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Article

Design and Validity of a Choice-Modeling Questionnaire to Analyze the Feasibility of Implementing Physical Activity on Prescription at Primary Health-Care Settings

by
Sergio Calonge-Pascual
1,
Francisco Fuentes-Jiménez
1,
José A. Casajús Mallén
2,3 and
Marcela González-Gross
1,3,*
1
ImFINE Research Group, Faculty of Physical Activity and Sport Sciences-INEF, Universidad Politécnica de Madrid, C/Martín Fierro 7, 28040 Madrid, Spain
2
GENUD Research Group, Faculty of Health Sciences, University of Zaragoza, Pedro Miral s/n, 50008 Zaragoza, Spain
3
Biomedical Research Center of Physiopathology of Obesity and Nutrition, CIBERobn, (CB12/03/30038), Carlos III Health Institute, Avenida de Monforte de Lemos 5, 28029 Madrid, Spain
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2020, 17(18), 6627; https://doi.org/10.3390/ijerph17186627
Submission received: 6 July 2020 / Revised: 27 August 2020 / Accepted: 3 September 2020 / Published: 11 September 2020
(This article belongs to the Special Issue Measurement and Evaluation in Physical Education, Physical Activity and Sports)
Review Reports Versions Notes

Abstract

:
Worldwide health policies are trying to implement physical activity on prescription (PAP) at healthcare settings. However, there is not a proper methodology to analyze PHC organizational staff factors. This study aims to validate two questionnaires to assess the self-perception of nurses and general practitioners to implement PAP at primary healthcare (PHC) settings. The designed choice-modeling Google-form questionnaire was sent to 11 expert nurses and 11 expert sports medicine physicians. Experts evaluated each question on a 1–5 points Likert-type scale according to their expertise. Aiken’s V coefficient values ≥0.75 were used to validate separately each question using the Visual Basic-6.0 software. A total of 10 sports medicine physicians and 10 nurses with 28.4 ± 5.1 y and 16.3 ± 11.8 y of PAP experience, respectively, validated the questionnaire. One expert in each group was not considered for offering 3 ± SD answers in ≥2 questions respect to the mean of the rest of experts. Final Aiken’s V coefficient values were 0.89 (0.77–1.00) for the nurses’ questionnaire and 0.84 (0.77–0.95) for the physicians’ one. The questionnaires designed to assess the PAP self-perception of PHC nurses and physicians were validated. This methodology could be used to analyze PHC organizational staff factors in order to achieve an efficient PAP implementation in other PHC contexts.

1. Introduction

The global age-standardized prevalence of physical inactivity is around 25% in the world [1]. Physical inactivity and sedentary behavior represent currently a leading risk factor for non-communicable chronic diseases (NCDs) [2]. Since, in 2015, Saltin et al. established that exercise prescriptions could treat at least 26 different NCDs [3], physical activity (PA) has increased in importance and represents a cornerstone in the prevention, at least, of 35 chronic conditions [2]. Recently, it has been published that even more than 40 NCDs could be prevented and treated by exercise prescriptions as a precision medicine [4]. Health benefits of exercise prescriptions are documented and well-known [5]. Therefore, several approaches are trying to promote PA on prescription (PAP) in healthcare (HC) settings, as for example, the proposal of the WHO for the European Region 2016–2025 [6], the worldwide strategy of the American College of Sport Medicine that is the Exercise is Medicine® initiative [7,8,9], and others [10,11,12].
Based on the strength of existing evidence, regular PA should be the first line of preventive and rehabilitation medicine; however, insufficient progress is being developed about the implementation of a model to increase PAP in HC settings [10,13,14]. Interest in PAP implementation has increased during last years, and adherence to non-pharmacological treatments had been traditionally focused by patient-related factors [15]. In contrast, some studies have shown the lack of public resources in the HC system [16,17,18] and for the HC team [16,19], the lack of exercise prescription training knowledge [20,21,22,23], lack of time in their Primary Healthcare (PHC) consultations [24], and the lack of awareness with exercises prescription [24,25], etc.
PHC providers should be considered as intra and interpersonal dimensions inside of the organizational HC system dimension under a social ecological perspective on PAP programs [26,27]. The relationship with the local health and sports community resources [28], managed by health promotion policy, should be strategically studied in order to developed a PAP strategy by a multidisciplinary or interdisciplinary approach [12]. In this sense, to identify all the main barriers and facilitators that influence PAP in HC settings should be a priority for an efficient implementation [10,17]. Some attempts have been made in the last years. Surveys have been designed and carried out in physicians from Canada [7,29], Germany [30,31], and USA [32,33], in health promoters from Australia [34,35] and physical therapists from Canada [36] and Nigeria [37]. However, there is not a consensus or a validated questionnaire to measure the self-perceived PAP barriers and facilitators in health promoters. Therefore, as part of a broader study, the aim of this study was to validate two questionnaires by a panel of experts who were familiar with the PAP construct, to assess the self-perception barriers and facilitators of nurses and general practitioners (GPs), as a first step to facilitate the implementation of PAP at PHC settings, under the umbrella of the Exercise is Medicine initiative.

