## 4 Discussion  
This systematic review assessed the diagnostic accuracy of digital solutions used for cognitive screening, further analyzing whether these were paper-based digital solutions or innovative digital solutions. There is low- to moderate-quality evidence suggesting that digital solutions are reasonably sensitive and specific to be used for cognitive impairment screening. The index tests assessed were quite variable, with sensitivity levels varying between 0.49 and 0.95 and specificity levels between 0.50 and 0.91. The index tests classified as innovative digital solutions offered at least a sensitivity value of 0.78 but showed lower specificity levels than the other subgroup (between 0.50 and 0.90). The index tests classified as paper-based digital solutions revealed at least a specificity value of 0.72, but sensitivity started at 0.49 (and eight studies out of fifteen reported sensitivity values below 0.78). The study that reported higher sensitivity values among those tests classified as paper-based digital solutions reported on the Beijing version of the MoCA (sensitivity = 0.95; specificity = 0.87) [62]. This performance was similar to the MoCA paper-and-pencil version of the instrument for detecting MCI in elderly Chinese living in communities (sensitivity = 0.81; specificity = 0.83) [77], suggesting that both versions are equivalent. For the subgroup of tests classified as innovative digital solutions, the Digital Screening System [76] showed the highest sensitivity and specificity levels (sensitivity = 0.85, specificity = 0.90). These two index tests were assessed against robust reference tests (a clinical assessment performed by a team of health professionals including a neurologist, a geriatrician, and a psychiatrist (MoCA-CC [62]), and experienced doctors and neuopsy-chologists (Digital Screening System [76])). The assessment by a team of specialists is the gold standard for cognitive evaluation [78]. The Digital Screening System aims to assess visuospatial constructional capabilities, visual memory function, and cognitive functions, such as visuospatial abilities, visual episodic memory, organization skills, attention, and visuomotor coordination. It is based on the neuropsychological test Rey-Osterrieth Complex Figure and uses a data-driven convolutional neural network architecture through transfer learning and deep learning methods [76]. Despite being developed from inception to be applied by electronic means, most innovative digital solutions are inspired by traditional neuropsychological tests. In the innovative digital solutions subgroup, the index test Virtual Supermarket Program (VSP) stands out for using virtual reality game-based tests in screening for MCI in older adults, showing an attempt to develop a test that uses a task from daily life, potentially increasing its ecological validity. Interestingly, this test showed high sensitivity and specificity values (sensitivity = 0.85; specificity = 0.80) [73], suggesting that there is value in exploring the use of game-based tests to screen for cognitive impairment. The index test that presented lower sensitivity and specificity in the subgroup of index tests based on paper-and-pencil tests is the MemTrax test (MTX) (sensitivity = 0.49, specificity = 0.78) [67]. This index test was based on the Continuous Recognition Task (CRT) paradigm. Among the index tests developed from inception to be applied as digital solutions, Cognivue [70] and CogEvo [58] showed the lowest sensitivity and specificity levels (Cognivue: sensitivity = 0.78, specificity = 0.50; CogEvo: sensitivity = 0.78, specificity = 0.54). These three index tests that presented the lowest sensitivity/specificity levels were compared against a reference standard consisting of only brief cognitive screening instruments (i.e., MoCA, SLUMS, and MMSE, respectively). The MoCA paper-and-pencil test demonstrated a sensitivity of 90% and a specificity of 87% for detecting MCI [15].