Due to the demographical development, age-related diseases will drastically increase over the next decades. To face this healthcare challenge, early and accurate identification of cognitive impairment is crucial. The assessment of neurocognitive functioning ideally requires a tool that is short, easy to administer and interpret, and has high diagnostic accuracy. In this context, the use of computerized test batteries is receiving increasing attention. Compared to paper-pencil tests, computerized test batteries have many advantages. The possibility to measure reaction times may provide additional information. Moreover, test questions are always presented the exact same way, examiner-related bias is eliminated, and results are available immediately after examination. Due to the ability to adjust the level of difficulty to the performance of the individual, floor and ceiling effects may be minimized. Additionally, costs are reduced, and fewer materials and less trained personnel are required. Finally, big data approaches and the use of machine learning algorithms are becoming more popular in the field of clinical diagnostics, and computerized cognitive test batteries may facilitate future data collection to this aim.

In 2014, we developed a self-administered tablet computer program for the iPad (CogCheck) to assess preoperative cognitive functioning in surgery patients.

The cognitive tests used in the CogCheck application are identical or similar to the paper-and-pencil tests that are currently used in dementia diagnostics. Replacing some of the paper-and-pencil tests by a computerized test battery may facilitate the routine neuropsychological examinations. Thus, we aim to investigate the diagnostic accuracy and user-friendliness of CogCheck when applied in a cognitively impaired patient sample. In a first step, the diagnostic properties of CogCheck will be examined by differentiating between healthy controls and patients with mild or major neurocognitive disorder (NCD) predominantly due to Alzheimer's disease (AD). Data from healthy controls have been collected (EKNZ Req-2016-00393) in a previous normative study of CogCheck. Thus a further aim is to investigate the user-friendliness of CogCheck in patients with mild or major NCD predominantly due to AD.

The primary aim of our study is to investigate the diagnostic accuracy of CogCheck for patients with mild or major NCD predominantly due to AD in a German-speaking population.

Secondary aims are: (1) to examine the user-friendliness of CogCheck in patients with mild or major NCD predominantly due to AD, (2) to compare the results between cognitively healthy individuals (EKNZ Req-2016-00393) and patients with mild or major NCD predominantly due to AD on each of the CogCheck subtest, (3) to establish an algorithm with the CogCheck subtests that optimally distinguishes between cognitively healthy controls (EKNZ Req-2016-00393) and patients with mild or major NCD predominantly due to AD, (4) to compare the diagnostic properties of CogCheck with the ones of the currently used paper-pencil tests.

Inclusion Criteria:

1. Age ≥65 years
2. Education ≥7 years
3. Fluency in the German language
4. Completed neuropsychological assessment (max. 3 months before data collection of CogCheck)
5. Informed consent signed
6. Clinical course based on caregiver information and neuropsychological assessment profile strongly suggest mild or major NCD predominantly due to AD.

Exclusion Criteria:

1. Severe sensory (e.g. auditory, visual) or motor impairment (e.g. essential tremor, paresis, dyskinesia) interfering with cognitive testing
2. MMSE score ≤20/30 or MoCA ≤12/30.

The study population is patients undergoing a neuropsychological assessment at the Memory Clinic of the University Department of Geriatric Medicine FELIX PLATTER in Basel, Switzerland.