2. Materials and Methods

Two questionnaires were validated according to the guidelines published by Tsang et al., in 2017 [38]. Following these guidelines, domains of interest and constructs were previously identified to assess what the questionnaire should measure and a check that no validated questionnaire is available in the scientific literature was performed. The baseline for the questionnaire design were focus groups discussions with 5 GPs and 5 nurses, which took place as part of a PhD thesis [12]. Briefly, GPs and nurses, separately, guided by an expert psychologist, commented during four hours about their opinions, barriers, and facilitators to implement PAP in PHC. Their answers were categorized and organized in a structured 30-question questionnaire, according to the five sections and category and subcategory constructs shown in Table 1.
Two choice-modeling, Google-form questionnaires were developed by our group [12] as an on-line self-administered format, because we thought that health professionals are able to complete the questionnaire on their own. A close-ended item format by multiple-choice, Likert-type scales and true/false answers were established, with a simple, short, and familiar language item design for the target respondents. As there is no rule for the length of questionnaires, it was designed to measure the full construct of interest, trying not be so long that respondents experienced fatigue or loss of motivation in completing it. A preliminary review and revision pool of items and pilot testing was conducted by all members of the Improvement of health by fitness, nutrition and exercise Research Group (ImFINE).
Finally, a content validity of the questionnaires was done by a panel of experts as previously had been done by other authors in other fields [39,40]. Eleven nurses and 11 GPs were selected. Inclusion criteria for being considered as an expert were: age ≥ 35 y; >3 y of PAP career experience and/or ≥20 y of academic background related to sports medicine, general practitioner medicine, nursing, public health promotion, and recent or previous relationship with a national public health or PHC system. Descriptive data of the experts are shown in Table 2 and Table 3.
The link to the questionnaires (nurses: https://forms.gle/CmJDQAjR5Pt1zLp36; sports medicine physicians https://forms.gle/coQttEgtBPYgH7Qj7) was sent via email, previous consent to participate. Experts had to indicate below each question their degree of agreement (1–5 points in the Likert-type scale, where 5 points indicated the highest agreement and 1 the lowest agreement). When an expert’s opinion was ≥3 ± standard deviation (SD) different from the mean of the other 9 experts in two or more questions, these values were not considered valid because of the discordance with the rest of experts. The coefficient of content validation for the final 10 experts was calculated using Aiken’s V coefficient (95% CI) [40]. This coefficient and the lower and upper confidence intervals were calculated using the free software ICaiken.exe (Visual Basic 6.0, Lima, Perú) [40]. A minimum Aiken’s V coefficient score of ≥0.75 was needed for each question to be validated [39].
The study was performed according to the principles established with the Declaration of Helsinki 1964 and further amendments and other national regulations for research projects involving human participants: Protection of Personal Data, Law 15/1999 of 13 December on the Protection of Personal Data provided in the current legislation (Royal Decree 1720/2007 of 21 December). The protocol study was approved by the Ethical Committee of the “Hospital Universitario Fundación Alcorcón” and the Central Commission for research of the Region of Madrid (RP1811600040).

3. Results

A total 10 sports medicine physicians and 10 nurses with a mean of 28.4 ± 5.1 y and 16.3 ± 11.8 y in PAP experience, respectively, were finally considered for the validation of the questionnaires.
The 30 items of each questionnaire were agreed by each expert from 1 to 5 points, being 5 the maximum agreed value. The sports medicine physician expert 3 (Table 4) and the expert 7 of the nurses’ questionnaire (Table 5) were not considered for offering 3 ± SD answers in ≥2 questions with respect to the mean of the rest of the experts.
To validate both questionnaires, Aiken’s V coefficient values were calculated. For the questionnaires, we obtained a mean value of 0.89 (0.77–1.00) for nurses and 0.84 (0.77–0.95) for physicians. Results for all items of each questionnaire are shown in Table 6. The highest (≥0.9) Aiken’s V coefficient values were obtained for the items, number 1, 5, 8, 13, 19 in both questionnaires (i.e., Supplementary Material Questionnaire S1: GPs’ questionnaire).

