Análise da produção científica sobre saúde móvel e mudança de comportamento em saúde
Palavras-chave:
Saúde Móvel, Tecnologia em saúde, ComportamentoResumo
Introdução: Trata-se de um estudo cienciométrico da literatura científica sobre mHealth (saúde móvel) e mudança de comportamento em saúde. Métodos: A pesquisa foi realizada na base de dados PubMed, utilizando-se o termo “Health behavior change and mHealth” e resultou na identificação de 62 artigos. Resultados: Os anos de 2015, 2016 e 2017 detiveram o maior número de artigos publicados sobre o tema, identificando-se os temas “doenças crônicas” e “saúde em geral” como os de maior interesse da comunidade científica. As tecnologias e serviços em mHealth mais utilizadas nas intervenções para modificar as condutas em saúde foram os aplicativos e as mensagens de texto. Conclusão: O resultado cienciométrico contribui para a compreensão do estado da arte das pesquisas e para nortear futuras pesquisas sobre as intervenções mHealth e mudança de comportamento em saúde.
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Referências
1. Silva DAS, Pereira IMM. Estágios de mudança de comportamento para atividade física e fatores associados em acadêmicos de educação física. Rev Bras Atividade Física Saúde 2010; 15: 15–20.
2. Tonosaki LMD, Rech CR, Mazo GZ, et al. Barreiras e facilitadores para a participação em um programa de mudança de comportamento: análise de grupos focais. Rev Bras Ciências do Esporte 2018; 40: 138–145.
3. World Health Organization. mHealth: new horizons for health through mobile technologies: second global survey on eHealth. Glob Obs eHealth Ser 2011; 3: 103.
4. Cabrita M, op den Akker H, Tabak M, et al. Persuasive technology to support active and healthy ageing: An exploration of past, present, and future. J Biomed Inform 2018; 84: 17–30.
5. Buss PM, Pellegrini Filho A. A saúde e seus determinantes sociais. Physis Rev Saúde Coletiva 2007; 17: 77–93.
6. Free C, Knight R, Robertson S, et al. Smoking cessation support delivered via mobile phone text messaging (txt2stop): a single-blind, randomised trial. Lancet 2011; 378: 49–55.
7. Cole-Lewis H, Kershaw T. Text messaging as a tool for behavior change in disease prevention and management. Epidemiol Rev 2010; 32: 56–69.
8. Yao Q, Chen K, Yao L, et al. Scientometric trends and knowledge maps of global health systems research. Heal Res Policy Syst 2014; 12: 26.
9. Blázquez-Ruiz J, Guerrero-Bote VP, Moya-Anegón F. New Scientometric-Based Knowledge Map of Food Science Research (2003 to 2014). Compr Rev Food Sci Food Saf 2016; 15: 1040–1055.
10. Mingers J, Leydesdorff L. A review of theory and practice in scientometrics. Eur J Oper Res 2015; 246: 1–19.
11. Falagas ME, Pitsouni EI, Malietzis GA, et al. Comparison of PubMed, Scopus, Web of Science, and Google Scholar: strengths and weaknesses. FASEB J 2008; 22: 338–342.
12. WHO | World Health Organization. Global status report on noncommunicable diseases. Geneva, Switzerland, https://www.who.int/nmh/publications/ncd-status-report-2014/en/ (2014).
13. Ministério da Saúde. As Cartas da Promoção da Saúde. Brasília-DF: Editora MS, http://bvsms.saude.gov.br/bvs/publicacoes/cartas_promocao.pdf (2002).
14. WHO | World Health Organization. 10 facts on obesity. Fact Files 2017; 1–10.
15. West JH, Belvedere LM, Andreasen R, et al. Controlling Your “App”etite: How Diet and Nutrition-Related Mobile Apps Lead to Behavior Change. JMIR mHealth uHealth 2017; 5: e95.
16. Schoeppe S, Alley S, Rebar AL, et al. Apps to improve diet, physical activity and sedentary behaviour in children and adolescents: a review of quality, features and behaviour change techniques. Int J Behav Nutr Phys Act 2017; 14: 83.
