Abstract Aim To identify and map out existing nurse‐led models of care for treatment and prevention of metabolic syndrome in primary care settings. Design A scoping review. Methods Conducted in accordance with the JBI methodology. Data Sources A search of the databases PubMed, CINAHL Complete, Cochrane Library, Scopus, handsearch and a grey literature search was conducted in June 2022 and updated in March 2023. Results Title and abstract screening was performed on 926 articles resulting in 40 articles for full text screening. Full text screening yielded seven articles that met inclusion criteria. Conclusion Additional research is needed on nursing models of care to prevent and treat metabolic syndrome. Future studies should concentrate on rigour with clearly defined objective inclusion criteria. Implications to Clinical Practice This review contributes a synthesis of the evidence on nurse‐led models for metabolic syndrome in primary care. Impact This scoping review addresses metabolic syndrome, the precursor to non‐communicable disease. The review mapped the evidence for nurse‐led models of care for metabolic syndrome in the primary care setting. These findings promote the development and evaluation of novel nurse‐led models of care which can mitigate the effect of the current epidemic. Reporting Method PRISMA checklist for scoping reviews. No patient or public contribution was part of this study. Protocol Registration: Open Science Framework accessible at: https://osf.io/jfpw7/ .
Background Electronic health systems contain large amounts of unstructured data (UD) which are often unanalyzed due to the time and costs involved. Unanalyzed data creates missed opportunities to improve health outcomes. Natural language processing (NLP) is the foundation of generative artificial intelligence (GAI), which is the basis for large language models, such as ChatGPT. NLP and GAI are machine learning methods that analyze large amounts of data in a short time at minimal cost. The ability of NLP to conduct qualitative analyses is increasing, yet the results can lack context and nuance in their findings, requiring human intervention. Methods Our study compared outcomes, time, and costs of a previously published qualitative study. Our approach partnered an NLP model and a qualitative researcher (NLP+). UD from behavioral health patients were analyzed using NLP and a Latent Dirichlet allocation to identify the topics using probability of word coherence scores. The topics were then analyzed by a qualitative researcher, translated into themes, and compared with the original findings. Results The NLP + method results aligned with the original, qualitative derived themes. Our model also identified two additional themes which were not originally detected. The NLP + method required 6 hours of labor, 3 minutes for transcription, and a transcription cost of $1.17. The original, qualitative researcher only method required more than 36 hours ($2,250) of time and $1,100 for transcription. Conclusions While natural language processing analyzes voluminous amounts of data in seconds, context and nuance in human language are regularly missed. Combining a qualitative researcher with NLP + could be deployed in many settings, reducing time and costs, and improving context. Until large language models are more prevalent, a human interaction can help translate the patient experience by contextualizing data rich in social determinant indicators which may otherwise go unanalyzed.
ABSTRACT In addiction treatment, harm reduction is a philosophy that aims to reduce the harms from ongoing alcohol and other drug use. Although abstinence may be the ‘gold standard’ in reducing harm from ongoing alcohol and other drug use, harm reduction recognises that abstinence may not be achievable for certain individuals. Accordingly, harm reduction is used to enable medical or mental health treatment for individuals who continue to use alcohol and other drugs, providing a form of care which meets individuals where they present to healthcare facilities. Harm reduction accepts ongoing alcohol and other drug use, while providing a traditionally marginalised cohort of individuals access to healthcare services. In this perspective paper, we argue that the role of nurses in promoting and utilising harm reduction as part of their regular practice is essential to both reducing harm from alcohol and other drug use, engaging individuals who use alcohol and other drugs in healthcare services, and providing a means to accept individuals as they are to build trust and rapport for engagement in addiction treatment when they are ready, and at their own pace. Nurses, by virtue of their role and number in the healthcare landscape (approximately 28 million globally), are ideally placed to implement harm reduction in their practice to achieve better outcomes for individuals who use alcohol and other drugs.
