Dataset Information

Technology-based counselling in dementia (TeCoDem): study protocol of a mixed-methods systematic review with qualitative comparative analysis and meta-analysis.

ABSTRACT:

Introduction

Information technology can enhance timely and individual support for people with dementia and informal carers. There is some evidence that people with dementia and informal carers would benefit from technology-based counselling. However, it remains unclear which features of those interventions relate to beneficial outcomes and which aspects are necessary for a successful implementation. Therefore, the primary objectives are: (1) to identify conditions of successful implementation of technology-based counselling interventions in dementia and (2) to investigate the effectiveness of those interventions.

Methods and analysis

We will conduct a mixed-methods systematic review. The first primary objective requires evidence from various study designs addressing aspects on effective and non-effective implementation of technology-based counselling. This could be telephone-based, web-based or mobile-based interventions for people with dementia and informal carers. For the second primary objective, randomised controlled trials (RCTs) dealing with any outcomes will be included. Year of publication and language will not be restricted. We will search CINAHL, Cochrane Library, MEDLINE, PsycINFO and Web of Science up to April 2021. Additionally, we will perform web searching and citation tracking. To achieve the first primary objective, a Qualitative Comparative Analysis (QCA) will be conducted. The QCA enables us to identify necessary or sufficient components for a successful implementation. To reach the second primary objective, a meta-analysis will be performed with respect to potential clinical and statistical heterogeneity of RCTs. The revised Risk of Bias tool 2.0 will be used to check the risk of bias in RCTs. For all other study designs, the Mixed Method Appraisal Tool will be used.

Ethics and dissemination

Ethics approval is not required for this review. We will disseminate our findings through scientific and non-scientific journal articles and conference presentations as well as formats directed to the public and decision-makers in healthcare.

Prospero registration number

CRD42021245473.

SUBMITTER: Hirt J

PROVIDER: S-EPMC8655568 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature

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Publications

Technology-based counselling in dementia (TeCoDem): study protocol of a mixed-methods systematic review with qualitative comparative analysis and meta-analysis.

Hirt Julian J Langer Gero G Wilde Fabian F Bauernschmidt Dorothee D Meyer Gabriele G Bieber Anja A

BMJ open 20211208 12

<h4>Introduction</h4>Information technology can enhance timely and individual support for people with dementia and informal carers. There is some evidence that people with dementia and informal carers would benefit from technology-based counselling. However, it remains unclear which features of those interventions relate to beneficial outcomes and which aspects are necessary for a successful implementation. Therefore, the primary objectives are: (1) to identify conditions of successful implement ...[more]

PMID: 34880025

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Project description:IntroductionInformal carers support persons with dementia to live at home, even with deteriorating physical, social and cognitive issues. This study aims to examine the experiences and impact of Assistive Technology (AT) on carers, providing care for a person with dementia.MethodsThis is an explanatory sequential mixed methods study. The quantitative phase was an online and postal survey using the Carers Assistive Technology Experience Questionnaire and Short Form-12 (SF-12) questionnaire, with carers of persons with dementia in the UK, who used AT. The qualitative phase involved in-depth telephone interviews with a purposive sample of survey respondents and was analysed using hermeneutic phenomenology to develop, compare and explain the findings of the survey.ResultsThe survey included data from 201 carers. Smartphones (45.5%) and tablet computers (45.0%) were the most frequently used AT. Multiple AT were used in the care of persons with dementia predominantly for safety (78.5%), communication (66.0%), and reminders (62.5%). The SF-12 indicated that carers in the 46-65 age group and carers who were not extremely satisfied with AT had lower mental component scores whilst carers who lived with the person with dementia and older carers had lower physical component scores. Twenty-three carers participated in the interviews, and 5 themes with 14 sub-themes were identified. The interviews helped confirm data from the survey on the impact of AT on the physical, mental and social wellbeing of the carers. It helped describe reasons for satisfaction with AT; how AT was used in daily life and strengthened caring relationships and how wider support systems enhanced the care of a person with dementia using AT.ConclusionsThis study describes the use of AT in the real-world context. AT supplements the care provided to people with dementia in the community. Appropriate use, access to AT and abilities of the carer can enhance the support provided through AT to both carers and the person with dementia.

