Latent structure of the hospital anxiety and depression scale: a 10 year systematic review

Objective: To systematically review the latent structure of the Hospital Anxiety and Depression scale (HADS). Methods: A systematic review of the literature was conducted across Medline, ISI Web of Knowledge, CINAHL, PsycINfo and EmBase databases spanning articles published between May 2000 and May 2010. Studies conducting latent variable analysis of the HADS were included. Results: Twenty-five of the 50 reviewed studies revealed a two-factor structure, the most commonly found HADS structure. Additionally, five studies revealed unidimensional, 17 studies revealed three-factor, and two studies revealed fourfactor structures. One study provided equal support for two- and three-factor structures. Different latent variable analysis methods revealed correspondingly different structures: exploratory factor analysis studies revealed primarily twofactor structures, confirmatory factor analysis studies revealed primarily threefactor structures, and item response theory studies revealed primarily unidimensional structures. Conclusion: The heterogeneous results of the current review suggest that the latent structure of the HADS is unclear, and dependent on statistical methods invoked. While the HADS has been shown to be an effective measure of emotional distress, its inability to consistently differentiate between the constructs of anxiety and depression means that its use needs to be targeted to more general measurement of distres

Psychosocial aspects of successful ageing and resilience: critique, integration and implications

As the number of older adults increases worldwide, it is becoming increasingly important to find effective ways of fostering better aging trajectories. The models used to shape this process inform research, policy, practice and impact older adults themselves. Two important aging models are successful aging(SA) and resilience(RES). Aligning the conceptual framework in research contexts with those of older adults’ perspectives is an integral component of driving forward the research agenda in a manner that has the greatest potential benefit older adults. Studies conducted with laypersons indicate that psychosocial components are important components of successful aging models; therefore, it is imperative that these non-biomedical components are incorporated. There are many similarities between SA and RES models, but an important distinguishing feature is the incorporation of adversity into conceptualizations of resilience. SA models suggest high levels of functioning as a requirement for aging successfully, regardless of the circumstances the individual experiences; resilience models take into account the level of adversity being experienced by the individual. Individuals can demonstrate RES by having a more positive outcome than would be expected given their level of adversity. The incorporation of psychosocial constructs into SA models and the integration of SA and RES paradigms has important implications for research and for older adults themselves. Through the promotion of models of aging that include psychosocial components and elements of adversity, greater generalizability to a broader population is possible with enhanced potential for research derived from these efforts to more positively influence individuals’ trajectories of aging

Neuroimaging and Analytical Methods for Studying the Pathways from Mild Cognitive Impairment to Alzheimer’s Disease: Protocol for a Rapid Systematic Review

Background Alzheimer’s disease (AD) is a neurodegenerative disorder commonly associated with deficits of cognition and changes in behavior. Mild cognitive impairment (MCI) is the prodromal stage of AD that is defined by slight cognitive decline. Not all with MCI progress to AD dementia. Thus, the accurate prediction of progression to Alzheimer’s, particularly in the stage of MCI could potentially offer developing treatments to delay or prevent the transition process. The objective of the present study is to investigate the most recent neuroimaging procedures in the domain of prediction of transition from MCI to AD dementia for clinical applications and to systematically discuss the machine learning techniques used for the prediction of MCI conversion. Methods Electronic databases including PubMed, SCOPUS, and Web of Science will be searched from January 1, 2017, to the date of search commencement to provide a rapid review of the most recent studies that have investigated the prediction of conversion from MCI to Alzheimer’s using neuroimaging modalities in randomized trial or observational studies. Two reviewers will screen full texts of included papers using predefined eligibility criteria. Studies will be included if addressed research on AD dementia and MCI, explained the results in a way that would be able to report the performance measures such as the accuracy, sensitivity, and specificity. Only studies addressed Alzheimer’s type of dementia and its early-stage MCI using neuroimaging modalities will be included. We will exclude other forms of dementia such as vascular dementia, frontotemporal dementia, and Parkinson’s disease. The risk of bias in individual studies will be appraised using an appropriate tool. If feasible, we will conduct a random effects meta-analysis. Sensitivity analyses will be conducted to explore the potential sources of heterogeneity. Discussion The information gathered in our study will establish the extent of the evidence underlying the prediction of conversion to AD dementia from its early stage and will provide a rigorous and updated synthesis of neuroimaging modalities allied with the data analysis techniques used to measure the brain changes during the conversion process

The association between depressive symptoms in the community, non-psychiatric hospital admission and hospital outcomes: a systematic review.