17. Wilkinson JL, Strickling K, Payne HE, et al. Evaluation of Diet-Related Infographics on Pinterest for Use of Behavior Change Theories: A Content Analysis. JMIR mHealth uHealth 2016; 4: e133.
18. Partridge SR, McGeechan K, Bauman A, et al. Improved confidence in performing nutrition and physical activity behaviours mediates behavioural change in young adults: Mediation results of a randomised controlled mHealth intervention. Appetite 2017; 108: 425–433.
19. Partridge SR, McGeechan K, Bauman A, et al. Improved eating behaviours mediate weight gain prevention of young adults: moderation and mediation results of a randomised controlled trial of TXT2BFiT, mHealth program. Int J Behav Nutr Phys Act 2016; 13: 44.
20. Cohen A, Perozich A, Rajan R, et al. Framed, Interactive Theory-Driven Texting: Effects of Message Framing on Health Behavior Change for Weight Loss. Fam Community Health 2017; 40: 43–51.
21. Spark LC, Fjeldsoe BS, Eakin EG, et al. Efficacy of a Text Message-Delivered Extended Contact Intervention on Maintenance of Weight Loss, Physical Activity, and Dietary Behavior Change. JMIR mHealth uHealth 2015; 3: e88.
22. Waterlander W, Whittaker R, McRobbie H, et al. Development of an Evidence-Based mHealth Weight Management Program Using a Formative Research Process. JMIR mhealth uhealth 2014; 2: e18.
23. Smith KL, Kerr DA, Fenner AA, et al. Adolescents Just Do Not Know What They Want: A Qualitative Study to Describe Obese Adolescents’ Experiences of Text Messaging to Support Behavior Change Maintenance Post Intervention. J Med Internet Res 2014; 16: e103.
24. Sharifi M, Dryden EM, Horan CM, et al. Leveraging Text Messaging and Mobile Technology to Support Pediatric Obesity-Related Behavior Change: A Qualitative Study Using Parent Focus Groups and Interviews. J Med Internet Res 2013; 15: e272.
25. Hoj TH, Covey EL, Jones AC, et al. How Do Apps Work? An Analysis of Physical Activity App Users’ Perceptions of Behavior Change Mechanisms. JMIR mHealth uHealth 2017; 5: e114.
26. Direito A, Carraça E, Rawstorn J, et al. mHealth Technologies to Influence Physical Activity and Sedentary Behaviors: Behavior Change Techniques, Systematic Review and Meta-Analysis of Randomized Controlled Trials. Ann Behav Med 2017; 51: 226–239.
27. Miyamoto SW, Henderson S, Young HM, et al. Tracking Health Data Is Not Enough: A Qualitative Exploration of the Role of Healthcare Partnerships and mHealth Technology to Promote Physical Activity and to Sustain Behavior Change. JMIR mHealth uHealth 2016; 4: e5.
28. Rabbi M, Pfammatter A, Zhang M, et al. Automated Personalized Feedback for Physical Activity and Dietary Behavior Change With Mobile Phones: A Randomized Controlled Trial on Adults. JMIR mHealth uHealth 2015; 3: e42.
29. Müller AM, Khoo S, Morris T. Text Messaging for Exercise Promotion in Older Adults From an Upper-Middle-Income Country: Randomized Controlled Trial. J Med Internet Res 2016; 18: e5.
30. Belmon LS, Middelweerd A, te Velde SJ, et al. Dutch Young Adults Ratings of Behavior Change Techniques Applied in Mobile Phone Apps to Promote Physical Activity: A Cross-Sectional Survey. JMIR mHealth uHealth 2015; 3: e103.
31. Klasnja P, Consolvo S, Mcdonald DW, et al. Using Mobile & Personal Sensing Technologies to Support Health Behavior Change in Everyday Life : Lessons Learned University of Washington , Seattle , WA ; 2 Intel Research Seattle , Seattle , WA. AMIA 2009 Symp Proc 2009; 338–342.
32. Vandelanotte C, Müller AM, Short CE, et al. Past, Present, and Future of eHealth and mHealth Research to Improve Physical Activity and Dietary Behaviors. J Nutr Educ Behav 2016; 48: 219-228.e1.
