We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.
To save this undefined to your undefined account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you used this feature, you will be asked to authorise Cambridge Core to connect with your undefined account.
Find out more about saving content to .
To send this article to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
This study aimed to apply the generalizability theory (G-theory) to investigate dynamic and enduring patterns of subjective cognitive complaints (SCC), and reliability of two widely used SCC assessment tools.
Design:
G-theory was applied to assessment scales using longitudinal measurement design with five assessments spanning 10 years of follow-up.
Setting:
Community-dwelling older adults aged 70–90 years and their informants, living in Sydney, Australia, participated in the longitudinal Sydney Memory and Ageing Study.
Participants:
The sample included 232 participants aged 70 years and older, and 232 associated informants. Participants were predominantly White Europeans (97.8%). The sample of informants included 76 males (32.8%), 153 females (65.9%), and their age ranged from 27 to 86 years, with a mean age of 61.3 years (SD = 14.38).
Measurements:
The Memory Complaint Questionnaire (MAC-Q) and the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE).
Results:
The IQCODE demonstrated strong reliability in measuring enduring patterns of SCC with G = 0.86. Marginally acceptable reliability of the 6-item MAC-Q (G = 0.77–0.80) was optimized by removing one item resulting in G = 0.80–0.81. Most items of both assessments were measuring enduring SCC with exception of one dynamic MAC-Q item. The IQCODE significantly predicted global cognition scores and risk of dementia incident across all occasions, while MAC-Q scores were only significant predictors on some occasions.
Conclusions:
While both informants’ (IQCODE) and self-reported (MAC-Q) SCC scores were generalizable across sample population and occasions, self-reported (MAC-Q) scores may be less accurate in predicting cognitive ability and diagnosis of each individual.
Disinhibited behaviors in dementia are associated with multiple negative outcomes. However, effective interventions are under-researched. This systematic review aims to provide an overview of intervention studies that report outcome measures of disinhibited behaviors in dementia.
Design:
Systematic searches of the databases MEDLINE, EMBASE, and PsychINFO, Social Work Abstracts and Cochrane Central Register of Controlled Trial databases were conducted for publications published between 2002 and March 2020. We included hand-searched reviews, original articles, case reports, cohort studies, and randomized controlled trials (RCTs). All studies were rated for research quality. Statistical and clinical significance were considered for individual studies. Effect sizes were included where provided or calculated where possible. Mean effect sizes were calculated for RCTs only.
Participants:
The systematic review included studies involving people living with dementia.
Measurements:
The Neuropsychiatric Inventory disinhibition subscale was used most often.
Results:
Nine pharmacological and 21 nonpharmacological intervention studies utilized different theoretical/clinical approaches. These included pain management, antidepressants, models of care, education and/or training, music-based approaches, and physical activity. The quality of research in RCTs was strong with a greater effect size in nonpharmacological compared to pharmacological approaches (mean Cohen’s d = 0.49 and 0.27, respectively). Disinhibition was a secondary outcome in all studies.
Conclusion:
Pharmacological (including pain management and antidepressants) and, more so, nonpharmacological (models of care, education/training, physical activity, and music) approaches were effective in reducing disinhibition.
Many studies document cognitive decline following specific types of acute illness hospitalizations (AIH) such as surgery, critical care, or those complicated by delirium. However, cognitive decline may be a complication following all types of AIH. This systematic review will summarize longitudinal observational studies documenting cognitive changes following AIH in the majority admitted population and conduct meta-analysis (MA) to assess the quantitative effect of AIH on post-hospitalization cognitive decline (PHCD).
Methods:
We followed Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. Selection criteria were defined to identify studies of older age adults exposed to AIH with cognitive measures. 6566 titles were screened. 46 reports were reviewed qualitatively, of which seven contributed data to the MA. Risk of bias was assessed using the Newcastle–Ottawa Scale.
Results:
The qualitative review suggested increased cognitive decline following AIH, but several reports were particularly vulnerable to bias. Domain-specific outcomes following AIH included declines in memory and processing speed. Increasing age and the severity of illness were the most consistent risk factors for PHCD. PHCD was supported by MA of seven eligible studies with 41,453 participants (Cohen’s d = −0.25, 95% CI [−0.02, −0.49] I2 35%).
Conclusions:
There is preliminary evidence that AIH exposure accelerates or triggers cognitive decline in the elderly patient. PHCD reported in specific contexts could be subsets of a larger phenomenon and caused by overlapping mechanisms. Future research must clarify the trajectory, clinical significance, and etiology of PHCD: a priority in the face of an aging population with increasing rates of both cognitive impairment and hospitalization.
Common mental disorders (CMDs), particularly depression, are major contributors to the global mental health burden. South Asia, while diverse, has cultural, social, and economic challenges, which are common across the region, not least an aging population. This creates an imperative to better understand how CMD affects older people in this context, which relies on valid and culturally appropriate screening and research tools. This review aims to scope the availability of CMD screening tools for older people in South Asia. As a secondary aim, this review will summarize the use of these tools in epidemiology, and the extent to which they have been validated or adapted for this population.
