Interventions for preventing delirium in older people in institutional long-term care

BACKGROUND: Delirium is a common and distressing mental disorder. It is often caused by a combination of stressor events in susceptible people, particularly older people living with frailty and dementia. Adults living in institutional long-term care (LTC) are at particularly high risk of delirium. An episode of delirium increases risks of admission to hospital, development or worsening of dementia and death. Multicomponent interventions can reduce the incidence of delirium by a third in the hospital setting. However, it is currently unclear whether interventions to prevent delirium in LTC are effective. This is an update of a Cochrane Review first published in 2014. OBJECTIVES: To assess the effectiveness of interventions for preventing delirium in older people in institutional long-term care settings. SEARCH METHODS: We searched ALOIS (www.medicine.ox.ac.uk/alois), the Cochrane Dementia and Cognitive Improvement Group (CDCIG) 's Specialised Register of dementia trials (dementia.cochrane.org/our-trials-register), to 27 February 2019. The search was sufficiently sensitive to identify all studies relating to delirium. We ran additional separate searches in the Cochrane Central Register of Controlled Trials (CENTRAL), major healthcare databases, trial registers and grey literature sources to ensure that the search was comprehensive. SELECTION CRITERIA: We included randomised controlled trials (RCTs) and cluster-randomised controlled trials (cluster-RCTs) of single and multicomponent, non-pharmacological and pharmacological interventions for preventing delirium in older people (aged 65 years and over) in permanent LTC residence. DATA COLLECTION AND ANALYSIS: We used standard methodological procedures expected by Cochrane. Primary outcomes were prevalence, incidence and severity of delirium; and mortality. Secondary outcomes included falls, hospital admissions and other adverse events; cognitive function; new diagnoses of dementia; activities of daily living; quality of life; and cost-related outcomes. We used risk ratios (RRs) as measures of treatment effect for dichotomous outcomes, hazard ratios (HR) for time-to-event outcomes and mean difference (MD) for continuous outcomes. For each outcome, we assessed the overall certainty of the evidence using GRADE methods. MAIN RESULTS: We included three trials with 3851 participants. All three were cluster-RCTs. Two of the trials were of complex, single-component, non-pharmacological interventions and one trial was a feasibility trial of a complex, multicomponent, non-pharmacological intervention. Risk of bias ratings were mixed across the three trials. Due to the heterogeneous nature of the interventions, we did not combine the results statistically, but produced a narrative summary.It was not possible to determine the effect of a hydration-based intervention on delirium incidence (RR 0.85, 95% confidence interval (CI) 0.18 to 4.00; 1 study, 98 participants; very low-certainty evidence downgraded for risk of bias and very serious imprecision). This study did not assess delirium prevalence, severity or mortality.The introduction of a computerised system to identify medications that may contribute to delirium risk and trigger a medication review was probably associated with a reduction in delirium incidence (12-month HR 0.42, CI 0.34 to 0.51; 1 study, 7311 participant-months; moderate-certainty evidence downgraded for risk of bias) but probably had little or no effect on mortality (HR 0.88, CI 0.66 to 1.17; 1 study, 9412 participant-months; moderate-certainty evidence downgraded for imprecision), hospital admissions (HR 0.89, CI 0.72 to 1.10; 1 study, 7599 participant-months; moderate-certainty evidence downgraded for imprecision) or falls (HR 1.03, CI 0.92 to 1.15; 1 study, 2275 participant-months; low-certainty evidence downgraded for imprecision and risk of bias). Delirium prevalence and severity were not assessed.In the enhanced educational intervention study, aimed at changing practice to address key delirium risk factors, it was not possible to determine the effect of the intervention on delirium incidence (RR 0.62, 95% CI 0.16 to 2.39; 1 study, 137 resident months; very low-certainty evidence downgraded for risk of bias and serious imprecision) or delirium prevalence (RR 0.57, 95% CI 0.15 to 2.19; 1 study, 160 participants; very low-certainty evidence downgraded for risk of bias and serious imprecision). There was probably little or no effect on mortality (RR 0.82, CI 0.50 to 1.34; 1 study, 215 participants; moderate-certainty evidence downgraded for imprecision). The intervention was probably associated with a reduction in hospital admissions (RR 0.67, CI 0.57 to 0.79; 1 study, 494 participants; moderate-certainty evidence downgraded due to indirectness). AUTHORS' CONCLUSIONS: Our review identified limited evidence on interventions for preventing delirium in older people in LTC. A software-based intervention to identify medications that could contribute to delirium risk and trigger a pharmacist-led medication review, probably reduces incidence of delirium in older people in institutional LTC. This is based on one large RCT in the US and may not be practical in other countries or settings which do not have comparable information technology services available in care homes. In the educational intervention aimed at identifying risk factors for delirium and developing bespoke solutions within care homes, it was not possible to determine the effect of the intervention on delirium incidence, prevalence or mortality. This evidence is based on a small feasibility trial. Our review identified three ongoing trials of multicomponent delirium prevention interventions. We identified no trials of pharmacological agents. Future trials of multicomponent non-pharmacological delirium prevention interventions for older people in LTC are needed to help inform the provision of evidence-based care for this vulnerable group

