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Background: Subjective cognitive complaints (SCCs) are considered a risk factor for objective cognitive decline and conversion to dementia. The aim of this study was to determine whether self-reported or informant-reported SCCs best predict progression to mild cognitive impairment (MCI) and/or dementia., Methods: We reviewed prospective longitudinal studies of Cognitively Unimpaired (CU) older adults with self-reported and informant-reported SCCs at baseline, assessed by questions or questionnaires that considered the transition to MCI and/or dementia. A random-effects meta-analysis was performed to obtain pooled estimates and 95% CIs., Results: Both self-reported and informant-reported SCCs are associated with an elevated risk of transition from CU to MCI and/or dementia. The association appears stronger and more robust for informant-reported data [1.38, with a 95% CI of 1.16 -1.64, p < 0.001] than for self-reported data [1.27 (95% CI 1.06 - 1.534, p = 0.011]., Conclusions: Our results suggest that corroborated information from one informant could provide important details for distinguishing between normal aging and clinical states., Competing Interests: Declaration of interest The authors have no conflicts of interest to report., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

The increasing prevalence of dementia demands innovative solutions; however, existing technological products often lack tailored support for individuals living with this condition. The Living Lab approach, as a collaborative innovation method, holds promise in addressing this issue by actively involving end-users in the design and development of solutions adapted to their needs. Despite this potential, the approach still faces challenges due to its lack of recognition as a research methodology and its absence of tailored guidelines, particularly in dementia care, prompting inquiries into its effectiveness. This narrative review aims to fill this gap by identifying and analysing digital health Living Labs focusing on dementia solutions. Additionally, it proposes guidelines for enhancing their operations, ensuring sustainability, scalability, and greater impact on dementia care. Fifteen Living Labs were identified and analyzed. Based on trends, best practices, and literature, the guidelines emphasize user engagement, interdisciplinary collaboration, technological infrastructure, regulatory compliance, transparent innovation processes, impact measurement, sustainability, scalability, dissemination, and financial management. Implementing these guidelines can enhance the effectiveness and long-term impact of Living Labs in dementia care, fostering new collaborations globally.

Objective: To analyze the validity of self and informant reports, depressive symptomatology, and some sociodemographic variables to predict the risk of cognitive decline at different follow-up times. Methods: A total of 337 participants over 50 years of age included in the CompAS and classified as Cognitively Unimpaired (CU), Subjective Cognitive Decline (SCD) and Mild Cognitive Impairment (MCI) groups were assessed at baseline and three follow-ups. A short version of the QAM was administered to assess the severity of subjective cognitive complaints (SCCs), and the GDS-15 was used to evaluate the depressive symptoms. At each follow-up assessment, participants were reclassified according to the stability, regression or progression of their conditions. Logistic regression analysis was used to predict which CU, SCD and MCI participants would remain stable, regress or progress at a 3rd follow-up by using self- and informant-reported complaints, depressive symptomatology, age and education at baseline and 2nd follow-ups as the predictive variables. Results: Overall, self-reported complaints predicted progression between the asymptomatic and presymptomatic stages. As the objective deterioration increased, i.e., when SCD progressed to MCI or dementia, the SCCs reported by informants proved the best predictors of progression. Depressive symptomatology was also a predictor of progression from CU to SCD and from SCD to MCI. Conclusion: A late increase in self-reported complaints make valid estimates to predict subjective decline at asymptomatic stages. However, an early increase in complaints reported by informants was more accurate in predicting objective decline from asymptomatic stages. Both, early and late decrease in selfreported complaints successfully predict dementia from prodromic stage. Only late decrease in self-reported complaints predict reversion from prodromic and pre-symptomatic stages. [ABSTRACT FROM AUTHOR]

Background: The presence of subjective cognitive complaints (SCCs) is a core criterion for diagnosis of subjective cognitive decline (SCD); however, no standard procedure for distinguishing normative and non-normative SCCs has yet been established.Objective: To determine whether differentiation of participants with SCD according to SCC severity improves the validity of the prediction of progression in SCD and MCI and to explore validity metrics for two extreme thresholds of the distribution in scores in a questionnaire on SCCs.Methods: Two hundred and fifty-three older adults with SCCs participating in the Compostela Aging Study (CompAS) were classified as MCI or SCD at baseline. The participants underwent two follow-up assessments and were classified as cognitively stable or worsened. Severity of SCCs (low and high) in SCD was established by using two different percentiles of the questionnaire score distribution as cut-off points. The validity of these cut-off points for predicting progression using socio-demographic, health, and neuropsychological variables was tested by machine learning (ML) analysis.Results: Severity of SCCs in SCD established considering the 5th percentile as a cut-off point proved to be the best metric for predicting progression. The variables with the main role in conforming the predictive algorithm were those related to memory, cognitive reserve, general health, and the stability of diagnosis over time.Conclusion: Moderate to high complainers showed an increased probability of progression in cognitive decline, suggesting the clinical relevance of standard procedures to determine SCC severity. Our findings highlight the important role of the multimodal ML approach in predicting progression. [ABSTRACT FROM AUTHOR]

Subjective cognitive decline (SCD) is considered a pre-symptomatic stage of dementia characterized by cognitive complaints. The ability of education to reduce the risk of dementia is well known. Our objective is to investigate the influence of education on the risk of progression from SCD to MCI or dementia. Prospective longitudinal studies of adults (≥50 years) with SCD evaluating progression to objective cognitive decline, MCI, or dementia were selected. Pooled estimates (random effects model) and 95 % confidence intervals were calculated, exploring heterogeneity. Standardized education differences, Odds Ratio, or Hazard Ratio between converters and non-converters were estimated. The systematic review carried out showed that high education, as well as other cognitive reserve proxies, delays cognitive decline. The first meta-analysis showed a significant association of SCD with conversion in both high and low education strata. A second meta-analysis considering education as a continuous variable found that SCD converters showed two years less education than non-converters. Our results suggest that education has a delaying effect against cognitive decline progression. The presumed improvement in accurately detecting cognitive decline associated with better metacognitive skills in higher-educated SCD participants does not seem to neutralize the incremental risk of objective cognitive decline associated with lower educational attainment. • Educación alone or together with other CR proxies decreases the risk of progression toward objective cognitive impairment. • Association between CR and the risk of cognitive decline in SCD has been reported in follow-up studies from 2 to 9 years. • SCD with conversion is associated with both high and low education strata. • SCD converters had 2 years less education on average than SCD non-converters. • Higher education and therefore better skills to detect cognitive decline does not neutralize the positive effect of CR. [ABSTRACT FROM AUTHOR]