OBJECTIVES: This paper aims to systematically review observational studies that have analysed whether depressive symptoms in the community are associated with higher general hospital admissions, longer hospital stays and increased risk of re-admission. METHODS: We identified prospective studies that looked at depressive symptoms in the community as a risk factor for non-psychiatric general hospital admissions, length of stay or risk of re-admission. The search was carried out on MEDLINE, PsycINFO, Cochrane Library Database, and followed up with contact with authors and scanning of reference lists. RESULTS: Eleven studies fulfilled our inclusion and exclusion criteria, and all were deemed to be of moderate to high quality. Meta-analysis of seven studies with relevant data suggested that depressive symptoms may be a predictor of subsequent admission to a general hospital in unadjusted analyses (RR=1.36, 95% CI: 1.28-1.44), but findings after adjustment for confounding variables were inconsistent. The narrative synthesis also reported depressive symptoms to be independently associated with longer length of stay, and higher re-admission risk. CONCLUSIONS: Depressive symptoms are associated with a higher risk of hospitalisation, longer length of stay and a higher re-admission risk. Some of these associations may be mediated by other factors, and should be explored in more details.No funding bodies had any role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The authors have no competing interests to report. No specific funding was set aside for this project. Matthew Prina was supported by the Medical Research Council [grant number RG56433].This is the final published version. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.jpsychores.2014.11.00

Development and Validation of a Multi-domain Multimorbidity Resilience Index for an Older Population: Results from the Baseline Canadian Longitudinal Study on Aging

Background  Multimorbidity is recognized as a major public health issue that increases with age and affects approximately two-thirds of older people in Canada, the US, Australia and many European countries. This study develops and tests a three domain (functional, social and psychological) multimorbidity resilience composite index based on a previously developed lifecourse model of multimorbidity resilience, incorporating measures of adversity and positive adaptation. The criterion validity of the measure is demonstrated by means of an analysis of key outcome variables drawn from the literature. Methods  We used the baseline data from the Comprehensive Cohort of the Canadian Longitudinal Study on Aging. Associations of functional, social, psychological as well as total resilience with two health utilization and three illness context outcome variables were examined using logistic regression analyses, adjusted for age, gender, marital status, income, education, region, and number of chronic conditions. Results  The sample included all 6771 Canadian adults aged 65 or older (mean age 73.0, 57% women) who reported two or more of 27 possible chronic conditions. Total resilience was associated with: perceived health (OR = 1.68, CI 1.59–1.77); sleep quality (OR = 1.34, CI 1.30–1.38); perceived pain (OR = 0.80, CI 0.77–0.83); hospital overnight stays (OR = 0.87, CI 0.83–0.91); and emergency department visits (OR = 0.90, CI 0.87–0.94)., after adjusting for socio-demographic factors, and number of chronic conditions. These associations were similar for the unadjusted models, as well as for the functional, social and psychological resilience sub-indices. Conclusions  Combining components of adversity and positive adaptation within functional, social and psychological domains produces a measure of multimorbidity resilience that is associated with more positive health outcomes. Several implications of a composite multimorbidity resilience measure for clinical practice are identified. This measure can be replicated using measures found in other secondary health data sets. Future validation using longitudinal data is warranted

Help-Seeking Behaviours Among Older Adults: A Scoping Review Protocol

Introduction Despite evidence that illustrates the unmet healthcare needs of older adults, there is limited research examining their help-seeking behaviour, of which direct intervention can improve patient outcomes. Research in this area conducted with a focus on ethnic minority older adults is also needed, as their help-seeking behaviours may be influenced by various cultural factors. This scoping review aims to explore the global literature on the factors associated with help-seeking behaviours of older adults and how cultural values and backgrounds may impact ethnic minority older adults’ help-seeking behaviours in different ways.   Methods and analysis The scoping review process will be guided by the methodology framework of Arksey and O’Malley and the Preferred Reporting Items for Systematic Reviews and Meta-analysis Protocols Extension for Scoping Reviews guidelines. The following electronic databases will be systematically searched from January 2005 onwards: MEDLINE/PubMed, Web of Science, PsycINFO, CINAHL and Scopus. Studies of various designs and methodologies consisting of older adults aged 65 years or older, who are exhibiting help-seeking behaviours for the purpose of remedying a physical or mental health challenge, will be considered for inclusion. Two reviewers will screen full texts and chart data. The results of this scoping review will be summarised quantitatively through numerical counts and qualitatively through a narrative synthesis.   Ethics and dissemination As this is a scoping review of published literature, ethics approval is not required. Results will be disseminated through publication in a peer-reviewed journal.   Discussion This scoping review will synthesise the current literature related to the help-seeking behaviours of older adults and ethnic minority older adults. It will identify current gaps in research and potential ways to move forward in developing or implementing strategies that support the various health needs of the diverse older adult population

