Virtual Cognitive Screenings and Interviews of Patients with Neurodegenerative Conditions Associated with Alzheimer’s Disease and Parkinson’s Disease

Abstract

The current pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), commonly referred to as COVID-19, brings myriad challenges to research conducted among those more susceptible to the virus. According to the United States (US) Centers for Disease Control (CDC), eight out of ten re-ported COVID-19 deaths are among people > 65 years of age and older. Nonetheless, researchers must continue the crucial work of investigating and understanding diseases that affect the elderly. The focus of this white paper is to assess the challenges associated with research within the elderly population with neurocognitive conditions. Specifically, this paper addresses the need for the standardized administration of performance measures (e.g., neurocognitive assessments) among a dementia population while ensuring the physical safety of participants. Consideration is given to the administration of performance measures and the availability and feasibility of administering these measures remotely to a population that may have difficulty using novel technologies. In implementing remote research assessments, it is suggested that researchers fol-low a GAMMA approach by: 1) establishing clear Guidance on remote visit expectations and processes; 2) establishing Appropriate exclusionary criteria in the development of the study design; 3) providing subjects Appropriate study Materials for visual processing; 4) incorporating Multiple data sources in the overall study design (e.g., caregiver input); and 5) Acknowledging that there will be study limitations as researchers use emerging technology with this patient population, and using mitigation strategies for these limitations where possible.

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Lenderking, W. , Abel, C. , Brookes, E. , Sargalo, N. , Filipenko, D. , Smith, C. and Lo, R. (2021) Virtual Cognitive Screenings and Interviews of Patients with Neurodegenerative Conditions Associated with Alzheimer’s Disease and Parkinson’s Disease. Advances in Alzheimer's Disease, 10, 19-32. doi: 10.4236/aad.2021.102002.

1. Introduction

Due to the widespread nature of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the number of deaths globally associated with COVID-19 continues to increase [1]. The groups most vulnerable to the virus in society are the elderly and those with underlying health conditions, resulting in higher mortality among these groups [2] [3] [4]. According to the World Health Organization [5], there are approximately 50 million people living with dementia worldwide, with 10 million new cases every year; this accounts for approximately 5% - 8% of the general population over the age of 60 years [6]. While the elderly population may be particularly vulnerable to COVID-19, the need continues for research into Alzheimer’s disease (AD) and other forms of dementia.

The United States (US) Food and Drug Administration (FDA) has published Guidance for the conduct of clinical trials during the COVID-19 pandemic [6]. The FDA guidelines recommend utilization of alternative methods of completing study visits, for example, virtual visits held by telephone, to ensure the safety of vulnerable participants. Since it remains crucial to collect screening and performance measures (e.g., the Dementia Severity Rating Scale (DSRS) [7], Clinical Dementia Rating (CDR) [8], and Mini-Mental State Examination (MMSE) [9] ), and to evaluate disease severity, other options are needed for collecting qualitative and performance data from the dementia population and their caregivers. In addition to assessing cognitive performance using performance-based outcomes (PerfOs), outcomes data are often collected from these patients using other clinical outcome assessment (COA) measures to assess how they are feeling as well as their level of functioning and quality of life (QoL).

The use of virtual technology in research is becoming both more necessary and more acceptable. Due to the characteristics of dementia such as disturbed emotions, perception, motor activity, mood [10], and cognitive impairment [11], and since populations with cognitive issues may face additional challenges when moving away from traditional, in-person data collection, there are considerable hurdles to overcome and logistical complications to consider.

