Tolerance to Dizziness Intensity Increases With Age in People With Chronic Dizziness

Background: Dizziness is a common complaint in older adults. To know which factors are instrumental in enabling patients with chronic dizziness to tolerate their symptoms to a certain degree in everyday life can help to develop tailored therapies. Methods: Data from 358 patients with chronic dizziness and vertigo who had attended a multimodal daycare treatment program were recorded. Data included sociodemographic parameters, dizziness-related characteristics, the Vertigo Symptom Scale (VSS), and the Hospital Anxiety and Depression Scale (HADS). Descriptive statistics, elastic net regression, and mediation analysis were used. Results: A higher tolerance of dizziness was associated with higher age, higher intensity of dizziness, lower burden of dizziness, higher HADS depression, structural reason for dizziness (type), permanent dizziness, absence of attacks, and longer disease duration. In contrast, younger persons with attack-like dizziness reported to tolerate less dizziness. Age had a significant direct effect on tolerance (72% of the total effect) and a significant indirect effect via intensity on tolerance (28% of the total effect) in the mediation analysis. Conclusion: It can only be speculated that negative stereotypes about age-related complaints may play a role in this. Why older people tolerate more dizziness and to what extent this may contribute to lower healthcare utilization need to be investigated in further studies

Detecting Reasons for Nonadherence to Medication in Adults with Epilepsy: A Review of Self-Report Measures and Key Predictors

This review presents individual reasons for self-reported nonadherence in people with epilepsy (PWE). A literature search was performed on the PubMed/Medline and Scopus databases for studies published up to March 2022. Thirty-six studies were included using the following inclusion criteria: original studies on adults with epilepsy, use of subjective self-report adherence measurement methods, and publication in English. Data were extracted using a standardized data extraction table, including the year of publication, authors, cohort size, study design, adherence measurement method, and self-reported reasons for nonadherence. Self-reported reasons for nonadherence were grouped following the WHO model with the five dimensions of nonadherence. In addition, study characteristics and sociodemographic information are reported. Of the 36 included studies, 81% were observational. The average nonadherence rate was nearly 50%. Across all studies, patient-associated, therapy-associated, and circumstance-related factors were the most frequently reported dimensions of nonadherence. These factors include forgetfulness, presence of side-effects, and history of seizures. Regarding healthcare system factors, financial problems were the most reported reason for nonadherence. Stigmatization and quality of life were the most frequently cited factors influencing nonadherence in the disease- and circumstance-related dimensions. The results suggest that interventions for improving adherence should incorporate all dimensions of nonadherence

Longitudinal analysis of the Non-Motor Symptoms Scale in Parkinson's Disease (NMSS): An exploratory network analysis approach

Introduction Parkinson's disease (PD) is a multisystem neurodegenerative disorder characterized by motor and non-motor symptoms. In particular, non-motor symptoms have become increasingly relevant to disease progression. This study aimed to reveal which non-motor symptoms have the highest impact on the complex interacting system of various non-motor symptoms and to determine the progression of these interactions over time. Methods We performed exploratory network analyses of 499 patients with PD from the Cohort of Patients with Parkinson's Disease in Spain study, who had Non-Motor Symptoms Scale in Parkinson's Disease ratings obtained at baseline and a 2-year follow-up. Patients were aged between 30 and 75 years and had no dementia. The strength centrality measures were determined using the extended Bayesian information criterion and the least absolute shrinkage and selection operator. A network comparison test was conducted for the longitudinal analyses. Results Our study revealed that the depressive symptoms anhedonia and feeling sad had the strongest impact on the overall pattern of non-motor symptoms in PD. Although several non-motor symptoms increase in intensity over time, their complex interacting networks remain stable. Conclusion Our results suggest that anhedonia and feeling sad are influential non-motor symptoms in the network and, thus, are promising targets for interventions as they are closely linked to other non-motor symptoms

Prospective associations between hand grip strength and subsequent depressive symptoms in men and women aged 50 years and older: insights from the Survey of Health, Aging, and Retirement in Europe

