Support exercise as medicine in health care

Transcription

1 Support exercise as medicine in health care AJ Bouma

2 Exercise as medicine in health care 1. Barrier-belief lifestyle counseling in primary care: a randomized controlled trial of efficacy 2. A cross sectional analysis of motivation and decisionmaking in referrals to lifestyle interventions by primary care general practitioners; a call for guidance 3. The pie=m project; development of a tool to support exercise as medicine in hospital care

3 Study 1: Barrier-belief lifestyle counseling in primary care: a randomized controlled trial of efficacy Adrie Bouma¹, Paul van Wilgen², Koen Lemmink 3, Roy Stewart 4, Arie Dijkstra 3, & Ron Diercks 4 ¹ University of Applied Sciences, The Netherlands ² Transcare, The Netherlands 3 University of Groningen, The Netherlands 4 University Medical Center Groningen, The Netherlands

4 Background Being physically active regularly has many health benefits 1 Positive effects of lifestyle counseling within primary care are proven 2 For improvement of lifestyle interventions there is a need for theory-based behavioral change strategies 3 Learning to cope with barriers seems a key factor in sustained behavioural change 4,5 1 Bredin & Warburton, 2013; Balk et al., Bully et al., Gagliardi et al., 2015; Bully et al., Amireault et al., Bouma et al., 2014

5 Barrier-beliefs stimulating beliefs inhibiting beliefs Bouma AJ, Van Wilgen CP, Dijkstra A. The barrier-belief approach in the counselling of physical activity. Patient Education and Counselling 98 (2015).

6 Research aim To analyze the effects of a barrier-belief counseling intervention on PA, diet, body composition and quality of life outcomes vs. standard lifestyle intervention

7 Methods RCT in a primary care setting Participants: inactive adults (aged 18-70) Conditions: Barrier-belief counseling intervention (n=113) Standard lifestyle intervention (n=91) Non-treated control group (n=36)

8 Barrier-belief Study 1. results counseling intervention (BBCI) Objective: to lower the inhibiting effect of BBs. Individual intervention Tailored to peoples motivation Mini-goals to change behavior Release existing norms on physical activity and diet 1. Design means to reach the goal; 2. Change goals to change barrier-beliefs; 3. Restructure/change barrier-beliefs, and 4. Accept the investments and costs demanded by barrier-beliefs Bouma AJ, Van Wilgen CP, Dijkstra A. The barrier-belief approach in the counselling of physical activity. Patient Education and Counselling 98 (2015)

9 Standard Lifestyle Intervention (SLI) Small group intervention Phase-specific coaching structured to the Trans Theoretical Model Goals according to standards on PA and diet Control group No intervention

10 Methods Outcomes: PA: accelerometer 1 and SQUASH questionnaire 2 - Moderate-to-vigorous PA (MVPA) - Light PA (LPA) - Sedentary behavior (SED) - Total SQUASH activity score (TOTact) Diet (self-report) on frequency of main meals, and amount of snacks, fruit and vegetables on an average week 3 Body composition: BMI, body fat, circumference of waist 4 Quality of life EORTC QLQ-C30 5, LASA 6, Cantril s Ladder 7 1 Plasqui & Westerterp, Wendel-Vos, Schuit, Saris & Kromhout, Bogers, Van Assema, Kester, Westerterp & Dagnelie, Omron, HBF Scott et al., Locke et al., Diener, Emmons, Larsen & Griffin, 1985

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13 Sample N = 204, attrition rate 40%, completers: N = % women, 49 % married, 45 % secondary-vocational educated, 55 % employed Age from 18 to 70 years; M = 50, SD = 13 Fraction with BMI 25 30%; M = 32.5, SD = 5.3 Fraction with BMI 30 50%; M = 35.5, SD = 4.3 Exercise: <30 min 52 % min 28 % >60 min 13 %

14 Results Main time+group interaction effect on MVPA (P =.005); LPA (P =.05); SED (P =.03); QOL (P =.004) Effects on TOTact, diet and body composition were positive however, differences with the SLI appeared non-significant time+group interaction effects: TOTact (P =.68); diet (P =.88); BMI (P =.47); body fat (P =.96); waist (P =.70).

15 Conclusions The BBCI was significantly (p<.01) more effective on PA in the short and the long term compared with the SLI and control group and.. BB-approach seems promising for improvement of active lifestyle interventions Bouma, A. J., van Wilgen, P., Lemmink, K. A., Stewart, R., Dijkstra, A., & Diercks, R. L. (2018). Barrier-belief lifestyle counseling in primary care: A randomized controlled trial of efficacy. Patient education and counseling, 101(12).

16 Study 2: A cross sectional analysis of motivation and decision-making in referrals to lifestyle interventions by primary care general practitioners; a call for guidance Adrie Bouma¹, Paul van Wilgen², Frank Baarveld 3, Arie Dijkstra 3, & Ron Diercks 4 ¹ Hanze University of Applied Sciences, The Netherlands ² Transcare, The Netherlands 3 University of Groningen, The Netherlands 4 University Medical Center Groningen, The Netherlands

17 Background GPs have an important role to play in referral to lifestyle interventions 1,2 GP referrals to lifestyle interventions are not broadly applied 3 Little empirical evidence on factors that influence GPs referral behavior to lifestyle interventions 1. Branca F et al., The challenge of obesity in the WHO european region and the strategies for response: Summary. World Health Organization; Jacobson DM et al., Physical activity counseling in the adult primary care setting: Position statement of the American college of preventive medicine. Am J Prev Med. 2005;29(2): Peterson JA. Get moving! Physical activity counseling in primary care. J Am Acad Nurse Pract. 2007;19(7):

18 Research aims To explore GPs motivation to refer to lifestyle interventions; 2. To investigate the association between GPs own lifestylebehaviors and their referral behavior; 3. To explore patient indicators in the decision-making process of the GPs referral to lifestyle interventions.