Virtual and telephone interviews have been used for some years in qualitative data collection among patient populations [12] and caregivers, for example in amyotrophic lateral sclerosis (ALS) [13]. A modified 26-item version of the MMSE has been validated for telephone use (TMMSE) [14] for patients with AD; the TMMSE omits items that are not possible to confirm during telephone completion (i.e., “What floor of the building are we on?”) and adds new or revised items for the telephone administration (e.g., the examiner asks the patient to follow a three-step command, “Say, ‘hello,’ tap the mouthpiece of the phone 3 times, then say, ‘I’m back.’”) [15]. Educational information has been delivered to caregivers of patients with dementia via the telephone for support in self-efficacy and assessment of caregiver burden [16]. This paper will discuss the use of technology among patient populations with AD, Parkinson’s disease (PD), and mild cognitive impairment (MCI), and the use of remote data collection, specifically qualitative interviewing and performance tools, to assess disease severity.

2. Methods

Targeted Clinical Trial Review

A review of ongoing and completed clinical trials conducted in neurodegenerative conditions including AD, PD, and MCI populations was conducted using the FDA clinicaltrials.gov database in April 2020. The search aimed to identify COA measures being used in these populations. Three separate searches were conducted using the following terms: “Alzheimer’s disease (AD),” “Parkinson’s disease (PD),” or “mild cognitive impairment (MCI),” Phase II and III, 2017 to present (past 3 years), adult, and older adults. Figure 1 illustrates the process used to determine the measures for review in the current paper.

We also searched products with patient-reported outcome (PRO) claims that had been approved by the FDA and European Medicines Agency (EMA), using the FDA and EMA databases to identify COA measures utilized to support label claims in AD, PD, and MCI.

Review of Electronic Platforms

A manual internet search of available electronic data platforms and videoconferencing systems was performed using the terms “videoconferencing platforms” and “web-based platforms.” Each identified platform was reviewed for suitability

Figure 1. Selection of measures for review.

for use in data collection among patients with neurodegenerative conditions. Information about previous use of the platforms included whether they have been used in healthcare or research settings, and HIPAA compliance was assessed for each (Table 1). Other information such as video sharing capability, screen sharing, file sharing, technical support, and security was collected for each platform.

Table 1. Review of online data and videoconferencing platforms.

The existing FDA Guidance allows use of software in the context of health care and research. To protect patient privacy, remote data acquisition, transmission, and storage must be secure. This includes electronic platforms designed for remote assessments that are required to have automated audit trails [6]. Although platforms for remote data collection are not considered to be medical devices as they are not specifically intended for use in the diagnosis, treatment, or prevention of disease, they must provide a secure way of communication [17]. When considering an electronic platform, it is critical to review its compliance with HIPAA requirements to ensure that the electronic health information collected through the software is protected.

3. Results

Review of measures

The targeted search identified a total of 204 clinical trials (n = 129 AD, n = 35 PD, n = 40 MCI). The studies were screened for utilization of a COA measure. Those that mentioned COAs used were included in the review. COAs were utilized in 129 studies to assess symptoms (AD: n = 82, PD: n = 26, MCI: n = 21).

A total of 84 COA measures were identified as having been used in those 129 trials (21 performance-related outcomes (PerfOs), 36 PROs, 8 clinician-reported outcomes (ClinROs), and 19 generic measures (PROS not specific to neurodegeneration). Studies that incorporated the use of a PRO, PerfO, or ClinRO were included in the review.

Sixteen COA measures (14 disease-specific PerfOs, 2 generic PerfO measures) were identified as having been used most frequently across the three conditions, and were selected for further review of their suitability for completion in a virtual/remote, non-face-to-face setting with technological devices (Table 2 and Table 3). The Alzheimer’s Disease Assessment Scale-Cognitive Subscale (ADAS-Cog), Alzheimer’s Disease Cooperative Study-activities of daily living scale (ACDS-ADL), and Clinician Interview-Based Impression of Change (CIBIC) measures were also mentioned as part of label claims in these conditions. Each of the sixteen COA measures was assessed for suitability for virtual/remote completion. Props and tools required as part of the assessment (i.e., paper, pen, stopwatch, and objects for item recognition) as well as worksheets and scoring methods were reviewed in detail.

