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A simple dietary assessment tool to monitor food intake of hospitalized adult patients

Overview of attention for article published in Journal of Multidisciplinary Healthcare, July 2016
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Title
A simple dietary assessment tool to monitor food intake of hospitalized adult patients
Published in
Journal of Multidisciplinary Healthcare, July 2016
DOI 10.2147/jmdh.s105000
Pubmed ID
Authors

Dwi Budiningsari, Suzana Shahar, Zahara Abdul Manaf, Susetyowati Susetyowati

Abstract

Monitoring food intake of patients during hospitalization using simple methods and minimal training is an ongoing problem in hospitals. Therefore, there is a need to develop and validate a simple, easy to use, and quick tool that enables staff to estimate dietary intake. Thus, this study aimed to develop and validate the Pictorial Dietary Assessment Tool (PDAT). A total of 37 health care staff members consisting of dietitians, nurses, and serving assistants estimated 130 breakfast and lunch meals consumed by 67 patients using PDAT. PDAT was developed based on the hospital menu that consists of staple food (rice or porridge), animal source protein (chicken, meat, eggs, and fish), and non-animal source protein (tau fu and tempeh), with a total of six pictorials of food at each meal time. Weighed food intake was used as a gold standard to validate PDAT. Agreement between methods was analyzed using correlations, paired t-test, Bland-Altman plots, kappa statistics, and McNemar's test. Sensitivity, specificity, and area under the curve of receiver operating characteristic were calculated to identify whether patients who had an inadequate food intake were categorized as at risk by the PDAT, based on the food weighing method. Agreement between different backgrounds of health care staff was calculated by intraclass correlation coefficient and analysis of variance test. There was a significant correlation between the weighing food method and PDAT for energy (r=0.919, P<0.05), protein (r=0.843, P<0.05), carbohydrate (r=0.912, P<0.05), and fat (r=0.952; P<0.05). Nutrient intakes as assessed using PDAT and food weighing were rather similar (295±163 vs 292±158 kcal for energy; 13.9±7.8 vs 14.1±8.0 g for protein; 46.1±21.4 vs 46.7±22.3 g for carbohydrate; 7.4±3.1 vs 7.4±3.1 g for fat; P>0.05). The PDAT and food weighing method showed a satisfactory agreement beyond chance (k) (0.81 for staple food and animal source protein; 0.735 for non-animal source protein). Intraclass correlation coefficient ranged between 0.91 and 0.96 among respondents. There were no differences in energy, protein, carbohydrate, and fat intake estimated among health care staff (P=0.967; P=0.951; P=0.888; P=0.847, respectively). In conclusion, PDAT provides a valid estimation of macronutrient consumption among hospitalized adult patients.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 122 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 122 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 28 23%
Student > Master 25 20%
Student > Ph. D. Student 12 10%
Researcher 7 6%
Lecturer 4 3%
Other 17 14%
Unknown 29 24%
Readers by discipline Count As %
Nursing and Health Professions 46 38%
Medicine and Dentistry 28 23%
Engineering 4 3%
Computer Science 3 2%
Agricultural and Biological Sciences 2 2%
Other 8 7%
Unknown 31 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 January 2019.
All research outputs
#14,857,703
of 22,881,964 outputs
Outputs from Journal of Multidisciplinary Healthcare
#467
of 822 outputs
Outputs of similar age
#212,914
of 351,892 outputs
Outputs of similar age from Journal of Multidisciplinary Healthcare
#8
of 11 outputs
Altmetric has tracked 22,881,964 research outputs across all sources so far. This one is in the 33rd percentile – i.e., 33% of other outputs scored the same or lower than it.
So far Altmetric has tracked 822 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.1. This one is in the 39th percentile – i.e., 39% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 351,892 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.