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20 Methods Cross-sectional study with a digital survey Participants: 99 Dutch primary care GPs Outcomes: Motivation to refer: beliefs regarding lifestyle interventions Referral behavior: considering referral and self-reported actual referral GP s lifestyle behavior: physical activity, diet, BMI, smoking (self-report) Decision-making regarding referring patients to lifestyle interventions: - Imposed patient indicators; - Spontaneously suggested decisive patient indicators; - Case-based referring (vignettes).

21 Sample N = 134, completers: N = 99 61% women Age (M = 50) Type of practice Solo 22% Duo 22% Health centre 33% Missing 23% Working status Practice owner 35% Locum GP 2% In employment 65% Years of practice (M = 20)

22 Results 40% - not motivated for lifestyle interventions, based on their attitudes, social norms, and perceived behavioral control 60% - perceived difficulties referring patients to lifestyle interventions 28% - considered briefly in all patients whether they were eligible for referral 81% - indicated having the possibility to refer 52% - regularly referred patients to a lifestyle intervention in the last year

23 Results GPs refer behavior significantly related to their perceived subjective norm and perceived behavioral control GPs referral behavior significantly related to their own physical activity and diet behavior Most decisive patient indicators for referral: somatic risk factors; perception of patient s motivation to change their lifestyle; socio-demographic factors (age, educational level, ethnicity).

24 Conclusions Increase social support: more attention by national professional associations for GPs Increase perceived behavioral control: formal procedure for referral to lifestyle interventions integration of healthcare professionals with GPs practice For a better referral in practice: develop a E=M tool to - indicate which patients are eligible for lifestyle referral; - identify patient s lifestyle behavior and motivation; - provide information about eligible programs, also for specific groups in the vicinity (e.g. age-groups, ethnicity-groups). Bouma AJ, Van Wilgen P, Baarveld F, Diercks RL, Dijkstra A. A cross sectional analysis of motivation and decision-making in referrals to lifestyle interventions by primary care general practitioners; A call for guidance. American Journal of Lifestyle Medicine

25 Study 3: The pie=m project; development of a tool to support exercise as medicine in hospital care Bouma AJ 1,2, Nassau van F 3, Nauta J 3, Krops LA 1, Ploeg van der HP 3, Jong de J 2, Stevens M 4, Schwertz MA 5, Zwerver J 6, Van den Akker-Scheek I 4,6, Diercks RL 4,6, Verhagen EALM 3, PIE=M consortium, Woude van der LHV 7, Dekker R 1,6. 1 University of Groningen, University Medical Center Groningen, Department of Rehabilitation Medicine, Groningen, The Netherlands; 2 Institute of Sports Studies, Hanze University of Applied Sciences, Groningen, The Netherlands; 3 Department of Public and Occupational Health, Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands; 4 University of Groningen, University Medical Center Groningen, Department of Orthopedic Surgery, The Netherlands; 5 University of Groningen, University Medical Center Groningen, Department of Genetics, The Netherlands; 6 University of Groningen, University Medical Center Groningen, Centre of Sports Medicine, The Netherlands; 7 University of Groningen, University Medical Center Groningen, Center for Human Movement Sciences, Groningen, The Netherlands.

26 Background The prescription of physical activity in clinical care has been pleaded worldwide through the exercise is medicine (E=M) paradigm 1. E=M currently has no position in general routine hospital care 2. 1 Cowan RE. (2016) Exercise Is Medicine Initiative: Physical Activity as a Vital Sign and Prescription in Adult Rehabilitation Practice. Arch Phys Med Rehabil 97:S Glasgow RE, Vogt TM, Boles SM. (1999) Evaluating the public health impact of health promotion interventions: the RE-AIM framework. Am J Public Health 89:

27 Research aims 1. To perform an in-depth study of the current implementation status of E=M in routine clinical care. 2. To develop a tool that assists and facilitates an individually tailored E=M advice for patients on physical activity and type of intervention. 3. To evaluate the feasibility of implementing E=M in different clinical departments of two Dutch hospitals.

28 Methods 1. Quantitative and qualitative research to study the current implementation status of E=M in clinical care as well as its facilitators and barriers to implementation among clinicians and hospital managers. 2. An E=M tool will be developed, using a prediction model, based on individual determinants of physical activity behavior and motivation, relative to existing standards and local big data. 3. A pilot-study will be conducted with a process evaluation, which will integrate the tool in routine care.

29 Results 1. Insight in the current implementation status of E=M and in factors that influence the actual E=M implementation 2. E=M tool providing a tailored E=M prescription for patients as part of clinical care 3. Implementation strategy of the E=M tool for clinical practice.

30 Figure: E=M tool flow diagram

31 Conclusions This project will: Contribute to the implementation of E=M; Support the decision making of lifestyle referral of clinicians; Provide insights which can be used to assist in implementing active lifestyle prescriptions in the medical curriculum.

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