abstract: Dietary self-monitoring has been shown to be a predictor of weight loss success and is a prevalent part of behavioral weight control programs. As more weight loss applications have become available on smartphones, this feasibility study investigated whether the use of a smartphone application, or a smartphone memo feature would improve dietary self-monitoring over the traditional paper-and-pencil method. The study also looked at whether the difference in methods would affect weight loss. Forty-seven adults (BMI 25 to 40 kg/m2) completed an 8-week study focused on tracking the difference in adherence to a self-monitoring protocol and subsequent weight loss. Participants owning iPhones (n=17) used the 'Lose It' application (AP) for diet and exercise tracking and were compared to smartphone participants who recorded dietary intake using a memo (ME) feature (n=15) on their phone and participants using the traditional paper-and-pencil (PA) method (n=15). There was no significant difference in completion rates between groups with an overall completion rate of 85.5%. The overall mean adherence to self-monitoring for the 8-week period was better in the AP group than the PA group (p = .024). No significant difference was found between the AP group and ME group (p = .148), or the ME group and the PA group (p = .457). Weight loss for the 8 week study was significant for all groups (p = .028). There was no significant difference in weight loss between groups. Number of days recorded regardless of group assignment showed a weak correlation to weight loss success (p = .068). Smartphone owners seeking to lose weight should be encouraged by the potential success associated with dietary tracking using a smartphone app as opposed to the traditional paper-and-pencil method. / Dissertation/Thesis / M.S. Nutrition 2012

This thesis investigates self-tracking practices of users of MyFitnessPal calorie counting app. The thesis researches everyday self-trackers users who have started using the app on their own and are not part of any self-tracking community and focuses on the practices of self-tracking. The thesis responds to the literature on self-tracking that has often neglected everyday self-trackers and practices of self-tracking. First, many studies, whether sociological investigations or human-computer interaction research, focus on members of Quantified Self (QS) community (Choe, Lee, Lee, Pratt, & Kientz, 2014; Li, Dey, & Forlizzi, 2010; Neff & Nafus, 2015; Sharon & Zandbergen, 2016). QS is a community of individuals who are interested in learning more about themselves through, oftentimes unusual and complex, self-tracking, which involves modification of existing technologies or even creation of new ones. Thus, focusing on QS members neglects the individual everyday self-trackers, their experiences and practices. Second, existing studies have mainly focused on health or social implications of self-tracking (Lupton, 2012b, 2013d, 2014a, Swan, 2012b, 2013). These include, but are not limited to, potential of self-tracking to assist diagnosis (Wile, Ranawaya, & Kiss, 2014), or behaviour change (Chiauzzi, Rodarte, & Dasmahapatra, 2015), self-tracking increasing surveillance, public pedagogy (Rich & Miah, 2014) and subjection to neoliberal values and promotion of healthism (Lupton, 2012b, 2013a) or leading to monetisation of exercise (Till, 2014). While these studies have yielded important insights, they do not help us to understand what people actually do when they self-track, i.e. what practices self-tracking involves and how people engaged in self-tracking manage them. Guided by the STS approach that highlights the importance of observing the mundane practices and need to focus on technology users, this thesis explores the practices of everyday self-trackers. The exploration of the practices of self-tracking among the everyday self-trackers is based on 31 interviews with early mid-life individuals, who were mainly recruited from gyms and shared their self-tracking experience of using the MyFitnessPal calorie counting app. The analytical chapters answer three questions: What is self-tracking by calorie counting in the everyday like? How is self-tracking by calorie counting done? What are the practices through which self-tracking affects those engaged in it? To answer the first question, I juxtapose self-tracking goals, use and effects as they are represented in the literature on the QS to those of my participants. Doing this reveals that self-tracking in the everyday is perceived and done quite differently than the QS metaphor would allow us to believe. The goals of the participants are mundane (weight loss), they do not use the sophisticated features of the app and are not interested in the historical data, the effects of the app are not life-changing and temporary closely tied to the use of the app. This stands in contrast to QS metaphor where self-tracking is geared towards continuous self-improvement, driven by intricate data analysis and biohacking. To answer the second question, I focus on self-tracking by calorie counting with MyFitnessPal as a dieting practice. I explore how self-tracking affects the daily practices as well as is incorporated in participants lives. The users, thus, aim to find an approach to temporal aspects of tracking and precision that would fit most conveniently with their other daily practices. They manipulate their use of the app to accommodate any meals that are not in their usual dieting routine. This highlights that dieting through self-tracking is not a straightforward data collection and involves practical strategies and negotiations, and can both influence and be influenced by other everyday practices. The third question focuses on quantification, that is the production and communication of numbers (W. N. Espeland & Stevens, 2008, p. 402). Quantification has usually been discussed at institutional levels, in terms of government, science or, in the case of Espeland and Sauder s (W. N. Espeland & Sauder, 2007) seminal work, in terms of academic rankings. I adopt the insights from these studies to make sense of the quantification at the individual level using MyFitnessPal. I draw out two features of individual quantification that distinguish it from institutional one, mainly that quantification is done for oneself only and it relies on self-governance. Further, I outline how quantification affects such decisions as whether to eat, what to eat and how much to eat. Quantification also works as commensuration as participants compared different foods referring to their calorie value. However, unlike in the case of institutional quantification, individual quantification did not have to be accepted unquestionably and often other values of food would be weighted in relation to calories when participants made choices what to eat. Ultimately, this thesis contributes a new perspective on self-tracking as it explores the mundanity of it. It adds fine-grained insights into the everyday practices of self-tracking by adopting a novel analytical angle that centres on practices and by exploring a neglected user group of everyday self-trackers.

