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More than a third of the adult population in England have prediabetes, a condition that occurs when glucose levels are higher than normal but not high enough to be diagnosed as diabetes. Between 5 and 10% of people with prediabetes will go on to develop diabetes each year. Lifestyle (diet and activity) interventions have been shown to reduce the risk of prediabetes progressing to Type 2 diabetes. However, in practice high levels of professional support coupled with increasing incidence of prediabetes are not sustainable in their current format. The internet has the potential to provide an alternative means of supporting large numbers of individuals in making lifestyle changes. However, provision of information on its own is not enough to engage individuals to change - additional support via personalised feedback is required to sustain the level of motivation needed for long term behaviour change.
AIM: The investigators hypothesis is that communicating with individuals at high risk of Type 2 diabetes via a web-based lifestyle app will lead to changes in lifestyle behaviours resulting in an improved glycaemic control and reduction in diabetes risk.
METHOD: The study will be conducted over 6 months. Patients identified in GP practice who are at high risk of developing diabetes will be invited to take part in this feasibility study.
Intervention (6 months): This will consist of a web-based lifestyle app and personalised behaviour modification advice delivered via messaging by a dietitian. Participants will also be issued with a pedometer. Data on the dietary intake and activity levels will be collected on the web-based lifestyle app. Contact between the dietitian and participants will consist of weekly messaging to facilitate changes in diet and activity behaviour through motivational and cognitive behavioural strategies.
Blood biochemistry (HbA1c, FBG, LFT's and lipids), BP, weight, BMI, and waist circumference will be measured at 0, 3 and 6 months. The blood test will be taken by a practice nurse at the GP practices and sent off for analysis. A 5 day food diary, well-being and activity questionnaires will be collected at 0, 3 and 6 months by the researcher.
At the end of the intervention period, participants will be invited to attend a focus group to assess participants' perceptions/ease of use and barriers to use of the technology employed to assist behaviour change
Diabetes is a chronic condition. Currently there are 2.9 million people diagnosed with diabetes in the UK, with a further estimated 850,000 people who have the condition but are unaware of this (Diabetes UK, 2011). Due to the ageing population and an increase in obesity, Type 2 diabetes is increasing at an alarming rate. Diabetes UK (2011) predicts that by 2025, the number of people with diabetes will have risen to 5 million. Recent studies indicate that more than a third of the adult population in England have prediabetes (Mainous et al 2014). A condition that occurs when glucose levels are higher than normal but not high enough to be diagnosed as diabetes; between 5 and 10% of people with prediabetes will go on to develop diabetes each year (Tabak et al 2012). Lifestyle interventions aimed at making healthy dietary choices, increasing activity levels and losing excess body weight have been shown to reduce the risk of prediabetes progressing to Type 2 diabetes by 58% (Penn et al., 2013). However, in practice high levels of professional support coupled with increasing incidence of prediabetes are not sustainable in their current format. Synthesis of data from population studies, suggests a potential for less intensive interventions to be both feasible and able to reduce the risk of progressions to diabetes (Johnson et al., 2013). The internet has the potential to provide an alternative means of supporting large numbers of individuals in making diet and activity changes. However, studies highlight that information provision on its own is not enough to engage individuals to change, additional support via personalised feedback is required to sustain the level of motivation needed for long term behaviour change (Estabrook et al., 2005; Nes et al., 2013).
The investigators hypothesis is that communicating with individuals at high risk of Type 2 diabetes via a web-based lifestyle app will lead to changes in lifestyle behaviours (diet and activity) resulting in improved glycaemic control and reduction in diabetes risk. To conduct a rigorous evaluation of this novel intervention will require a large and expensive multi-centre RCT. However, there are several areas of uncertainty which need to be removed before the investigators could conduct such a study with confidence. At the same time, the investigators wish to be reasonably certain that the intervention being tested in the larger trial has a good chance of being successful. Thus the purpose of this present study is to determine the feasibility of this web-based lifestyle app intervention in people with prediabetes hence determining the acceptability, practicability, integration and efficacy of the main study's procedures.
Methods: The study will be conducted over 6 months in general practices. A convenience sample of consenting patients (n=30) registered at GP practices who are at high risk of developing diabetes will be invited to take part in this feasibility study.
