811 research outputs found
Social network analysis of rural medical school immersion in a rural clinical school
Background: The impact of new medical graduates on the social dimensions of the rural medical workforce is yet to be examined. Social Network Analysis (SNA) is able to visualize and measure these dimensions. We apply this method to examine the workforce characteristics of graduates from a representative Australian Rural Clinical School.
Methods: Participants were medical graduates of the Rural Clinical School of Western Australia (RCSWA) from the 2001–2014 cohorts, identified as being in rural work in 2017 by the Australian Health Practitioner Regulation Agency. SNA was used to examine the relationships between site of origin and of work destination. Data were entered into UCInet 6 as tied pairs, and visualized using Netdraw. UCINet statistics relating to node centrality were obtained from the node editor.
Results: SNA measures showed that the 124 of 709 graduates in rural practice were distributed around Australia, and that their practice was strongly focused on the North, with a clear centre in the remote Western Australian town of Broome. Women were strongly recruited, and were widely distributed.
Conclusions: RCSWA appears to be a “weak tie” according to SNA theory: the School attracts graduates to rural nodes where they had only passing prior contact. The multiple activities that comprise the social capital of the most attractive, remote, node demonstrate the clear workforce effects of being a “bridge, broker and boundary spanner” in SNA terms, and add new understanding about recruiting to the rural workforce
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Strategies used in the pursuit of achievability during goal setting in rehabilitation
We used conversation analysis of six audio- and video-recorded goal setting meetings that were attended by patients and their respective treating team to explore and describe the interaction of participants during interdisciplinary goal setting, and to identify the strategies used to agree goals. The health care professionals involved in the six sessions included four physiotherapists, four occupational therapists, four nurses, one speech and language therapist, and one neuropsychologist. The participants included 3 patients with multiple sclerosis, 2 patients with spinal cord lesions, and 1 patient with stroke from an inpatient neurological rehabilitation unit. Detailed analysis revealed how the treating team shaped the meetings. The most notable finding was that there was rarely a straightforward translation of patient wishes into agreed-on written goals, with the treating team leading goal modification so that goals were achievable. Despite professional dominance, patients also influenced the course of the interaction, particularly when offering resistance to goals proposed by the treating team
Beyond standard rehabilitation programs : working with people with MS for adequate goal setting and rehabilitation treatment evaluation
Shared decision-making occurs when the decision is ‘preference sensitive’. It consists of identifying the different treatment options (choice talk), considering the advantages and disadvantages of each option (option talk), and then supporting making the decision in the light of an individual’s experiences and values (decision talk). It is most effective when working with an ‘activated patient’, that is, one who is prepared for the shared decision-making role. In rehabilitation, many decisions are preference sensitive. These decisions may be framed as ‘goal setting’. Skilled clinicians can support patients to learn goal setting skills until the person has the skills to maintain health supporting behaviours most of the time, only seeing a clinical team at times of change or crisis. The steps in goal setting can be summarised as building empathy, creating a contract, identifying priorities, summarising the conversation, articulating the goal, defining actions, building coping plans, and then reviewing progress. Working with people with MS can extend beyond working with individuals to a consideration of what people with MS want from services. This can result in the co-production and co-design of services, as well as the identification of research priorities as exemplified by the James Lind Alliance
Machine Learning in Falls Prediction; A cognition-based predictor of falls for the acute neurological in-patient population
Background Information: Falls are associated with high direct and indirect
costs, and significant morbidity and mortality for patients. Pathological falls
are usually a result of a compromised motor system, and/or cognition. Very
little research has been conducted on predicting falls based on this premise.
Aims: To demonstrate that cognitive and motor tests can be used to create a
robust predictive tool for falls.
Methods: Three tests of attention and executive function (Stroop, Trail
Making, and Semantic Fluency), a measure of physical function (Walk-12), a
series of questions (concerning recent falls, surgery and physical function)
and demographic information were collected from a cohort of 323 patients at a
tertiary neurological center. The principal outcome was a fall during the
in-patient stay (n = 54). Data-driven, predictive modelling was employed to
identify the statistical modelling strategies which are most accurate in
predicting falls, and which yield the most parsimonious models of clinical
relevance.