Project description:BackgroundCommunication is a critical component of the patient-provider relationship; however, limited research exists on the role of nonverbal communication. Virtual human training is an informatics-based educational strategy that offers various benefits in communication skill training directed at providers. Recent informatics-based interventions aimed at improving communication have mainly focused on verbal communication, yet research is needed to better understand how virtual humans can improve verbal and nonverbal communication and further elucidate the patient-provider dyad.ObjectiveThe purpose of this study is to enhance a conceptual model that incorporates technology to examine verbal and nonverbal components of communication and develop a nonverbal assessment that will be included in the virtual simulation for further testing.MethodsThis study will consist of a multistage mixed methods design, including convergent and exploratory sequential components. A convergent mixed methods study will be conducted to examine the mediating effects of nonverbal communication. Quantitative (eg, MPathic game scores, Kinect nonverbal data, objective structured clinical examination communication score, and Roter Interaction Analysis System and Facial Action Coding System coding of video) and qualitative data (eg, video recordings of MPathic-virtual reality [VR] interventions and student reflections) will be collected simultaneously. Data will be merged to determine the most crucial components of nonverbal behavior in human-computer interaction. An exploratory sequential design will proceed, consisting of a grounded theory qualitative phase. Using theoretical, purposeful sampling, interviews will be conducted with oncology providers probing intentional nonverbal behaviors. The qualitative findings will aid the development of a nonverbal communication model that will be included in a virtual human. The subsequent quantitative strand will incorporate and validate a new automated nonverbal communication behavior assessment into the virtual human simulation, MPathic-VR, by assessing interrater reliability, code interactions, and dyadic data analysis by comparing Kinect responses (system recorded) to manually scored records for specific nonverbal behaviors. Data will be integrated using building integration to develop the automated nonverbal communication behavior assessment and conduct a quality check of these nonverbal features.ResultsSecondary data from the MPathic-VR randomized controlled trial data set (210 medical students and 840 video recordings of interactions) were analyzed in the first part of this study. Results showed differential experiences by performance in the intervention group. Following the analysis of the convergent design, participants consisting of medical providers (n=30) will be recruited for the qualitative phase of the subsequent exploratory sequential design. We plan to complete data collection by July 2023 to analyze and integrate these findings.ConclusionsThe results from this study contribute to the improvement of patient-provider communication, both verbal and nonverbal, including the dissemination of health information and health outcomes for patients. Further, this research aims to transfer to various topical areas, including medication safety, informed consent processes, patient instructions, and treatment adherence between patients and providers.International registered report identifier (irrid)DERR1-10.2196/46601.

Project description:IntroductionInformal caregivers provide the majority of care to individuals with chronic health conditions, benefiting the care recipient and reducing use of formal care services. However, providing informal care negatively impacts the mental health of many caregivers. E-mental health interventions have emerged as a way to provide accessible mental healthcare to caregivers. Much attention has been given to reviewing the effectiveness and efficacy of such interventions, however, factors related to implementation have received less consideration. Therefore, this mixed-methods systematic review will aim to examine factors associated with the effectiveness and implementation of e-mental health interventions for caregivers.Methods and analysisEligible studies published since 1 January 2007 will be searched for in several electronic databases (CINAHL Plus with Full Text, the Cochrane Library, EMBASE, PsycINFO, PubMed and Web of Science), clinical trial registries and OpenGrey, with all screening steps conducted by two independent reviewers. Studies will be included if they focus on the implementation or effectiveness of e-mental health interventions designed for informal adult caregivers of adults with cancer, heart disease, stroke, diabetes, dementia or chronic obstructive pulmonary disease. Pragmatic randomised controlled trials quantitatively reporting on caregiver anxiety, depression, psychological distress or stress will be used for a qualitative comparative analysis to identify combinations of conditions that result in effective interventions. Qualitative and quantitative data on implementation of e-mental health interventions for caregivers will be integrated in a thematic synthesis to identify barriers and facilitators to implementation. These results will inform future development and implementation planning of e-mental health interventions for caregivers.Ethics and disseminationEthical approval is not required for this study as no primary data will be collected. Results will be disseminated in the form of a scientific publication and presentations at academic conferences and plain language summaries for various stakeholders.Prospero registration numberCRD42020155727.

