## 4 Discussion
### RQ2: Participant Emergent Personas
#### 4.2.3 Nora the Non-Starter  
* **Attitude:** I wait until everyone else in my neighborhood gets the technology before I bother. I give technology exactly one chance to work. If it doesn't, then I want to throw it out. * **Technology experience:** Limited; I only use the basics like phone calls, emails, texting, Twitter (X), and Facebook messaging. I can be convinced to use technology if it has a functional use that I need, like with my Bluetooth hearing aid and off-brand robot vacuum cleaner. * **Support from others:** I do not have people in my life to help me use new technology. This means that if I can't figure out how to use it on my own right away, I probably won't use it at all. * **Life situations:** It takes other people to keep me going with using technologies in routines, especially if the routines require energy from me. If I don't have this support, anything new will fade away. * **Personality:** I am steadfast. Once I make up my mind about technology, the technology, and other people cannot change my mind. If other people think the technology is easy to use, but I can't make it work, it is probably the fault of the technology, and not worth my effort trying to make it work. * **Emotional connection:** I feel no emotional connection to most technologies. Some new technologies only take up space. * **Progress through acceptance phases:** I have high expectations of technology, and if it does not work the way I think it should, I will only find disadvantages in it and discard it quickly, skipping to a Non Use phase without fully experiencing the technology. It is possible for me to form routines with the technology, but only if somebody else creates these routines and makes the technology automatically work for me. 3 RQ3: How to Identify Which Phases Are Occurring and Suggested Changes to Longitudinal Technology Acceptance Framework  
Based on this research, we have several recommendations for improving longitudinal technology acceptance studies. We propose a new method for identifying acceptance phases, which acknowledges the fluidity of the phased framework of longitudinal technology acceptance. We have new recommendations for coding participant responses as fitting in each phase. Finally, we have recommendations for improved interview questions to help researchers keep from biasing participant responses toward certain acceptance phases. First, we propose a new method for identifying which phase(s) participants are in. In prior work, researchers labeled phases based on the expected timeline and which phase was dominantly coded for the average participant at each given time [9; 58; 96; 97]. In this research, we found that phases were not so clean-cut, with evidence of participantsexperiencing multiple phases at once and progressing through the phases in different orders. To better suit these data, we propose a new method of identifying which phase(s) each participant is in during a given session, based on observing \"peaks\" in phase codes. We refer readers to Section 3.1 for a detailed description of our novel method. This method allows for more nuance and precision in understanding individuals' experiences. We also have new recommendations for how researchers should code participant responses as fitting into a phase. For example, when participants noticed the disadvantages of the robots, this is currently coded as evidence for the \(\textbf{Identification}_{6}\) phase. However, we found that often it instead signaled that people did not like the robot, would not use it, and might progress toward the disuse phase. Thus, we provide a more detailed coding guideline to help future researchers more accurately determine what acceptance phase(s) participants are in (Appendix E). Finally, we recommend changes for interview questions for longitudinal studies on technology acceptance phases. Interview sessions should avoid questions that directly point to codes from the phases, as it will increase that phase's appearance at various intervals rather than when it naturally appears for individuals.