33. Brannon EE, Cushing CC. A Systematic Review: Is There an App for That? Translational Science of Pediatric Behavior Change for Physical Activity and Dietary Interventions. J Pediatr Psychol 2015; 40: 373–384.
34. Polisseni ML de C, Ribeiro LC. Exercício físico como fator de proteção para a saúde em servidores públicos. Rev Bras Med do Esporte 2014; 20: 340–344.
35. Gustafsson E, Thomée S, Grimby-Ekman A, et al. Texting on mobile phones and musculoskeletal disorders in young adults: A five-year cohort study. Appl Ergon 2017; 58: 208–214.
36. Lee M, Hong Y, Lee S, et al. The effects of smartphone use on upper extremity muscle activity and pain threshold. J Phys Ther Sci 2015; 27: 1743–1745.
37. Paulo Henrique LMTG, Grégore Iven M, Garcia. Comportamento Sedentário. Rev Corpoconsciência 2014; 18: 23–36.
38. Owen N, Sparling PB, Healy GN, et al. Sedentary Behavior: Emerging Evidence for a New Health Risk. Mayo Clin Proc 2010; 85: 1138–1141.
39. Direito A, Walsh D, Hinbarji M, et al. Using the Intervention Mapping and Behavioral Intervention Technology Frameworks: Development of an mHealth Intervention for Physical Activity and Sedentary Behavior Change. Heal Educ Behav 2018; 45: 331–348.
40. Walsh JC, Corbett T, Hogan M, et al. An mHealth Intervention Using a Smartphone App to Increase Walking Behavior in Young Adults: A Pilot Study. JMIR mHealth uHealth 2016; 4: e109.
41. Mercer K, Li M, Giangregorio L, et al. Behavior Change Techniques Present in Wearable Activity Trackers: A Critical Analysis. JMIR mHealth uHealth 2016; 4: e40.
42. Kingkaew P, Glidewell L, Walwyn R, et al. Identifying effective components for mobile health behaviour change interventions for smoking cessation and service uptake: protocol of a systematic review and planned meta-analysis. Syst Rev 2017; 6: 193.
43. Paige SR, Alber JM, Stellefson ML, et al. Missing the mark for patient engagement: mHealth literacy strategies and behavior change processes in smoking cessation apps. Patient Educ Couns 2018; 101: 951–955.
44. Shibasaki S, Gardner K, Sibthorpe B. Using Knowledge Translation to Craft “Sticky” Social Media Health Messages That Provoke Interest, Raise Awareness, Impart Knowledge, and Inspire Change. JMIR mHealth uHealth 2016; 4: e115.
45. Zeng EY, Heffner JL, Copeland WK, et al. Get with the program: Adherence to a smartphone app for smoking cessation. Addict Behav 2016; 63: 120–124.
46. Liao Y, Wu Q, Tang J, et al. The efficacy of mobile phone-based text message interventions (‘Happy Quit’) for smoking cessation in China. BMC Public Health 2016; 16: 833.
47. Kukafka R, Jeong IC, Finkelstein J. Optimizing Decision Support for Tailored Health Behavior Change Applications. Stud Heal Technol informatics / Vol 216 MEDINFO 2015 eHealth-enabled Heal 2015; 216: 108–12.
48. WHO | World Health Organization. World No Tobacco Day 2018: tobacco breaks hearts–choose health, not tobacco. Geneva, Switzerland, http://apps.who.int/iris/bitstream/handle/10665/272675/WHO-NMH-PND-18.4-eng.pdf (2018).
49. Klasnja P, Pratt W. Healthcare in the pocket: Mapping the space of mobile-phone health interventions. J Biomed Inform 2012; 45: 184–198.
50. Abroms LC, Johnson PR, Heminger CL, et al. Quit4baby: results from a pilot test of a mobile smoking cessation program for pregnant women. JMIR mHealth uHealth 2015; 3: e10.
51. Formagini TDB, Ervilha RR, Machado NM, et al. Revisão dos aplicativos de smartphones para cessação do tabagismo disponíveis em língua portuguesa. Cad Saude Publica 2017; 33: 1–11.
52. Lamas I, Cadete MMM. Do desejo à ação: fatores que interferem na abordagem nutricional para mudança de hábito alimentar. Rev Enferm UFPE 2017; 11: 2432–2444.
