Effectiveness of a Fitbit Based Sleep and Physical Activity Intervention in an Early Intervention Psychosis (EIP) Service

Griffiths, Chris; Silva, Ksenija da; Hina, Farah; Jugon, Sue; Willis, Gemma; Yardley, Samantha; Walker, Jonathon; Kelbrick, Marlene

doi:10.4236/ojpsych.2022.122015

Cited by 7 publications

(5 citation statements)

References 52 publications

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“…Prediabetes: All patients were given lifestyle modification advice, as well as offered other interventions such as walking groups and the offer to participate in our Welltrack study (use of Fitbit to improve activity and well-being). 31,32 Patients were also referred to a GP for further lifestyle modification, and one patient enrolled in the NHS Diabetes Prevention Programme. One patient participated in the Well-track study.…”

Section: Interventions Offered To Those With Prediabetes and Diabetesmentioning

confidence: 99%

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The over‐35s: prediabetes and diabetes within an EIP service

Bandgar,

Kelbrick,

Paduret

et al. 2024

Prog Neurol Psychiatry

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Little is known about the rates of prediabetes and diabetes in those over the age of 35 years in UK early intervention for psychosis (EIP) services. In this article, the authors discuss their retrospective case note service evaluation of patients within an NHS EIP service where they evaluate the prevalence of prediabetes and diabetes in the ‘over‐35’ cohort, its monitoring and management. The ‘over‐35’ cohort represented a third of the EIP caseload and is a high‐risk group for prediabetes and diabetes. More research and innovative strategies are needed in terms of both lifestyle and pharmacological interventions in this patient population to reduce the risk of developing, and improve management of type 2 diabetes.

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Section: Interventions Offered To Those With Prediabetes and Diabetesmentioning

confidence: 99%

“…In total five of six patients with diabetes had either already participated in the Well-track (Fitbit) 31,32 study or had started to participate.…”

Section: Interventions Offered To Those With Prediabetes and Diabetesmentioning

confidence: 99%

The over‐35s: prediabetes and diabetes within an EIP service

Bandgar,

Kelbrick,

Paduret

et al. 2024

Prog Neurol Psychiatry

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“…To seek to address sleep, physical activity, and wellbeing of community-based depression and EIP service patients, a physical activity and sleep hygiene intervention (Well-Track) has been developed and tested over a period of four years. Based on our previous findings that Well-Track improved participants' physical activity, sleep quality, motivation, self-awareness, daily/weekly routines, wellbeing, healthy lifestyles, and quality of life, and reduced anxiety and depression levels [51] [52] [53] [54] [55], our hypothesis is that it will have a positive impact on depression, mental wellbeing, insomnia, and body weight in both EIP and ARMS patients.…”

Section: The Nhs Long Term Plan and The Mental Health Implementation ...mentioning

confidence: 99%

“Well-Track”: Fitbit Based Physical Activity and Sleep Hygiene Intervention for Early Intervention in Psychosis (EIP) and At-Risk Mental State (ARMS) Service Patients

Griffiths,

da Silva,

Jugon

et al. 2023

OJPsych

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Background: Compared to the general population, people who are at a high risk of or experience severe mental illness (SMI) such as psychosis, are more likely to have low levels of physical activity, high levels of sedentary behaviour, and sleep problems. Intervention: The Well-Track intervention comprises a wearable activity and sleep tracker (Fitbit); one session with mental health service staff providing physical activity and sleep hygiene advice; a brief motivational interview; completing a goal setting workbook; and one or two further engagement, feedback and discussion sessions. Participants: Twenty-four participants using an early intervention in psychosis (EIP) or at-risk mental state (ARMS) service completed an eight-week, three session intervention (14 males and 10 females), with an age range of 18 -61, and average age of 27.75 years. Methods: An open-label patient cohort design with no control group. Pre-intervention, 4-week and 8-week intervention assessments using participant self-report measures: Patient Health Questionnaire (PHQ-9) (depression), Warwick-Edinburgh Mental Wellbeing Scale (WEMWBS), and Sleep Conditioning Index (SCI); and clinician measurement of body weight. Results: Mean scores showed a significant improvement in PHQ-9 from 9.29 (SD 5.89) to 5.58 (SD 3.68) at 4 weeks and to 5.83 (SD 4.40) at 8 weeks, with large effect sizes. For those who met a diagnosis of depression at baseline, at 4 week follow-up seven participants (26%) experienced remission and nine (33%) reliable improvement, and at 8 week follow-up four (21%) experienced remission and seven (37%) reliable improvement.