Determinants of Physical Health Self-Management Behaviours in Adults With Serious Mental Illness:A Systematic Review

Behavioural interventions can support the adoption of healthier lifestyles and improve physical health outcomes, but it is unclear what factors might drive success of such interventions in people with serious mental illness (SMI). We systematically identified and reviewed evidence of the association between determinants of physical health self-management behaviours in adults with SMI. Data about American Association of Diabetes Educator’s Self-Care Behaviours (AADE-7) were mapped against the novel Mechanisms of Action (MoA) framework. Twenty-eight studies were included in the review, reporting evidence on 104 determinant-behaviour links. Beliefs about capabilities and beliefs about consequences were the most important determinants of behaviour, especially for being physically active and healthy eating. There was some evidence that emotion and environmental context and resources played a role in determining reducing risks, being active, and taking medications. We found very limited evidence associated with problem solving, and no study assessed links between MoAs and healthy coping. Although the review predominantly identified evidence about associations from cross-sectional studies that lacked validated and objective measures of self-management behaviours, these findings can facilitate the identification of behaviour change techniques with hypothesised links to determinants to support self-management in people with SMI

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Development of a Supported Self-management Intervention for People With Severe Mental Illness and Type 2 Diabetes: Theory and Evidence-Based Co-design Approach

BackgroundType 2 diabetes is 2 to 3 times more common among people with severe mental illness (SMI). Self-management is crucial, with additional challenges faced by people with SMI. Therefore, it is essential that any diabetes self-management program for people with SMI addresses the unique needs of people living with both conditions and the inequalities they experience within health care services. ObjectiveWe combined theory, empirical evidence, and co-design approaches to develop a type 2 diabetes self-management intervention for people with SMI. MethodsThe development process encompassed 4 steps: step 1 involved prioritizing the mechanisms of action (MoAs) and behavior change techniques (BCTs) for the intervention. Using findings from primary qualitative research and systematic reviews, we selected candidate MoAs to target in the intervention and candidate BCTs to use. Expert stakeholders then ranked these MoAs and BCTs using a 2-phase survey. The average scores were used to generate a prioritized list of MoAs and BCTs. During step 2, we presented the survey results to an expert consensus workshop to seek expert agreement with the definitive list of MoAs and BCTs for the intervention and identify potential modes of delivery. Step 3 involved the development of trigger films using the evidence from steps 1 and 2. We used animations to present the experiences of people with SMI managing diabetes. These films were used in step 4, where we used a stakeholder co-design approach. This involved a series of structured workshops, where the co-design activities were informed by theory and evidence. ResultsUpon the completion of the 4-step process, we developed the DIAMONDS (diabetes and mental illness, improving outcomes and self-management) intervention. It is a tailored self-management intervention based on the synthesis of the outputs from the co-design process. The intervention incorporates a digital app, a paper-based workbook, and one-to-one coaching designed to meet the needs of people with SMI and coexisting type 2 diabetes. ConclusionsThe intervention development work was underpinned by the MoA theoretical framework and incorporated systematic reviews, primary qualitative research, expert stakeholder surveys, and evidence generated during co-design workshops. The intervention will now be tested for feasibility before undergoing a definitive evaluation in a pragmatic randomized controlled trial