53. Mummah SA, King AC, Gardner CD, et al. Iterative development of Vegethon: a theory-based mobile app intervention to increase vegetable consumption. Int J Behav Nutr Phys Act 2016; 13: 90.
54. French RS, McCarthy O, Baraitser P, et al. Young People’s Views and Experiences of a Mobile Phone Texting Intervention to Promote Safer Sex Behavior. JMIR mHealth uHealth 2016; 4: e26.
55. Mauriello LM, Van Marter DF, Umanzor CD, et al. Using mHealth to Deliver Behavior Change Interventions Within Prenatal Care at Community Health Centers. Am J Heal Promot 2016; 30: 554–562.
56. Higgs ES, Goldberg AB, Labrique AB, et al. Understanding the Role of mHealth and Other Media Interventions for Behavior Change to Enhance Child Survival and Development in Low- and Middle-Income Countries: An Evidence Review. J Health Commun 2014; 19: 164–189.
57. WHO - World Health Organization. Sexually transmitted infections (STIs). WHO News - Fact sheets 2019; 1.
58. WHO | World Health Organization. Under-five mortality. Global Health Observatory (GHO) data 2016; 1.
59. WHO | World Health Organization. Causes of child mortality -2017. Global Health Observatory (GHO) data 2017; 1.
60. Rosa CQ da, Silveira DS da, Costa JSD da. Fatores associados à não realização de pré-natal em município de grande porte. Rev Saude Publica 2014; 48: 977–984.
61. Garnett C, Crane D, West R, et al. Identification of Behavior Change Techniques and Engagement Strategies to Design a Smartphone App to Reduce Alcohol Consumption Using a Formal Consensus Method. JMIR mHealth uHealth 2015; 3: e73.
62. Crane D, Garnett C, Brown J, et al. Behavior Change Techniques in Popular Alcohol Reduction Apps: content analysis. J Med Internet Res 2015; 17: e118.
63. WHO | World Health Organization. Global status report on alcohol and health. Geneva, Switzerland, http://www.who.int/substance_abuse/publications/global_alcohol_report/msbgsruprofiles.pdf (2014).
64. Santos CMVT, Andrade JA de, Amorim A do C, et al. Application on mobile platform “Idoso Ativo” (Active Aging): exercises for lower limbs combining technology and health. Fisioter em Mov 2018; 31: 1–10.
65. Cross D, Thomson S, Sinclair A. Research in Brazil: a report for Capes by Clarivate Analytics, http://www.capes.gov.br/images/stories/download/diversos/17012018-CAPES-InCitesReport-Final.pdf (2017).
66. Björnberg A. Euro health consumer index 2017 report. Health consumer powerhouse 2017; 100.
2. Tonosaki LMD, Rech CR, Mazo GZ, et al. Barreiras e facilitadores para a participação em um programa de mudança de comportamento: análise de grupos focais. Rev Bras Ciências do Esporte 2018; 40: 138–145.
3. World Health Organization. mHealth: new horizons for health through mobile technologies: second global survey on eHealth. Glob Obs eHealth Ser 2011; 3: 103.
4. Cabrita M, op den Akker H, Tabak M, et al. Persuasive technology to support active and healthy ageing: An exploration of past, present, and future. J Biomed Inform 2018; 84: 17–30.
5. Buss PM, Pellegrini Filho A. A saúde e seus determinantes sociais. Physis Rev Saúde Coletiva 2007; 17: 77–93.
6. Free C, Knight R, Robertson S, et al. Smoking cessation support delivered via mobile phone text messaging (txt2stop): a single-blind, randomised trial. Lancet 2011; 378: 49–55.
7. Cole-Lewis H, Kershaw T. Text messaging as a tool for behavior change in disease prevention and management. Epidemiol Rev 2010; 32: 56–69.
8. Yao Q, Chen K, Yao L, et al. Scientometric trends and knowledge maps of global health systems research. Heal Res Policy Syst 2014; 12: 26.
9. Blázquez-Ruiz J, Guerrero-Bote VP, Moya-Anegón F. New Scientometric-Based Knowledge Map of Food Science Research (2003 to 2014). Compr Rev Food Sci Food Saf 2016; 15: 1040–1055.
