Measurement Challenges in Research With Individuals With Cognitive Impairment

Multidimensional digital biomarker phenotypes for mild cognitive impairment: considerations for early identification, diagnosis and monitoring

Mild Cognitive Impairment (MCI) poses a challenge for a growing population worldwide. Early identification of risk for and diagnosis of MCI is critical to providing the right interventions at the right time. The paucity of reliable, valid, and scalable methods for predicting, diagnosing, and monitoring MCI with traditional biomarkers is noteworthy. Digital biomarkers hold new promise in understanding MCI. Identifying digital biomarkers specifically for MCI, however, is complex. The biomarker profile for MCI is expected to be multidimensional with multiple phenotypes based on different etiologies. Advanced methodological approaches, such as high-dimensional statistics and deep machine learning, will be needed to build these multidimensional digital biomarker profiles for MCI. Comparing patients to these MCI phenotypes in clinical practice can assist clinicians in better determining etiologies, some of which may be reversible, and developing more precise care plans. Key considerations in developing reliable multidimensional digital biomarker profiles specific to an MCI population are also explored.

Webcam-Based Eye-Tracking of Attentional Biases in Alzheimer's Disease: A Proof-Of-Concept Study

OBJECTIVES

To measure home-based older adults' attentional biases (AB) using webcam-based eye-tracking (WBET) and examine internal consistency.

METHODS

Twelve participants with and without cognitive impairment completed online self-report anxiety and depression screens, and a 96-trial dot-probe task with eye-gaze tracking. For each trial, participants fixated on a cross, free-viewed sad-neutral, sad-angry, sad-happy, angry-neutral, angry-happy, and happy-neutral facial expression pairings, and then fixated on a dot. In emotional-neutral pairings, the time spent looking (dwell-time) at neutral was averaged and subtracted from the emotional average to indicate biases "away from" (negative score) and "toward" (positive score) each emotional face. Internal consistency was estimated for dwell-times and bias scores using Cronbach's alpha and Spearman - Brown corrected split-half coefficients.

RESULTS

The full-cohort and a comorbid anxious and depressed sub-group (n = 6) displayed AB away from sad faces, and toward angry and happy faces, with happy-face AB being more pronounced. AB indices demonstrated low reliability except sub-group happy-face indices. Happy-face AB demonstrated the highest reliability.

CONCLUSIONS

AB measures were in-line with lab-based eye-tracking literature, providing some support for WBET-based measurement.

CLINICAL IMPLICATIONS

Establishing the feasibility of WBET-based measures is a step toward an objective home-based clinical tool. Literature-based suggestions are provided to improve reliability.

Integrating Neuroimaging Measures in Nursing Research

BACKGROUND

Medical and scientific advancement worldwide has led to a longer lifespan. With the population aging comes the risk of developing cognitive decline. The incorporation of neuroimaging measures in evaluating cognitive changes is limited in nursing research. The aim of this review is to introduce nurse scientists to neuroimaging measures employed to assess the association between brain and cognitive changes.

METHODS

Relevant literature was identified by searching CINAHL, Web of Science, and PubMed databases using the following keywords: "neuroimaging measures," "aging," "cognition," "qualitative scoring," "cognitive ability," "molecular," "structural," and "functional."

RESULTS

Neuroimaging measures can be categorized into structural, functional, and molecular imaging approaches. The structural imaging technique visualizes the anatomical regions of the brain. Visual examination and volumetric segmentation of select structural sequences extract information such as white matter hyperintensities and cerebral atrophy. Functional imaging techniques evaluate brain regions and underlying processes using blood-oxygen-dependent signals. Molecular imaging technique is the real-time visualization of biological processes at the cellular and molecular levels in a given region. Examples of biological measures associated with neurodegeneration include decreased glutamine level, elevated total choline, and elevated Myo-inositol.

DISCUSSION

Nursing is at the forefront of addressing upstream factors impacting health outcomes across a lifespan of a population at increased risk of progressive cognitive decline. Nurse researchers can become more facile in using these measures both in qualitative and quantitative methodology by leveraging previously gathered neuroimaging clinical data for research purposes to better characterize the associations between symptom progression, disease risk, and health outcomes.

Factors associated with reporting of the Prevention of Falls Network Europe (ProFaNE) core outcome set domains in randomized trials on falls in older people: a citation analysis and correlational study

Background

Core outcome sets are advocated as a means to standardize outcome reporting across randomized controlled trials (RCTs) and reduce selective outcome reporting. In 2005, the Prevention of Falls Network Europe (ProFaNE) published a core outcome set identifying five domains that should be measured and reported, at a minimum, in RCTs or meta-analysis on falls in older people. As reporting of all five domains of the ProFaNE core outcome set has been minimal, we set out to investigate factors associated with reporting of the ProFaNE core outcome set domains in a purposeful sample of RCTs on falls in older people.

Methods

We conducted a systematic citation analysis to identify all reports of RCTs focused on falls in older people that cited the ProFaNE core outcome set between October 2005 and July 2021. We abstracted author-level, study-level, and manuscript-level data and whether each domain of the ProFaNE core outcome set was reported. We used penalized LASSO regression to identify factors associated with the mean percentage of ProFaNE core outcome set domains reported.

Results

We identified 85 eligible reports of RCTs. Articles were published between 2007 and 2021, described 75 unique RCTs, and were authored by 76 unique corresponding authors. The percentage of ProFaNE core outcome set domains reported ranged from 0 to 100%, with a median of 40% and mean (standard deviation, SD) of 52.2% (25.1). RCTs funded by a non-industry source reported a higher mean percentage of domains than RCTs without a non-industry funding source (estimated mean difference = 17.5%; 95% confidence interval (CI) 1.8–33.2). RCTs examining exercise (15.4%; 95% CI 1.9–28.9) or multi-component/factorial (17.4%; 95% CI 4.7–30.1) interventions each reported a higher mean percentage of domains than RCTs examining other intervention types.

Conclusions

We found that RCTs funded by at least one non-industry source, examining exercise or multi-component/factorial interventions, reported the highest percentages of ProFaNE core outcome set domains. Findings may help inform strategies to increase the impact of the ProFaNE core outcome set. Ultimately, this may lead to enhanced knowledge of the effectiveness and safety of interventions to prevent and/or manage falls in older people.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13063-022-06642-w.