J. Med. Internet Res. - There's an app for that: content analysis of paid health and fitness apps.

Tópicos

{ inform(2794) health(2639) internet(1427) }
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{ monitor(1329) mobil(1314) devic(1160) }
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{ medic(1828) order(1363) alert(1069) }
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{ concept(1167) ontolog(924) domain(897) }
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{ risk(3053) factor(974) diseas(938) }
{ visual(1396) interact(850) tool(830) }
{ compound(1573) activ(1297) structur(1058) }
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{ record(1888) medic(1808) patient(1693) }
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{ gene(2352) biolog(1181) express(1162) }
{ first(2504) two(1366) second(1323) }
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{ time(1939) patient(1703) rate(768) }
{ analysi(2126) use(1163) compon(1037) }
{ health(1844) social(1437) communiti(874) }
{ structur(1116) can(940) graph(676) }
{ high(1669) rate(1365) level(1280) }
{ use(1733) differ(960) four(931) }
{ drug(1928) target(777) effect(648) }
{ result(1111) use(1088) new(759) }
{ implement(1333) system(1263) develop(1122) }
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{ process(1125) use(805) approach(778) }
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{ detect(2391) sensit(1101) algorithm(908) }

Resumo

CKGROUND: The introduction of Apple's iPhone provided a platform for developers to design third-party apps, which greatly expanded the functionality and utility of mobile devices for public health.OBJECTIVE: This study provides an overview of the developers' written descriptions of health and fitness apps and appraises each app's potential for influencing behavior change.METHODS: Data for this study came from a content analysis of health and fitness app descriptions available on iTunes during February 2011. The Health Education Curriculum Analysis Tool (HECAT) and the Precede-Proceed Model (PPM) were used as frameworks to guide the coding of 3336 paid apps.RESULTS: Compared to apps with a cost less than US $0.99, apps exceeding US $0.99 were more likely to be scored as intending to promote health or prevent disease (92.55%, 1925/3336 vs 83.59%, 1411/3336; P<.001), to be credible or trustworthy (91.11%, 1895/3336 vs 86.14%, 1454/3349; P<.001), and more likely to be used personally or recommended to a health care client (72.93%, 1517/2644 vs 66.77%, 1127/2644; P<.001). Apps related to healthy eating, physical activity, and personal health and wellness were more common than apps for substance abuse, mental and emotional health, violence prevention and safety, and sexual and reproductive health. Reinforcing apps were less common than predisposing and enabling apps. Only 1.86% (62/3336) of apps included all 3 factors (ie, predisposing, enabling, and reinforcing).CONCLUSIONS: Development efforts could target public health behaviors for which few apps currently exist. Furthermore, practitioners should be cautious when promoting the use of apps as it appears most provide health-related information (predisposing) or make attempts at enabling behavior, with almost none including all theoretical factors recommended for behavior change.

Resumo Limpo

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