Intervention This will consist of a web-based lifestyle app and personalised behaviour modification advice by a registered dietitian delivered via messaging. Participants will be issued with a pedometer and instructed to wear this daily during all wakeful and non-bathing activities. Participants will access web-based material on prediabetes through the lifestyle app. Data on their dietary intake and activity levels will be collected on the web-based lifestyle app, this is password protected. Contact between the dietitian and participants will consist of weekly messaging to facilitate changes in diet and activity behaviour through motivational and cognitive behavioural strategies. Changes in diet and activity levels will be recorded as personalised goals which will be monitored and reviewed by both the participants and dietitian. In addition participants will be encouraged to complete a 5 day food diary using household measures or estimates of food portion sizes or weights (this will include weekend plus 3 week days) at 5 time points during the study (weeks 4, 8, 12, 18 and 22). The dietary data collected on an on-line food diary can be used by participants to self-monitor their progress against dietary recommendations based on guidelines from Diabetes UK and NICE (2012), which will be highlighted on the web platform.
Data Collection Blood biochemistry (HbA1c, FBG, LFT's and lipids), BP, weight, height, BMI and waist circumference will be measured at baseline, 3 and 6 months. The blood test will be taken by a practice nurse at the GP practices and sent off for analysis. Five day food diary (5 consecutive day period including weekend plus 3 week days using a 24hr food diary) and activity questionnaire (plus data for 7 days via the activity tracker) will be collected at baseline, 3 and 6 months. To minimise contamination the first 2 days of activity data will be discarded. A follow up telephone interview will be conducted to enhance accuracy of the food diaries. This method is more responsive to dietary changes than food frequency questionnaires and is recommended for assessing intervention-related dietary change (Harris et al., 2011).
The following questionnaire data will be collected at baseline, 3 and 6 months:
Functional Health Status will be measured using the validated Medical Outcomes Study 36-item Short-Form Survey (SF-36) (Ware and Sherbourne, 1992).
WHO wellbeing index a 5 item questionnaire will monitor changes in psychological well-being in relation to a change in treatment regimen and screen for depression (Hajos et al., 2013).
ICECAP a 5 item questionnaire using a 4 item preference weighted response. It provides a broader measure of well-being for comparing the effectiveness and cost-effectiveness of the increasingly diverse array of health and social care interventions (Al-Janabi et al., 2012).
Self-efficacy diet and exercise questionnaire. The perceived competence for maintaining a healthy diet and regular physical exercise are measured with four items each (Williams and Deci, 2013).
International Physical Activity Questionnaire (IPAQ). Is a validated questionnaire (Craig et al., 2003) consisting of 27 questions. It measures different types of physical activity that people engage in as part of their everyday lives.
Focus group: At the end of the intervention period, data will be collected via 2 focus groups, one from each recruiting GP practice, to assess patient's perceptions/ease of use and barriers to use of the technology employed to assist behaviour change and level of engagement with the technology used in this study. Data will be collected via semi-structured interviews which will be audio- recorded and then transcribed for thematic analysis.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Lifestyle counselling | Experimental | This will consist of a web-based lifestyle app and personalised behaviour modification advice by a registered dietitian delivered via messaging. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Lifestyle counselling | Behavioral | This will consist of a web-based lifestyle app and personalised behaviour modification advice by a registered dietitian delivered via messaging. Participants will be issued with a pedometer and instructed to wear this daily. Participants will access web-based material on prediabetes through the lifestyle app. Contact between the dietitian and participants will consist of weekly messaging to facilitate changes in diet and activity behaviour through motivational and cognitive behavioural strategies. Changes in diet and activity levels will be recorded as personalised goals which will be monitored and reviewed by both the participants and dietitian. In addition participants will be encouraged to complete a food diary to self-monitor their progress against dietary recommendations. |
| Measure | Description | Time Frame |
|---|---|---|
| Participants acceptability of intervention by focus group | Participants will be invited to attend a focus group at the end of the 6 month intervention period | 6 months |
| Measure | Description | Time Frame |
|---|---|---|
| Blood biochemistry (HbA1c, FBG, Lipids, LFT) by blood test | The blood test will be taken by a practice nurse at the GP practices and sent off for analysis as per normal protocol | 6 months |
| Body weight and height to BMI and waist circumference by anthropometric measures |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Avril Collinson, PhD | University of Plymouth | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University of Plymouth | Plymouth | PL6 8BH | United Kingdom |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 23451166 | Background | Penn L, White M, Lindstrom J, den Boer AT, Blaak E, Eriksson JG, Feskens E, Ilanne-Parikka P, Keinanen-Kiukaanniemi SM, Walker M, Mathers JC, Uusitupa M, Tuomilehto J. Importance of weight loss maintenance and risk prediction in the prevention of type 2 diabetes: analysis of European Diabetes Prevention Study RCT. PLoS One. 2013;8(2):e57143. doi: 10.1371/journal.pone.0057143. Epub 2013 Feb 25. | |
| 1593914 |
| Label | URL |
|---|---|
| Preventing type 2 diabetes: risk identification and interventions for individuals at high risk \[PH38\] | View source |
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Participants will be provided with their biochemical results from their GPs and have access to dietary, weight and activity data through the lifestyle app.