Conceptualising and Operationalising Resilience in Older Adults

Context: As a result of increases in life expectancy and decreases in fertility, the proportion of the population entering later life has increased dramatically in recent decades. When faced with age-related challenges, some older adults respond more positively to adversity than would be expected given the level of adversity that they have experienced, demonstrating ‘resilience’. Objectives: Having a clear conceptual framework for resilience is a prerequisite to operationalising resilience in a research context. Methods: Here we compare and contrast several approaches to the operationalisation of resilience: psychometric-driven and data-driven (variable-centred and individual-centred) methods. Results: Psychometric-driven methods involve the administration of established questionnaires aimed at quantifying resilience. Data-driven techniques use statistical procedures to examine and/or operationalise resilience and can be broadly categorised into variable-centred methods, i.e. interaction and residuals, and individual-centred methods, i.e. categorical and latent class. Conclusions: The specific question(s) driving the research and the nature of the variables a researcher intends to use in their adversity-outcome dyad will largely dictate which methods are more (or less) appropriate in that circumstance. A measured approach to the ways in which resilience is investigated is warranted in order to facilitate the most useful application of this burgeoning field of research

Digital Interventions for Depression and Anxiety in Older Adults: Protocol for a Systematic Review

Background: There is a high prevalence of older adults experiencing depression and anxiety. In response to heightened demands for mental health interventions that are accessible and affordable, there has been a recent rise in the number of digital mental health interventions (DMHIs) that have been developed and incorporated into mental health treatments. Digital interventions are promising in their ability to provide researchers, medical practitioners, and patients with personalized tools for assessing behavior, consultation, treatment, and care that can be used remotely. Reviews and meta-analyses have shown the benefits of DMHIs for the treatment and prevention of depression, anxiety, and other mental illnesses, but there is still a lack of studies that focus on the benefits and use of DMHIs in the older population. Objective: The aim of this systematic review is to investigate the current evidence for the effect of technology-delivered interventions, such as smartphone/tablet applications, remote monitoring and tracking devices, and wearable technology, for the treatment and prevention of depression and anxiety in adults older than 50 years. Methods: The academic databases SCOPUS, PsycINFO, AgeLine (EBSCO), and Medline (PubMed) will be searched from January 1, 2010, to the date of search commencement to provide a review of existing randomized controlled trial studies. The search will include 3 key concepts: “older adults,” “digital intervention,” and “depression/anxiety.” A set of inclusion criteria will be followed during screening by two reviewers. Data will be extracted to address aims and objectives of the review. The risk of bias for each study will be determined using appropriate tools. If possible, a random-effects meta-analysis will be performed, and the heterogeneity of effect sizes will be calculated. Results: Preliminary searches were conducted in September 2020. The review is anticipated to be completed by April 2021. Conclusions: The data accumulated in this systematic review will demonstrate the potential benefits of technology-delivered interventions for the treatment of depression and anxiety disorders in older adults. This review will also identify any gaps in current studies of aging and mental health interventions, thereby navigating a way to move forward and paving the path to more accessible and user-friendly digital health interventions for the diverse population of older adults

Health-related quality of life in the Cambridge City over-75s Cohort (CC75C): development of a dementia-specific scale and descriptive analyses.

BACKGROUND: The assessment of Health Related Quality of Life (HRQL) is important in people with dementia as it could influence their care and support plan. Many studies on dementia do not specifically set out to measure dementia-specific HRQL but do include related items. The aim of this study is to explore the distribution of HRQL by functional and socio-demographic variables in a population-based setting. METHODS: Domains of DEMQOL's conceptual framework were mapped in the Cambridge City over 75's Cohort (CC75C) Study. HRQL was estimated in 110 participants aged 80+ years with a confirmed diagnosis of dementia with mild/moderate severity. Acceptability (missing values and normality of the total score), internal consistency (Cronbach's alpha), convergent, discriminant and known group differences validity (Spearman correlations, Wilcoxon Mann-Whitney and Kruskal-Wallis tests) were assessed. The distribution of HRQL by socio-demographic and functional descriptors was explored. RESULTS: The HRQL score ranged from 0 to 16 and showed an internal consistency Alpha of 0.74. Validity of the instrument was found to be acceptable. Men had higher HRQL than women. Marital status had a greater effect on HRQL for men than it did for women. The HRQL of those with good self-reported health was higher than those with fair/poor self-reported health. HRQL was not associated with dementia severity. CONCLUSIONS: To our knowledge this is the first study to examine the distribution of dementia-specific HRQL in a population sample of the very old. We have mapped an existing conceptual framework of dementia specific HRQL onto an existing study and demonstrated the feasibility of this approach. Findings in this study suggest that whereas there is big emphasis in dementia severity, characteristics such as gender should be taken into account when assessing and implementing programmes to improve HRQL