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The new adventures of regulatory focus: Self-uncertainty and the quest for a diagnostic self-evaluation
... Considering that their assessment tendencies are weak, individuals classified in C3 are unlikely to be inclined to engage in detailed and comprehensive self-evaluations (Higgins, 2012b) and, thus, might be more motivated to maintain extant self-knowledge rather than acquire new one. Consequently, according to Leonardelli and Lakin's (2010) general model of self-evaluation, this tendency could be reflected in the fact that these students' selfenhancement and self-verification motives are likely to be more prevalent than their self-improvement and self-assessment ones. ...
... Moreover, a powerful assessment orientation could be related to a strong motivation to update self-knowledge in order to keep it accurate. In combination with a strong promotion focus, this motivation to change self-knowledge is posited to be associated with self-improvement rather than self-enhancement (Leonardelli & Lakin, 2010). ...
... As a result of the differential strength between promotion and prevention, self-evaluation processes for students classified in C5 are likely to focus on positive (rather than negative) selfknowledge. In turn, this emphasis is posited to be associated with self-improvement and self-enhancement concerns rather than with self-verification and self-assessment ones (Leonardelli & Lakin, 2010). ...
Model-based clustering methods, commonly referred to as finite mixture modeling, have been applied to a wide variety of cross-sectional and longitudinal data to account for heterogeneity in population characteristics. In this article, we elucidate 2 such approaches: growth mixture modeling and latent profile analysis. Both techniques are illustrated using motivation data from 2 studies. General strategies for fitting these classes of mixture models are discussed, as are extensions to other applications.
... The SDM definition of uncertainty is different from the goal-oriented definition-e.g., as lack of control (Kay et al. 2008), impossibility to have one's needs satisfied (Martin 1999), inability to process causal inferences concerning social events (Weary et al. 2010), and threat-e.g., as a trigger of anxiety ; see also Monat et al. 1972, p. 237, cited in Greco andRoger 2001), as fear of the unknown (Carleton 2016). Instead, the SDM definition partially overlaps both the view of uncertainty as destabilization of the self-e.g., self-uncertainty (Hogg 2007;van den Bos 2009), threat to self-esteem (Leonardelli and Lakin 2010) as well as death salience (Greenberg and Arndt 2011), when the latter is interpreted as a form of threat to the sense of self (van den Bos 2009). It also overlaps the view of uncertainty as violation of meaning-as failure of meaning (Proulx and Inzlicht 2012), violation of worldview (worldview violation model; Major et al. 2007), exposure to environmental complexity (Peterson and Flanders 2002), and increased entropy (Hirsh et al. 2012). ...
This paper presents a novel psychological model of the socio-cognitive management of uncertainty, the semiotic dimensional model (SDM). The SDM claims that uncertainty increases the momentum of affect-laden meanings in meaning-making. This is so because affective meanings provide a simplified interpretation of the world that restores the experience of being able to make sense of the reality destabilized by uncertainty. Moreover, the SDM models the affective meanings in terms of low-dimensional mental phase space (MPS). Each dimension of the MPS detects a facet of the context. The lower the MPS dimensionality, the lower the number of facets of the context processed, therefore, the more simplified the meaning-making is. We attained the first empirical validation of the SDM in a sample of 120 Italian people. First, the SDM assumption that the low-dimensional MPS is the computational descriptor of affective meaning was tested. Second, an experimental study was designed in which uncertainty was manipulated so as to assess its effects on the dimensionality of participants’ MPS. It was hypothesized that uncertainty induces a decrease in the MPS dimensionality. Results were consistent with both hypotheses. Theoretical implications of the SDM and its relationship with other theories are discussed and future research direction outlined.
... Although offering mHealth content that promotes positive emotions could reinforce activities that require low effort (e.g., daily self-reporting), this has not been empirically established. The second form is based on research in the area of cognitive and social psychology (Brown & Dutton, 1995;Hull et al., 1988) which indicates that people strive to manage uncertainty by seeking and attending to information about themselves (Derricks & Earl, 2019;Leonardelli & Lakin, 2010;Van den Bos, 2009). Although people are interested in receiving personalized data (Rabbi et al., 2018;Singh et al., 2016), it is unclear whether such information reinforces mHealth self-reporting. ...