Verbally Administered Measures for Virtual Administration

The Clinical Dementia Rating Scale Sum of Boxes (CDR-SOB) is a global assessment dementia screener used to assess severity of dementia using a 5-point scale system. The CDR-SOB does not require the use of props for administration; the interviewer conducts separate interviews with both the participant and the study partner (e.g., caregiver), recording their responses for comparison using the score sheet. The CDR-SOB can be conducted via telephone or web-conferencing and, in a recent study, showed no significant statistical difference from in-person administration [15]. The Logical Memory Test (LMT), Hopkins Verbal Learning Test (HVLT), Free and Cued Selective Reminding Test (FCSRT), and Controlled Oral Word Association Test (COWAT) are widely used measures designed to assess episodic memory, verbal learning, and verbal

Table 2. COA measures utilized in AD, PD, and MCI clinical trials.

Table 3. COA measures mentioned in label claims search.

fluency. These measures are all administered verbally by an interviewer and could also be administered remotely without adjustments to the measures [18] [19]. Indeed, in studies conducted in healthy, elderly populations without dementia, the Wechsler LMT, HVLT, Bushke Selective Reminding Task, and COWAT [18] [19] measures showed no statistically significant differences when administered face-to-face versus via telephone, with the exception of the delayed portion of the Bushke Selective Reminding Task [18].

Pen-and-Paper Measures for Virtual Administration

The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) and the ADAS-Cog are frequently used measures designed to assess attention, language, immediate and delayed memory, as well as visuospatial skills. These measures require props (i.e., a pen, watch, flower, harmonica, or other things) in the item recognition and recall sections. These items could be shown to participants via web-conferencing, or alternative tasks could be developed that do not require props. Worksheets are required for completion of pen-and-paper tasks in the RBANS, ADAS-Cog, MMSE, and Montreal Cognitive Assessment (MoCA) by the participant. These worksheets could be mailed to participants in advance of the assessment, with instructions noting that patients are not to open the packet until instructed to do so by the administrator. The ADAS-Cog has been conducted remotely in older adults with and without cognitive impairment successfully [20], with strong correlation between in-person and web-conference data collection in those with MMSE < 17. However, potential barriers could include access to and ease of use of technology [21]. Use of web-conferencing and cameras could enable props such as word cards to be shown to the participant. The 26-item TMMSE has been previously utilized in studies where data were not collected in person and showed strong correlation with the in-person administration of the MMSE [14].

Device-based Measures for Virtual Administration

The Cambridge Neuropsychological Test Automated Battery (CANTAB) and those from Cogstate Ltd are designed to detect changes in neuropsychological ability and are conducted electronically using a tablet computer provided to the participant during the interview. Devices could be shipped to participants ahead of the interview provided that participants are able to log into and use the device without assistance from the interviewer. Alternatively, a caregiver could receive training on how to set the assessment up for the participant. One potential risk is that sponsors and researchers may be loath to send out valuable hardware that may not be returned in a timely manner.

The MoCA has been modified for virtual use by the developer, with telephone, video-conference, and app-based options available [22]. The telephone option removes the visual elements of the test, while the video-conferencing and app options allow administration of the full measure [22]. A recent study among an elderly population of veterans indicated that in-person and video-administration methods showed comparable accuracy and inter-rater reliability [23] [24].

Additionally, the RBANS has been validated for virtual administration through the use of video-conferencing and interfacing iPads [23] [25]. Analyses have shown that scores obtained via virtual administration are highly correlated with those obtained via face-to-face administration, with minimal differences in measure index scores [25] [26].

Phone App Measures for Virtual Administration

The 9 Hole Peg test and the 6-Minute Walk test are performance-based measures designed to detect hand dexterity and aerobic capacity. These measures are not widely available for remote completion; the challenge remains that they require equipment and observation by an interviewer. However, the 9 Hole Peg test has been developed for use in an app [27] using Apple’s ResearchKit [28] and tested for use in patients with multiple sclerosis.

