A novel mobile phone application to assess nutrition environment measures in low- and middle-income countries.

Food and nutrition bulletin · 2014 · Unclear · Insufficient evidence

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UnclearInsufficient evidencePaper 3027

A mobile phone application version of the Guatemala NEMS-S showed very high interrater reliability compared with the paper survey (Cohen's kappa > 0.90). Test-retest reliability ranged from kappa 0.78 to 0.91, and completion time was 5 minutes shorter with th…

Study snapshot

PublicationFood and nutrition bulletin · 2014

Study typeother

Reported directionUnclear

Evidence ratingInsufficient

Abstract

BACKGROUND: Consumer nutrition environment measures are important to understanding the food environment, which affects individual dietary intake. A nutrition environment measures survey for supermarkets (NEMS-S) has been designed on paper for use in Guatemala. However, a paper survey is not an inconspicuous data collection method. OBJECTIVE: To design, pilot test, and validate the Guatemala NEMS-S in the form of a mobile phone application (mobile app). METHODS: CommCare, a free and open-source software application, was used to design the NEMS-S for Guatemala in the form of a mobile app. Two raters tested the mobile app in a single Guatemalan supermarket. Both the interrater and the test-retest reliability of the mobile app were determined using percent agreement and Cohen's kappa score and compared with the interrater and test-retest reliability of the paper version. RESULTS: Interrater reliability was very high between the paper survey and the mobile app (Cohen's kappa > 0.90). Test-retest reliability ranged from kappa 0.78 to 0.91. Between two certified NEMS-S raters, survey completion time using the mobile app was 5 minutes less than that with the paper form (35 vs. 40 minutes). CONCLUSIONS: The NEMS-S mobile app provides for more rapid data collection, with equivalent reliability and validity to the NEMS-S paper version, with advantages over a paper-based survey of multiple language capability and concomitant data entry.

Machine Enhanced Logic

AI evidence extraction

Structured fields below were generated from the paper’s abstract and metadata to make the evidence easier to inspect. Automated extraction may be incomplete or incorrect; verify important details against the original paper.

Study typeother

Effect directionunclear

PopulationNot supplied

Sample sizeNot supplied

ExposureNot supplied

Evidence strengthInsufficientConfidence: 66% · Peer reviewed: yes

Main findings

Outcomes measured

Interrater reliability (percent agreement, Cohen's kappa)
Test-retest reliability (percent agreement, Cohen's kappa)
Survey completion time

Limitations

Pilot testing was conducted in a single Guatemalan supermarket
Only two raters were used
No sample size reported in the abstract

View raw extracted JSON

{
  "study_type": "other",
  "exposure": {
    "band": null,
    "source": "mobile phone",
    "frequency_mhz": null,
    "sar_wkg": null,
    "duration": null
  },
  "population": null,
  "sample_size": null,
  "outcomes": [
    "Interrater reliability (percent agreement, Cohen's kappa)",
    "Test-retest reliability (percent agreement, Cohen's kappa)",
    "Survey completion time"
  ],
  "main_findings": "A mobile phone application version of the Guatemala NEMS-S showed very high interrater reliability compared with the paper survey (Cohen's kappa > 0.90). Test-retest reliability ranged from kappa 0.78 to 0.91, and completion time was 5 minutes shorter with the mobile app (35 vs. 40 minutes).",
  "effect_direction": "unclear",
  "limitations": [
    "Pilot testing was conducted in a single Guatemalan supermarket",
    "Only two raters were used",
    "No sample size reported in the abstract"
  ],
  "evidence_strength": "insufficient",
  "confidence": 0.66,
  "peer_reviewed_likely": "yes",
  "keywords": [
    "mobile phone application",
    "CommCare",
    "nutrition environment measures survey",
    "NEMS-S",
    "Guatemala",
    "interrater reliability",
    "test-retest reliability",
    "survey completion time"
  ],
  "suggested_hubs": []
}

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AI-extracted fields are generated from the abstract and metadata and may be incomplete or incorrect. This material is for informational purposes and is not medical advice.

Identifiers and source

DOI: 10.1177/156482651403500302
PubMed: 25902589

Read the original paper →

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