An inexpensive electrochemical sensor for the detection of formic acid (HCOOH), recently recognized as a biomarker associated with cognitive abilities, can reveal early-stage Alzheimer's disease. In this context, electrochemical sensors based on graphitic carbon nitride (GCN) nanosheets are developed to detect formic acid. Additionally, GCN nanostructures are chemically decorated with various hard-acid cationic dopants, including Cr3+, Fe3+, and Sn4+ ions, and treated with formic acid to study the influence of cationic dopants and formic acid treatment on the surface morphology, electrochemical characteristics such as electroactive surface area, heterogeneous rate constant, interfacial charge-transfer resistance, and sensing properties of the resulting Cr-GCN, Fe-GCN, or Sn-GCN materials. Cationic dopants generally enhance the electrochemical properties and effectiveness of the resulting sensors, with Cr-GCN exhibiting the highest sensitivity of 4.87 μA/μM. In contrast, formic acid treatment of pristine and cation-doped GCN has a detrimental effect on the electrocatalytic properties of these materials. Overall, these electrochemical sensors, characterized by their excellent sensitivity, sub-micromolar (< 1 μM) formic acid detection capability, and cost-effectiveness, hold significant potential in facilitating point-of-care testing, disease monitoring, and predicting treatment outcomes related to Alzheimer's disease.