2017
DOI: 10.1007/s00779-017-1025-1
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A word of advice: how to tailor motivational text messages based on behavior change theory to personality and gender

Abstract: 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 … Show more

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Cited by 49 publications
(40 citation statements)
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“…However, the same message was sent to all participants in the POW condition, regardless of the specific status of each participant. In a later work, the same researchers, who created the original corpus, conducted additional research and found that these motivational messages could be more effective if their delivery is tailored on the personality and gender of the recipient [20], or even the designer of the message, i.e., an expert or a peer [18]. This is one aspect that should be considered in future research involving motivational messages.…”
Section: Discussionmentioning
confidence: 98%
See 1 more Smart Citation
“…However, the same message was sent to all participants in the POW condition, regardless of the specific status of each participant. In a later work, the same researchers, who created the original corpus, conducted additional research and found that these motivational messages could be more effective if their delivery is tailored on the personality and gender of the recipient [20], or even the designer of the message, i.e., an expert or a peer [18]. This is one aspect that should be considered in future research involving motivational messages.…”
Section: Discussionmentioning
confidence: 98%
“…Therefore, the estimates of the DID study are obtained from the interaction terms in the underlying regression used previously in the within group study. These coefficients and their p-values are reported in Table 10 20 . The difference of IMI scores between the FIX and CON groups decreased by 0.63 points between the beginning and the end of the experiment 21 (95% CI, −1.07 to −0.20, p < .01).…”
Section: H1mentioning
confidence: 99%
“…This differs to other works on the development of other such SARs or chatbots which have typically utilised theoretical models from psychology (e.g. behaviour change theory [39]), ethnographic observations of human interactions [31] or machine learning (e.g. [5,23]).…”
Section: Studying Conventional Therapy To Inform Sar Designmentioning
confidence: 89%
“…In addition, because this is the type of self-quantification experience we focus on, research related to trait theory in psychology has shown that relying on the user's personality traits is also interesting to better support behavior change through exercise adherence [43][44][45][46].…”
Section: Learning Phasementioning
confidence: 99%