An Implementation of Interactive Healthy Eating Index and Healthcare System on Mobile Platform in College Student Samples

Chen, Shyh‐Wei; Chiang, Dai-Lun; Chen, Tzer-Shyong; Lin, Han-Yu; Chung, Yu-Fang; Lai, Feipei

doi:10.1109/access.2018.2881996

Cited by 7 publications

(11 citation statements)

References 15 publications

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“…Over half (43/80, 53.8% 51,55,57–60,62–66,68,71,72,74,80,83–85,87,88,91,92,94,99,106,108,111,112,117–119,122–126,129,132,133 ) of studies did not report a theoretical framework for intervention development. Of the 37 studies (46.3% 54,61,67,69,70,73,75–79,82,86,89,90,93,95–98,100–105,107,109,110,113–116,121,127,128,130,131 ) that did, social‐cognitive theory was most commonly reported (8/80, 10.0% 54,76,86,97,104,105,107,121 ).…”

Section: Resultsmentioning

confidence: 99%

“…Most were randomized (31/80, 38.8% 56,57,[59][60][61][62][63]65,68,[73][74][75]89,93,94,96,[98][99][100]105,109,111,114,115,[117][118][119]126,129,130,132,134 ) or quasi-experimental trials (22/80, 27.5% single group pre-post 51,67,70,71,[77][78][79]81,86,87,91,97,103,106,108,112,113,[120][121][122]…”

Section: Study Characteristicsmentioning

confidence: 99%

“…three targeted sleep alone (3/80, 3.8% 82,111 ); and one targeted sedentary behavior (1/80, 1.3% 59 ). Where two movement behaviors were targeted (8/80, 10.0%), these were physical activity and sedentary behavior (4/80, 5.0% 80,98,100,127 ) and physical activity and sleep (3/80, 3.8% 77,114,128 [68][69][70]79,82,83,85,88,89,91,92,[95][96][97]103,[106][107][108][109]113,114,124,126,[128][129][130] ), pedometer (not app based; 19/80, 23.8% 55,[60][61][62][63][64][65][66][67][68]87,94,112,115,…”

Section: Intervention Characteristicsmentioning

confidence: 99%

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mHealth interventions targeting movement behaviors in Asia: A scoping review

et al. 2021

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Summary mHealth interventions can promote healthy movement behaviors (physical activity, sedentary behavior, and sleep). However, recent reviews include few studies from Asia, despite it being home to over 60% of the world population. The aim is to map the current evidence for mHealth interventions targeting movement behaviors in Asia. Six databases were searched up until August 2021. Included studies described an mHealth intervention targeting one or more movement behaviors, delivered in a country/territory in Asia, to a general population. A total of 3986 unique records were screened for eligibility in duplicate. Eighty studies with 1,413,652 participants were included. Most were randomized (38.8%) or quasi‐experimental (27.5%) trials. Studies were from 17 countries/territories (out of 55); majority were high‐ (65.0%) or upper middle‐income (28.7%). Physical activity was targeted most often (93.8%), few targeted sedentary behavior (7.5%), or sleep (8.8%). Most targeted one movement behavior (90.0%), and none targeted all three together. Interventions typically incorporated a single mHealth component (70.0%; app, pedometer, text messages, wearable) and were delivered remotely (66.3%). The average intervention length was 121.8 (SD 127.6) days. mHealth interventions in Asia have primarily targeted physical activity in high‐ and upper middle‐income countries. There are few interventions targeting sedentary behavior or sleep, and no interventions in low‐income countries.

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Section: Resultsmentioning

confidence: 99%

Section: Study Characteristicsmentioning

confidence: 99%

Section: Intervention Characteristicsmentioning

confidence: 99%

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mHealth interventions targeting movement behaviors in Asia: A scoping review

et al. 2021

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“…The guidelines to follow in any healthy diet are summarized in: (1) variety in foods; (2) reduce fat consumption; (3) increase the consumption of complex carbohydrates such as fruits and vitamins; (4) increase the consumption of fiber-rich foods; (5) reduce sugar and salt; (6) maintain the intake of vitamin D and calcium; (7) hydrate; (8) moderate alcohol consumption; (9) make 4 or 5 meals a day reducing the amounts in each one; and (10) exercise regularly. Technology is a highly effective tool for controlling diet and physical activity [1], [2].…”

Section: Introductionmentioning

confidence: 99%

“…The steps that we have carried out throughout the work have been: (1) to review existing Calorie Control Apps; (2) to analyse algorithms registering the purchased groceries and select a food collection to compare; (3) to develop the FoodScan App; and (4) to conduct a user evaluation.…”

Section: Introductionmentioning

confidence: 99%