4. Discussion

The both choice-modeling Google-form questionnaires about self-perception of PAP barriers and facilitators by nurses and physicians were validated after a previous design following a rigorous method based on a content-analysis processing of two verbatim transcribed focus group sessions [12].
Item 1, focused on the preventive health benefits of PA and exercise, could discriminate if HC professionals do or do not promote PA, because of the lack of knowledge about the benefits or for other reasons still not resolved. However, the scientific literature provides clear evidence about the benefits of PA on human health [2,3,4]. PAP interventions in PCH settings have still a reduced evidence and need to be enhanced [41]. Previously, Desveaux et al. proposed a questionnaire to find facilitators and barriers of patients and HC providers in regard to a community-based exercise program [29], in a similar way than Myles et al., in Canada [36], Bock et al., in Germany [30], Freene et al., in Austalia [35], and Oyeyemi et al., in Nigeria [37]. Trying to filling in the gap, we propose a new validated questionnaire for analyzing feasibility of PAP in HC settings considering all dimensions and their respective integrated factors, according to the WHO 5 dimensions adherence model [16,42].
Item 5 was designed to assess the stage of change on PAP behavior for PHC professionals, according to the stage of changes of the transtheoretical model [43]. This question was introduced because many studies have evaluated the lifestyle behavior changes in patients or people [44,45], although currently to produce changes towards positive healthy lifestyles for a long-term time is not recognized as an efficient strategy in HC settings [45]. The participants of the previous focus group interview sessions [12] showed a lack of awareness as the majority of their professional colleagues. Because of this, the item tries to assess PAP behavior, based on the 5 stages of change behavior (pre-contemplation, contemplation, preparation, action, maintenance) in PHC providers. WHO proposed already in 2003 that health professionals need to be trained in non-pharmacological adherence treatments [16]. In order to improve adherence levels to PAP as a non-pharmacological treatment, to know what happens with patients is as important as to know about PHC staff. The panel of experts who validated the questionnaires seems to agree with this. Item 8 of the questionnaire was designed to assess the awareness on PAP by health professionals regarding the potential influence with their patients [24,25]. The experts agreed with the relevance of the question to be considered as an indicator in the self-perception barrier of PHC professionals in PAP. Item 13 asked about how PHC professionals were willing to collaborate in PA promotion through a multidisciplinary PHC team. This was scored as important by the experts, in line with the Exercise is Medicine initiative, which encourages multidisciplinarity [8,9]. Finally, item 19, related to the interest on PAP training courses for PHC professionals, was highly scored by all experts, being an indicator to enhance the efficient PAP implementation in PHC settings in accordance with previous studies [23,46,47]. Additionally, other training courses were demanded by the professionals, related to motivational interviews for PAP and time management and identified as resources needed to establish PAP efficiently in PHC settings, in accordance with other authors [48,49,50]. Therefore, this item was also included in the questionnaire and scored high by the experts.
This study could offer the key point to establish a validated questionnaire to analyze the main barriers of nurses and physicians at PHC settings to use PAP in their consultations under their self-perception, as a key factor, according to the social-ecological model [27]. In addition, knowing the positive predisposition of all PHC respondents, especially physicians, to collaborate with other health promoters and local community resources, these questions could be used to find the facilitators to design an effective PAP strategy to implement PAP in PHC settings, according to the health necessities and such as is proposed by recent European and global initiatives [6,51,52]. Limitations for this study were the equivalence on contents offered in the questions for nurses and physicians, according to the similitude of results in the content analysis of the semi-structured focus group sessions developed with them. This study has several strengths, as the validation procedure is based on a rigorous qualitative research process and the experts are highly prestigious in their fields. In a further study, a similar questionnaire process could be developed with exercise professionals in order to establish the self-perceived barriers and facilitators for an interdisciplinary PAP implementation team at HC settings.

5. Conclusions

The two 30 choice-modeling questions of the Google-form questionnaires have been validated by a panel of 10 experts and both are ready to be used in PHC systems to assess the self-perception of PAP facilitators and barriers of nurses and general practitioners. This should lead to facilitate the implementation of an efficient cost-effective and useful public health strategy in the HC system according to the Exercise is Medicine strategy.

