Evaluating the Effectiveness of QR-Code–Based Microlearning in Enhancing Medical Equipment Use and Maintenance among Nurses in Decentralized Health Facilities in Sri Lanka.

Last registered on December 26, 2025

Pre-Trial

General Information

Title

RCT ID

AEARCTR-0017450

Initial registration date

December 12, 2025

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published

December 26, 2025, 2:16 AM EST

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

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Primary Investigator

Name

Iroshini Dissanayake

Affiliation

Graduate School of Innovation and Practice for Smart Society, Hiroshima University

Contact Primary Investigator

Other Primary Investigator(s)

Additional Trial Information

Status

On going

Start date

2025-11-03

End date

2026-07-31

Keywords

Education, Health

Additional Keywords

Microlearning; QR codes; Medical equipment; Nurses education; Digital training

JEL code(s)

Secondary IDs

Prior work

This trial does not extend or rely on any prior RCTs.

Abstract

Purpose:
This study aims to assess whether QR-code-based microlearning can improve nurses' knowledge and equipment handling practices in a decentralized Sri Lankan hospital, and to compare the effectiveness of two microlearning modes, video + text vs voice message + text, as a key contribution to digital health training evidence.
Design/methodology/approach:
A cluster randomized controlled trial across 88 divisional hospitals assigns facilities to two intervention arms (video + text, voice message + text) or a control group. Outcomes include knowledge assessments, equipment functionality audits at baseline, 3 months, and 6 months, targeting six essential biomedical devices.
Findings:
Expected findings: Both microlearning formats are expected to improve knowledge retention and equipment functionality relative to the control group, with the video + text mode anticipated to produce stronger and more sustained gains. This comparative effectiveness component provides rigorous evidence on mode differences within QR-enabled microlearning.
Research limitations/implications:
As the study is conducted in decentralized hospitals within one province, generalizability may be limited. However, results will offer practical guidance for scaling low-cost digital training across LMIC health systems and inform future research on microlearning fidelity, sustainability, and real-world clinical integration.
Originality/value:
There is a lack of evidence to compare two microlearning modes embedded directly onto medical devices through QR codes. It demonstrates the scalable context-appropriate method to strengthen human technology interaction, improve medical equipment functionality, and support resilient and equitable health service delivery in resource-constrained settings.

External Link(s)

Registration Citation

Citation

Dissanayake, Iroshini. 2025. "Evaluating the Effectiveness of QR-Code–Based Microlearning in Enhancing Medical Equipment Use and Maintenance among Nurses in Decentralized Health Facilities in Sri Lanka.." AEA RCT Registry. December 26. https://doi.org/10.1257/rct.17450-1.0

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

Arm 1: QR Video + Text Microlearning (T1)

QR codes mounted on or near each device link to short, brand-neutral modules containing:
• a video demonstration of safe operation
• step-by-step text instructions
• pre-use safety checks
• preventive care
• first-line troubleshooting
• escalation guidance

Arm 2: QR Voice + Text Microlearning (T2)

Same content structure as T1, but multimedia is voice-instruction + text (no video).
Designed as a lightweight, low-bandwidth alternative.

Control

Usual practice during the trial period.
Hospitals receive full access to all QR modules after primary outcomes are completed.

Intervention Start Date

2025-11-18

Intervention End Date

2025-11-28

Primary Outcomes

Primary Outcomes (end points)

Nurse knowledge score (0–100)

Measured via 15–20 item multiple-choice Knowledge Assessment Questionnaire (KAQ).
Parallel forms A, B, C administered at baseline, 3 months, and 6 months.
Outcome metric: continuous (0–100).

Primary Outcomes (explanation)

Nurse Knowledge Score (0–100)
The knowledge outcome is constructed from the Knowledge Assessment Questionnaire (KAQ) consisting of 15–20 multiple-choice questions, each scored as:
1 = correct
0 = incorrect
For each nurse at each time point:
Sum all correct responses
Divide by the total possible score
Multiply by 100

Knowledge Score = (Total Correct / Total Questions) × 100
Parallel test forms A, B, and C are used at baseline, 3 months, and 6 months to reduce recall bias, but all forms contain the same number of items and difficulty structure, allowing consistent scoring.
Thus the outcome is a continuous score (0–100).