Results: The Trail test was identified as the best predictor of falls.
Moreover, addition of any others variables, to the results of the Trail test
did not improve the prediction (Wilcoxon signed-rank p < .001). The best
statistical strategy for predicting falls was the random forest (Wilcoxon
signed-rank p < .001), based solely on results of the Trail test. Tuning of the
model results in the following optimized values: 68% (+- 7.7) sensitivity, 90%
(+- 2.3) specificity, with a positive predictive value of 60%, when the
relevant data is available.
Conclusion: Predictive modelling has identified a simple yet powerful machine
learning prediction strategy based on a single clinical test, the Trail test.
Predictive evaluation shows this strategy to be robust, suggesting predictive
modelling and machine learning as the standard for future predictive tools
What is 'Early intervention' for work related difficulties for people with multiple sclerosis?: a case study report
Background: Employment matters and at diagnosis most people with multiple sclerosis are in full time work or education. 75% of people with multiple sclerosis report the condition has impacted on this employment or career opportunities. Early intervention to support people in work is advocated for in the literature. This paper starts the journey of exploring what is meant by early.
Methods: A randomized control trial was undertaken offering either occupational therapy led early intervention or usual care to people diagnosed with multiple sclerosis within one year. Two cases were purposively selected from the treatment group and used to illustrate the importance as well as the nature of early intervention.
Results: Both participants received occupational therapy led support which included fatigue management, advice about legal rights, support accessing services such as Access to Work, and support with disclosure in the workplace.
Conclusions: Neither of the participants had reported any work problems at the point of referral. However the clinical intervention led to the identification of small concerns and worries. The education and support offered to these two participants alleviated these worries. Early support and education to enable people with multiple sclerosis to manage their condition in the work place can have a positive impact. This may equip them better for the journey ahead
Quality-of-life measures for use within care homes:A systematic review of their measurement properties
Objective: the aims of this review were (i) to identify quality-of-life (QoL) measures which have had their measurement properties validated in people residing in care homes or nursing homes, and to critically compare and summarise these instruments and (ii) to make recommendations for measurement instruments.
Methods: bibliographic databases PsycINFO, PubMed, Cochrane, CINAHL and Embase were searched for articles evaluating measurement properties of QoL instruments in people residing in care homes. Methodological quality of studies was assessed using the consensus-based standards for the selection of health measurement instruments checklist. Measurement properties of instruments were appraised using a systematic checklist.
Results: the search strategy resulted in 3252 unique citations, of which 15 articles were included in this review. These articles assessed 13 instruments, 8 of which were dementia or Alzheimer specific instruments. The QUALIDEM, a dementia-specific observational instrument, had the widest array of information available on its measurement properties, which were mostly satisfactory. Most measurement instruments lacked information on hypotheses testing and content validity. Information on responsiveness and measurement error was not available for any instrument.
Conclusions: for people with dementia living in care homes, the QUALIDEM is recommended for measuring QoL. For residents without dementia, we recommend Kane et al.'s Psychosocial Quality of Life Domains questionnaire. Studies of higher methodological quality, assessing a wider range of measurement properties are needed to allow a more fully informed choice of QoL instrument
Relative incidence and predictors of pulmonary arterial hypertension complicating type 2 diabetes: The Fremantle Diabetes Study Phase I
Aims: To determine the relative incidence and predictors of pulmonary arterial hypertension (PAH) in type 2 diabetes.
Methods: Hospitalizations for/with and death from/with PAH, and all-cause mortality, were ascertained from validated databases for participants from the longitudinal, community-based Fremantle Diabetes Study Phase I (FDS1; n = 1287) and age-, sex- and zip code-matched people without diabetes (n = 5153) between entry (1993–1996) and end-2017. Incidence rates (IRs) and IR ratios (IRRs) were calculated. Cox proportional hazards and competing risk models generated cause-specific (cs) and subdistribution (sd) hazard ratios (HRs) for incident PAH.
