The community mental health team fidelity scale: A measure of program fidelity of social networks interventions for severe mental illness

Open dialogue (OD) is a multi-component therapeutic and organizational intervention for crisis and continuing community mental health care with a therapeutic focus on clients’ social networks. The development and implementation of this model of care in the United Kingdom requires considerable contextual adaptations which need to be assessed to support effective implementation. Program fidelity–the extent to which core components of an intervention are delivered as intended by an intervention protocol at all levels–is crucial for these adaptations. Aims: To develop, pilot, and implement a program fidelity measure for community mental health services providing OD and ‘treatment as usual’ (TAU) or standard NHS crisis and community care. Methods: Measure structure, content, and scoring were developed and refined through an iterative process of discussion between the research team and OD experts. Measure was piloted in the 6 OD and 6 TAU services participating in a large-scale research program. Results: Initial data suggests that the Community Mental Health Team Fidelity Scale (COM-FIDE) is a potentially reliable and feasible measure of the fidelity of community mental health services and specific OD components of such services

Drought climate adaptation program: producing enhanced agricultural crop insurance systems: summary report

Queensland farmers are subject to highly variable climatic conditions, including drought and floods, which can undermine production. Insurance could play an important role in helping Queensland farmers manage their climate risk. However, currently, the use of insurance to manage climate-related production risk is poorly understood and utilised by farmers. This project aims to address this gap by providing information on climate risks and the role of insurance for managing these. This project conducted focused reviews on climate risk in agriculture and on how insurance products could be used to address these risks. The project also carried out on-ground surveys from cotton and sugar industry and conducted modelling to assess risks and the role of insurance for cotton and sugar cane farmers in Queensland. Prototype climate assessment risk and reporting tools were also developed. The reviews carried out in this project identified that Queensland’s agricultural sector is highly exposed to production volatility as a result of weather risks. It is our view that the Queensland agricultural sector has an excellent opportunity to provide its farmers with protection against uninsured seasonal risks to crop production. Key climate and farming systems risks were identified by interviewing a total of 55 farmers (23 cotton growers and 32 sugar cane growers) across Queensland. Key climate risks to the cotton industry include hail, drought/dry years (lack of rainfall during planting and season), quality downgrade (discolouration), excessive heat, floods and wet weather (during the season and especially during harvest). Similarly, for the sugar industry, key climate risks include drought, flood, excessive rainfall during harvest, cyclone, pests and disease. Key messages from farmer surveys are that current insurance products available to Queensland farmers (specifically, cotton and sugar cane farmers) may not address critical risks to the production and/or profitability of these systems and that farmers would prefer to have comprehensive insurance products available that cover them against profitability losses across multiple risk factors. Based on survey findings three prototype insurance products were developed for the cotton industry Insurance products developed were Drought Cover: insufficient rainfall during the planting season – August to November; Drought Cover: insufficient rainfall during growing season – November to February; and Wet Harvest Cover: excessive rainfall during harvest season – March to June. Two prototype insurance products were developed for the sugar industry. They include; Cyclone Cover: crop damage during cyclone season – November to April; and Wet Harvest Cover: excessive rainfall during harvest season – June to December Rainfall-indexed based worked examples were also developed for sugar and cotton industry growers

Drought climate adaptation program: producing enhanced agricultural crop insurance systems: final report