Supplementary Materials

The following are available online at https://www.mdpi.com/1660-4601/17/18/6627/s1, Questionnaire S1: GPs’ questionnaire.

Author Contributions

Conceptualization, S.C.-P., F.F.-J. and M.G.-G.; Methodology, S.C.-P., F.F.-J.; Software, S.C.-P.; Validation, S.C.-P.; Formal Analysis, S.C.-P.; Investigation, S.C.-P., F.F.-J and M.G.-G.; Resources, S.C.-P. and M.G.-G.; Data Curation, S.C.-P. and F.F.-J.; Writing—Original Draft Preparation, S.C.-P.; Writing—Review & Editing, S.C.-P., F.F.-J., J.A.C.M. and M.G.-G.; Visualization, J.A.C.M., and M.G.-G.; Supervision, J.A.C.M., and M.G.-G.; Project Administration, J.A.C.M., and M.G.-G.; Funding Acquisition, J.A.C.M. and M.G.-G. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Acknowledgments

We would like to thank to all experts who offered their help to validate both questionnaires selflessly and the EXERNET Research Network on Physical Activity and Health for supporting this study.

Conflicts of Interest

The authors declare no conflict of interest.

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Table
Table 1. Summarized and justified structure of the questionnaire related to each category obtained by focus groups sessions.
Table 1. Summarized and justified structure of the questionnaire related to each category obtained by focus groups sessions.
CONSTRUCTS OF THE QUESTIONNAIRE
SectionCategorySubcategoryNo. QuestionObservations
1.Brief explanation Summarized questionnaire presentation
2.Personal and professional date Personal and professional information
3.Knowledge about PA benefits 1, 4Objective basic knowledge about PAP to be considered accurate their following answers.
4.Stage of change on PAP 5Stage change on PAP behavior in PHC by nurses and physicians
5.Self-perception Physical Activity (PA) pattern of Primary Healthcare (PHC) staffSelf-perception PA behavior of PHC professionals6To check the possibly influence in PAP an active behavior
Physical Activity on Prescription (PAP) backgroundPAP knowledge and use7, 8, 9, 10Knowledge and use about PAP by nurses and primary physicians
PHC staff position to PAPLeadership to PA promotion11, 12Leader position in a PA promotion networking
Leadership to exercise prescription14, 15Leader position in exercise prescription networking
Collaborative PA promotion13, 17, 18Collaborative PA promotion networking
Collaborative exercise prescription16, 17, 18Collaborative exercise prescription networking
PAP training coursesPAP training courses status and necessities19, 20, 21, 22, 23, 24, 25, 26PAP training courses status and resource necessities in nurses and physicians of primary healthcare
PAP as preventive and rehabilitation resourcePAP awareness by PHC Staff8, 29.2Use of PAP in the prevention and treatment of chronic diseases in PHC settings
PAP Awareness by patients29.6Mass media advices to the patient by healthcare system
PAP barriersPAP anamnesis vital sign tool27, 28PA as vital sign in the health tool
Improving consultation time management29.3Time to PAP in PHC consultation
External policies relationships in PAP29.5PAP action plan by the healthcare system and external institutional relationship
Lack of space resources29.1Lack of space to measure fitness and PA/sedentary levels
Lack of Material-economic resources29.4Lack of economic and material resources
PAP solutionsModify PAP vital sign tool30.1Add an improved PA vital sign tool
New space resources30.2Add a space to measure fitness and PA and possible PA training programs
To create PAP networking30.3Develop a PAP networking
To offer PAP Training courses30.4PAP Training courses to healthcare professionals
PA advisement policies30.5PA advisement strategies in mass media
Progressive PAP implementation in PHC30.6Progressive implantation of PAP in primary healthcare system
To enhance material and economic resources for PAP30.7Add economic resources
