the one used in this study offer automated scoring, reduced administrative burden, and instant clinical integration, leading to improved provider responsiveness (5,6).

The use of validated instruments such as the PHQ-9, GAD-7, and MoCA-short ensures reliability in detecting clinically significant conditions. Previous studies have supported the use of the PHQ-9 in primary care for depression screening due to its diagnostic sensitivity and ease of use (7), while GAD-7 is well-established for detecting generalized anxiety disorder (8). The shortened version of MoCA has also proven useful for preliminary cognitive screening in busy outpatient settings (9,10).

Similarly, Park et al. reported that comprehensive digital tools could enhance screening and follow-up, particularly when embedded into routine practice (11). In this study, 84.3% of those with positive results were followed up appropriately by the providers, demonstrating that real-time alerts to clinicians can facilitate timely management—a challenge that often impedes traditional screening approaches (12,13).

Furthermore, ease of use is a critical factor influencing the adoption of technology in clinical settings, especially among populations with varying digital literacy levels (14,15).

Despite these promising results, this study has limitations. Being a single-center pilot study with a limited sample size, generalizability is restricted. Additionally, the follow-up focused only on physician documentation and did not track long-term patient outcomes, such as symptom improvement or referral completion. Future research should involve multicenter trials, incorporate longitudinal assessments, and explore cost-effectiveness to better understand scalability.

This pilot study provides evidence that digital cognitive tools can be effectively embedded in primary care for mental health screening. High user engagement, accurate identification of at-risk individuals, and appropriate physician response indicate that digital integration may bridge significant gaps in mental health detection and intervention. Broader implementation and further evaluation across diverse populations are warranted.

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