Queensland farmers are subject to highly variable climatic conditions, including drought and floods, which can undermine production. Insurance could play an important role in helping Queensland farmers manage their climate risk. However, currently the use of insurance to manage climate related production risk is poorly understood and utilised by farmers. This project aims to address this gap by providing information on climate risks and the role of insurance for managing these. This project conducted focussed reviews on climate risk in agriculture and on how insurance products could be used to address these risks. The project also carried out on-ground surveys from cotton and sugar industry and conducted modelling to assess risks and the role of insurance for cotton and sugar cane farmers in Queensland. Prototype climate assessment risk and reporting tools were also developed. The reviews carried out in this project identified that Queensland’s agricultural sector is highly exposed to production volatility as a result of weather risks. It is our view that the Queensland agricultural sector has an excellent opportunity to provide its farmers with protection against uninsured seasonal risks to crop production. Key climate and farming systems risks were identified by interviewing a total of 55 farmers (23 cotton growers and 32 sugar cane growers) across Queensland. Key climate risks to the cotton industry include hail, drought/dry years (lack of rainfall during planting and season), quality downgrade (discolouration), excessive heat, floods and wet weather (during season and especially during harvest). Similarly, for the sugar industry, key climate risks include, drought, flood, excessive rainfall during harvest, cyclone, pests and disease. Key messages from farmer surveys are that current insurance products available to Queensland farmers (specifically, cotton and sugar cane farmers) may not address critical risks to the production and/or profitability of these systems and that farmers would prefer to have comprehensive insurance products available that cover them against profitability losses across multiple risk factors. A ‘climate and agricultural risk assessment and reporting tool’ (prototype) was developed as part of the project. This ‘tool’ allows quantification of key climate risks, initially for the sugar and cotton industry. The tool provides an option to generate a detail climate risk report based on historical data and a future seasonal climate forecast for an individual location. The tool data also serves as a dataset portal, allowing for the download of data in a required template. Cotton and sugarcane crop models APSIM and DSSAT were employed to simulate the growth and yield for 10 and 12 sites, respectively, across Queensland over the period 1940-2017 for various crop management factors. Comparing the simulated yields (from each model or the mean simulated value from ensemble models) to the observed yield (available at regional scale) the trend in year to year variability is satisfactorily captured for cotton on average, whereas for sugarcane there is a trend to overestimate or underestimate the yield depending on the site. Based on survey findings three prototype insurance products were developed for the cotton industry Insurance products developed were Drought Cover: insufficient rainfall during the planting season – August to November; Drought Cover: insufficient rainfall during growing season – November to February; and Wet Harvest Cover: excessive rainfall during harvest season – March to June. Two prototype insurance products were developed for sugar industry. They include; Cyclone Cover: crop damage during cyclone season – November to April; and Wet Harvest Cover: excessive rainfall during harvest season – June to December. Rainfall-indexed based worked examples were also developed for sugar and cotton industry growers to better appreciate the insurance mechanisms

Drought climate adaptation program: producing enhanced agricultural crop insurance systems: final report

Queensland farmers are subject to highly variable climatic conditions, including drought and floods, which can undermine production. Insurance could play an important role in helping Queensland farmers manage their climate risk. However, currently the use of insurance to manage climate related production risk is poorly understood and utilised by farmers. This project aims to address this gap by providing information on climate risks and the role of insurance for managing these. This project conducted focussed reviews on climate risk in agriculture and on how insurance products could be used to address these risks. The project also carried out on-ground surveys from cotton and sugar industry and conducted modelling to assess risks and the role of insurance for cotton and sugar cane farmers in Queensland. Prototype climate assessment risk and reporting tools were also developed. The reviews carried out in this project identified that Queensland’s agricultural sector is highly exposed to production volatility as a result of weather risks. It is our view that the Queensland agricultural sector has an excellent opportunity to provide its farmers with protection against uninsured seasonal risks to crop production. Key climate and farming systems risks were identified by interviewing a total of 55 farmers (23 cotton growers and 32 sugar cane growers) across Queensland. Key climate risks to the cotton industry include hail, drought/dry years (lack of rainfall during planting and season), quality downgrade (discolouration), excessive heat, floods and wet weather (during season and especially during harvest). Similarly, for the sugar industry, key climate risks include, drought, flood, excessive rainfall during harvest, cyclone, pests and disease. Key messages from farmer surveys are that current insurance products available to Queensland farmers (specifically, cotton and sugar cane farmers) may not address critical risks to the production and/or profitability of these systems and that farmers would prefer to have comprehensive insurance products available that cover them against profitability losses across multiple risk factors. A ‘climate and agricultural risk assessment and reporting tool’ (prototype) was developed as part of the project. This ‘tool’ allows quantification of key climate risks, initially for the sugar and cotton industry. The tool provides an option to generate a detail climate risk report based on historical data and a future seasonal climate forecast for an individual location. The tool data also serves as a dataset portal, allowing for the download of data in a required template. Cotton and sugarcane crop models APSIM and DSSAT were employed to simulate the growth and yield for 10 and 12 sites, respectively, across Queensland over the period 1940-2017 for various crop management factors. Comparing the simulated yields (from each model or the mean simulated value from ensemble models) to the observed yield (available at regional scale) the trend in year to year variability is satisfactorily captured for cotton on average, whereas for sugarcane there is a trend to overestimate or underestimate the yield depending on the site. Based on survey findings three prototype insurance products were developed for the cotton industry Insurance products developed were Drought Cover: insufficient rainfall during the planting season – August to November; Drought Cover: insufficient rainfall during growing season – November to February; and Wet Harvest Cover: excessive rainfall during harvest season – March to June. Two prototype insurance products were developed for sugar industry. They include; Cyclone Cover: crop damage during cyclone season – November to April; and Wet Harvest Cover: excessive rainfall during harvest season – June to December. Rainfall-indexed based worked examples were also developed for sugar and cotton industry growers to better appreciate the insurance mechanisms