Project description:IntroductionDue to the increasing number of persons with dementia, the need for family and professional support is growing. Counselling services aim to support family dementia caregivers and the use of information and communication technology may improve accessibility to counselling. The effectiveness of technology-based counselling in dementia remains unclear so far. Few randomised controlled trials have been conducted assessing heterogeneous outcomes. Theoretical underpinnings for the development and evaluation of these complex interventions were lacking in most cases. We therefore aim to formulate an initial programme theory of a technology-assisted counselling intervention for family dementia caregivers and to create the data basis for the consensus process of a core outcome set.Methods and analysisThe methodological approaches for developing a programme theory and a core outcome set will be integrated. In a scoping review, data on the characteristics, theoretical foundations of counselling interventions and outcomes of clinical studies will be collected. The lifeworld perception of relevant stakeholders on the importance of counselling in family caregiving will be explored in a phenomenological substudy using semistructured interviews. The synthesis of data from the literature review and the qualitative substudy will be performed by developing a logic model. Mechanisms of action and assumed causal relationships are explicated in the elements of programme theory (theory of change, outcomes chain and theory of action). An initial programme theory is then formulated. In addition, a 'long list' of outcomes and assessment instruments will be compiled.Ethics and disseminationThe ethics committee of the Medical Faculty of the Martin Luther University Halle-Wittenberg approved the study protocol (no. 2023-093).Findings will be reported to participants and the funding organisation and disseminated in peer-reviewed journals and at national and international conferences.Trial registration numberThe ProCOS (Development and evaluation of a technology-assissted counselling intervention for family caregivers of persons with dementia - Programme theory and preparation of a core outcome set) project is registered with the Core Outcome Measures in Effectiveness Trials initiative (https://www.comet-initiative.org/Studies/Details/2884).

Project description:BackgroundPediatric asthma is a heterogeneous disease; however, current characterizations of its subtypes are limited. Machine learning (ML) methods are well-suited for identifying subtypes. In particular, deep neural networks can learn patient representations by leveraging longitudinal information captured in electronic health records (EHRs) while considering future outcomes. However, the traditional approach for subtype analysis requires large amounts of EHR data, which may contain protected health information causing potential concerns regarding patient privacy. Federated learning is the key technology to address privacy concerns while preserving the accuracy and performance of ML algorithms. Federated learning could enable multisite development and implementation of ML algorithms to facilitate the translation of artificial intelligence into clinical practice.ObjectiveThe aim of this study is to develop a research protocol for implementation of federated ML across a large clinical research network to identify and discover pediatric asthma subtypes and their progression over time.MethodsThis mixed methods study uses data and clinicians from the OneFlorida+ clinical research network, which is a large regional network covering linked and longitudinal patient-level real-world data (RWD) of over 20 million patients from Florida, Georgia, and Alabama in the United States. To characterize the subtypes, we will use OneFlorida+ data from 2011 to 2023 and develop a research-grade pediatric asthma computable phenotype and clinical natural language processing pipeline to identify pediatric patients with asthma aged 2-18 years. We will then apply federated learning to characterize pediatric asthma subtypes and their temporal progression. Using the Promoting Action on Research Implementation in Health Services framework, we will conduct focus groups with practicing pediatric asthma clinicians within the OneFlorida+ network to investigate the clinical utility of the subtypes. With a user-centered design, we will create prototypes to visualize the subtypes in the EHR to best assist with the clinical management of children with asthma.ResultsOneFlorida+ data from 2011 to 2023 have been collected for 411,628 patients aged 2-18 years along with 11,156,148 clinical notes. We expect to complete the computable phenotyping within the first year of the project, followed by subtyping during the second and third years, and then will perform the focus groups and establish the user-centered design in the fourth and fifth years of the project.ConclusionsPediatric asthma subtypes incorporating RWD from diverse populations could improve patient outcomes by moving the field closer to precision pediatric asthma care. Our privacy-preserving federated learning methodology and qualitative implementation work will address several challenges of applying ML to large, multicenter RWD data.International registered report identifier (irrid)DERR1-10.2196/57981.

Dataset Information

Technology-based counselling in dementia (TeCoDem): study protocol of a mixed-methods systematic review with qualitative comparative analysis and meta-analysis.

Introduction

Methods and analysis

Ethics and dissemination

Prospero registration number

Publications

Technology-based counselling in dementia (TeCoDem): study protocol of a mixed-methods systematic review with qualitative comparative analysis and meta-analysis.

Similar Datasets

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