The product label claims search identified five COAs in total (all ClinRO measures), which have been used in clinical trials to support label claims for Alzheimer’s treatment. The measures identified were the CIBIC with Caregiver Input (CIBIC+), ADAS-Cog, ADCS-ADL, Severe Impairment Battery (SIB), and Post-traumatic Stress Diagnostic Scale (PDS). With regards to PD, a total of five COAs (ClinROs, ObsROs, and PROs) were identified. These measures were the Unified Parkinson’s Disease Rating Scale (UPDRS), Scale for the Assessment of Positive Symptoms (SAPS-PD), Sickness Impact Profile (SIP), home daily diaries, and Investigator/clinician global impression (CGI).

Review of Electronic Platforms

Online data and videoconferencing platforms were also searched using a manual internet search, and were reviewed for suitability for use in data collection in this population using a checklist developed by the study team (Table 1). All of the 15 platforms identified were HIPAA compliant [29] [30]; all 15 were suitable for use on a desktop computer, 13 for use on a Tablet, and 13 for use on a Smartphone. Screen sharing was enabled on all but three of the platforms. All platforms, except for MegaMeeting, have been used in healthcare settings previously.

4. Discussion and Conclusion

Our review indicates that there are indeed viable performance and other outcome measures available for virtual administration among a mild-to-moderate dementia population. Furthermore, secure data-transfer platforms are available to ensure data privacy. With the rapid rise in smartphone and computer use, global technology continues to advance and bring new opportunities for research and data collection. However, the elderly are often at a disadvantage when presented with new technology due to a lack of fluency with, or apprehension about, devices and program applications [31] [32]. In light of the current pandemic, it is incumbent upon researchers to provide easily accessible platforms and procedures to ensure the physical safety of this vulnerable population during study assessments, while concurrently ensuring that the assessments are conducted in a standardized fashion. These considerations can be adequately met by employing a combination of strategies, referred to by the authors as the GAMMA Approach. This approach is described subsequently and is a suggested guide for researchers as they implement remote research assessments among patients with dementia.

Guidance on expectations—Prior to assessing and/or interviewing patients, researchers should provide clear Guidance on what the patient can expect and how the assessment and/or interview will be conducted. A document outlining procedures and any technological requirements should be provided to patients well in advance of the study interaction. If possible, the document should also include screenshots and a step-by-step guide to ensure patients can easily navigate any technology that they are required to use and/or set-up prior to the assessment and/or interview. Some recent qualitative studies in older, healthy adults have shown that older populations are interested in adopting new technology [33] [34], but are hesitant to do so due to how quickly technology changes and concerns with data privacy [33].

Appropriate Exclusionary Criteria—Importantly, researchers must ensure Appropriate exclusionary criteria are used. Recognizing the severity of the disease and level of impairment should be a key driving factor as researchers develop study designs. The use of virtual platforms and advanced technology may prove too burdensome among patients with more advanced disease, and may result in increased agitation or frustration among patient participants. Patients with more severe cognitive deficits may not be the proper candidates for virtual assessments, and paper-and-pencil administration of performance measures may ultimately be the best choice for the more clinically advanced dementia populations. For data collection purposes, it is recommended that cognitive assessment of patients with severe dementia continue to be conducted in person.

Materials for Visual Processing—During the interview or assessment, patients should be provided materials for visual processing, either through a shared computer screen or a mailed hard copy of documents to be discussed. This allows an additional level of engagement and opportunity to process materials and can troubleshoot potential issues such as poor attention or mild hearing impairments.

