| Title |
The My Meal Intake Tool (M-MIT): Validity of a Patient Self-Assessment for Food and Fluid Intake at a Single Meal
|
|---|---|
| Published in |
The journal of nutrition, health & aging, January 2018
|
| DOI | 10.1007/s12603-016-0859-y |
| Pubmed ID | |
| Authors |
J. McCullough, H. Keller |
| Abstract |
Hospital malnutrition is an under-recognized issue that leads to a variety of adverse outcomes, especially for older adults. Food/fluid intake (FFI) monitoring in hospital can be used to identify those who are improving and those who need further treatment. Current monitoring practices such as calorie counts are impractical for all patients and a patient-completed tool, if valid, could support routine FFI monitoring. The aim of this research was to determine whether the patient-completed My Meal Intake Tool (M-MIT) can accurately represent FFI at a single meal. Cross-sectional, multi-site. Four acute care hospitals in Canada. 120 patients (65+ yrs, adequate cognition). Participants completed M-MIT for a single meal. Food and fluid waste was visually estimated by a research dietitian at each hospital. Sensitivity (Se), specificity (Sp) and overall agreement were calculated for both food and fluid intake by comparing M-MIT and dietitian estimations to determine criterion validity of M-MIT. Patient and research dietitian comments were used to make revisions to the M-MIT. Using a cut-point of ≤50% intake, Se was 76.2% and 61.9% and Sp was 74.0% and 80.5% for solid and fluids respectively (p<0.001). M-MIT identified a greater proportion of participants (37.2%) as having low FFI (≤50%) than dietitians (25.0%), as well as a greater proportion identified with low fluid intake (28.3% vs. 24.6%). Modest revisions were made to improve the tool. This study has demonstrated initial validity of M-MIT for use in older patients with adequate cognition. Use of M-MIT could promote FFI monitoring as a routine practice to make clinical decisions about care. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 52 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 11 | 21% |
| Student > Bachelor | 10 | 19% |
| Student > Ph. D. Student | 6 | 12% |
| Researcher | 3 | 6% |
| Lecturer | 2 | 4% |
| Other | 7 | 13% |
| Unknown | 13 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Nursing and Health Professions | 16 | 31% |
| Medicine and Dentistry | 10 | 19% |
| Engineering | 2 | 4% |
| Mathematics | 1 | 2% |
| Agricultural and Biological Sciences | 1 | 2% |
| Other | 7 | 13% |
| Unknown | 15 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 01 May 2018.
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#23,084,818
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Outputs from The journal of nutrition, health & aging
#1,871
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Outputs of similar age from The journal of nutrition, health & aging
#62
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