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There is evidence that quality improvement projects developed with the participation of patients and family members are more likely to result in a sustainable change. To identify the intervening factors is an important step in promoting and supporting patient and family members’ engagement.

A survey was carried out with 90 hospitals. A total of 35 intervening factors were evaluated by the healthcare professionals from the quality area using a Likert scale. Factor analysis was applied to identify the relationship among the factors and cluster analysis and the standardized scores for each new latent variable were obtained to observe the association between them and hospitals profile. Cluster analysis allowed to group the hospitals with similar responses and to analyze whether there was any association with the profile of the institutions.

A total of ten intervening factors are identified: two in the financial dimension, five in the structural and three in the personal and cultural. The standardized scores of latent variables suggest that the financial factors could be affected by the hospital capacity. The structural factors could be impacted by the accreditation status, location (region) and administrative control (ownership). And the personal and cultural factors could be by the location and dominant organizational culture. All of factors are influenced by the performed quality management activities. The cluster analysis allowed the identification of three groups in the financial dimension, and four in the other two dimensions. Except for the accreditation status in the personal and cultural dimension, no evidence of association between the groups and the variables raised to characterize the profile of the hospitals was found.

The study contributed to identify the relationship among the intervening factors turning possible to simplify and reduce them more comprehensively than those originally identified in the literature and at the same time maintaining the representativeness of the original variables.

People with intellectual disability die prematurely and from avoidable causes. Innovative solutions and proactive strategies have been limited in addressing this disparity. This paper aims to detail the process of developing a risk stratification tool to identify those individuals who are higher risk of premature mortality.

This study used population health management principles to conceptualise a risk stratification tool for avoidable deaths in people with intellectual disability. A review of the literature examined the existing evidence of causes of death in people with intellectual disability. A qualitative methodology using focused groups of specialist clinicians was used to understand the factors that contributed towards avoidable deaths in people with intellectual disability. Delphi groups were used for consensus on the variables for inclusion in the risk stratification tool (Decision Support Tool for Physical Health).

A pilot of the Decision Support Tool for Physical Health within specialist intellectual disability service demonstrated effective utility and acceptability in clinical practice. The tool has also demonstrated good face and construct validity. A further study is currently being completed to examine concurrent and predictive validity of the tool.

To the best of the authors’ knowledge, this is the only study that has used a systematic approach to designing a risk stratification tool for identifying premature mortality in people with intellectual disability. The Decision Support Tool for Physical Health in clinical practice aims to guide clinical responses and prioritise those identified as at higher risk of avoidable deaths.

Secure children’s homes (SCHs) restrict the liberty of young people considered to be a danger to themselves or others. However, not all young people referred to SCHs find a placement, and little is known about the outcomes of the young person after an SCH or alternative placement. The purpose of this paper is to understand which characteristics most likely predict allocation to an SCH placement, and to explore the outcomes of the young people in the year after referral.

A retrospective electronic cohort study was conducted using linked social care data sets in England. The study population was all young people from England referred to SCHs for welfare reasons between 1st October 2016 to 31st March 2018 (n = 527). Logistic regression tested for differences in characteristics of SCH placement allocation and outcomes in the year after referral.

In total, 60% of young people referred to an SCH were allocated a place. Factors predicting successful or unsuccessful SCH allocation were previous placement in an SCH (OR = 2.12, p = 0.01); being female (OR = 2.26, p = 0.001); older age (OR = 0.75, p = 0.001); and a history of challenging behaviour (OR = 0.34, p = 0.01). In the year after referral, there were little differences in outcomes between young people placed in a SCH versus alternative accommodation.

The study raised concerns about the capacity of current services to recognise and meet the needs of this complex and vulnerable group of young people and highlights the necessity to explore and evaluate alternatives to SCHs.

The mental and physical health of those residing in Australian rural and remote communities is poorer compared to major cities. Physical health comorbidities contribute to almost 80% of premature mortality for people living with mental illness. Leisure time physical activity (LTPA) is a well-established intervention to improve physical and mental health. To address the physical and mental health of rural and remote communities through LTPA, the community’s level of readiness should be first determined. This study aims to use the community readiness model (CRM) to explore community readiness in a remote Australian community to address mental health through LTPA.

Individual semi-structured interviews were conducted using the CRM on LTPA to address mental health. Quantitative outcomes scored the community’s stage of readiness for LTPA programmes to address mental health using the CRM categories of one (no awareness) to nine (high level of community ownership). Qualitative outcomes were thematically analysed, guided by Braun and Clark.

The community scored six (initiation) for community efforts and knowledge of LTPA programmes and seven (stabilisation) for leadership. The community’s attitude towards LTPA and resources for programmes scored four (pre-planning), and knowledge of LTPA scored three (vague awareness).

To the best of the authors’ knowledge, this is the first Australian study to use CRM to examine community readiness to use LTPA to improve mental health in a remote community. The CRM was shown to be a useful tool to identify factors for intervention design that might optimise community empowerment in using LTPA to improve mental health at the community level.