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| ID | Term |
|---|---|
| D018149 | Glucose Intolerance |
| ID | Term |
|---|---|
| D006943 | Hyperglycemia |
| D044882 | Glucose Metabolism Disorders |
| D008659 | Metabolic Diseases |
| D009750 | Nutritional and Metabolic Diseases |
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|
Anthropometric measures will be taken by the research assistant |
| 6 months |
| Blood pressure by sphygmomanometer | A practice nurse will take the blood pressure measurements | 6 months |
| Health status, well being, food intake and exercise levels by questionnaires | A number of questionnaires will be used to assess these parameters | 6 months |
| Background |
| Ware JE Jr, Sherbourne CD. The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection. Med Care. 1992 Jun;30(6):473-83. |
| 22998334 | Background | Johnson M, Jones R, Freeman C, Woods HB, Gillett M, Goyder E, Payne N. Can diabetes prevention programmes be translated effectively into real-world settings and still deliver improved outcomes? A synthesis of evidence. Diabet Med. 2013 Jan;30(1):3-15. doi: 10.1111/dme.12018. |
| 25500370 | Background | Mainous AG 3rd, Tanner RJ, Coates TD, Baker R. Prediabetes, elevated iron and all-cause mortality: a cohort study. BMJ Open. 2014 Dec 11;4(12):e006491. doi: 10.1136/bmjopen-2014-006491. |
| 21598064 | Background | Al-Janabi H, Flynn TN, Coast J. Development of a self-report measure of capability wellbeing for adults: the ICECAP-A. Qual Life Res. 2012 Feb;21(1):167-76. doi: 10.1007/s11136-011-9927-2. Epub 2011 May 20. |
| 12900694 | Background | Craig CL, Marshall AL, Sjostrom M, Bauman AE, Booth ML, Ainsworth BE, Pratt M, Ekelund U, Yngve A, Sallis JF, Oja P. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc. 2003 Aug;35(8):1381-95. doi: 10.1249/01.MSS.0000078924.61453.FB. |
| 23072401 | Background | Hajos TR, Pouwer F, Skovlund SE, Den Oudsten BL, Geelhoed-Duijvestijn PH, Tack CJ, Snoek FJ. Psychometric and screening properties of the WHO-5 well-being index in adult outpatients with Type 1 or Type 2 diabetes mellitus. Diabet Med. 2013 Feb;30(2):e63-9. doi: 10.1111/dme.12040. |
| 22683128 | Background | Tabak AG, Herder C, Rathmann W, Brunner EJ, Kivimaki M. Prediabetes: a high-risk state for diabetes development. Lancet. 2012 Jun 16;379(9833):2279-90. doi: 10.1016/S0140-6736(12)60283-9. Epub 2012 Jun 9. |
| 23433735 | Background | Nes AA, Eide H, Kristjansdottir OB, van Dulmen S. Web-based, self-management enhancing interventions with e-diaries and personalized feedback for persons with chronic illness: a tale of three studies. Patient Educ Couns. 2013 Dec;93(3):451-8. doi: 10.1016/j.pec.2013.01.022. Epub 2013 Feb 21. |
| 15919639 | Background | Estabrooks PA, Nelson CC, Xu S, King D, Bayliss EA, Gaglio B, Nutting PA, Glasgow RE. The frequency and behavioral outcomes of goal choices in the self-management of diabetes. Diabetes Educ. 2005 May-Jun;31(3):391-400. doi: 10.1177/0145721705276578. |
| 22030014 | Background | Harris J, Felix L, Miners A, Murray E, Michie S, Ferguson E, Free C, Lock K, Landon J, Edwards P. Adaptive e-learning to improve dietary behaviour: a systematic review and cost-effectiveness analysis. Health Technol Assess. 2011 Oct;15(37):1-160. doi: 10.3310/hta15370. |