Health behaviour change among users of NHS Health Trainer Services Benjamin Gardner1, James Cane1, Nichola Rumsey2 & Susan Michie1 1: University College London; 2: University of the West of England 3rd July 2012 This work was undertaken as part of a BPS DHP consultancy to the Department of Health (2003-2010) Evaluations of the NHS Health Trainer Service • 2007-09: data from hub leads (‘hub reports’) • Yearly audits of workforce and clients – Who are the HTs? – Is the workforce growing? – Who is using the HT service? (Wilkinson et al, 2007; D Smith et al, 2008) • 2009: DCRS data • Evaluation of service effectiveness • Does behaviour change among users of the HT service? Questions 1) Who uses the HT service? - Are we reaching ‘hard to reach’ clients? 2) Does (diet and activity) behaviour change following use of HT service? 3) Do all clients benefit equally? Data • Drawn from DCRS – Period: 1st April 2008 – 31st March 2009 – Data extracted from DCRS v2.4 by BPCSSA • Final extraction for DCRS report: December 2009 • Final extraction for paper mid-2010 – Data recording on DCRS then non-compulsory • At start of time period, estimated from hub report that 62% of HTSs entered data into DCRS • Paper accepted for publication in Dec 2011 Data availability Drop-out bias? • Setting PHPs: – White clients (35%) and Asian clients (30%) more likely to set PHPs than Black clients (25%) – More PHPs set in least deprived quintile (42%) than others (~36%) • Pre-post HTS data availability: – White clients (35%) more likely to have pre-post than Asian (30%) or Black clients (27%) – More data available in least deprived quintile (45%) than others (~29%) Measures Pre- and post-HTS - Baseline demographics - Pre- and post-HTS: • Behaviour measures – BMI (height, weight) – Self-reported behaviour (diet [snacks, fruit & veg], activity [moderate/intensive sessions]) Results 1) Who uses the HTS? • 3503 female (79%) (UK population, 2001 = 51% female) • Typical age 36-45 years (22.4%) (UK 2001 = 19%) • Deprivation: – – – – – Q1 (most deprived): Q2 Q3 Q4 Q5 (least deprived) 1836 (43.2%) 1093 (25.7%) 688 (16.2%) 405 (9.5%) 230 (5.4%) Results 1) Who uses the HTS? • Ethnicity: – – – – White Asian Black Mixed or other (UK 2001 = 93% White) 3647 (83.2%) 485 (11.1%) 175 (4.0%) 79 (1.8%) Results 1) Who uses the HTS – and for what purpose? • Weight status: – Obese – Overweight – Normal weight 2717 (72.3%) 824 (22.4%) 218 (5.8%) • PHP focus: – Diet – Physical activity 3346 (75.7%) 1072 (24.3%) Results 2) Diet change following diet PHP achievement Outcome Number of clients Pre-HTS mean Post-HTS mean % change Daily fruit & veg (portions) 2376 3.08 5.23 70% increase No. of daily fried snacks 1869 1.99 0.79 60% decrease BMI 3164 34.33 32.45 6% decrease Results 2) Activity change following activity PHP achievement Outcome N Pre-HTS mean Post-HTS mean % change Weekly moderate sessions 921 3.06 4.77 56% increase Weekly intensive sessions 637 0.63 1.71 171% increase BMI 595 32.46 31.24 4% decrease 3) Do all clients benefit equally? • Ethnicity or deprivation differences? – All clients • Deprivation & BMI: – Less BMI reduction in most deprived quintile vs all others (0.28 BMI points) – Diet: • Deprivation & BMI: – Less BMI reduction in most deprived quintile vs all others (0.24 BMI points) • Ethnicity & BMI: – Less BMI reduction in Asian versus White clients (0.55 BMI points) Conclusions • HTS is reaching disadvantaged clients and changing behaviour • Effects similar across demographic groups – But more PHPs set and more data recorded in less deprived groups Challenges and recommendations • Missing data problematic – Pre- and post-HTS behaviour data essential • Reliance on self-report – May overestimate behaviour change – Ideally need objective measures, e.g. biochemical verification, objectively measured weight • Whether data self-report or objective should be recorded Challenges and recommendations • Need to ensure continued fidelity to HTS as originally devised • Qualitative data needed – Quantitative data allows for ‘birds eye view’ group-level analyses – Qualitative data engages with contextualised individual experiences – Would reveal ‘real-life’ benefits of HTS Challenges and recommendations • Qualitative data needed – Brief interviews with clients/feedback from clients? • How do clients feel they have benefitted? – Written case studies? • Description of individual client’s journey – Need a DCRS repository for qualitative evidence storage Thank you Acknowledgements: Janet Andelin and Rachel Carse, Dept of Health Jan Smith, CORE, UCL Ertan Fidan & David Hopkinson, Birmingham Primary Care Shared Services Agency For a copy of the published paper, contact me at [email protected]
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