Design:
A scoping review was performed, following PRISMA guidelines. The search strategy was developed iteratively in Medline and translated to Embase, PsychInfo, Scopus, and Web of Science. Data were extracted from papers in which a tool was used to identify CMD in a South Asian older population (50+), including validation, adaptation, and use in epidemiology. Validation studies meeting the criteria were critically appraised using the Quality Assessment of Diagnostic Accuracy Studies – version 2 (QUADAS-2) tool.
Results:
Of the 4694 papers identified, 176 met the selection criteria at full-text screening as relevant examples of diagnostic or screening tool use. There were 15 tool validation studies, which were critically appraised. Of these, 10 were appropriate to evaluate as diagnostic tests. All of these tools assessed for depression. Geriatric Depression Scale (GDS)-based tools were predominant with variable diagnostic accuracy across different settings. Methodological issues were substantial based on the QUADAS-2 criteria. In the epidemiological studies identified (n = 160), depression alone was assessed for 82% of the studies. Tools lacking cultural validation were commonly used (43%).
Conclusions:
This review identifies a number of current research gaps including a need for culturally relevant validation studies, and attention to other CMDs such as anxiety.
There is growing evidence that people with mild dementia can benefit from using tablets and apps. Due to their cognitive decline, people with dementia need support in learning how to use these devices. The objective of this review was to identify which training interventions work best to help people with mild dementia (re)learn how to use technologies, including handheld touchscreen devices. Because the uptake of these devices in people with dementia is quite new, training interventions for the use of other technologies were also included, such as technologies assisting people in Instrumental Activities of Daily Living (IADL).
Design:
An electronic search was conducted in the following databases: PubMed, APA PsycInfo (EBSCO), and CINAHL (EBSCO). Themes discussed include the learning effects; training method (e.g. errorful (EF) and errorless (EL) learning); training intensity and setting; technology task type; dementia type and severity; and study design and outcome measures.
Results:
In total, 16 studies were included. All studies reported positive learning effects and improved task performance in people with dementia, regardless of dementia severity, training intensity, setting, and the method used. Although the EL training method was successful more often than the EF training method, it would be inappropriate to conclude that the EL method is more effective, because the majority of studies only investigated EL training interventions with (multiple) single-case study designs.
Conclusion:
Future research should consider using more robust study designs, such as RCTs, to evaluate the effectiveness of training interventions for (re)learning technology-orientated tasks, including operating handheld touchscreen devices.
Wisdom is a personality trait comprising seven components: self-reflection, pro-social behaviors, emotional regulation, acceptance of diverse perspectives, decisiveness, social advising, and spirituality. Wisdom, a potentially modifiable trait, is strongly associated with well-being. We have published a validated 28-item San Diego Wisdom Scale, the SD-WISE-28. Brief scales are necessary for use in large population-based studies and in clinical practice. The present study aimed to create an abbreviated 7-item version of the SD-WISE.
Method:
Participants included 2093 people, aged 20-82 years, recruited and surveyed through the online crowdsourcing platform Amazon Mechanical Turk. The participants’ mean age was 46 years, with 55% women. Participants completed the SD-WISE-28 as well as validation scales for various positive and negative constructs. Psychometric analyses (factor analysis and item response theory) were used to select one item from each of the seven SD-WISE-28 subscales.
Results:
We selected a combination of items that produced acceptable unidimensional model fit and good reliability (ω = 0.74). Item statistics suggested that all seven items were strong indicators of wisdom, although the association was weakest for spirituality. Analyses indicated that the 28-item and 7-item SD-WISE are both very highly correlated (r = 0.92) and produce a nearly identical pattern of correlations with demographic and validity variables.
Conclusion:
The SD-WISE-7, and its derived Jeste-Thomas Wisdom Index (JTWI) score, balances reliability and brevity for research applications.
This study examined the relationships between social capital, perceived neighborhood environment, and depressive symptoms among older adults living in rural China, and the moderating effect of self-rated health (SRH) in these relationships.
Participants:
A quota sampling method was applied to recruit 447 participants aged 60 years and older in rural communities in Jilin province, China in 2019.
Measurements:
Depressive symptoms were measured by the Center for Epidemiologic Studies Depression Scale. Structural equation modeling was used to build latent constructs of social capital and test the proposed model. Multiple group analysis was used to test the moderation effects.
Results:
Cognitive social capital and structural social capital were both associated with depressive symptoms controlling for participants’ demographics, socioeconomic status, and health status. After adding perceived environment variables in the model, the relationship between cognitive social capital and depressive symptoms became nonsignificant, while structural social capital remained became a significant factor (β = −.168, p < .01). Satisfaction with health care was significantly associated with depressive symptoms among those with poor SRH (β = −.272, p < .01), whereas satisfaction with security and transportation were strongly associated with depressive symptoms among those with good SRH (security: β = −.148, p < .01; transportation: β = −.174, p < .01).
Conclusions:
Study findings highlighted the importance of social capital and neighborhood environment as potential protective factors of depressive symptoms in later life. Policy and intervention implications were also discussed.