Multiple Data Sources—The incorporation of multiple data sources should be considered in the overall study design. For example, including caregivers (e.g., spouses, adult children, professional caregivers, etc.) can provide an additional level of robustness to the data, as well as an additional level of comfort to the patient. Caregivers can be incorporated into the study design to allow assistance with technology and provide proxy-reports on the patient’s level of cognitive functioning, either via interview or completion of an ObsRO. Additionally, the patient’s referring clinician can provide another level of detail that neither the patient nor caregiver can convey. Specifically, the clinician can provide detailed clinical feedback through interviews or through the completion of a ClinRO. Ideally, patients, caregivers, and clinicians could complete complimentary questionnaires that are widely used and validated for comparison with each other to determine the degree of alignment across observations and reports. A variety of complimentary measures are available from multiple sources, such as Health Measures (https://www.healthmeasures.net/), such as the PROMIS, NIH Toolbox, and the NeuroQoL measures [35].

Acknowledges Study Limitations—Finally, it is important to note that, as with any emerging technology and research, there will be study limitations. For example, measures may be administered in a non-standardized fashion, patients and caregivers may under-report disease symptoms or impacts, or patients may not have the level of insight needed to answer the research questions. Current research validating alternative administrations of measures will continue to be critical as we navigate technological resources and continue research under what has become the “new normal.” Anticipating study limitations and trying to find additional solutions in advance is important to the success and generalizability of the research.

Conflicts of Interest

The authors declare no conflicts of interest regarding the publication of this paper.

