Changes in perceived ageism during the COVID-19 pandemic: impact on quality of life and mental well-being among Dutch adults aged 55 and older.

Objectives: The COVID-19 pandemic brought ageism to the forefront of public discourse. Negative ageism incurs more negative self-perceptions of aging, which affects physical and mental functioning. Whether negative ageism as perceived and experienced by older adults has worsened as the pandemic lingered, and how such changes impact quality of life (QoL) and mental well-being (MWB), remain urgent questions.Method: In a sample of adults aged 55 or older (n = 500), we aimed to address this by administering the Perceived Ageism Questionnaire twice during the pandemic (T1: between October 2020 and May 2021; T2: on average 45 wk after T1).Results: Higher levels of perceived negative ageism were associated with lower QoL and MWB, at least partially through its unfavorable effects on self-perceptions of aging, even after controlling for ageism experiences in the preceding year (at T2, corrected for T1). Furthermore, we found that perceived negative ageism increased from T1 to T2, which had negative implications for QoL/MWB. Opposite effects were found for perceived positive ageism, although less consistently.Conclusion: These patterns reveal that ageism as perceived and experienced by adults of 55 or older became stronger and more negative throughout the COVID-19 pandemic, which had detrimental implications for individuals' QoL and MWB. These disconcerting findings emphasize the importance of combatting negative ageism in our society.

Predicting Progression to Parkinson's Disease Dementia Using Multivariate Normative Comparisons.

OBJECTIVE: Parkinson's disease with mild cognitive impairment (PD-MCI) is a risk factor for progression to PD dementia (PDD) at a later stage of the disease. The consensus criteria of PD-MCI use a traditional test-by-test normative comparison. The aim of this study was to investigate whether a new multivariate statistical method provides a more sensitive tool for predicting dementia status at 3- and 5-year follow-ups. This method allows a formal evaluation of a patient's profile of test scores given a large aggregated database with regression-based norms. METHOD: The cognitive test results of 123 newly diagnosed PD patients from a previously published longitudinal study were analyzed with three different methods. First, the PD-MCI criteria were applied in the traditional way. Second, the PD-MCI criteria were applied using the large aggregated normative database. Last, multivariate normative comparisons (MNCs) were made using the same aggregated normative database. The outcome variable was progression to dementia within 3 and 5 years. RESULTS: The MNC was characterized by higher sensitivity and higher specificity in predicting progression to PDD at follow-up than the two PD-MCI criteria methods, although the difference in classification accuracy did not reach statistical significance. CONCLUSION: We conclude that MNCs could allow for a more accurate prediction of PDD than the traditional PD-MCI criteria, because there are encouraging trends in both increased sensitivity and increased specificity. (JINS, 2019, 25, 678-687).

Universal Scale of Intelligence Estimates (USIE): Representing Intelligence Estimated From Level of Education.

In clinical neuropsychology, it is often necessary to estimate a patient's premorbid level of cognitive functioning in order to evaluate whether his scores on cognitive tests should be considered abnormal. In practice, test results from before the onset of brain pathology are rarely available, and the patient's level of education is used instead as an estimate of his premorbid level. Unfortunately, level of education may be expressed on many different scales of education, which are difficult to use interchangeably. Here, we introduce a new scale that has the capacity to replace existing scales and can be used interchangeably with any of them: the Universal Scale of Intelligence Estimates (USIE). To achieve this, we propose to map all levels of existing educational scales to standard IQ scores. This USIE point estimate is supplemented with an estimation interval. We assert that USIE offers some important benefits for clinical practice and research.

Remembering the news: modeling retention data from a study with 14,000 participants.

A retention study is presented in which participants answered questions about news events, with a retention interval that varied within participants between 1 day and 2 years. The study involved more than 14,000 participants and around 500,000 data points. The data were analyzed separately for participants who answered questions in Dutch or in English, providing an opportunity for replication. We fitted models of varying complexity to the data in order to test several hypotheses concerning retention. Evidence for an asymptote in retention was found in only one data set, and participants with greater media exposure displayed a higher degree of learning but no difference in forgetting. Thus, forgetting was independent of initial learning. Older adults were found to have forgetting curves similar to those of younger adults.

Mode shifting between storage and recall based on novelty detection in oscillating hippocampal circuits.

It has been suggested that hippocampal mode shifting between a storage and a retrieval state might be under the control of acetylcholine (ACh) levels, as set by an autoregulatory hippocampo-septo-hippocampal loop. The present study investigates how such a mechanism might operate in a large-scale connectionist model of this circuitry that takes into account the major hippocampal subdivisions, oscillatory population dynamics and the time scale on which ACh exerts its effects in the hippocampus. The model assumes that hippocampal mode shifting is regulated by a novelty signal generated in the hippocampus. The simulations suggest that this signal originates in the dentate. Novel patterns presented to this structure lead to brief periods of depressed firing in the hippocampal circuitry. During these periods, an inhibitory influence of the hippocampus on the septum is lifted, leading to increased firing of cholinergic neurons. The resulting increase in ACh release in the hippocampus produces network dynamics that favor learning over retrieval. Resumption of activity in the hippocampus leads to the reinstatement of inhibition. Despite theta-locked rhythmic firing of ACh neurons in the septum, ACh modulation in the model fluctuates smoothly on a time scale of seconds. It is shown that this is compatible with the time scale on which memory processes take place. A number of strong predictions regarding memory function are derived from the model.