Secondary Outcomes

Secondary Outcomes (end points)

Equipment Functionality (Ready / Not Ready)

Binary classification using the Equipment Functionality Audit (EFA).
Percentage Ready per hospital will also be analyzed.

Secondary Outcomes (explanation)

Equipment Functionality (Ready / Not Ready)
This outcome is constructed using the Equipment Functionality Audit (EFA).
Each target device (defibrillator, syringe pump, ECG, autoclave, bedside monitor, suction machine) is assessed for:
Power/battery
Cables and accessories
Alarms and self-test
Cleanliness
Labeling
Critical components specific to the device

Each device is classified as:
Ready = 1 (all essential components functioning)
Not Ready = 0 (any critical failure)

At the hospital level, two metrics will be constructed:
Binary outcome per device:
Ready (1) vs Not Ready (0).
Hospital-level percentage Ready:
% Ready = (Number of Ready devices / Total assessed devices) × 100.
The binary variable will be used for the mixed-effects logistic regression (primary), while the percentage score is used for descriptive summaries and robustness checks.

Experimental Design

This study is a three-arm cluster randomized controlled trial evaluating whether QR-code–based microlearning improves nurses’ knowledge and medical equipment functionality in decentralized health facilities in Sri Lanka. The trial is conducted in 88 divisional hospitals in the Central Province. Hospitals serve as the unit of randomization, and all nurses working in clinical wards that routinely use the target devices are eligible to participate.

Hospitals are randomly assigned in equal proportions to one of three groups:

Treatment 1: QR codes linking to short video-based microlearning modules with accompanying text

Treatment 2: QR codes linking to audio-based microlearning modules with accompanying text

Control: Usual practice, with no QR codes provided during the study period

Outcomes are measured at baseline, 3 months, and 6 months.
The primary outcome is nurses’ knowledge, assessed using a standardized multiple-choice questionnaire scored on a 0–100 scale.
The secondary outcome is medical equipment functionality, measured using a structured audit that classifies devices as Ready or Not Ready.

The trial is designed to compare each microlearning approach to usual practice, and to compare the two microlearning formats with each other. All analyses will follow an intention-to-treat framework and will account for the clustered design.

Experimental Design Details

Not available

Randomization Method

Randomization was performed in the office using computer-generated random numbers. Hospitals were randomized in a 1:1:1 allocation to the three arms, with stratification by district and hospital type to ensure balanced distribution across study groups.

Randomization Unit

The hospital is the unit of randomization. All 88 divisional hospitals are randomized as clusters into one of the three study arms. Individual nurses are not randomized.

Was the treatment clustered?

Yes

Experiment Characteristics

Sample size: planned number of clusters

88 divisional hospitals

Sample size: planned number of observations

Approximately 500 nurses

Sample size (or number of clusters) by treatment arms

28 divisional hospitals in Treatment 1 (QR video + text)
28 divisional hospitals in Treatment 2 (QR voice + text)
32 divisional hospitals in Control (usual practice)

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Power calculation: Minimum Detectable Effect Size for Main Outcomes For the primary outcome (nurse knowledge, 0–100 scale), with 88 hospitals (average cluster size ≈ 6; total N ≈ 522 nurses, ≈174 per arm) and an assumed intracluster correlation ICC in the range 0.03–0.05, the design effect is approximately 1.15–1.25. Under these assumptions, the trial has 80% power at α = 0.05 (two-sided) to detect a standardized mean difference of about d = 0.35–0.40. On the 0–100 knowledge scale, assuming a standard deviation ≈ 20 points, this corresponds to a minimum detectable effect of roughly 7–8 points, i.e. a 7–8 percentage-point increase in knowledge scores between treatment and control arms. For the secondary main outcome (device functionality: Ready vs Not Ready), with the same cluster structure, the study is powered to detect an improvement of roughly 10–15 percentage points in the proportion of devices classified as Ready at 6 months, depending on the true ICC for device readiness.

Supporting Documents and Materials

IRB

Institutional Review Boards (IRBs)

IRB Name

Graduate School of Humanities and Social Sciences, Hiroshima University

IRB Approval Date

2025-09-26

IRB Approval Number

HR-LPES-003217

IRB Name

Faculty of Allied Health Sciences, University of Peradeniya, Sri Lanka

IRB Approval Date

2025-09-25

IRB Approval Number

AHS/ERC/2025/152 | September 25, 2025

Analysis Plan