Objective:
Mobile technologies allow for accessible and cost-effective health monitoring and intervention delivery. Despite these advantages, mobile health (mHealth) engagement is often insufficient. While monetary incentives may increase engagement, they can backfire, dampening intrinsic motivations and undermining intervention scalability. Theories from psychology and behavioral economics suggest useful nonmonetary strategies for promoting engagement; however, examinations of the applicability of these strategies to mHealth engagement are lacking. This proof-of-concept study evaluates the translation of theoretically-grounded engagement strategies into mHealth, by testing their potential utility in promoting daily self-reporting.
Method:
A microrandomized trial (MRT) was conducted with adolescents and emerging adults with past-month substance use. Participants were randomized multiple times daily to receive theoretically-grounded strategies, namely reciprocity (the delivery of inspirational quote prior to self-reporting window) and nonmonetary reinforcers (e.g., the delivery of meme/gif following self-reporting completion) to improve proximal engagement in daily mHealth self-reporting.
Results:
Daily self-reporting rates (62.3%; n = 68) were slightly lower than prior literature, albeit with much lower financial incentives. The utility of specific strategies was found to depend on contextual factors pertaining to the individual's receptivity and risk for disengagement. For example, the effect of reciprocity significantly varied depending on whether this strategy was employed (vs. not employed) during the weekend. The nonmonetary reinforcement strategy resulted in different outcomes when operationalized in various ways.
Conclusions:
While the results support the translation of the reciprocity strategy into this mHealth setting, the translation of nonmonetary reinforcement requires further consideration prior to inclusion in a full scale MRT. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
... e rst kind was what we called life insights; life insights are visualizations of past tracked data. We decided to include life insights because focus-group participants wanted to see their past data and prior mHealth work found that seeing pa erns in one's own data was intrinsically motivating and could encourage regular self-tracking [70,90,134,137,138]. We created seven di erent life insights that visualized past week's (i) stress, (ii) loneliness, (iii) level of fun, (iv) how new and exciting their days were, (v) free hours each day, (vi) tap count, and (vii) the number of seconds required to complete the spatial task. ...
Mobile health (mHealth) applications are a powerful medium for providing behavioral interventions, and systematic reviews suggest that theory-based interventions are more effective. However, how exactly theoretical concepts should be translated into features of technological interventions is often not clear. There is a gulf between the abstract nature of psychological theory and the concreteness of the designs needed to build health technologies. In this paper, we use SARA, a mobile app we developed to support substance-use research among adolescents and young adults, as a case study of a process of translating behavioral theory into mHealth intervention design. SARA was designed to increase adherence to daily self-report in longitudinal epidemiological studies. To achieve this goal, we implemented a number of constructs from the operant conditioning theory. We describe our design process and discuss how we operationalized theoretical constructs in the light of design constraints, user feedback, and empirical data from four formative studies.
... (i) daily stress, (ii) amount of free time in the day, (iii) degree of loneliness in the day, (iv) level [71,72,73]. People are frequently unclear about their personal abilities and they learn about themselves by attending to and seeking self-relevant information [71,72,74,75]. Consistent with this notion, previous work has demonstrated that people are interested in receiving feedback about their past self-reported experiences [76]; in fact, most health apps and wearables (e.g., fitbit) use visualizations of past data to provide feedback to their users. ...
Background:
Substance use is an alarming public health issue associated with significant morbidity and mortality. Adolescents and emerging adults are at particularly high risk because substance use typically initiates and peaks during this developmental period. Mobile health apps are a promising data collection and intervention delivery tool for substance-using youth as most teens and young adults own a mobile phone. However, engagement with data collection for most mobile health applications is low, and often, large fractions of users stop providing data after a week of use.
Objective:
Substance Abuse Research Assistant (SARA) is a mobile application to increase or sustain engagement of substance data collection overtime. SARA provides a variety of engagement strategies to incentivize data collection: a virtual aquarium in the app grows with fish and aquatic resources; occasionally, funny or inspirational contents (eg, memes or text messages) are provided to generate positive emotions. We plan to assess the efficacy of SARA's engagement strategies over time by conducting a micro-randomized trial, where the engagement strategies will be sequentially manipulated.