IntroductionIn previous cross-sectional and longitudinal studies, depressive symptoms have been associated with lower hand grip strength (HGS), which is a convenient measure of overall muscular strength and serves as a marker of poor health. Most studies have considered low sample sizes or highly selective patient cohorts.MethodsWe studied the association between depressive symptoms (EURO-D) and HGS in three waves from the cross-national panel dataset Survey of Health, Aging, and Retirement in Europe (SHARE). Linear regressions and Generalized Estimating Equations (GEE) were conducted to determine factors associated with depressive symptoms and investigate whether HGS predicts future depressive symptoms.ResultsCross-sectional HGS explained 7.0% (Wave 4), 5.7% (Wave 5), and 6.4% (Wave 6) of the EURO-D variance. In the GEE, we analyzed people without depression in Wave 4 (N = 39,572). HGS predicted future EURO-D (B = −0.21, OR = 0.979, 95%CI (0.979, 0.980), p < 0.001) and remained a significant predictor of future depressive symptoms after adjustment for age, sex, psychosocial and physical covariates.DiscussionMuscle strength is a known marker for physical health, but a relation with mental health has also been proposed previously. This study confirmed the link between HGS and depressive symptoms in men and women aged ≥50 years in a large longitudinal dataset. Further research is required to understand the mechanisms behind this link to determine whether HGS can serve as a specific marker of depressive symptomology, or whether they coexist due to common underlying disease processes

Self-Reported Nonadherence to Medication Is Not Associated with Health-Related Quality of Life in Parkinson’s Disease

Nonadherence is a growing issue in the treatment of Parkinson’s disease (PD). Many factors are known to influence nonadherence, but little is known about the influence of quality of life (QoL). Detailed clinical data were obtained from 164 patients with PD using the Parkinson’s Disease Questionnaire-39 (PDQ-39) and the German Stendal Adherence with Medication Score (SAMS). Descriptive statistics were used to identify reasons for nonadherence, and multivariable linear models were used to study associations between QoL and clinical parameters as well as nonadherence. Multivariate analysis of variance (MANOVA) and multivariate analysis of covariance (MANCOVA) were used to study the effect of the SAMS on PDQ domains and other medical covariates. The results showed that 10.4% (n = 17) of patients were fully adherent, 66.4% (n = 109) were moderately nonadherent, and 23.2% (n = 38) were nonadherent. Nonadherence was associated with male gender, lower Montreal Cognitive Assessment (MoCA) score, higher non-motor symptoms questionnaire (NMS-Quest) score, greater number of medications per day (an indicator of comorbidity), and higher Beck Depression Inventory (BDI) score. QoL was correlated with male gender, lower MoCA score, higher NMS-Quest score, more comorbidities, and higher BDI score, but was not correlated with nonadherence

Data on medication adherence in adults with neurological disorders: The NeuroGerAd study

Measurement(s) adherence Technology Type(s) questionnaires Factor Type(s) personal factors Sample Characteristic - Organism Homo sapiens Sample Characteristic - Environment inpatient and outpatient setting Sample Characteristic - Location German

Data_Sheet_1_Trajectories of quality of life in people with diabetes mellitus: results from the survey of health, ageing and retirement in Europe.docx

IntroductionPrevious longitudinal studies identified various factors predicting changes in Quality of Life (QoL) in people with diabetes mellitus (PwDM). However, in these studies, the stability of QoL has not been assessed with respect to individual differences.MethodsWe studied the predictive influence of variables on the development of QoL in PwDM across three waves (2013–2017) from the cross-national panel dataset Survey of Health, Ageing, and Retirement in Europe (SHARE). To determine clinically meaningful changes in QoL, we identified minimal clinically important difference (MCID). Linear regressions and Linear Mixed Models (LMM) were conducted to determine factors associated with changes in QoL.ResultsOn average, QoL remained stable across three waves in 2989 PwDM, with a marginal difference only present between the first and last wave. However, when looking at individual trajectories, 19 different longitudinal patterns of QoL were identified across the three time-points, with 38.8% of participants showing stable QoL. Linear regression linked lower QoL to female gender, less education, loneliness, reduced memory function, physical inactivity, reduced health, depression, and mobility limitations. LMM showed that the random effect of ID had the strongest impact on QoL across the three waves, suggesting highly individual QoL patterns.ConclusionThis study enhances the understanding of the stability of QoL measures, which are often used as primary endpoints in clinical research. We demonstrated that using traditional averaging methods, QoL appears stable on group level. However, our analysis indicated that QoL should be measured on an individual level.</p