Development and validation of a case definition for problematic menopause in primary care electronic medical records

Abstract Background Menopause is a normal transition in a woman’s life. For some women, it is a stage without significant difficulties; for others, menopause symptoms can severely affect their quality of life. This study developed and validated a case definition for problematic menopause using Canadian primary care electronic medical records, which is an essential step in examining the condition and improving quality of care. Methods We used data from the Canadian Primary Care Sentinel Surveillance Network including billing and diagnostic codes, diagnostic free-text, problem list entries, medications, and referrals. These data formed the basis of an expert-reviewed reference standard data set and contained the features that were used to train a machine learning model based on classification and regression trees. An ad hoc feature importance measure coupled with recursive feature elimination and clustering were applied to reduce our initial 86,000 element feature set to a few tens of the most relevant features in the data, while class balancing was accomplished with random under- and over-sampling. The final case definition was generated from the tree-based machine learning model output combined with a feature importance algorithm. Two independent samples were used: one for training / testing the machine learning algorithm and the other for case definition validation. Results We randomly selected 2,776 women aged 45–60 for this analysis and created a case definition, consisting of two occurrences within 24 months of International Classification of Diseases, Ninth Revision, Clinical Modification code 627 (or any sub-codes) OR one occurrence of Anatomical Therapeutic Chemical classification code G03CA (or any sub-codes) within the patient chart, that was highly effective at detecting problematic menopause cases. This definition produced a sensitivity of 81.5% (95% CI: 76.3-85.9%), specificity of 93.5% (91.9-94.8%), positive predictive value of 73.8% (68.3-78.6%), and negative predictive value of 95.7% (94.4-96.8%). Conclusion Our case definition for problematic menopause demonstrated high validity metrics and so is expected to be useful for epidemiological study and surveillance. This case definition will enable future studies exploring the management of menopause in primary care settings

Clinical effectiveness and cost-effectiveness of collaborative care for depression in UK primary care (CADET): a cluster randomised controlled trial.