Addiction nurses are highly skilled providers of holistic care and ensuring workforce sustainability is key to providing quality care to a traditionally marginalised group of healthcare consumers. The aim of this study was to explore perceived stigma towards the addiction nursing speciality, addiction nursing (also known as alcohol and other drug nursing) and its impact on workforce sustainability, retention and recruitment. Secondary analysis of qualitative interview data with nurses (n = 50) and survey data (n = 337) was conducted as part of a workforce mapping exercise in 2019. COREQ reporting guidelines were used. After structural coding was applied, three themes emerged: stigma experienced by clients of alcohol and other drug treatment services, stigma experienced by addiction nurses and a lack of awareness of the specialty of addiction nursing itself. Participants overwhelmingly felt that these forms of stigma made addiction nursing less attractive to new entrants, particularly new nurses and posed a threat to the sustainability of the specialty. The findings from this study indicate that urgent attention is required to address stigma towards individuals who use alcohol and other drugs, and the nurses providing care for them. Furthermore, creating awareness of the addiction nursing specialty is paramount to ensure workforce sustainability and to improve care for individuals who use alcohol and other drugs. Beyond addiction nurses, our results indicate that stigma towards other specialties (such as mental health nursing) is a substantive barrier to workforce sustainability.
Background: Qualitative methods analyze contextualized, unstructured data. These methods are time and cost intensive, often resulting in small sample sizes and yielding findings that are complicated to replicate. Integrating natural language processing (NLP) into a qualitative project can increase efficiency through time and cost savings; increase sample sizes; and allow for validation through replication. This study compared the findings, costs, and time spent between a traditional qualitative method (Investigator only) to a method pairing a qualitative investigator with an NLP function (Investigator +NLP). Methods: Using secondary data from a previously published study, the investigators designed an NLP process in Python to yield a corpus, keywords, keyword influence, and the primary topics. A qualitative researcher reviewed and interpreted the output. These findings were compared to the previous study results. Results: Using comparative review, our results closely matched the original findings. The NLP + Investigator method reduced the project time by a minimum of 120 hours and costs by $1,500. Discussion: Qualitative research can evolve by incorporating NLP methods. These methods can increase sample size, reduce project time, and significantly reduce costs. The results of an integrated NLP process create a corpus and code which can be reviewed and verified, thus allowing a replicable, qualitative study. New data can be added over time and analyzed using the same interpretation and identification. Off the shelf qualitative software may be easier to use, but it can be expensive and may not offer a tailored approach or easily interpretable outcomes which further benefits researchers.
This study investigated the recovery process for individuals engaged in treatment for substance use disorders (SUDs) who had co-occurring anxiety and depression. The participants were eight individuals engaged in treatment. The results of a Grounded Theory design and methods revealed the core category and substantive theory, Stumbling toward Vulnerability. Four phases in which the participants progressed in a linear way emerged. The study results have implications for the role of the advance practice psychiatric-mental health nurse in the early assessment of mental illness for clients with SUDs by providing integrated treatment for these individuals, and focusing on health and wellness as a recovery outcome. Based on the findings, hypotheses for further research are recommended.
Objectives: This pilot study explored the feasibility and acceptability of using research as the basis of a therapeutic group intervention for hearing voices/auditory hallucinations.Methods: Using a Participatory Action Research methodology, seven male current or previous residents of a low secure hospital participated in the study. Participants independently conducted research on ideas that were generated and operationalised by the group, on a weekly basis over a seven-month period.Participants focused on developing a new ‘easy to complete’ recovery/resilience measure. The group also themselves developed a qualitative interview schedule, and participated in interviews at the conclusion of the intervention period. In addition to the four participants who engaged throughout the intervention period and contributed towards the analysis of transcripts, three other participant’s (two who disengaged on moving to a new area and one who consented to participate but never attended) took part in post-intervention interviews.Results: The study demonstrated preliminary evidence supporting the utility of a ‘Therapeutic Research Group’ intervention for people who experience distressing voices. In addition to feedback about the positive impact participating in the group had on well-being, participants offered advice on overcoming barriers and increasing the popularity of therapeutic interventions. Participants also developed a new recovery/resilience measure (the M-PART) whose preliminary face validity appears positive.Discussion: Mental health service users/survivors can independently make important contributions to advancing knowledge and improving services. Further research examining whether ‘the conducting of research’ could form the basis of a therapeutic intervention is warranted. Empirical testing of the M-PART measure is also necessary.
Diversity, equity, inclusion, and antiracism (DEI-A) are critical to providing adequate health care to all populations. High-fidelity simulations and role-play scenarios allow students to experience caring for clients from diverse backgrounds. This article discusses the project development and implementation of a DEI-A simulation day placed in a community health clinical course.
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