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

Resilience measurement in later life: a systematic review and psychometric analysis

OBJECTIVES: To systematically review and examine the psychometric properties of established resilience scales in older adults, i.e. ≥60 years. METHODS: A systematic review of Scopus and Web of Science databases was undertaken using the search strategy "resilience" AND (ageing OR aging)". Independent title/abstract and fulltext screening were undertaken, identifying original peer-reviewed English articles that conducted psychometric validation studies of resilience metrics in samples aged ≥60 years. Data on the reliability/validity of the included metrics were extracted from primary studies. RESULTS: Five thousand five hundred nine studies were identified by the database search, 426 used resilience psychometrics, and six psychometric analysis studies were included in the final analysis. These studies conducted analyses of the Connor Davidson Resilience Scale (CD-RISC) and its shortened 10-item version (CD-RISC10), the Resilience Scale (RS) and its shortened 5- (RS-5) and 11- (RS-11) item versions, and the Brief Resilient Coping Scale (BRCS). All scales demonstrated acceptable levels of internal consistency, convergent/discriminant validity and theoretical construct validity. Factor structures for the RS, RS-11 and CD-RISC diverged from the structures in the original studies. CONCLUSION: The RS, RS-5, RS-11, CD-RISC, CD-RISC10 and BRCS demonstrate psychometric robustness adequate for continued use in older populations. However, results from the current study and pre-existing theoretical construct validity studies most strongly support the use of the RS, with modest and preliminary support for the CD-RISC and BRCS, respectively. Future studies assessing the validity of these metrics in older populations, particularly with respect to factor structure, would further strengthen the case for the use of these scales

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

What is the relationship between validated frailty scores and mortality for adults with COVID-19 in acute hospital care? A systematic review

Background & aim: The aim of this systematic review was to quantify the association between frailty and COVID-19 in relation to mortality in hospitalised patients. / Methods: Medline, Embase, Web of Science and the grey literature were searched for papers from inception to 10th September 2020; the search was re-run in Medline up until the 9th December 2020. Screening, data extraction and quality grading were undertaken by two reviewers. Results were summarised using descriptive statistics, including a meta-analysis of overall mortality; the relationships between frailty and COVID-19 mortality were summarised narratively. / Results: 2,286 papers were screened resulting in 26 being included in the review. Most studies were from Europe, half from the UK, and one from Brazil; the median sample size was 242.5, median age 73.1 and 43.5% were female. 22/26 used the Clinical Frailty Scale; reported mortality ranged from 14 to 65%. Most, but not all studies showed an association between increasing frailty and a greater risk of dying. Two studies indicated a sub-additive relationship between frailty, COVID-19 and death, and two studies showed no association. / Conclusions: Whilst the majority of studies have shown a positive association between COVID-19 related death and increasing frailty, some studies suggested a more nuanced understanding of frailty and outcomes in COVID-19 is needed. Clinicians should exert caution in placing too much emphasis on the influence of frailty alone when discussing likely prognosis in older people with COVID-19 illness