10. Mingers J, Leydesdorff L. A review of theory and practice in scientometrics. Eur J Oper Res 2015; 246: 1–19.
11. Falagas ME, Pitsouni EI, Malietzis GA, et al. Comparison of PubMed, Scopus, Web of Science, and Google Scholar: strengths and weaknesses. FASEB J 2008; 22: 338–342.
12. WHO | World Health Organization. Global status report on noncommunicable diseases. Geneva, Switzerland, https://www.who.int/nmh/publications/ncd-status-report-2014/en/ (2014).
13. Ministério da Saúde. As Cartas da Promoção da Saúde. Brasília-DF: Editora MS, http://bvsms.saude.gov.br/bvs/publicacoes/cartas_promocao.pdf (2002).
14. WHO | World Health Organization. 10 facts on obesity. Fact Files 2017; 1–10.
15. West JH, Belvedere LM, Andreasen R, et al. Controlling Your “App”etite: How Diet and Nutrition-Related Mobile Apps Lead to Behavior Change. JMIR mHealth uHealth 2017; 5: e95.
16. Schoeppe S, Alley S, Rebar AL, et al. Apps to improve diet, physical activity and sedentary behaviour in children and adolescents: a review of quality, features and behaviour change techniques. Int J Behav Nutr Phys Act 2017; 14: 83.
17. Wilkinson JL, Strickling K, Payne HE, et al. Evaluation of Diet-Related Infographics on Pinterest for Use of Behavior Change Theories: A Content Analysis. JMIR mHealth uHealth 2016; 4: e133.
18. Partridge SR, McGeechan K, Bauman A, et al. Improved confidence in performing nutrition and physical activity behaviours mediates behavioural change in young adults: Mediation results of a randomised controlled mHealth intervention. Appetite 2017; 108: 425–433.
19. Partridge SR, McGeechan K, Bauman A, et al. Improved eating behaviours mediate weight gain prevention of young adults: moderation and mediation results of a randomised controlled trial of TXT2BFiT, mHealth program. Int J Behav Nutr Phys Act 2016; 13: 44.
20. Cohen A, Perozich A, Rajan R, et al. Framed, Interactive Theory-Driven Texting: Effects of Message Framing on Health Behavior Change for Weight Loss. Fam Community Health 2017; 40: 43–51.
21. Spark LC, Fjeldsoe BS, Eakin EG, et al. Efficacy of a Text Message-Delivered Extended Contact Intervention on Maintenance of Weight Loss, Physical Activity, and Dietary Behavior Change. JMIR mHealth uHealth 2015; 3: e88.
22. Waterlander W, Whittaker R, McRobbie H, et al. Development of an Evidence-Based mHealth Weight Management Program Using a Formative Research Process. JMIR mhealth uhealth 2014; 2: e18.
23. Smith KL, Kerr DA, Fenner AA, et al. Adolescents Just Do Not Know What They Want: A Qualitative Study to Describe Obese Adolescents’ Experiences of Text Messaging to Support Behavior Change Maintenance Post Intervention. J Med Internet Res 2014; 16: e103.
24. Sharifi M, Dryden EM, Horan CM, et al. Leveraging Text Messaging and Mobile Technology to Support Pediatric Obesity-Related Behavior Change: A Qualitative Study Using Parent Focus Groups and Interviews. J Med Internet Res 2013; 15: e272.
25. Hoj TH, Covey EL, Jones AC, et al. How Do Apps Work? An Analysis of Physical Activity App Users’ Perceptions of Behavior Change Mechanisms. JMIR mHealth uHealth 2017; 5: e114.
26. Direito A, Carraça E, Rawstorn J, et al. mHealth Technologies to Influence Physical Activity and Sedentary Behaviors: Behavior Change Techniques, Systematic Review and Meta-Analysis of Randomized Controlled Trials. Ann Behav Med 2017; 51: 226–239.
27. Miyamoto SW, Henderson S, Young HM, et al. Tracking Health Data Is Not Enough: A Qualitative Exploration of the Role of Healthcare Partnerships and mHealth Technology to Promote Physical Activity and to Sustain Behavior Change. JMIR mHealth uHealth 2016; 4: e5.
