D2A: Smartphone-Based Malnutrition Screening Data from a Pilot in Kenya

A seven-month pilot study with 180 households in Kenya tested a smartphone app for self-collection of child malnutrition data. The dataset likely contains Family MUAC measurements and household drivers of wasting, comparing app-based and paper-based screening methods. Ravi Bhavnani authored this research, which was last updated on figshare in March 2026.

Use Cases

• Compare the accuracy of digital versus paper-based malnutrition classification based on the pilot study results.
• Analyze household reporting completion rates based on the described assistance from Community Health Volunteers.
• Model the cost-effectiveness of app-based data collection over time based on the reported amortized cost.
• Study the feasibility of self-reporting by caregivers in remote areas based on the described susceptibility of paper methods to interruption.

Strengths

• Data is derived from a structured seven-month pilot study involving 180 households.
• Results include specific metrics: similar classification accuracy, a 15% higher completion rate with assistance, and lower amortized cost.
• Dataset is openly licensed under CC-BY-4.0, facilitating reuse and analysis.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The 1.2 MB file size suggests a small dataset, potentially limiting analytical scope.

Provenance

Source

figshare

Collection Method

Data collected via a smartphone app (D2A) during a seven-month pilot study, with some assistance from Community Health Volunteers.

Time Range

Covers a seven-month pilot study period; specific dates are not provided.

Freshness

Last updated 2026-03-18 07:46:07; freshness should be verified.

Geography

Kenya