Born in Bradford’s Better Start (BiBBS) interventional birth cohort study: Interim cohort profile

Background: The Born in Bradford’s Better Start (BiBBS) interventional birth cohort study was designed as an innovative cohort platform for efficient evaluation of early life interventions delivered through the Better Start Bradford programme. There are a growing number of interventional cohorts being implemented internationally. This paper provides an interim analysis of BiBBS in order to share learning about the feasibility and value of this method. Methods: Recruitment began in January 2016 and will complete in December 2023 with a target sample of 5,000 pregnancies. An interim data cut was completed for all pregnancies recruited between January 2016 and November 2019 with an expected due date between 1st April 2016 and 8th March 2020. Descriptive statistics were completed on the data. Results: Of 4,823 eligible pregnancies, 2,626 (54%) pregnancies were recruited, resulting in 2,392 mothers and 2,501 children. The sample are representative of the pregnant population (61% Pakistani heritage; 12% White British; 8% other South Asian and 6% Central and Eastern European ethnicity). The majority of participants (84%) live in the lowest decile of the Index of Multiple Deprivation, and many live in vulnerable circumstances. A high proportion (85%) of BiBBS families have engaged in one or more of the Better Start Bradford interventions. Levels of participation varied by the characteristics of the interventions, such as the requirement for active participation and the length of commitment to a programme. Conclusions: We have demonstrated the feasibility of recruiting an interventional cohort that includes seldom heard families from ethnic minority and deprived backgrounds. The high level of uptake of interventions is encouraging for the goal of evaluating the process and outcomes of multiple early life interventions using the innovative interventional cohort approach. BiBBS covers a period before, during and after the coronavirus disease 2019 (COVID-19) pandemic which adds scientific value to the cohort

Exploring the facilitators, barriers, and strategies for self-management in adults living with severe mental illness, with and without long-term conditions: A qualitative evidence synthesis

Background People living with severe mental illness (SMI) have a reduced life expectancy by around 15–20 years, in part due to higher rates of long-term conditions (LTCs) such as diabetes and heart disease. Evidence suggests that people with SMI experience difficulties managing their physical health. Little is known, however, about the barriers, facilitators and strategies for self-management of LTCs for people with SMI. Aim To systematically review and synthesise the qualitative evidence exploring facilitators, barriers and strategies for self-management of physical health in adults with SMI, both with and without long-term conditions. Methods CINAHL, Conference Proceedings Citation Index- Science, HMIC, Medline, NICE Evidence and PsycInfo were searched to identify qualitative studies that explored barriers, facilitators and strategies for self-management in adults with SMI (with or without co-morbid LTCs). Articles were screened independently by two independent reviewers. Eligible studies were purposively sampled for synthesis according to the richness and relevance of data, and thematically synthesised. Results Seventy-four articles met the inclusion criteria for the review; 25 articles, reporting findings from 21 studies, were included in the synthesis. Seven studies focused on co-morbid LTC self-management for people with SMI, with the remaining articles exploring self-management in general. Six analytic themes and 28 sub-themes were identified from the synthesis. The themes included: the burden of SMI; living with co-morbidities; beliefs and attitudes about self-management; support from others for self-management; social and environmental factors; and routine, structure and planning. Conclusions The synthesis identified a range of barriers and facilitators to self-management, including the burden of living with SMI, social support, attitudes towards self-management and access to resources. To adequately support people with SMI with co-morbid LTCs, healthcare professionals need to account for how barriers and facilitators to self-management are influenced by SMI, and meet the unique needs of this population.</p

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