28. Rabbi M, Pfammatter A, Zhang M, et al. Automated Personalized Feedback for Physical Activity and Dietary Behavior Change With Mobile Phones: A Randomized Controlled Trial on Adults. JMIR mHealth uHealth 2015; 3: e42.
29. Müller AM, Khoo S, Morris T. Text Messaging for Exercise Promotion in Older Adults From an Upper-Middle-Income Country: Randomized Controlled Trial. J Med Internet Res 2016; 18: e5.
30. Belmon LS, Middelweerd A, te Velde SJ, et al. Dutch Young Adults Ratings of Behavior Change Techniques Applied in Mobile Phone Apps to Promote Physical Activity: A Cross-Sectional Survey. JMIR mHealth uHealth 2015; 3: e103.
31. Klasnja P, Consolvo S, Mcdonald DW, et al. Using Mobile & Personal Sensing Technologies to Support Health Behavior Change in Everyday Life : Lessons Learned University of Washington , Seattle , WA ; 2 Intel Research Seattle , Seattle , WA. AMIA 2009 Symp Proc 2009; 338–342.
32. Vandelanotte C, Müller AM, Short CE, et al. Past, Present, and Future of eHealth and mHealth Research to Improve Physical Activity and Dietary Behaviors. J Nutr Educ Behav 2016; 48: 219-228.e1.
33. Brannon EE, Cushing CC. A Systematic Review: Is There an App for That? Translational Science of Pediatric Behavior Change for Physical Activity and Dietary Interventions. J Pediatr Psychol 2015; 40: 373–384.
34. Polisseni ML de C, Ribeiro LC. Exercício físico como fator de proteção para a saúde em servidores públicos. Rev Bras Med do Esporte 2014; 20: 340–344.
35. Gustafsson E, Thomée S, Grimby-Ekman A, et al. Texting on mobile phones and musculoskeletal disorders in young adults: A five-year cohort study. Appl Ergon 2017; 58: 208–214.
36. Lee M, Hong Y, Lee S, et al. The effects of smartphone use on upper extremity muscle activity and pain threshold. J Phys Ther Sci 2015; 27: 1743–1745.
37. Paulo Henrique LMTG, Grégore Iven M, Garcia. Comportamento Sedentário. Rev Corpoconsciência 2014; 18: 23–36.
38. Owen N, Sparling PB, Healy GN, et al. Sedentary Behavior: Emerging Evidence for a New Health Risk. Mayo Clin Proc 2010; 85: 1138–1141.
39. Direito A, Walsh D, Hinbarji M, et al. Using the Intervention Mapping and Behavioral Intervention Technology Frameworks: Development of an mHealth Intervention for Physical Activity and Sedentary Behavior Change. Heal Educ Behav 2018; 45: 331–348.
40. Walsh JC, Corbett T, Hogan M, et al. An mHealth Intervention Using a Smartphone App to Increase Walking Behavior in Young Adults: A Pilot Study. JMIR mHealth uHealth 2016; 4: e109.
41. Mercer K, Li M, Giangregorio L, et al. Behavior Change Techniques Present in Wearable Activity Trackers: A Critical Analysis. JMIR mHealth uHealth 2016; 4: e40.
42. Kingkaew P, Glidewell L, Walwyn R, et al. Identifying effective components for mobile health behaviour change interventions for smoking cessation and service uptake: protocol of a systematic review and planned meta-analysis. Syst Rev 2017; 6: 193.
43. Paige SR, Alber JM, Stellefson ML, et al. Missing the mark for patient engagement: mHealth literacy strategies and behavior change processes in smoking cessation apps. Patient Educ Couns 2018; 101: 951–955.
44. Shibasaki S, Gardner K, Sibthorpe B. Using Knowledge Translation to Craft “Sticky” Social Media Health Messages That Provoke Interest, Raise Awareness, Impart Knowledge, and Inspire Change. JMIR mHealth uHealth 2016; 4: e115.
45. Zeng EY, Heffner JL, Copeland WK, et al. Get with the program: Adherence to a smartphone app for smoking cessation. Addict Behav 2016; 63: 120–124.