PAP leadership units at PHC30.8PAP leader position and structure in the PHC system
Use of first consultation (nursering)30.9Use of first nurse consultation to measure physical fitness, PA levels, or something related to PAP
Use of external PHC resources30.10Use of space outside PHC settings. i.e., walking routes, sports centers, etc.
To increase PAP consultation time30.11Increase PAP consultation time because now is insufficient
Table
Table 2. Descriptive data of sports medicine physicians’ experts in physical activity on prescription (PAP).
Table 2. Descriptive data of sports medicine physicians’ experts in physical activity on prescription (PAP).
ExpertRange AgeSexPAP ExperienceAcademic BackgroundLast University Studies Finished (Year)Career Experience (Years)
151–55FemaleResearcher, University professorPh.D.198520
251–55FemaleUniversity professor, Healthcare professionalPh.D.198825
11 *56–60MaleResearcher, University professor, Healthcare professionalPh.D.198336
456–60MaleHealthcare professionalPh.D.198231
5>60FemaleHealthcare professional, Public Health promoterPh.D.197736
656–60MaleResearcher, University professor, Healthcare professionalPh.D.198630
7> 60MaleUniversity professor, Healthcare professionalMaster’s degree & Bachelor’s degree198430
8>60FemaleHealthcare professionalPh.D.198125
9>60MaleResearcher, University professorPh.D.198125
1051–55FemaleResearcher, University professorPh.D.198926
Total 50% Male 28.4 ± 5.1
* Expert exchanged.
Table
Table 3. Descriptive data of nurses’ experts in physical activity on prescription (PAP).
Table 3. Descriptive data of nurses’ experts in physical activity on prescription (PAP).
ExpertRange AgeSexPAP ExperienceAcademic BackgroundLast University Studies Finished (Year)Career Experience (Years)
156–60FemaleHealthcare professionalBachelor’s degree198335
246–50MaleResearcher, University professor, Healthcare professionalBachelor’s degree198228
341–45FemaleResearcher, University professorPh.D.200519
436–40FemaleUniversity professorPh.D.200310
541–45MaleHealthcare professionalMaster’s degree & Bachelor’s degree199520
641–45FemaleHealthcare professionalBachelor’s degree19953
11 *36–40FemaleHealthcare professionalMaster’s degree20044
846–50FemaleHealthcare professional, Public Health promoterMaster’s degree20109
936–40MaleHealthcare professionalBachelor’s degree20025
1051–55FemaleHealthcare professionalMaster’s degree198230
Total 30% Male 16.3 ± 11.8
* Expert exchanged.
Table
Table 4. Values offered by the sports medicine physicians’ experts in all questionnaire items for the validation.
Table 4. Values offered by the sports medicine physicians’ experts in all questionnaire items for the validation.
Sports Medicine Physicians Questionnaire Validation
Expert 1Expert 2Expert 11 *Expert 4Expert 5Expert 6Expert 7Expert 8Expert 9Expert 10Expert 3 *
Item 155544555555
Item 255424555545
Item 354343555533
Item 455453455554
Item 545553555555
Item 655344554554
Item 745544355555
Item 845544555553
Item 934334554554
Item 1034334555554
Item 1143344454554
Item 1243434555541 **
Item 1334554555553
Item 1443554554544
Item 1533554555541 **
Item 1633554555553
Item 1734454555554
Item 1834354554553
Item 1934554555555
Item 2034544555553
Item 2143344555544
Item 2233444555543
Item 2334344555543
Item 2444343555552
Item 2544343555553
Item 2634343555553
Item 2744554553551 **
Item 2834444554551 **
Item 2935444555342
Item 3044454555544
* Expert exchanged; ** values ≥ 3 ± SD of the mean of the rest of the 9 experts.
Table
Table 5. Values offered by the nurses’ experts in all questionnaire items for the validation.
Table 5. Values offered by the nurses’ experts in all questionnaire items for the validation.
Nurses Questionnaire Validation
Expert 1Expert 2Expert 3Expert 4Expert 5Expert 6Expert 11 *Expert 8Expert 9Expert 10Expert 7 *
Item 154544545552
Item 254334544451 **
Item 355354545355
Item 445444545554
Item 554555544451 **
Item 654344535554
Item 754454543554
Item 854555534553
