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1.
Diabet Med ; 35(12): 1630-1634, 2018 12.
Artigo em Inglês | MEDLINE | ID: mdl-29888553

RESUMO

The language used by healthcare professionals can have a profound impact on how people living with diabetes, and those who care for them, experience their condition and feel about living with it day-to-day. At its best, good use of language, both verbal and written, can lower anxiety, build confidence, educate and help to improve self-care. Conversely, poor communication can be stigmatizing, hurtful and undermining of self-care and can have a detrimental effect on clinical outcomes. The language used in the care of those with diabetes has the power to reinforce negative stereotypes, but it also has the power to promote positive ones. The use of language is controversial and has many perspectives. The development of this position statement aimed to take account of these as well as the current evidence base. A working group, representing people with diabetes and key organizations with an interest in the care of people with diabetes, was established to review the use of language. The work of this group has culminated in this position statement for England. It follows the contribution of Australia and the USA to this important international debate. The group has set out practical examples of language that will encourage positive interactions with those living with diabetes and subsequently promote positive outcomes. These examples are based on a review of the evidence and are supported by a simple set of principles.


Assuntos
Comunicação , Diabetes Mellitus/terapia , Pessoal de Saúde , Idioma , Assistência Centrada no Paciente/normas , Relações Profissional-Paciente , Comitês Consultivos , Barreiras de Comunicação , Inglaterra , Pessoal de Saúde/educação , Pessoal de Saúde/normas , Humanos , Habilidades Sociais , Terminologia como Assunto
2.
BMJ Open ; 11(7): e050713, 2021 07 14.
Artigo em Inglês | MEDLINE | ID: mdl-34261691

RESUMO

INTRODUCTION: Optimising glycaemic control in type 1 diabetes (T1D) remains challenging. Flash glucose monitoring with FreeStyle Libre 2 (FSL2) is a novel alternative to the current standard of care self-monitoring of blood glucose (SMBG). No randomised controlled trials to date have explored the potential benefits of FSL2 in T1D. We aim to assess the impact of FSL2 in people with suboptimal glycaemic control T1D in comparison with SMBG. METHODS: This open-label, multicentre, randomised (via stochastic minimisation), parallel design study conducted at eight UK secondary and primary care centres will aim to recruit 180 people age ≥16 years with T1D for >1 year and glycated haemoglobin (HbA1c) 7.5%-11%. Eligible participants will be randomised to 24 weeks of FSL2 (intervention) or SMBG (control) periods, after 2-week of blinded sensor wear. Participants will be assessed virtually or in-person owing to the COVID-19 pandemic. HbA1c will be measured at baseline, 12 and 24 weeks (primary outcome). Participants will be contacted at 4 and 12 weeks for glucose optimisation. Control participants will wear a blinded sensor during the last 2 weeks. Psychosocial outcomes will be measured at baseline and 24 weeks. Secondary outcomes include sensor-based metrics, insulin doses, adverse events and self-report psychosocial measures. Utility, acceptability, expectations and experience of using FSL2 will be explored. Data on health service resource utilisation will be collected. ANALYSIS: Efficacy analyses will follow intention-to-treat principle. Outcomes will be analysed using analysis of covariance, adjusted for the baseline value of the corresponding outcome, minimisation factors and other known prognostic factors. Both within-trial and life-time economic evaluations, informed by modelling from the perspective of the National Health Service setting, will be performed. ETHICS: The study was approved by Greater Manchester West Research Ethics Committee (reference 19/NW/0081). Informed consent will be sought from all participants. TRIAL REGISTRATION NUMBER: NCT03815006. PROTOCOL VERSION: 4.0 dated 29 June 2020.


Assuntos
COVID-19 , Diabetes Mellitus Tipo 1 , Adolescente , Glicemia , Automonitorização da Glicemia , Diabetes Mellitus Tipo 1/tratamento farmacológico , Humanos , Hipoglicemiantes , Estudos Multicêntricos como Assunto , Pandemias , Ensaios Clínicos Controlados Aleatórios como Assunto , SARS-CoV-2 , Medicina Estatal , Reino Unido
3.
NPJ Digit Med ; 4(1): 138, 2021 Sep 17.
Artigo em Inglês | MEDLINE | ID: mdl-34535755

RESUMO

People with diabetes (PWD) have an increased risk of developing influenza-related complications, including pneumonia, abnormal glycemic events, and hospitalization. Annual influenza vaccination is recommended for PWD, but vaccination rates are suboptimal. The study aimed to increase influenza vaccination rate in people with self-reported diabetes. This study was a prospective, 1:1 randomized controlled trial of a 6-month Digital Diabetes Intervention in U.S. adults with diabetes. The intervention group received monthly messages through an online health platform. The control group received no intervention. Difference in self-reported vaccination rates was tested using multivariable logistic regression controlling for demographics and comorbidities. The study was registered at clinicaltrials.gov: NCT03870997. A total of 10,429 participants reported influenza vaccination status (5158 intervention, mean age (±SD) = 46.8 (11.1), 78.5% female; 5271 control, Mean age (±SD) = 46.7 (11.2), 79.4% female). After a 6-month intervention, 64.2% of the intervention arm reported influenza vaccination, vers us 61.1% in the control arm (diff = 3.1, RR = 1.05, 95% CI [1.02, 1.08], p = 0.0013, number needed to treat = 33 to obtain 1 additional vaccination). Completion of one or more intervention messages was associated with up to an 8% increase in vaccination rate (OR 1.27, 95% CI [1.17, 1.38], p < 0.0001). The intervention improved influenza vaccination rates in PWD, suggesting that leveraging new technology to deliver knowledge and information can improve influenza vaccination rates in high-risk populations to reduce public health burden of influenza. Rapid cycle innovation could maximize the effects of these digital interventions in the future with other populations and vaccines.

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