The HEADWIND Study - Part 2

Accuracy of the HEADWIND-model will be assessed using real car driving data recorded in progressive hypoglycemia and driving data will be analysed using applied machine learning technology for hypoglycemia detection.

Change of swerving during driving in hypoglycemia (< 3.9mmol/L) will be compared to euglycemia (5.5 mmol/L). Driving parameters will be recorded by the study car.

Change of spinning during driving in hypoglycemia (< 3.9mmol/L) will be compared to euglycemia (5.5 mmol/L). Driving parameters will be recorded by the study car.

Change of velocity during driving in hypoglycemia (< 3.9mmol/L) will be compared to euglycemia (5.5 mmol/L). Driving parameters will be recorded by the study car.

Change of steer during driving in hypoglycemia (< 3.9mmol/L) will be compared to euglycemia (5.5 mmol/L). Driving parameters will be recorded by the study car.

Change of brake during driving in hypoglycemia (< 3.9mmol/L) will be compared to euglycemia (5.5 mmol/L). Driving parameters will be recorded by the study car.

Change of steer torque during driving in hypoglycemia (< 3.9mmol/L) will be compared to euglycemia (5.5 mmol/L). Driving parameters will be recorded by the study car.

Change of steer speed during driving in hypoglycemia (< 3.9mmol/L) will be compared to euglycemia (5.5 mmol/L). Driving parameters will be recorded by the study car.

Plasma-glucose level (mmol/L) when driving performance begins to be impaired will be assessed based on significantly altered driving parameters in serious hypoglycemia (< 3.0 mmol/L) compared to euglycemia (5.5mmol/L).

Based on significantly altered driving parameters in serious hypoglycemia (< 3.0 mmol/L) driving performance based on swerving, spinning, velocity, steer, brake, steer torque and steer speed, before and after hypoglycemia will be assessed

Change of heart-rate during driving in hypoglycemia will be compared to euglycemia. Change of heart-rate will be measured with a holter-ecg and wearable devices.

Change of heart-rate variability during driving in hypoglycemia will be compared to euglycemia. Heart-rate variability will be measured with a holter-ecg and wearable devices.

Change of EDA during driving in hypoglycemia will be compared to euglycemia. EDA will be measured with wearable devices.

Change of skin temperature during driving in hypoglycemia will be compared to euglycemia. Change of skin temperature will be measured with wearable devices and a thermal camera.

Change of eye movement and gaze behaviour during driving in hypoglycemia will be compared to euglycemia. Eye movement of the participant will be recorded by a camera and an eye-tracker.

Change of facial expression during driving in hypoglycemia will be compared to euglycemia. Facial expression will be recorded by a camera.

Accuracy of dysglycemia detection using physiological data (heart-rate, heart-rate variability, skin temperature, EDA) recorded with wearable devices during the study period will be analysed using applied machine learning technology.

Using video data recorded by a camera and a thermal camera accuracy in hypoglycaemia detection will be analysed with applied machine learning technology.

Using eye-tracking data recorded by a camera and an eye-tracker (to record gaze behaviour) accuracy in hypoglycemia detection will be analysed with applied machine learning technology.

Accuracy (mean absolute relative difference, MARD) of CGM Sensor (Dexcom G6) in euglycemia (3.9 - 10 mmol/L), hypoglycemia (3.0 - 3.9mmol/L) and severe hypoglycemia (< 3.0 mmol/L) will be assessed based on plasma glucose measurements

Time-delay (minutes) of CGM Sensor (Dexcom G6) during progressive hypoglycemia (hypoglycemic clamp) will be assessed compared to plasma glucose.

Change of glucagon before driving, during driving in euglycemia (5.5mmol/L), in hypoglycemia (< 3.9mmol/L), severe hypoglycemia (< 3mmol/L) and after hypoglycemia will be assessed.

Change of GH before driving, during driving in euglycemia (5.5mmol/L), in hypoglycemia (< 3.9mmol/L), severe hypoglycemia (< 3mmol/L) and after hypoglycemia will be assessed.

Change of catecholamines before driving, during driving in euglycemia (5.5mmol/L), in hypoglycemia (< 3.9mmol/L), severe hypoglycemia (< 3mmol/L) and after hypoglycemia will be assessed.

Change of cortisol before driving, during driving in euglycemia (5.5mmol/L), in hypoglycemia (< 3.9mmol/L), severe hypoglycemia (< 3mmol/L) and after hypoglycemia will be assessed.

Insulin levels will be measured before driving, during driving in euglycemia (5.5mmol/L), in hypoglycemia (< 3.9mmol/L), serious hypoglycemia (< 3mmol/L) and after hypoglycemia will be assessed.

Blood glucose at time point of hypoglycemia detection by the HEADWIND-model will be determined.

Time point of hypoglycemia detection by CGM will be compared to time point of hypoglycemia detection by the HEADWIND-model.

Blood glucose at time point of hypoglycemia detection by the HEADWIND- model compared to glucose value of CGM at same time point will be assessed.