Methods:
We aim to recruit participants (aged 14-24 years), who report any binge drinking or marijuana use in the past month. Participants are instructed to use SARA for 1 month. During this period, participants are asked to complete one survey and two active tasks every day between 6 pm and midnight. Through the survey, we assess participants' daily mood, stress levels, loneliness, and hopefulness, while through the active tasks, we measure reaction time and spatial memory. To incentivize and support the data collection, a variety of engagement strategies are used. First, predata collection strategies include the following: (1) at 4 pm, a push notification may be issued with an inspirational message from a contemporary celebrity; or (2) at 6 pm, a push notification may be issued reminding about data collection and incentives. Second, postdata collection strategies include various rewards such as points which can be used to grow a virtual aquarium with fishes and other treasures and modest monetary rewards (up to US $12; US $1 for each 3-day streak); also, participants may receive funny or inspirational content as memes or gifs or visualizations of prior data. During the study, the participants will be randomized every day to receive different engagement strategies. In the primary analysis, we will assess whether issuing 4 pm push-notifications or memes or gifs, respectively, increases self-reporting on the current or the following day.
Results:
The microrandomized trial started on August 21, 2017 and the trial ended on February 28, 2018. Seventy-three participants were recruited. Data analysis is currently underway.
Conclusions:
To the best of our knowledge, SARA is the first mobile phone app that systematically manipulates engagement strategies in order to identify the best sequence of strategies that keep participants engaged in data collection. Once the optimal strategies to collect data are identified, future versions of SARA will use this data to provide just-in-time adaptive interventions to reduce substance use among youth.
Trial registration:
ClinicalTrials.gov NCT03255317; https://clinicaltrials.gov/show/NCT03255317 (Archived by WebCite at http://www.webcitation.org/70raGWV0e).
Registered report identifier:
RR1-10.2196/9850.
... Future research may investigate other person and context variables that may influence motivational focus. According to regulatory focus theory (Higgins 1998), people with a promotion focus are more concerned with change (i.e., improving their current state) whereas those with a prevention focus are more concerned with maintenance (i.e., not worsen their current state; see also Leonardelli and Lakin 2009). Further studies may explore whether a promotion focus makes people focus more on the future whereas a prevention focus makes them focus more on the reality. ...
The impact of implicit theories on the choice of self-regulation strategies of goal setting
... Future research may investigate other person and context variables that may influence motivational focus. According to regulatory focus theory (Higgins 1998), people with a promotion focus are more concerned with change (i.e., improving their current state) whereas those with a prevention focus are more concerned with maintenance (i.e., not worsen their current state; see also Leonardelli and Lakin 2009). Further studies may explore whether a promotion focus makes people focus more on the future whereas a prevention focus makes them focus more on the reality. ...
Personen, die glauben, ihre Fähigkeiten sind veränderbar, achten mehr auf die Zukunft als auf die Realität
Knowing what we don't yet know is critical for learning. Nonetheless, people typically overestimate their prowess—but is this true of everyone? Three studies examined who shows overconfidence and why. Study 1 demonstrated that participants with an entity (fixed) theory of intelligence, those known to avoid negative information, showed significantly more overconfidence than those with more incremental (malleable) theories. In Study 2, participants who were taught an entity theory of intelligence allocated less attention to difficult problems than those taught an incremental theory. Participants in this entity condition also displayed more overconfidence than those in the incremental condition, and this difference in overconfidence was mediated by the observed bias in attention to difficult problems. Finally, in Study 3, directing participants' attention to difficult aspects of the task reduced the overconfidence of those with more entity views of intelligence. Implications for reducing biased self-assessments that can interfere with learning were discussed.
The ways in which individuals think and feel about themselves play a significant role in guiding behavior across many domains in life. The current studies investigate how individuals may shift the positivity of self-evaluations in order to sustain their chronic or momentary motivational concerns. Specifically, we propose that more positive self-evaluations support eagerness that sustains promotion-focused concerns with advancement, whereas less positive self-evaluations support vigilance that sustains prevention-focused concerns with safety. The current studies provide evidence that self-evaluation inflation is associated with promotion concerns whereas self-evaluation deflation is associated with prevention concerns, whether regulatory focus is situationally manipulated (Studies 1, 2b, and 3) or measured as a chronic individual difference (Study 2a). Following regulatory focus primes, individuals in a promotion focus showed relatively greater accessibility of positive versus negative self-knowledge compared to individuals in a prevention focus (Study 1). In an ongoing performance situation, participants in a promotion focus reported higher self-esteem than participants in a prevention focus (Studies 2a and 2b). Finally, individuals in a promotion focus persisted longer on an anagram task when given an opportunity to focus on their strengths versus weaknesses, which was not the case for individuals in a prevention focus (Study 3). Across studies, the predicted interactions were consistently obtained, although sometimes the effects were stronger for promotion or prevention motivation. We discuss implications for existing models of the motives underlying self-evaluation.
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