Family Resilience

Research and design of technologies for collaborative cancer care.

UX Researcher
UX Designer
Aug 2022 - Current
Evaluating research for collaborative caregiving technologies for cancer through prototype design and user testing.


I am currently leading a research study to understand how caregiving challenges evolve over the course of the cancer journey. The research aims to build upon existing literature to establish caregiving best practices in the context of cancer. As part of a six-person research team, my key contributions span from conducting usability tests to analyzing user data, and designing high-fidelity prototypes.


Our lab's earlier work has identified five Family Adaptive Systems (FAS) based on the Family Resilience Theory. These systems characterize the adaptability and navigational processes families deploy throughout their cancer journey.

User Research

User Interviews

We conducted a total of 26 semi-structured interviews with families whose child was hospitalized for cancer treatment including patients at Riley Hospital for Children. The parents had children ages ranged between 3 - 15 years and considered themselves primary caregivers.

Thematic Analysis

The interviews were coded using three themes

Brainstorming and identifying key family communication challenges they faced from the start of their child’s hospitalization.
How potential technological solutions could solve their problems if implemented.
Feedback on features derived from a literature review of other relevant design papers on ​​care coordination.

Over 200 pages of transcribed conversation were themed using Atlas.ti to highlight concepts concerned with challenges, potential solutions and feedback on conventional features.

The interviews were run through three rounds of coding.

  1. First round: Decoded quotes from each participant and all the features that emerged as important.
  2. Second round: Identified specific themes based on their context to caregivers of a hospitalized child including social connections, task management, security and access, finance, connections with medical personnel, etc.
  3. Third round: placed the identified themes in the Family Adaptive Systems Framework.

The outcome of this study was a set of challenges, design features and feedback categorized under each adaptive system.

  • Dominant Themes

    Most quotes were from the Management and Control and Information systems.
  • Identified Need

    This clearly showed the need for the additional Information system in the realm of caregiving as an extension of the classical Family Resilience Model.
  • Underlying Themes

    This data was also a strong advocate of the hypothesis that health information and self-management is the key challenges faced by caregivers of chronic conditions like Cancer.

  • Lack of Sentiment differentiation

    The analysis did not differentiate between positive and negative quotes. Therefore more quotes did not necessarily signify positive attribution.
  • Participant Diversity

    Our participants also represent limited family structure diversity. We could not recruit same-sex couples or single parents.
  • Education Bias

    Our participant’s education demographics were skewed towards higher education.
  • Education Bias

Personas and Scenarios

The objective with making personas and scenario was to establish a

  • common consensus of goals and pain points for the researchers and designers on the team. We also used it to provide
  • providing context to families during usability testing.


We created a persona for a family of four whose daughter was undergoing chemotherapy. We established the biography, goals, and pain points for each of the four members of the family.


Five scenarios were created from the most important systems ( Information, Management and Control ). The scenarios aimed at empathizing with the problems outlined by the caregivers in the interviews and also visualize potential solutions to the outlined problems.


Feature Prioritization

  • Feature Development
    The team developed a set of 44 features between the five family resilience systems using
    - literature review of HCI and CSCW papers,
    - previous interview feedback
    - brainstorming sessions
  • Feature Prioritization
    To understand how caregivers prioritized the features the team conducted a card sorting session with 13 families that have had a child hospitalized for cancer. The families were asked to order the cards ( features ) in each system according to their priority.
  • Feature Ranking
    The family was allowed to give more than one feature the same priority to not to force the user to choose priority. The features were still relatively vague and a high level understanding of user preference was more important than the exact ranking of a feature.
  • Data Analysis
    The card sorting sessions were analyzed both quantitatively and qualitatively. The quantitative analysis for the Management and Control features and the ranking between systems is given in the Tableau dashboard.
  • Strong Consensus

    The top five ranked features also had the low variance showing high confidence in user preference.
  • Scope for improvement

    High variance medium rank features like "Remembering important tasks we talked about in a call using AI", were highly ranked by some but some people were completely opposed to it. If certain qualms like data-privacy ( for the feature above ) could be solved these features could be good candidates as features.
  • Normalization

    feature rankings had to be normalized to a scale of 1-10 which meant some families had their rankings diluted ( rank 1 features were converted to rank 2.5 ).
  • Selection Bias

    There was a moderate to strong correlation ( -0.625 ) between the number of features and relative importance of the systems. This could mean that the families had a bias towards the systems that appeared more important due to a higher number of features.
Ranking of features from the Management and Control System


The ideation phase was divided into two phases

  1. Low Fidelity Wireframes:
    The emphasis during the low fidelity phase was divergence into exploring all possible implementations of feature sets.
  2. User Flow Diagrams and High Fidelity Prototypes:
    The emphasis during this phase was convergence where features were reduced to highlight only important features.

Cognitive Overload

“And you want to give yourself hope by saying, okay, this is going to save the child, this intervention is going to be helpful.You continuously want to believe in these things. And this is at the top of your mind when this is ongoing. It’s just a lot of things happening.”

- Father, Family 5

The main focus of the prototyping design was reducing the complexity and information that a parent had to go through. As an example for the homepage

  1. Version 1: Included high priority features from the card sorting
  2. Version 2: Minimized visual interfaces that included only important information from each feature.
  3. Tested version: The home page still had too many features and we made the decision to design the final version based on feedback from testing instead of our assumptions.
Version 1
Version 2
Tested Version


Using insights from feature prioritization and ideation, the final prototype contains the following features

  1. Shared Calendars : Enabling everyone involved in the caregiving process to stay updated about scheduled events, appointments, and important dates.
  2. Shared To-do Lists: Collaboration among different caregivers and ensures that all important tasks are accounted for and completed in a timely manner.
  3. Syncing Medical Data: This feature allows for the synchronization of medical data across various devices. It ensures that all caregivers have access to the most up-to-date information about the patient's health status.
  4. Generating Updates and Summaries: This feature uses content from audio calls, messages, etc., to generate useful summaries and updates.
  5. Text Message Channels: This feature provides a means for caregivers to communicate using text messages. It allows for quick and easy exchange of information and updates among the caregiving team.

High Fidelity Prototype

A subset of all the features were chosen based on the following criteria

Priority of features

based on a combination of quantitative data ( ranking from the card sorting study ) and qualitative data ( feedback from transcripts of card sorting sessions and interviews ).

Importance of the feature system

to which the feature belonged. The most important systems where the Management and Control and Information systems.


Some features were deemed important but users preferred that there would be another application for them ( Financial tools ).


User Testing

The prototype has currently been tested with 8 participants. The testing is currently ongoing, we are testing for the the following

  • Use Cases for each feature and the instances of use in caregiving.
  • Usability of the features and improvements to the design.
  • Additional Features caregivers would like to see in the application.

Potential Impact

This research has the potential to improve caregiver collaboration and reduce burden.

Social Connection
Caregiving technology can improve their social life and overall well-being. A survey from AARP stated that 40%of caregivers reported feeling socially isolated.
According to the National Library of Medicine, caregivers of chronic conditions have a 63% higher mortality rate than non-caregivers.
According to a 2011 report from the AARP, caregivers forced to leave the workforce lose an estimated $304,000 in wages and benefits over their lifetime.