Support exercise as medicine in health care

Support exercise as medicine in health care

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

decision-making 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

Study 1: Barrier-belief lifestyle

counseling in primary care: a

randomized controlled trial of efficacy

Adrie Bouma¹, Paul van Wilgen², Koen Lemmink3_{, Roy Stewart}4_,

Arie Dijkstra3_{, & Ron Diercks}4

¹ University of Applied Sciences, The Netherlands ² Transcare, The Netherlands

3 _{University of Groningen, The Netherlands}

Background

• Being physically active regularly has many health benefits1 • Positive effects of lifestyle counseling within primary care are

proven2

• For improvement of lifestyle interventions there is a need for theory-based behavioral change strategies3

• Learning to cope with barriers seems a key factor in sustained behavioural change4,5

1_{Bredin & Warburton, 2013; Balk et al., 2015} 2_{Bully et al., 2015}

3_{Gagliardi et al., 2015; Bully et al., 2015} 4_{Amireault et al., 2013}

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).

stimulating

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

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)

Study 1. results

Barrier-belief 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) 129-136.

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

Methods

Outcomes:

 PA: accelerometer1 and SQUASH questionnaire2

- 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 week3

 Body composition: BMI, body fat, circumference of waist4  Quality of life EORTC QLQ-C305, LASA6, Cantril’s Ladder7

1_{Plasqui & Westerterp, 2007}

2_{Wendel-Vos, Schuit, Saris & Kromhout, 2003}

3_{Bogers, Van Assema, Kester, Westerterp & Dagnelie, 2004} 4_{Omron, HBF 511}

5_{Scott et al., 2008} 6_{Locke et al., 2007}

Sample

• N = 204, attrition rate 40%, completers: N = 123

• 61 % 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 % • 30-60 min 28 % • >60 min 13 %

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).

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

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 Baarveld3_{, Arie}

Dijkstra3_{, & Ron Diercks}4

¹ Hanze University of Applied Sciences, The Netherlands ² Transcare, The Netherlands

3 _{University of Groningen, The Netherlands}

Background

› GPs have an important role to play in referral to lifestyle interventions1,2

› GP referrals to lifestyle interventions are not broadly applied3 › 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; 2007.

2. 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):158-162. 3. Peterson JA. Get moving! Physical activity counseling in primary care. J Am Acad Nurse Pract. 2007;19(7):349-357.

Research aims

1. To explore GPs´ motivation to refer to lifestyle interventions; 2. To investigate the association between GPs’ own

lifestyle-behaviors and their referral behavior;

3. To explore patient indicators in the decision-making process of the GPs’ referral to lifestyle interventions.

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).

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)

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

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).

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. 2017.

Study 3: The pie=m project;

development of a tool to support

exercise as medicine in hospital care

Bouma AJ1,2_{, Nassau van F}3_{,Nauta J}3_{, Krops LA}1_{, Ploeg van der}

HP3_{, Jong de J}2_{, Stevens M}4_{, Schwertz MA}5_{, Zwerver J}6_{, Van den}

Akker-Scheek I4,6_{, Diercks RL}4,6_{, Verhagen EALM}3_{, PIE=M}

consortium, Woude van der LHV7_{,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}

Background

› The prescription of physical activity in clinical care has been pleaded worldwide through the ‘exercise is medicine’ (E=M) paradigm1_.

› E=M currently has no position in general routine hospital care2_.

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:S232–7.

2_{Glasgow RE, Vogt TM, Boles SM. (1999) Evaluating the public health impact of health promotion}

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.

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.

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

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

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