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“…Literature [8] study investigated the means of improving students' physical fitness and health level in various aspects to different degrees; literature [9] analysed the reasons for the gradual increase of students' vision and obesity problems, which mainly include the lack of attention to physical exercise, the lack of physical education, and insufficient financial investment; literature [10] analysed the ways of improving students' physical fitness for individual interventions, which mainly include family interventions, social interventions and school interventions. three aspects; Literature [11] analysed the method of student improvement from three dimensions of skill, form and spirit; Literature [12] proposed a method of student fitness testing that integrates the four factors of physical fitness, recreational sports, physical dance and physical exercise; Literature [13] investigated real-time fitness testing and status analysis using the WeChat mini-programme as a medium and the platform of individual students' physical fitness and daily exercise; Literature [14] used the "Three Precision" applet to accurately analyse student health data. To sum up the research results of domestic and foreign students' physical health intervention, the current theoretical research tends to be mature, the combination of network platforms and students' physical individual intervention is only in the stage of qualitative analysis, and there is a lack of quantitative analysis [15], especially the combination of data mining, artificial intelligence, small programs and other technologies for students' physical individual intervention, there are inaccuracies in the analysis and evaluation of the problem of strong subjectivity and other issues [16].…”

Section: Introductionmentioning

confidence: 99%

Individual Intervention and Assessment of Students' Physical Fitness Based on the "Three Precision" Applet and Mixed Strategy Optimised CNN Networks

Zhang

2024

EAI Endorsed Trans Perv Health Tech

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With the development of network technology and intelligent application platforms, the "Three Precision" applet as a method of individual intervention for students' physical fitness can not only enable students to obtain the improvement of physical fitness and lifelong sports habits, but also establish a new bridge of cooperation between home and school. The analysis method of student physical fitness individual intervention assessment is affected by a variety of factors such as the framework design of the WeChat applet platform and the subjectivity of the intervention, which leads to the inefficiency of the student physical fitness individual intervention assessment method. To address this problem, we analyse the mode and content of students' physical fitness individual intervention based on the "Three Precision" applet, extract the feature vectors of students' physical fitness individual intervention, construct a system of students' physical fitness individual intervention assessment indexes, and establish a method of students' physical fitness individual intervention assessment based on big data technology and WeChat applet by combining the mushroom propagation optimization algorithm and convolutional neural network. Individual intervention assessment method based on big data technology and WeChat applet. The effectiveness and robustness of the proposed method are verified by using the data recorded in the "Three Precision" applet as the input data of the model. The results show that the proposed method meets the real-time requirements and improves the prediction accuracy of the individual intervention assessment method, which significantly improves the efficiency of the individual intervention assessment of students' physical fitness.

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Effectiveness of a Fitbit Based Sleep and Physical Activity Intervention in an Early Intervention Psychosis (EIP) Service

Cited by 7 publications

References 52 publications

The over‐35s: prediabetes and diabetes within an EIP service

The over‐35s: prediabetes and diabetes within an EIP service

“Well-Track”: Fitbit Based Physical Activity and Sleep Hygiene Intervention for Early Intervention in Psychosis (EIP) and At-Risk Mental State (ARMS) Service Patients

Individual Intervention and Assessment of Students' Physical Fitness Based on the "Three Precision" Applet and Mixed Strategy Optimised CNN Networks

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