Item 954455535555
Item 1054454544355
Item 1154545545554
Item 1244455535342
Item 1345555535554
Item 1455455545552
Item 1555455535442
Item 1655555535454
Item 1755545545555
Item 1855555545555
Item 1925555545555
Item 2055555545555
Item 2145455545555
Item 2255555555555
Item 2355555545555
Item 2424445535455
Item 2555455545555
Item 2625245535455
Item 2735245541553
Item 2855345542554
Item 2944555545555
Item 3055555545555
* Expert exchanged; ** values ≥3 ± SD of the mean of rest 9 experts.
Table
Table 6. The mean and Aiken’s V coefficient score for all the thirty items offered by the ten experts.
Table 6. The mean and Aiken’s V coefficient score for all the thirty items offered by the ten experts.
GPs’ QuestionnaireNurses’ Questionnaire
Item12345MeanAiken’s V (95% CI *) Value (Range)12345MeanAiken’s V (95% CI *) Value (Range)
1000284.800.95 (0.83–0.98)000464.600.90 (0.76–0.96)
2010364.400.85 (0.70–0.92)002534.100.77 (0.62–0.87)
3003254.200.80 (0.65–0.89)002264.400.85 (0.70–0.92)
4001274.600.90 (0.76–0.96)000554.500.87 (0.73–0.94)
5001184.700.92 (0.80–0.97)000464.600.90 (0.76–0.96)
6001364.500.87 (0.73–0.94)002354.300.82 (0.68–0.91)
7001364.500.87 (0.73–0.94)001454.400.85 (0.70–0.92)
8000374.700.92 (0.80–0.97)001274.600.90 (0.76–0.96)
9003344.100.77 (0.62–0.87)001274.600.90 (0.76–0.96)
10003254.200.80 (0.65–0.89)001544.300.82 (0.68–0.91)
11002534.100.77 (0.62–0.87)000374.700.92 (0.80–0.97)
12002444.200.80 (0.65–0.89)002444.200.80 (0.65–0.89)
13001274.600.90 (0.76–0.96)001184.700.92 (0.80–0.97)
14001454.400.85 (0.70–0.92)000284.800.95 (0.83–0.98)
15002264.400.85 (0.70–0.92)000364.500.87 (0.73–0.94)
16002174.500.87 (0.73–0.94)001184.700.92 (0.80–0.97)
17001364.500.87 (0.73–0.94)000284.800.95 (0.83–0.98)
18002354.300.82 (0.68–0.91)000194.900.97 (0.87–0.99)
19001274.600.90 (0.76–0.96)010184.600.90 (0.76–0.96)
20001364.50.87 (0.73–0.94)000194.900.97 (0.87–0.99)
21002444.200.80 (0.65–0.89)000374.700.92 (0.80–0.97)
22002444.200.80 (0.65–0.89)0000105.001.00 (0.91–1.00)
23002444.200.80 (0.65–0.89)000194.900.97 (0.87–0.99)
24002354.300.82 (0.68–0.91)011444.100.77 (0.62–0.87)
25002354.300.82 (0.68–0.91)000284.800.95 (0.83–0.98)
26002444.200.80 (0.65–0.89)012254.100.77 (0.62–0.87)
27001364.500.87 (0.73–0.94)012254.100.77 (0.62–0.87)
28001544.300.82 (0.68–0.91)011264.300.82 (0.68–0.91)
29002444.200.80 (0.65–0.89)000374.700.92 (0.80–0.97)
30000554.500.87 (0.73–0.94)000014.900.97 (0.87–0.99)
Total 0.84 (SD ± 0.04) 0.89 (SD ± 0.06)
The Likert scale varied from 1 to 5, where the minimum (1) value is according to a very poor relevance and the maximum (5) to the highest degree of relevance. CI *: confidence intervals. GPs: general practitioners.

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Calonge-Pascual, S.; Fuentes-Jiménez, F.; Casajús Mallén, J.A.; González-Gross, M. Design and Validity of a Choice-Modeling Questionnaire to Analyze the Feasibility of Implementing Physical Activity on Prescription at Primary Health-Care Settings. Int. J. Environ. Res. Public Health 2020, 17, 6627. https://doi.org/10.3390/ijerph17186627

AMA Style

Calonge-Pascual S, Fuentes-Jiménez F, Casajús Mallén JA, González-Gross M. Design and Validity of a Choice-Modeling Questionnaire to Analyze the Feasibility of Implementing Physical Activity on Prescription at Primary Health-Care Settings. International Journal of Environmental Research and Public Health. 2020; 17(18):6627. https://doi.org/10.3390/ijerph17186627

Chicago/Turabian Style

Calonge-Pascual, Sergio, Francisco Fuentes-Jiménez, José A. Casajús Mallén, and Marcela González-Gross. 2020. "Design and Validity of a Choice-Modeling Questionnaire to Analyze the Feasibility of Implementing Physical Activity on Prescription at Primary Health-Care Settings" International Journal of Environmental Research and Public Health 17, no. 18: 6627. https://doi.org/10.3390/ijerph17186627

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