BACKGROUND: Collaborative care is effective for depression management in the USA. There is little UK evidence on its clinical effectiveness and cost-effectiveness. OBJECTIVE: To determine the clinical effectiveness and cost-effectiveness of collaborative care compared with usual care in the management of patients with moderate to severe depression. DESIGN: Cluster randomised controlled trial. SETTING: UK primary care practices (n = 51) in three UK primary care districts. PARTICIPANTS: A total of 581 adults aged ≥ 18 years in general practice with a current International Classification of Diseases, Tenth Edition depressive episode, excluding acutely suicidal people, those with psychosis, bipolar disorder or low mood associated with bereavement, those whose primary presentation was substance abuse and those receiving psychological treatment. INTERVENTIONS: Collaborative care: 14 weeks of 6-12 telephone contacts by care managers; mental health specialist supervision, including depression education, medication management, behavioural activation, relapse prevention and primary care liaison. Usual care was general practitioner standard practice. MAIN OUTCOME MEASURES: Blinded researchers collected depression [Patient Health Questionnaire-9 (PHQ-9)], anxiety (General Anxiety Disorder-7) and quality of life (European Quality of Life-5 Dimensions three-level version), Short Form questionnaire-36 items) outcomes at 4, 12 and 36 months, satisfaction (Client Satisfaction Questionnaire-8) outcomes at 4 months and treatment and service use costs at 12 months. RESULTS: In total, 276 and 305 participants were randomised to collaborative care and usual care respectively. Collaborative care participants had a mean depression score that was 1.33 PHQ-9 points lower [n = 230; 95% confidence interval (CI) 0.35 to 2.31; p = 0.009] than that of participants in usual care at 4 months and 1.36 PHQ-9 points lower (n = 275; 95% CI 0.07 to 2.64; p = 0.04) at 12 months after adjustment for baseline depression (effect size 0.28, 95% CI 0.01 to 0.52; odds ratio for recovery 1.88, 95% CI 1.28 to 2.75; number needed to treat 6.5). Quality of mental health but not physical health was significantly better for collaborative care at 4 months but not at 12 months. There was no difference for anxiety. Participants receiving collaborative care were significantly more satisfied with treatment. Differences between groups had disappeared at 36 months. Collaborative care had a mean cost of £272.50 per participant with similar health and social care service use between collaborative care and usual care. Collaborative care offered a mean incremental gain of 0.02 (95% CI -0.02 to 0.06) quality-adjusted life-years (QALYs) over 12 months at a mean incremental cost of £270.72 (95% CI -£202.98 to £886.04) and had an estimated mean cost per QALY of £14,248, which is below current UK willingness-to-pay thresholds. Sensitivity analyses including informal care costs indicated that collaborative care is expected to be less costly and more effective. The amount of participant behavioural activation was the only effect mediator. CONCLUSIONS: Collaborative care improves depression up to 12 months after initiation of the intervention, is preferred by patients over usual care, offers health gains at a relatively low cost, is cost-effective compared with usual care and is mediated by patient activation. Supervision was by expert clinicians and of short duration and more intensive therapy may have improved outcomes. In addition, one participant requiring inpatient treatment incurred very significant costs and substantially inflated our cost per QALY estimate. Future work should test enhanced intervention content not collaborative care per se. TRIAL REGISTRATION: Current Controlled Trials ISRCTN32829227. FUNDING: This project was funded by the Medical Research Council (MRC) (G0701013) and managed by the National Institute for Health Research (NIHR) on behalf of the MRC-NIHR partnership

Race, colonial history and national identity: Resident Evil 5 as a Japanese game

Resident Evil 5 is a zombie game made by Capcom featuring a White American protagonist and set in Africa. This paper argues that approaching this as a Japanese game reveals aspects of a Japanese racial and colonial social imaginary that are missed if this context of production is ignored. In terms of race, the game presents hybrid racial subjectivities that can be related to Japanese perspectives of Blackness and Whiteness where these terms are two poles of difference and identity through which an essentialised Japanese identity is constructed in what Iwabuchi calls “strategic hybridism” (Iwabuchi, 2002). In terms of colonialism, the game echoes structures of Japanese colonialism through which Japanese colonialism is obliquely memorialised and a “normal” Japanese global subjectivity can be performed

Routine Outcomes Monitoring to Support Improving Care for Schizophrenia: Report from the VA Mental Health QUERI

In schizophrenia, treatments that improve outcomes have not been reliably disseminated. A major barrier to improving care has been a lack of routinely collected outcomes data that identify patients who are failing to improve or not receiving effective treatments. To support high quality care, the VA Mental Health QUERI used literature review, expert interviews, and a national panel process to increase consensus regarding outcomes monitoring instruments and strategies that support quality improvement. There was very good consensus in the domains of psychotic symptoms, side-effects, drugs and alcohol, depression, caregivers, vocational functioning, and community tenure. There are validated instruments and assessment strategies that are feasible for quality improvement in routine practice

Effective healthcare teams require effective team members: defining teamwork competencies

BACKGROUND: Although effective teamwork has been consistently identified as a requirement for enhanced clinical outcomes in the provision of healthcare, there is limited knowledge of what makes health professionals effective team members, and even less information on how to develop skills for teamwork. This study identified critical teamwork competencies for health service managers. METHODS: Members of a state branch of the professional association of Australian health service managers participated in a teamwork survey. RESULTS: The 37% response rate enabled identification of a management teamwork competency set comprising leadership, knowledge of organizational goals and strategies and organizational commitment, respect for others, commitment to working collaboratively and to achieving a quality outcome. CONCLUSION: Although not part of the research question the data suggested that the competencies for effective teamwork are perceived to be different for management and clinical teams, and there are differences in the perceptions of effective teamwork competencies between male and female health service managers. This study adds to the growing evidence that the focus on individual skill development and individual accountability and achievement that results from existing models of health professional training, and which is continually reinforced by human resource management practices within healthcare systems, is not consistent with the competencies required for effective teamwork