The 3-step method for estimating the effects of auxiliary variables (i.e., covariates and distal outcome) in mixture modeling provides a useful way to specify complex mixture models. One of the ...benefits of this method is that the measurement parameters of the mixture model are not influenced by the auxiliary variable(s). In addition, it allows for models that involve multiple latent class variables to be specified without each part of the model influencing the others. This article describes a unique latent transition analysis model where the measurement models are a latent class analysis model and a growth mixture model. We highlight the application of this model to study kindergarten readiness profiles and link it to elementary students' reading trajectories. Mplus syntax for the 3-step specification is provided.
Abstract Background Improving the public’s understanding of how regional and socioeconomic inequalities create and perpetuate inequalities in health, is argued to be necessary for building support ...for policies geared towards creating a more equal society. However, research exploring public perceptions of health inequalities, and how they are generated, is limited. This is particularly so for young people. Our study sought to explore young people’s lived experiences and understandings of health inequalities. Methods We carried out focus group discussions ( n = 18) with 42 young people, aged 13–21, recruited from six youth organisations in England in 2021. The organisations were located in areas of high deprivation in South Yorkshire, the North East and London. Young people from each organisation took part in three interlinked focus group discussions designed to explore their (i) perceptions of factors impacting their health in their local area, (ii) understandings of health inequalities and (iii) priorities for change. Due to the Covid-19 pandemic, most discussions took place online ( n = 15). However, with one group in the North East, we carried out discussions face-to-face ( n = 3). Data were analysed thematically and we used NVivo-12 software to facilitate data management. Results Young people from all groups demonstrated an awareness of a North-South divide in England, UK. They described how disparities in local economies and employment landscapes between the North and the South led to tangible differences in everyday living and working conditions. They clearly articulated how these differences ultimately led to inequalities in people’s health and wellbeing, such as linking poverty and employment precarity to chronic stress. Young people did not believe these inequalities were inevitable. They described the Conservative government as prioritising the South and thus perpetuating inequalities through uneven investment. Conclusions Our study affords important insights into young people’s perceptions of how wider determinants can help explain the North-South health divide in England. It demonstrates young people’s contextualised understandings of the interplay between spatial, social and health inequalities. Our findings support calls for pro-equity policies to address the structural causes of regional divides in health. Further research, engaging young people in deliberative policy analysis, could build on this work.
Background Improving the public's understanding of how regional and socioeconomic inequalities create and perpetuate inequalities in health, is argued to be necessary for building support for ...policies geared towards creating a more equal society. However, research exploring public perceptions of health inequalities, and how they are generated, is limited. This is particularly so for young people. Our study sought to explore young people's lived experiences and understandings of health inequalities. Methods We carried out focus group discussions (n = 18) with 42 young people, aged 13-21, recruited from six youth organisations in England in 2021. The organisations were located in areas of high deprivation in South Yorkshire, the North East and London. Young people from each organisation took part in three interlinked focus group discussions designed to explore their (i) perceptions of factors impacting their health in their local area, (ii) understandings of health inequalities and (iii) priorities for change. Due to the Covid-19 pandemic, most discussions took place online (n = 15). However, with one group in the North East, we carried out discussions face-to-face (n = 3). Data were analysed thematically and we used NVivo-12 software to facilitate data management. Results Young people from all groups demonstrated an awareness of a North-South divide in England, UK. They described how disparities in local economies and employment landscapes between the North and the South led to tangible differences in everyday living and working conditions. They clearly articulated how these differences ultimately led to inequalities in people's health and wellbeing, such as linking poverty and employment precarity to chronic stress. Young people did not believe these inequalities were inevitable. They described the Conservative government as prioritising the South and thus perpetuating inequalities through uneven investment. Conclusions Our study affords important insights into young people's perceptions of how wider determinants can help explain the North-South health divide in England. It demonstrates young people's contextualised understandings of the interplay between spatial, social and health inequalities. Our findings support calls for pro-equity policies to address the structural causes of regional divides in health. Further research, engaging young people in deliberative policy analysis, could build on this work. Keywords: Health inequalities, North-South divide, Social determinants of health, Young people, Qualitative
Mechanisms by which liaison mental health services (LMHS) may bring about improved patient and organisational outcomes are poorly understood. A small number of logic models have been developed, but ...they fail to capture the complexity of clinical practice.
We synthesised data from a variety of sources including a large national survey, 73 in-depth interviews with acute and liaison staff working in hospitals with different types of liaison mental health services, and relevant local, national and international literature. We generated logic models for two common performance indicators used to assess organisational outcomes for LMHS: response times in the emergency department and hospital length of stay for people with mental health problems.
We identified 8 areas of complexity that influence performance, and 6 trade-offs which drove the models in different directions depending upon the balance of the trade-off. The logic models we developed could only be captured by consideration of more than one pass through the system, the complexity in which they operated, and the trade-offs that occurred.
Our findings are important for commissioners of liaison services. Reliance on simple target setting may result in services that are unbalanced and not patient-centred. Targets need to be reviewed on a regular basis, together with other data that reflect the wider impact of the service, and any external changes in the system that affect the performance of LMHS, which are beyond their control.
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