Diagnostic accuracy of the hypoglycaemia warning system (HEADWIND) to detect hypoglycaemia (blood glucose < 3.9 mmol/l and < 3.0 mmol/l) quantified as the area under the receiver operator characteristics curve (AUC ROC) using only driving parameters (HEADWIND-model) will be compared to the HEADWIND-model with the additional integration of physiological parameters, video and eye tracker data, in particular heart-rate, heart-rate variability, electrodermal activity (EDA), skin temperature and facial expression (HEADWINDplus-model)

Evaluation of self-estimated glucose during progressive hypoglycemia and correlation with measured blood glucose.

Evaluation of self-estimated driving-performance in severe hypoglycemia (< 3.0 mmol/L) compared to euglycemia (5.5mmol/L). Self-estimated driving performance will be assessed on a absolute 7-point scale from 0-6 (a lower value means better outcome).

Time point of self-perceived need-to-treat (hypoglycemia) compared to time point of hypoglycemia detection by the HEADWIND-model and CGM.

Correlation of perceived hypoglycemia symptoms on a scale from 0-6 (0 means better outcome) to measured blood glucose.

Correlation and comparison of perceived hypoglycemia symptoms on a scale from 0-6 (0 means better outcome) to baseline hypoglycemia awareness (Clarke-Score and Gold-Score, for both tests a score of higher or equal to 4 points indicates impaired awareness of hypoglycemia).

Driving mishaps and interventions will be assessed by the driving instructor using an assessment questionnaire with 4 questions on a 7 point Likert scale (lower value means worse outcome)

Driving performance will be assessed by the driving instructor using an assessment questionnaire with a score from 1 to 7 (7 means the best outcome)

Adverse Events will be recorded at each study visit.

Serious Adverse Events will be recorded at each study visit.

Perception of technology in general will be assessed via questionnaire based self-reports (technology readiness index) measures on the 5-point Likert Scale ranging from "strongly disagree" to "strongly agree" with a scale ranging from -2 to 2 with higher values representing a better outcome (after inversion of negative items). The total score will be averaged across participants and used individually to support the interview responses when necessary.

Pre-test experience with IVAs and technology in general will be assessed via questionnaire based self-reports (questionnaire of technology use and acceptance). The constructs Performance expectancy, Effort expectancy, Social influence, Facilitating conditions, Hedonic motivation, and Behavioural intention are measured on the 7-point Likert scale from "strongly disagree" to "strongly agree" with a scale range from -3 to 3 with higher values representing a better outcome. The construct Use is measured on the 7-point Likert scale ranging from "never" to "always" with a scale range from -3 to 3. The total score will be averaged per construct and across participants and used individually to support the interview responses when necessary.

Direct comparison of conversational turns between IVA and patient during the ecological momentary assessment and the hypoglycaemia support.

Comparison of perceived blood sugar level to measured blood glucose, perceived blood sugar level between drives (see outcome 21), and baseline hypoglycemia awareness (Clarke-Score and Gold-Score, for both tests a score of higher or equal to 4 points indicates impaired awareness of hypoglycemia).

Cognitive trust in competence with IVA will be assessed via questionnaire based self-reports (Cognitive trust in competence construct from Trust and adoption of recommendations agents questionnaire), measured on the 7-point Likert scale from "strongly disagree" to "strongly agree" with a scale range from -3 to 3 and with higher values representing a better outcome. Session alliance with IVA will be assessed via questionnaire based self-reports (item from Session Alliance Inventory), measured on the 6-point Likert scale from "not at all" to "completely" with a scale range from 0 to 5 and with higher values representing a better outcome. The questionnaire will be submitted after delivering IVA's support intervention and will be compared with the type of warning delivered (i.e. disclosure vs no disclosure).

General user experience of the EWS will be assessed via questionnaire based self-reports (questionnaire for User experience questionnaire and van der Laan scale) measured on an analogue scale with adjective at its extremes (e.g. easy to learn-hard to learn, boring-exciting, good-bad, etc.) with a scale range from 0 to 100. The scores will be averaged for each scale across participants and used individually to support the interview responses when necessary.

Acceptance and use of the EWS will be assessed via questionnaire based self-reports (questionnaire of technology use and acceptance) measured on the 7-point Likert scale from "strongly disagree" to "strongly agree" with a scale range from -3 to 3 with higher values representing a better outcome. The total score will be averaged per construct and across participants and used individually to support the interview responses when necessary.

Cognitive trust in competence and emotional trust in the recommendations from IVA will be assessed via questionnaire based self-reports (Cognitive trust in competence and emotional trust constructs from Trust and adoption of recommendations agents questionnaire) measured on the 7-point Likert scale from "strongly disagree" to "strongly agree" with a scale range from -3 to 3 and with higher values representing a better outcome. The total score will be averaged per construct and across participants and used individually to support the interview responses when necessary

Perceived working alliance with the IVA will be assessed via questionnaire based self-reports (session alliance inventory) measured on the 6-point Likert scale from "not at all" to "completely" with a scale range from 0 to 5 and with higher values representing a better outcome. The total score will be averaged per construct and across participants and used individually to support the interview responses when necessary