ABSTRACT
BACKGROUND: More sensitive and less burdensome efficacy end points are urgently needed to improve the effectiveness of clinical drug development for Alzheimer disease (AD). Although conventional end points lack sensitivity, digital technologies hold promise for amplifying the detection of treatment signals and capturing cognitive anomalies at earlier disease stages. Using digital technologies and combining several test modalities allow for the collection of richer information about cognitive and functional status, which is not ascertainable via conventional paper-and-pencil tests. OBJECTIVE: This study aimed to assess the psychometric properties, operational feasibility, and patient acceptance of 10 promising technologies that are to be used as efficacy end points to measure cognition in future clinical drug trials. METHODS: The Method for Evaluating Digital Endpoints in Alzheimer Disease study is an exploratory, cross-sectional, noninterventional study that will evaluate 10 digital technologies' ability to accurately classify participants into 4 cohorts according to the severity of cognitive impairment and dementia. Moreover, this study will assess the psychometric properties of each of the tested digital technologies, including the acceptable range to assess ceiling and floor effects, concurrent validity to correlate digital outcome measures to traditional paper-and-pencil tests in AD, reliability to compare test and retest, and responsiveness to evaluate the sensitivity to change in a mild cognitive challenge model. This study included 50 eligible male and female participants (aged between 60 and 80 years), of whom 13 (26%) were amyloid-negative, cognitively healthy participants (controls); 12 (24%) were amyloid-positive, cognitively healthy participants (presymptomatic); 13 (26%) had mild cognitive impairment (predementia); and 12 (24%) had mild AD (mild dementia). This study involved 4 in-clinic visits. During the initial visit, all participants completed all conventional paper-and-pencil assessments. During the following 3 visits, the participants underwent a series of novel digital assessments. RESULTS: Participant recruitment and data collection began in June 2020 and continued until June 2021. Hence, the data collection occurred during the COVID-19 pandemic (SARS-CoV-2 virus pandemic). Data were successfully collected from all digital technologies to evaluate statistical and operational performance and patient acceptance. This paper reports the baseline demographics and characteristics of the population studied as well as the study's progress during the pandemic. CONCLUSIONS: This study was designed to generate feasibility insights and validation data to help advance novel digital technologies in clinical drug development. The learnings from this study will help guide future methods for assessing novel digital technologies and inform clinical drug trials in early AD, aiming to enhance clinical end point strategies with digital technologies. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/35442.
ABSTRACT
BACKGROUND: Multiple survey studies have demonstrated a mental health (MH) burden of COVID-19 globally. However, few studies have examined relevant risk factors for pandemic-related MH issues. METHODS: A link to an online survey was posted from April 8th - June 11th, 2020 which included questions regarding COVID-19 experience, perceived impact of the pandemic on life domains (e.g., social communication, finances), behavioural alterations (e.g., online activities, substance use), and MH treatment history. Current psychiatric symptom severity and impairment were evaluated using the Generalized Anxiety Disorder-7, Patient Health Questionnaire-9, and the Perceived Stress Scale. RESULTS: Overall, 632 individuals (82% female, mean age:42.04 ± 16.56) in Canada and the United States completed the survey. While few reported contracting COVID-19 (0.5%), the impact of the pandemic was evident, with a vast majority reporting anxiety around COVID-19 infecting loved ones (88%). Almost half (43%) reported previous MH treatment and 31% met criteria for GAD, 29% for MDD and 63% reported significantly high levels of stress. Female sex, younger age and past MH treatment emerged as significant predictors of these issues(p < .01). Age-related differences in the impact of COVID-19 on life domains, substance use, and online activity were also noted. CONCLUSION: The findings from the current sample add to the growing literature suggesting negative effects of COVID-19 on MH, while highlighting specific risk factors. Age may be an important factor in predicting MH during this pandemic.