Selected Research & Consulting Work

Examples of projects across health research, statistical analysis, evidence synthesis, mixed methods, programme evaluation and advanced analytical research.

Some project details have been anonymised or generalised to protect client confidentiality.

Clinical Data & AI

Designing Reliable Clinical Data Systems for AI-Ready Decision-Making

Development of a structured interpretation framework for complex mental health data, improving consistency and preparing the data for reliable analytical and AI use.

Clinical data · Data frameworks · AI readiness

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Clinical Statistics

Statistical Analysis of Intensive Care Unit (ICU) Data for Clinical Research

Analysis of complex ICU patient data using structured data preparation, statistical testing and regression modelling to support clinical interpretation and publication.


Clinical data · Regression modelling · Publication support

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Evidence Synthesis

Systematic Review & Meta-Analysis for Clinical Decision-Making

Systematic review and meta-analysis of inconsistent clinical evidence to produce a structured synthesis and support robust interpretation of findings.

Systematic review · Meta-analysis · Evidence synthesis

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Programme Evaluation

Evaluating a Public Health Programme Using Mixed Methods

Mixed-methods evaluation combining health outcomes and contextual evidence to assess programme effectiveness and support decisions around implementation and scale.

Mixed methods · Health outcomes · Programme evaluation

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Additional Applied Research

Qualitative Research & Strategy

Qualitative Analysis of Decision-Making in Complex Investment Environments

Qualitative analysis examining how practitioners make decisions under uncertainty, translating recurring themes into a structured framework for interpretation and strategy.


Qualitative analysis · Thematic analysis · Decision research

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Research Design / Framework Development

Research Design & Data Framework Development for Data-Scarce Systems

In a fragmented fisheries sector, research design and data framework were developed to transform uncertainty into actionable insight, guiding investment and policy decisions.

Research design · Data frameworks · Applied research

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Featured Research & Publication

Understanding Social Support in Online Diabetes Communities

Mixed-Methods Research · Machine Learning · Health Informatics

Exploring how individuals seek and provide social support in an online diabetes community, taking into consideration users' progressive disease state by using advanced analytical methods. Read the publication

Research Challenge in Online Health Data Analysis

Online health communities have rich, unstructured text data on patients experience. The challenge was to understand how different types of support were expressed, how support varied across stages of the condition, and how these interactions could inform research and practical interventions.

Mixed-Methods and Machine Learning Approach

Development of a mixed-methods analytical framework that combined qualitative research with supervised machine learning techniques to retain depth of insight while enabling scalable analysis to identify, quantify, and compare patterns of social support.

Statistical Analysis and Machine Learning Implementation

  • Defined and refined social support categories through qualitative analysis
  • Built and annotated a training dataset
  • Engineered linguistic and behavioural features
  • Developed and evaluated machine learning models
  • Assessed patterns across diabetes stages

1. Enabled large scale analysis of social support exchanges in an online diabetes community.

2. Revealed patterns in how individuals seek and provide support across diabetes progressive stages.

3. Provided a framework applicable to other chronic conditions and online health communities.

Key Insight

Online diabetes communities function as dynamic ecosystems of social support, where users can move between seeking support and sharing knowledge as their experiences and needs evolve. When analysed effectively, these interactions reveal how support needs differ across individuals and contexts — providing valuable insight to inform more targeted, data-driven patient support and engagement strategies.

User Data

Posts

Feature Extraction

Text signals

Model

Classification

Output

Support types

Transforming unstructured data into reliable, decision-ready insight.

Published in peer-reviewed journal.

Discuss Your Project

Whether you need support with research design, analysis, evidence synthesis, evaluation or publication, Wells can provide specialist input at the stage you need it.