The electron-density distribution in urea, CO(NH(2))(2), was studied by high-precision single-crystal X-ray diffraction analysis at 148 (1) K. An experimental correction for TDS was applied to the X-ray intensities. R(merge)(F(2)) = 0.015. The displacement parameters agree quite well with results from neutron diffraction. The deformation density was obtained by refinement of 145 unique low-order reflections with the Hansen & Coppens [Acta Cryst. (1978), A34, 909-921] multipole model, resulting in R = 0.008, wR = 0.011 and S = 1.09. Orbital calculations were carried out applying different potentials to account for correlation and exchange: Hartree-Fock (HF), density-functional theory/local density approximation (DFT/LDA) and density-functional theory/generalized gradient approximation (DFT/GGA). Extensive comparisons of the deformation densities and structure factors were made between the results of the various calculations and the outcome of the refinement. The agreement between the experimental and theoretical results is excellent, judged by the deformation density and the structure factors [wR(HF) = 0.023, wR(DFT) = 0.019] and fair with respect to the results of a topological analysis. Density-functional calculations seem to yield slightly better results than Hartree-Fock calculations.
Developing systems that motivate people to change their behaviors, such as an exercise application for the smartphone, is challenging. One solution is to implement motivational strategies from existing behavior change theory and tailor these strategies to preferences based on personal characteristics, like personality and gender. We operationalized strategies by collecting representative motivational text messages and aligning the messages to ten theory-based behavior change strategies. We conducted an online survey with 350 participants, where the participants rated 50 of our text messages (each aligned to one of the ten strategies) on how motivating they found them. Results show that differences in personality and gender relate to significant differences in the evaluations of nine out of ten strategies. Eight out of ten strategies were perceived as either more or less motivating in relation to scores on the personality traits Openness, Extraversion, and Agreeableness. Four strategies were perceived as more motivating by men than by women. These findings show that personality and gender influence how motivational strategies are perceived. We conclude that our theory-based behavior change strategies can be more motivating by tailoring them to personality and gender of users of behavior change systems.
Developing motivational technology to support long-term behavior change is a challenge. A solution is to incorporate insights from behavior change theory and design technology to tailor to individual users. We carried out two studies to investigate whether the processes of change, from the Transtheoretical Model, can be effectively represented by motivational text messages. We crowdsourced peer-designed text messages and coded them into categories based on the processes of change. We evaluated whether people perceived messages tailored to their stage of change as motivating. We found that crowdsourcing is an effective method to design motivational messages. Our results indicate that different messages are perceived as motivating depending on the stage of behavior change a person is in. However, while motivational messages related to later stages of change were perceived as motivational for those stages, the motivational messages related to earlier stages of change were not. This indicates that a person's stage of change may not be the (only) key factor that determines behavior change. More individual factors need to be considered to design effective motivational technology.
We present a comparative analysis of motivational messages designed with a theory-driven approach. A previous study [4] involved crowdsourcing to design and evaluate motivational text messages for physical activity, and showed that these peer-designed text messages aligned to behavior change strategies from theory. However, the messages were predominantly rated as motivating in the later stages of behavior change, not in the earlier stages, including those strategies intended for the earlier stages. We speculated that the peers that designed the messages aligned to the strategies did not have sufficient expertise to motivate people in earlier stages. Therefore, we replicated the study with experts. We found that for two of the strategies expert-designed messages were found more motivating in the earliest stage, while for several of the strategies peer-designed messages were rated more motivating for later stages. We conclude that when using these strategies in behavior change technology, expert-designed messages could be more motivating in the earliest stage, while peer-designed messages could be more motivating in the later stages.
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