## 4 Results  
### Qualitative Study of Acceptability According to the Role Assumed  
In total, 632 responses were analyzed and placed in one of four possible categories (U+; U\(-\); T+; T\(-\)). This categorization was determined either unanimously (for 56% of responses) or by majority (for 19.7% of responses). A response categorized differently by each of the three judges was discarded (\"N/A\" category--26.3% of responses). Table 1 gives some examples of the responses collected and their distribution in the different possible categories. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**U+** & **U\(-\)** & **T+** & **T\(-\)** \\ \hline \multicolumn{4}{c}{“Can allow me to} \\ \multicolumn{4}{c}{detect an anomaly and} \\ \multicolumn{4}{c}{see if I’m not too far in} \\ \multicolumn{4}{c}{the red”;} \\ \multicolumn{4}{c}{“Allows me to evaluate} \\ \multicolumn{4}{c}{a person’s cardiac} \\ \multicolumn{4}{c}{\begin{tabular}{c} a \\ capacity, how far they \\ can go and schedule \\ workouts”; \\ \"It will reassure my \\ wife\"; \\ \"It reassures me to be \\ monitored\" \\ \"Allows you to know \\ what you have done \\ and have cardio data\"; \\ \"Allows for activity \\ tracking and remote \\ control\"; \\ \"Allows me to manage \\ my effort by looking at \\ the phone during the \\ activity\" \\ \end{tabular} & \
\begin{tabular}{c} “Does not show the \\ most interesting data”; \\ \"I am already equipped: \\ this tool can generate \\ stress and \\ over-control”; \\ “I am afraid of doing \\ something stupid.” \\ \end{tabular} &
\begin{tabular}{c} “Bad ergonomics: too many \\ devices to carry”; \\ “I couldn’t look at it while I was \\ pedaling”; \\ “It lacks geolocation to call for \\ “The use seems complex” \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Examples of Verbatim by Category and Response Time—SHERPAM project. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Role Mobilized for the** & **N** & **Valence** & **N** & **\%** \\ \hline \multicolumn{4}{c}{Future User (U)} & 266 & + & 195 & 30.9\% \\ \multicolumn{4}{c}{-} & \multicolumn{1}{c}{-} & 71 & 11.2\% \\ \hline \hline \multicolumn{4}{c}{Taster (T)} & 200 & + & 20 & 3.2\% \\ \hline \multicolumn{4}{c}{Subtotal} & & 466 & 73.7\% \\ \multicolumn{4}{c}{N/A} & & 166 & 26.3\% \\ \hline \multicolumn{4}{c}{Total} & & 632 & 100.0\% \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Categorization of qualitative data—SHERPAM project. Finally, the main role of each participant (using the answers they gave) was categorized for each measurement time: those with a majority of \"U\"-oriented answers were identified as participants in the role of future users. Those with a majority of \"T\" responses were identified as participants in the role of tester. When it was not possible to identify a majority role, the most frequently answers were used to select the role associated with it (one case at D0 which used the answer U+ three times out of six). If there was no majority response, the participant was removed from the analysis (one case at D + 21). Thus, each participant was placed in one of the two groups created on the basis of this categorization (U vs. T), whose behavioral intention can be compared. The first result shows that the raw frequency of occurrence of each response category differs significantly between D0 and D + 21. Indeed, the dispersion of responses reveals a complete inversion of the participants' positioning (Figure 3). While the majority of the answers collected at D0 were oriented towards a future user position (the aggregation of U+ and U\(-\), i.e., 68.3%--of which 73.5% were positively valenced answers), at D + 21 the answer were oriented towards a tester position since they represented 52.6% (i.e., T+ and T\(-\)) of the answers (of which 93.9% were negative) reported a judgment on the technology (\(\chi^{2}\) (466) = 190.20; \(p<0.001\)).