Aim: The aim of this study was to examine how service user involvement can contribute to the development of interpretative phenomenological analysis methodology and enhance research quality.
Background: Interpretative phenomenological analysis is a qualitative methodology used in nursing research internationally to understand human experiences that are essential to the participants. Service user involvement is requested in nursing research.
Design: We share experiences from 4 years of collaboration (2012-2015) on a mental health promotion project, which involved an advisory team.
Methods: Five research advisors either with a diagnosis or related to a person with severe mental illness constituted the team. They collaborated with the research fellow throughout the entire research process and have co-authored this article. We examined the joint process of analysing the empirical data from interviews. Our analytical discussions were audiotaped, transcribed and subsequently interpreted following the guidelines for good qualitative analysis in interpretative phenomenological analysis studies.
Results: The advisory team became 'the researcher's helping hand'. Multiple perspectives influenced the qualitative analysis, which gave more insightful interpretations of nuances, complexity, richness or ambiguity in the interviewed participants' accounts. The outcome of the service user involvement was increased breadth and depth in findings.
Conclusion: Service user involvement improved the research quality in a nursing research project on mental health promotion. The interpretative element of interpretative phenomenological analysis was enhanced by the emergence of multiple perspectives in the qualitative analysis of the empirical data. We argue that service user involvement and interpretative phenomenological analysis methodology can mutually reinforce each other and strengthen qualitative methodology.
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http://dx.doi.org/10.1111/jan.13093 | DOI Listing |
BMJ Open
January 2025
School of Psychology, Newcastle University, Newcastle upon Tyne, UK
Objective: Shared medical appointments (SMAs) are an innovative care delivery method that provides delivery of clinical care while also supporting self-management. Their usefulness for mental health conditions has only briefly been explored, though early evidence demonstrates their utility for supporting mental health management. Therefore, this study set out to better understand the views that adults with anxiety and depression have towards SMAs as a way of receiving care to support self-management in primary care.
View Article and Find Full Text PDFJMIR Res Protoc
January 2025
Data and Web Science Group, School of Business Informatics and Mathematics, University of Manneim, Mannheim, Germany.
Background: The rapid evolution of large language models (LLMs), such as Bidirectional Encoder Representations from Transformers (BERT; Google) and GPT (OpenAI), has introduced significant advancements in natural language processing. These models are increasingly integrated into various applications, including mental health support. However, the credibility of LLMs in providing reliable and explainable mental health information and support remains underexplored.
View Article and Find Full Text PDFJMIR Res Protoc
January 2025
Division of Services and Interventions Research, National Institute of Mental Health, Bethesda, MD, United States.
Background: Although substantial progress has been made in establishing evidence-based psychosocial clinical interventions and implementation strategies for mental health, translating research into practice-particularly in more accessible, community settings-has been slow.
Objective: This protocol outlines the renewal of the National Institute of Mental Health-funded University of Washington Advanced Laboratories for Accelerating the Reach and Impact of Treatments for Youth and Adults with Mental Illness Center, which draws from human-centered design (HCD) and implementation science to improve clinical interventions and implementation strategies. The Center's second round of funding (2023-2028) focuses on using the Discover, Design and Build, and Test (DDBT) framework to address 3 priority clinical intervention and implementation strategy mechanisms (ie, usability, engagement, and appropriateness), which we identified as challenges to implementation and scalability during the first iteration of the center.
Brain Inj
January 2025
Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia.
Introduction: Magnetic resonance imaging (MRI) has revolutionized our capacity to examine brain alterations in traumatic brain injury (TBI). However, little is known about the level of implementation of MRI techniques in clinical practice in TBI and associated obstacles.
Methods: A diverse set of health professionals completed 19 multiple choice and free text survey questions.
Beyond 5 G and 6 G, communication systems should be able to deliver high throughput, low latency, high dependability, and high energy efficiency services. The creation of hybrid systems that can meet and largely satisfy these needs is promised by the merging of systems based on optical communication and radio frequency (RF). Smart devices may work together to cooperatively train Machine Learning (ML) models in a distributed fashion using Federated Learning (FL), all without disclosing personal information to a central server.
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