The role of self-compassion in the psychological (mal)adjustment of older adults: a scoping review.

BACKGROUND: The identification of protection factors regarding older adults' mental health is essential. Self-compassion, the capacity to be kind towards the self during challenging times, may be one such factor. Although still scarce, some research in this field has already been conducted with older adults. Our research question was the following: what is currently known about the role of self-compassion in the psychological (mal)adjustment of older adults? OBJECTIVES: To review any study designs, in any setting, where self-compassion and any indicators of psychological (mal)adjustment were assessed in participants aged ≥60 years. DESIGN: A scoping review of English, Portuguese, and Spanish published and unpublished materials, using the EBSCOhost Research and PubMed databases and reference lists. Search terms included self-compassion, self compassion, older adults, elderly, seniors, and geriatrics. After screening and selection of the studies, we charted the relevant data. RESULTS: Eleven published studies (2012-2018) were reviewed. Self-compassion was associated with, and a predictor of, diverse mental health indicators in older adults. Self-compassion was also associated with indicators of physical health, moderated the relationship between physical health indicators and mental health indicators, and mediated the relationship between diverse mental health indicators. Results were obtained with participants of different nationalities and age. All studies had a cross-sectional design, and most studies recruited well-functioning community residents. CONCLUSIONS: Self-compassion is beneficial for the psychological adjustment of older adults and may also benefit their biological functioning. Self-compassion seems particularly relevant for those experiencing more negative life events. Studies with more robust methodologies are needed in order to replicate these findings.

ERP correlates of error processing during performance on the Halstead Category Test.

The Halstead Category Test (HCT) is a neuropsychological test that measures a person's ability to formulate and apply abstract principles. Performance must be adjusted based on feedback after each trial and errors are common until the underlying rules are discovered. Event-related potential (ERP) studies associated with the HCT are lacking. This paper demonstrates the use of a methodology inspired on Singular Spectrum Analysis (SSA) applied to EEG signals, to remove high amplitude ocular and movement artifacts during performance on the test. This filtering technique introduces no phase or latency distortions, with minimum loss of relevant EEG information. Importantly, the test was applied in its original clinical format, without introducing adaptations to ERP recordings. After signal treatment, the feedback-related negativity (FRN) wave, which is related to error-processing, was identified. This component peaked around 250ms, after feedback, in fronto-central electrodes. As expected, errors elicited more negative amplitudes than correct responses. Results are discussed in terms of the increased clinical potential that coupling ERP information with behavioral performance data can bring to the specificity of the HCT in diagnosing different types of impairment in frontal brain function.