References

[1] Wang, H., Li, T., Barbarino, P., Gauthier, S., Brodaty, H., Molinuevo, J.L., et al. (2020) Dementia Care during COVID-19. The Lancet, 395, 1190-1191.
https://doi.org/10.1016/S0140-6736(20)30755-8
[2] Brown, E.E., Kumar, S., Rajji, T.K., Pollock, B.G., Mulsant, B.H. (2020) Anticipating and Mitigating the Impact of the COVID-19 Pandemic on Alzheimer’s Disease and Related Dementias. The American Journal of Geriatric Psychiatry, 28, 712-721.
https://doi.org/10.1016/j.jagp.2020.04.010
[3] D’Adamo, H., Yoshikawa, T. and Ouslander, J.G. (2020) Coronavirus Disease 2019 in Geriatrics and Long-Term Care: The ABCDs of COVID-19. Journal of the American Geriatrics Society, 68, 912-917.
https://doi.org/10.1111/jgs.16445
[4] Lloyd-Sherlock, P., Ebrahim, S., Geffen, L. and McKee, M. (2020) Bearing the Brunt of COVID-19: Older People in Low and Middle Income Countries. British Medical Journal, 368, m1052.
https://doi.org/10.1136/bmj.m1052
[5] World Health Organization (WHO) (2019) Dementia Fact Sheet.
https://www.who.int/news-room/fact-sheets/detail/dementia
[6] Food and Drug Administration (FDA) (2020) FDA Guidance on Conduct of Clinical Trials of Medical Products during COVID-19 Public Health Emergency. Guidance for Industry, Investigators, and Institutional Review Boards.
https://www.fda.gov/regulatory-information/search-fda-guidance-documents/fda-guidance-conduct-clinical-trials-medical-products-during-covid-19-public-health-emergency
[7] Clark, C.M. and Ewbank, D.C. (1996) Performance of the Dementia Severity Rating Scale: A Caregiver Questionnaire for Rating Severity in Alzheimer Disease. Alzheimer Disease and Associated Disorders, 10, 31-39.
https://doi.org/10.1097/00002093-199601010-00006
[8] Morris, J.C. (1993) The Clinical Dementia Rating (CDR): Current Version and Scoring Rules. Neurology, 43, 2412-2414.
https://doi.org/10.1212/WNL.43.11.2412-a
[9] Cockrell, J.R. and Folstein, M.F. (2002) Mini-Mental State Examination. In: Abou-Saleh, M.T., Katona, C.L.E., Anand, K.A., Eds., Principles and Practice of Geriatric Psychiatry, 2002 Edition, John Wiley & Sons, Ltd., Chichester, West Sussex, UK, 140-141.
https://doi.org/10.1002/0470846410.ch27(ii)
[10] Cerejeira, J., Lagarto, L. and Mukaetova-Ladinska, E.B. (2012) Behavioral and Psychological Symptoms of Dementia. Frontiers in Neurology, 3, 73.
https://doi.org/10.3389/fneur.2012.00073
[11] Lyketsos, C.G., Lopez, O., Jones, B., Fitzpatrick, A.L., Breitner, J. and DeKosky, S. (2002) Prevalence of Neuropsychiatric Symptoms in Dementia and Mild Cognitive Impairment: Results from the Cardiovascular Health Study. The Journal of the American Medical Association, 288, 1475-1483.
https://doi.org/10.1001/jama.288.12.1475
[12] Trier-Bieniek, A. (2012) Framing the Telephone Interview as a Participant-Centred Tool for Qualitative Research: A Methodological Discussion. Qualitative Research, 12, 630-644.
https://doi.org/10.1177/1468794112439005
[13] Kasarskis, E.J., Dempsey-Hall, L., Thompson, M.M., Luu, L.C., Mendiondo, M. and Kryscio, R. (2005) Rating the Severity of ALS by Caregivers over the Telephone Using the ALSFRS-R. Amyotroph Lateral Sclerosis, 6, 50-54.
https://doi.org/10.1080/14660820510027107
[14] Newkirk, L.A., Kim, J.M., Thompson, J.M., Tinklenberg, J.R., Yesavage, J.A. and Taylor, J.L. (2004) Validation of a 26-Point Telephone Version of the Mini-Mental State Examination. Journal of Geriatric Psychiatry Neurology, 17, 81-87.
https://doi.org/10.1177/0891988704264534
[15] Williams, J.B.W., Hannesdottir, K., Randolph, C., Eureyecko, E., Langbaum, J., Tariot, P., et al. (2014) Telephone Administration of the CDR—Excellent Agreement with Face-to-Face Administration.
https://www.medavante-prophase.com/wp-content/uploads/2015/07/telephone_administration_cdr1859bbc10e6e6cf4a23fff0000ac3285.pdf
[16] Kwok, T., Wong, B., Isaac, I., Chui, K., Young, D. and Florence, H. (2013) Telephone-Delivered Psychoeducational Intervention for Hong Kong Chinese Dementia Caregivers: A Single-Blinded Randomized Controlled Trial. Clinical Interventions in Aging, 8, 1191-1197.
https://doi.org/10.2147/CIA.S48264
[17] Food and Drug Administration (FDA) (2019) Policy for Device Software Functions and Mobile Medical Applications. Guidance for Industry and Food and Drug Administration Staff.
https://www.fda.gov/regulatory-information/search-fda-guidance-documents/policy-device-software-functions-and-mobile-medical-applications