Results: In the pooled cohort (mean age 64.0 years, 49% males), 49 (3.8%) of the type 2 diabetes participants and 133 (2.6%) of those without diabetes developed PAH during 106,556 person-years of follow-up (IRs (95% CI) 262 (194– 346) and 151 (127–179) /100,000 person-years, respectively; IRR 1.73 (1.22–2.42), P = 0.001). Type 2 diabetes was associated with an unadjusted csHR of 1.97 (1.42–2.74) and sdHR of 1.44 (1.04–2.00) (P ≤ 0.03); after adjustment for age, sex, and co-morbidities, these were 1.43 (0.83–2.47) and 1.36 (0.97–1.91), respectively (P ≥ 0.07).
Conclusions: Type 2 diabetes is associated with an increased risk of PAH but this is no longer significant after adjustment for other explanatory variables and the competing risk of death.
© 2020 Elsevier Inc. All rights reserved
Developing vocational rehabilitation services for people with long-term neurological conditions : identifying facilitators and barriers to service provision
Purpose:
This study aimed to understand existing vocational rehabilitation (VR) service provision in one locality in London (population 3.74 million), identify any gaps and explore reasons for this, to support service development.
Method:
Using Soft Systems Methodology to guide the research process, semi - structured interviews were completed with nine participants, who were clinicians and managers providing VR within NHS services. Data were analysed thematically to build a ‘rich picture’ and develop a conceptual model of VR service delivery. Findings were then ratified with participants at an engagement event.
Results:
The findings indicate a spectrum of VR service provision for long - term neurological conditions with differing levels of funding in place. VR often takes place ‘under the radar’ and therefore the true VR needs of this population, and the extent of service provision is not known. There is inconsistency of understanding across the services as to what constitutes VR and outcomes are not routinely measured.
Conclusion:
For VR services to develop they require appropriate funding, driven by Government policy to commissioners. Clear definitions of VR, collecting and sharing outcome data and effective communication across services are needed at a local level. This is expressed in a conceptual model of VR service delivery
Minimum data set to measure rehabilitation needs and health outcome after major trauma : application of an international framework
BACKGROUND: Measurement of long term health outcome after trauma remains non-standardized and ambiguous which limits national and international comparison of burden of injuries. The World Health Organization (WHO) has recommended the application of the International Classification of Function, Disability and Health (ICF) to measure rehabilitation and health outcome worldwide. No previous poly-trauma studies have applied the ICF comprehensively to evaluate outcome after injury.
AIM: To apply the ICF categorization in patients with traumatic injuries to identify a minimum data set of important rehabilitation and health outcomes to enable national and international comparison of outcome data.
DESIGN: A mixed methods design of patient interviews and an on-line survey.
SETTING: An ethnically diverse urban major trauma center in London.
POPULATION: Adult patients with major traumatic injuries (poly-trauma) and international health care professionals (HCPs) working in acute and post-acute major trauma settings.
METHODS: Mixed methods investigated patients and health care professionals (HCPs) perspectives of important rehabilitation and health outcomes. Qualitative patient data and quantitative HCP data were linked to ICF categories. Combined data were refined to identify a minimum data set of important rehabilitation and health outcome categories.
RESULTS: Transcribed patient interview data (N.=32) were linked to 234 (64%) second level ICF categories. Two hundred and fourteen HCPs identified 121 from a possible 140 second level ICF categories (86%) as relevant and important. Patients and HCPs strongly agreed on ICF body structures and body functions categories which include temperament, energy and drive, memory, emotions, pain and repair function of the skin. Conversely, patients prioritised domestic tasks, recreation and work compared to HCP priorities of self-care and mobility. Twenty six environmental factors were identified. Patient and HCP data were refined to recommend a 109 possible ICF categories for a minimum data set.
CONCLUSIONS: The comprehensive measurement of health outcomes after trauma is important for patients, health professionals and trauma systems. An internationally applied ICF minimum data set will standardize the language used and concepts measured after major trauma to enable national and international comparison of outcome data
Comparison of Lipoprotein Based Insulin Resistance Score and Traditional Risk Factors in Adolescents with Obesity
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