## 4 Results
### Constructs and Methodological Approaches
#### 4.3.5 Productivity, Comfort, Emotions, Usability, Cognitive Processes, and Motion Sickness  
Researchers interested in _productivity_ collect behavioral data \(\mathrm{n_{p}}\) = 20, primarily about participants' secondary task performance (n = 6), including performance (e.g., characters per second, number of answered questions, etc.) but also engagement and accuracy (e.g., error rate) parameters (NDRT duration, frequency, or percentage). Single papers also observed participants, used eye-tracking or collected driving performance measures. In addition, only one semi-structured interview was conducted, see Table 12. In total, \(\mathrm{n_{p}}\) = 18 different parameters were collected across all papers investigating productivity. \begin{table}
\begin{tabular}{l l c} \hline \hline
**Collection Method for UX** & **Parameter** & \(\mathrm{n_{p}}\) \\ \hline \multirow{6}{*}{Standardized Questionnaire (4)} & AttrakDiff & 2 \\ \cline{2-3}  & User Experience Questionnaire (UEQ) & 1 \\ \cline{2-3}  & Van der Laan Acceptance Scale & 1 \\ \cline{2-3}  & Hedonia and Eudaimonia (HEMA) Scale & 1 \\ \cline{2-3}  & [PERSON]’s Need Scale & 1 \\ \hline Interviews (4) & Semi-structured interview & 4 \\ \hline Self-Defined Questionnaire (2) & N/D & 2 \\ \hline \multirow{6}{*}{Driving Performance (1)} & Acceleration & 1 \\ \cline{2-3}  & Brake & 1 \\ \cline{2-3}  & Speed Parameters & 1 \\ \cline{2-3}  & Number of Lane Changes & 1 \\ \hline Observation (1) & N/D & 3 \\ \hline Heart Rate Variability (1) & HR (BPM) & 1 \\ \hline UX-Curve (1) & N/D & 1 \\ \hline Think Aloud (1) & N/D & 1 \\ \hline Sorting (1) & N/D & 1 \\ \hline \hline \end{tabular}
\end{table} 
Table 11: UX collection methods and parameters. On the contrary, _comfort_ was investigated instead by self-reported data (\(n_{p}=11\)), mainly by self-defined (\(n=7\)) or standardized questionnaires (\(n=2\)), Driving Style Questionnaire (MDSI), UEQ, TAM, and UTAUT. One paper reported behavioral data about participants' acceleration, see Table 13. In total, \(n_{p}=6\) different parameters were collected across all papers investigating comfort. In addition, _emotions_ are investigated by self-reported data (\(n_{p}=12\)) using self-defined (\(n=4\)) and standardized questionnaires (\(n=4\)) like PANAS, Affect Grid, Multi-Modal Stress Questionnaire (MMSQ), Affect Scale [115], etc. Furthermore, emotions are investigated by observing facial expressions, think aloud technique or an interview (each \(n=1\)). See Table 14. In total, \(n_{p}=9\) different parameters were collected across all papers investigating emotions. Moreover, _usability_ is investigated as well mainly by self-developed (\(n=4\)) and standardized questionnaires (\(n=3\)), e.g., SUS is a popular method. Furthermore, semi-structured interviews (\(n=2\)) and the think aloud technique are also applied. Hence, solely self-reported data are collected (\(n_{p}=11\)), see Table 15. In total, \(n_{p}=4\) different parameters were collected across all papers investigating usability. \begin{table}
\begin{tabular}{l l l} \hline \hline
**Collection Method for Comfort (n)** & **Parameter** & \(n_{p}\) \\ \hline Self-Defined Questionnaire (7) & \(N/D\) & 7 \\ \hline \multirow{6}{*}{Standardized Questionnaire (2)} & Driving Style Questionnaire (MDSI) & 1 \\ \cline{2-3}  & Technology Acceptance Model (TAM) & 1 \\ \cline{2-3}  & Unified Theory of Acceptance and & 1 \\ \cline{2-3}  & Use of Technology (UTAUT) & \\ \cline{2-3}  & User Experience Questionnaire & 1 \\ \cline{2-3}  & (UEQ) & 1 \\ \hline Driving Performance (1) & Acceleration & 1 \\ \hline \hline \end{tabular}
\end{table} 
Table 13: Comfort collection methods and parameters. _Cognitive processes_, in contrast, are analyzed by self-reported (\(\text{n}_{\text{p}}\) = 4), behavioral (\(\text{n}_{\text{p}}\) = 4), and psycho-physiological data (\(\text{n}_{\text{p}}\) = 2). Thereby, most developed their own questionnaires (n = 3) and one paper used a standardized questionnaire, the Driver Stress Inventory (DSI).