Objectives: Digital interventions can change patients' experiences of managing their health, either creating additional burden or improving their experience of healthcare. This qualitative study aimed to explore perceived burdens and benefits for patients using a digital self-management intervention for reducing high blood pressure. A secondary aim was to further our understanding of how best to capture burdens and benefits when evaluating health interventions.
Design: Inductive qualitative process study nested in a randomised controlled trial.
Setting: Primary Care in the UK.
Participants: 35 participants taking antihypertensive medication and with uncontrolled blood pressure at baseline participated in semistructured telephone interviews.
Intervention: Digital self-management intervention to support blood pressure self-monitoring and medication change when recommended by the healthcare professional.
Analysis: Data were analysed using inductive thematic analysis with techniques from grounded theory.
Results: Seven themes were developed which reflected perceived burdens and benefits of using the intervention, including worry about health, uncertainty about self-monitoring and reassurance. The analysis showed how beliefs about their condition and treatment appeared to influence participants' appraisal of the value of the intervention. This suggested that considering illness and treatment perceptions in Burden of Treatment theory could further our understanding of how individuals appraise the personal costs and benefits of self-managing their health.
Conclusions: Patients' appraisal of the burden or benefit of using a complex self-management intervention seemed to be influenced by experiences within the intervention (such as perceived availability of support) and beliefs about their condition and treatment (such as perceived control and risk of side effects). Developing our ability to adequately capture these salient burdens and benefits for patients could help enhance evaluation of self-management interventions in the future. Many participants perceived important benefits from using the intervention, highlighting the need for theory to recognise that engaging in self-management can include positive as well as negative aspects.
Trial Registration Number: ISRCTN13790648; Pre-results.
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http://dx.doi.org/10.1136/bmjopen-2017-020843 | DOI Listing |
Rev Alerg Mex
December 2024
Master's in economics, HS Pharmacoeconomic Research, Mexico City, Mexico.
Objective: to perform a cost-effectiveness analysis of asthma treatment with budesonide/formoterol against other treatment options used at Mexico's National Institute for Respiratory Diseases.
Methods: A complete economic evaluation of cost-effectiveness from a public health perspective, comparing the use of budesonide/formoterol as maintenance therapy with fluticasone/vilanterol in 103 female asthma patients managed at INER between 2015 and 2021.
Results: Average cost per patient was $743.
World J Pediatr
January 2025
Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 200025, China.
Background: Type 2 diabetes mellitus (T2DM) poses an escalating public health challenge among adolescents and young adults worldwide. Despite the rising incidence, comprehensive data on the burden and trends of T2DM in this demographic remain scarce. This study aims to evaluate the burden of T2DM among individuals aged 10-24 years globally, regionally, and nationally from 1990 to 2021.
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New York University Grossman School of Medicine, New York, NY, USA.
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December 2024
Douglas Mental Health University Institute, Montreal, QC, Canada.
Background: White matter hyperintensities (WMHs) are increasingly recognized for their role in cognitive decline and the progression of neurodegenerative conditions including Alzheimer's disease (AD). Despite advances in imaging technologies, the exact contribution of WMHs to disease processes remains a subject of ongoing research. This study aims to apply machine learning approaches to determine critical features of AD-related neuropathologies in vivo.
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December 2024
National Institutes of Health (NIH)/National Institute of Neurological Disorders and Stroke (NINDS), Bethesda, MD, USA.
Background: AD/ADRD diseases currently impact more than 6 million people in the US. Rare forms of AD/ADRD are caused directly and unambiguously by genetic mutations. However, most AD/ADRD burden is complex in etiology and thought to result from an interplay among multiple incompletely understood genetic, biochemical, lifestyle, environmental and psychosocial risk factors.
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