Remote testing in Abbiategrasso (RTA): results from a counterbalanced cross-over study on direct-to-home neuropsychology with older adults.

BACKGROUND: The SARS-CoV-2 pandemic forced to rethink teleneuropsychology, since neuropsychological assessments started to be performed by phone or videoconference, with personal devices and without direct assistance from the clinician, a practice called "Direct-To-Home NeuroPsychology" (DTH-NP). AIMS: The present study, employing a counterbalanced cross-over design, was aimed at evaluating (1) the feasibility and (2) the acceptability of DTH-NP in Italian older adults without previously diagnosed neurocognitive disorder, (3) the comparability between remote and face-to-face administration of selected neuropsychological tests. METHODS: Fifty-eight community-dwelling older adults (65-85 years) were randomly assigned to one of two groups performing a complete neuropsychological assessment remotely (via phone call and videoconference) and face-to-face, in a counterbalance order, 8 weeks apart. The study recruitment rate was calculated, and the number of uncompleted tests and acceptability questionnaire responses were compared between the two administration modalities. Comparability was defined as good reliability of DTH-NP (intraclass correlation coefficient) and agreement between remote and face-to-face scores (Bland-Altman plots). RESULTS: Recruitment rate was 81%, with a preference for telephonic contact (79%). The acceptability analysis did not reveal any issues related to the DTH-NP assessment, even if most participants would rather repeat it face-to-face. Tests assessing short-term memory, language, and reasoning showed good comparability. DISCUSSION AND CONCLUSION: Our results point out to a good recruitment rate in a DTH-NP study in an Italian population of older adults (mean age = 80), satisfying acceptability of DTH-NP and remote-face-to-face comparability of certain verbally mediated tests. Further studies including larger samples in videoconference modality, and outpatients, could better clarify its strengths and limits.

An Improved Particle Swarm Optimization Algorithm for Irregular Flight Recovery Problem

As with the rapid development of air transportation and potential uncertainties caused by abnormal weather and other emergencies, such as Covid-19, irregular flights may occur. Under this situation, how to reduce the negative impact on airlines, especially how to rearrange the crew for each aircraft, becomes an important problem. To solve this problem, firstly, we established the model by minimizing the cost of crew recovery with time-space constraints. Secondly, in view of the fact that crew recovery belongs to an NP-hard problem, we proposed an improved particle swarm optimization (PSO) with mutation and crossover mechanisms to avoid prematurity and local optima. Thirdly, we designed an encoding scheme based on the characteristics of the problem. Finally, to verify the effectiveness of the improved PSO, the variant and the original PSO are used for comparison. And the experimental results show that the performance of the improved PSO algorithm is significantly better than the comparison algorithms in the irregular flight recovery problem covered in this paper. © 2022, Springer Nature Switzerland AG.