[18] Mitsis, E.M., Jacobs, D., Luo, X., Andrews, H., Andrews, K. and Sano, M. (2010) Evaluating Cognition in an Elderly Cohort via Telephone Assessment. International Journal of Geriatric Psychiatry, 25, 531-539.
https://doi.org/10.1002/gps.2373
[19] Bunker, L., Hshieh, T.T., Wong, B., Schmitt, E.M., Travison, T., Yee, J., et al. (2017) The SAGES Telephone Neuropsychological Battery: Correlation with In-Person Measures. International Journal of Geriatric Psychiatry, 32, 991-999.
https://doi.org/10.1002/gps.4558
[20] Schwab, N.A., DesRuisseaux, L.A., Weinberg, M.S. and Arnold, S.E. (2020) Saving Cognitive Outcome Data in Alzheimer’s Disease Clinical Trials during the COVID-19 Pandemic: Commentary on the Virtual Administration of the ADAS-Cog. Alzheimers and Dementia, 6, e12081.
https://doi.org/10.1002/trc2.12081
[21] Carotenuto, A., Rea, R., Traini, E., Ricci, G., Fasanaro, A.M. and Amenta, F. (2018) Cognitive Assessment of Patients with Alzheimer’s Disease by Telemedicine: Pilot Study. JMIR Mental Health, 5, e31.
https://doi.org/10.2196/mental.8097
[22] Montreal Cognitive Assessment (MoCA). Remote MoCA Testing.
https://www.mocatest.org/faq/
[23] Geddes, M.R., O’Connell, M.E., Fisk, J.D., Gauthier, S., Camicioli, R., Ismail, Z., et al. (2020) Remote Cognitive and Behavioral Assessment: Report of the Alzheimer Society of Canada Task Force on Dementia Care Best Practices for COVID-19. Alzheimers and Dementia, 12, e12111.
https://doi.org/10.1002/dad2.12111
[24] DeYoung, N. and Shenal, B.V. (2019) The Reliability of the Montreal Cognitive Assessment Using Telehealth in a Rural Setting with Veterans. Journal of Telemedicine Telecare, 25, 197-203.
https://doi.org/10.1177/1357633X17752030
[25] Randolph, C., Tierney, M.C., Mohr, E. and Chase, T.N. (1998) The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS): Preliminary Clinical Validity. Journal of Clinical and Experimental Neuropsychology, 20, 310-319.
https://doi.org/10.1076/jcen.20.3.310.823
[26] Galusha-Glasscock, J.M., Horton, D.K., Weiner, M.F. and Cullum, C.M. (2016) Video Teleconference Administration of the Repeatable Battery for the Assessment of Neuropsychological Status. Archives of Clinical Neuropsychology, 31, 8-11.
https://doi.org/10.1093/arclin/acv058
[27] Shazino (2016) Shazino Launches Neurons ResearchKit App to Help Multiple Sclerosis Patients. Press Release, Lyon, France.
http://blog.shazino.com/articles/science/neurons-multiple-sclerosis/
[28] Apple Inc. (2020) Introducing ResearchKit.
http://researchkit.org/
[29] Compliancy Group (2020) Is Microsoft Teams HIPAA Compliant?
https://compliancy-group.com/is-microsoft-teams-hipaa-compliant/#:~:text=Yes%2C%20Microsoft%20Teams%20is%20HIPAA%20compliant
[30] Dykes, A. (2020) The Best HIPAA Compliant Video Conferencing Tools for Telehealth. Blog, Technology Advice.
https://technologyadvice.com/blog/healthcare/hipaa-video-conferencing-tools/
[31] Vaportzis, E., Clausen, M.G. and Gow, A.J. (2017) Older Adults Perceptions of Technology and Barriers to Interacting with Tablet Computers: A Focus Group Study. Frontiers in Psychology, 8, 1687.
https://doi.org/10.3389/fpsyg.2017.01687
[32] Pew Research Center (2017) Barriers to Adoption and Attitudes towards Technology.
https://www.pewresearch.org/internet/2017/05/17/barriers-to-adoption-and-attitudes-towards-technology/
[33] Abdelrahman, N.G., Haque, R., Polverento, M.E., Wendling, A., Goetz, C.M. and Arnetz, B.B. (2021) Brain Health: Attitudes towards Technology Adoption in Older Adults. Healthcare, 9, 23.
https://doi.org/10.3390/healthcare9010023
[34] Betts, L.R., Hill, R. and Gardner, S.E. (2019) There’s Not Enough Knowledge Out There: Examining Older Adults’ Perceptions of Digital Technology Use and Digital Inclusion Classes. Journal of Applied Gerontology, 38, 1147-1166.
https://doi.org/10.1177/0733464817737621
[35] Health Measures. NIH Toolbox®.
https://www.healthmeasures.net/explore-measurement-systems/nih-toolbox
[36] Schmitt, F.A., Saxton, J., Ferris, S.H., Mackell, J. and Sun, Y. (2013) Evaluation of an 8-Item Severe Impairment Battery (SIB-8) vs. the Full SIB in Moderate to Severe Alzheimer’s Disease Patients Participating in a Donepezil Study. The International Journal of Clinical Practice, 67, 1050-1056.
https://doi.org/10.1111/ijcp.12188

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