Managing Type 1 Diabetes (T1D) requires comprehensive tracking of various factors that impact blood sugar levels, such as diet, sleep, exercise, mood, symptoms, and insulin. However, tracking health data for children with T1D presents unique challenges, as it requires active participation from both children and their parents. This is because children often lack the knowledge and independence for data collection. Thus, collaborative efforts among children and their parents are crucial for T1D management.

Our study aims to investigate the benefits, challenges, and strategies associated with responsibilities in collaborative tracking for children with T1D and their parents. 

• First, we identify different types of tracking approaches between children and their parents in collaborative tracking.

• Second, we highlight the challenges, strategies, and benefits associated with each type.

• Third, we offer design recommendations for collaborative health tracking technologies for children and parents.

We conducted a three-week probe study, using a data collection probe (a lightweight paper + digital tracking system) customized for participants’ tracking preferences. 

A total of 22 pairs of children with T1D (ages 6-12) and their caregivers were involved in our study. 

Our findings revealed that parents and children shared responsibility for tracking in different ways, resulting in unique challenges, strategies, and benefits. We identified that tracking types were varied across two dimensions: responsibility for tracking management and responsibility for data provision.

• First, either the child or the parent took responsibility for managing tracking overall, including maintaining the log and performing the actual recording.

• Second, either the child or the parent was responsible for providing data, since the individual responsible for tracking might not have had all the answers independently.

Based on these two factors, we identified the four types of tracking, which are child-independent, child-led, parent-led, and parent-independent.

When children had the skills and knowledge to independently log their health-related information, they took responsibility for tracking management and filled in the information in the tracker by themselves. Despite their independence in tracking, some children frequently forgot to log data or made mistakes while recording. Several parents expressed concerns about their children’s overconfidence or their inability to assess whether their children were tracking accurately, especially if there were discrepancies in data recorded between them.

To overcome these challenges, parents established routines to check in with their child or reviewed their child’s logs to identify any missing logs. Through these tracking efforts, children became more aware of their T1D management and developed a feeling of independence.

Children in the child-led tracking approach took the lead in tracking while receiving support from their parents for data sourcing. Although these children showed motivation to record comprehensive data with the help of their parents, sometimes their parents did not possess all the answers to their questions, such as the exact duration of the child’s activities. Moreover, some parents felt challenged when seeking a balance between giving precise answers and not allowing the child to become over-reliant. 

As children often sought assistance from their parents, parents tried to teach their children to acquire the data themselves. To prevent children from becoming overly reliant, some parents chose to engage in discussions with their children rather than providing direct answers. Through discussions, children could learn skills related to data tracking, such as math skills for carb counting or telling time. This allowed children to become more involved in self-care.

In parent-led tracking, parents took charge of overall tracking management, while requesting data from their child.

These parents strongly believed that subjective data types, such as mood, symptoms, and sleep quality, could only be accurately obtained by the child. Some parents used a combination of their own observations and their child’s answers for more accuracy. However, since parents requested information from their children, children often had increased feelings of surveillance, generating tensions between them.

Some parents noted discrepancies between their own observations and the child’s answers, leading to less trust in their child.

To foster better communication with children, parents encouraged openness in discussions such as finding a time when children can better share their thoughts.

When parents’ observations and their child’s responses diverged, they endeavored to arrive at a consensus through negotiation. Through these strategies, children became more open to discussing their health data and child-parent had increased bonding opportunities.

Parent-independent tracking occurred when parents took the responsibility of managing data by collecting it themselves through observations. This approach was primarily used for gathering objective data types, such as carb amount and insulin dosages. However, for subjective data types such as moods or sleep quality, parents had limitations because their observation of their child could have been different from the child's actual data. For instance, although a parent thought that their child was in a good mood, the child could have been nervous.

Moreover, when parents were not physically with their child, they were only able to collect partial data.

To gather comprehensive data, parents tried to gather data from others, such as siblings or school teachers. Overall, tracking independently allowed parents to have more flexibility and collect data in a timely manner. Moreover, their tracking behavior less influenced their child compared to the parent-led tracking type, allowing children to be more independent.

The findings show that collaboration on tracking data extends beyond helping each other collect more accurate data.

The collaborative efforts allowed the participants to learn skills and share different perspectives. Thus, collaborative health technologies could be designed to support these values for data collection. As active discussions around data collection held educational value for both children and parents, technologies could suggest discussion prompts between children and their parents on the collected data. Moreover, they could guide children to learn skills related to data collection such as math skills for carb counting. Parents could be also provided with guidelines to effectively engage in discussion with their child.

Our findings also highlight the importance of sharing different perspectives through collaborative tracking. Parents often cross-referenced their observations to children’s thoughts and opinions, especially for subjective data types such as moods or symptoms. To alleviate tensions related to surveillance and agency issues, technologies should be carefully designed to foster perspective sharing and effective discussions. Such a system could also allow children to specify the extent of data sharing with their parents by selecting certain data components such as a tracking topic or time. Furthermore, to facilitate children’s sharing of different perspectives on their parents’ observation, children could be provided with an objection feature to their parents’ data.