46. Liao Y, Wu Q, Tang J, et al. The efficacy of mobile phone-based text message interventions (‘Happy Quit’) for smoking cessation in China. BMC Public Health 2016; 16: 833.
47. Kukafka R, Jeong IC, Finkelstein J. Optimizing Decision Support for Tailored Health Behavior Change Applications. Stud Heal Technol informatics / Vol 216 MEDINFO 2015 eHealth-enabled Heal 2015; 216: 108–12.
48. WHO | World Health Organization. World No Tobacco Day 2018: tobacco breaks hearts–choose health, not tobacco. Geneva, Switzerland, http://apps.who.int/iris/bitstream/handle/10665/272675/WHO-NMH-PND-18.4-eng.pdf (2018).
49. Klasnja P, Pratt W. Healthcare in the pocket: Mapping the space of mobile-phone health interventions. J Biomed Inform 2012; 45: 184–198.
50. Abroms LC, Johnson PR, Heminger CL, et al. Quit4baby: results from a pilot test of a mobile smoking cessation program for pregnant women. JMIR mHealth uHealth 2015; 3: e10.
51. Formagini TDB, Ervilha RR, Machado NM, et al. Revisão dos aplicativos de smartphones para cessação do tabagismo disponíveis em língua portuguesa. Cad Saude Publica 2017; 33: 1–11.
52. Lamas I, Cadete MMM. Do desejo à ação: fatores que interferem na abordagem nutricional para mudança de hábito alimentar. Rev Enferm UFPE 2017; 11: 2432–2444.
53. Mummah SA, King AC, Gardner CD, et al. Iterative development of Vegethon: a theory-based mobile app intervention to increase vegetable consumption. Int J Behav Nutr Phys Act 2016; 13: 90.
54. French RS, McCarthy O, Baraitser P, et al. Young People’s Views and Experiences of a Mobile Phone Texting Intervention to Promote Safer Sex Behavior. JMIR mHealth uHealth 2016; 4: e26.
55. Mauriello LM, Van Marter DF, Umanzor CD, et al. Using mHealth to Deliver Behavior Change Interventions Within Prenatal Care at Community Health Centers. Am J Heal Promot 2016; 30: 554–562.
56. Higgs ES, Goldberg AB, Labrique AB, et al. Understanding the Role of mHealth and Other Media Interventions for Behavior Change to Enhance Child Survival and Development in Low- and Middle-Income Countries: An Evidence Review. J Health Commun 2014; 19: 164–189.
57. WHO - World Health Organization. Sexually transmitted infections (STIs). WHO News - Fact sheets 2019; 1.
58. WHO | World Health Organization. Under-five mortality. Global Health Observatory (GHO) data 2016; 1.
59. WHO | World Health Organization. Causes of child mortality -2017. Global Health Observatory (GHO) data 2017; 1.
60. Rosa CQ da, Silveira DS da, Costa JSD da. Fatores associados à não realização de pré-natal em município de grande porte. Rev Saude Publica 2014; 48: 977–984.
61. Garnett C, Crane D, West R, et al. Identification of Behavior Change Techniques and Engagement Strategies to Design a Smartphone App to Reduce Alcohol Consumption Using a Formal Consensus Method. JMIR mHealth uHealth 2015; 3: e73.
62. Crane D, Garnett C, Brown J, et al. Behavior Change Techniques in Popular Alcohol Reduction Apps: content analysis. J Med Internet Res 2015; 17: e118.
63. WHO | World Health Organization. Global status report on alcohol and health. Geneva, Switzerland, http://www.who.int/substance_abuse/publications/global_alcohol_report/msbgsruprofiles.pdf (2014).
64. Santos CMVT, Andrade JA de, Amorim A do C, et al. Application on mobile platform “Idoso Ativo” (Active Aging): exercises for lower limbs combining technology and health. Fisioter em Mov 2018; 31: 1–10.
65. Cross D, Thomson S, Sinclair A. Research in Brazil: a report for Capes by Clarivate Analytics, http://www.capes.gov.br/images/stories/download/diversos/17012018-CAPES-InCitesReport-Final.pdf (2017).
66. Björnberg A. Euro health consumer index 2017 report. Health consumer powerhouse 2017; 100.
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2024-04-15
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