abstract: The purpose of this study was to gather qualitative data on different and novel methods used to self-monitor diet and exercise during a weight loss study. Participants who used either a traditional paper and pencil method or a smart phone weight loss app for diet and exercise tracking were recruited for focus groups. Focus group discussions centered on the liked and disliked aspects of recording, perceived behavior changes, and suggestions for improved self-monitoring. Focus groups were organized based on the method of self-monitoring. The app group tracked calorie intake and expenditure via the "Lose It" app on their smart phones. The paper & pencil group recorded exercise and food intake in a journal and self-regulated diet based on recommended servings from each food group (or exchange lists). Focus group sessions were audio-recorded, transcribed and coded by the researcher and an independent coder. Results indicated that app participants liked the convenience, affordability, and user-friendly features, but wanted more nutrition advice. App participants liked self-managing their diet, not restricting certain foods or food groups and allowing for indulgences by balancing calories and exercise. Also, they desired an accurate estimation of energy expenditure from an app, based on individual characteristics (i.e., gender and age). Participants who recorded on paper liked the size for a visual layout of food entries, but desired a technology-enhanced method with an auto-calculation of calorie intake and expenditure. They also suggested increased accountability and opportunities for social support would enhance self-monitoring. Overall, an ideal technology-assisted self-monitoring app or program would be free and include an auto-calculation of calorie intake, a gender- and age- specific estimation of calories expended, easy entry of foods from a large database, the ability to enter whole recipes, nutrition information and recommendations, and be available via phone, tablet or computer (based on personal preference). / Dissertation/Thesis / M.S. Nutrition 2012

The purpose of this paper was to identify video feedback and self monitoring as a positive teaching strategy for improving the public speaking behavior in a classroom setting. An ABA withdrawal design was utilized with four adolescent, male teenage boys (ages 12-18). During the intervention, participants reviewed videotaped probes of their public speaking behavior and completed the self monitoring form. The results of the current study provided mixed results in that while some participants improved in one or more aspects of their behavior, only two of the four participants improved all aspects of their behavior. However, when taken into consideration with the anecdotal evidence provided there is some support for the use of video feedback with self monitoring to improve public speaking performance.

The present study sought to investigate the effects of meditation practice on the neural mechanisms of attention and self-monitoring by comparing a group of experienced meditators to matched controls. Self-report measures of mindfulness and self-compassion were assessed to examine whether meditation-related improvements in attention and self-monitoring were linked to increases in these qualities. Thus, differences between groups (meditator versus control) on all variables and relationships among variables (attention, self-monitoring, self-compassion, and mindfulness) were explored. Results indicate that individuals with meditation experience showed enhancement in neural networks related to selective attention and attentional allocation, as evidenced by larger P1/N1 and P3b amplitudes, relative to controls. Meditators also showed improved self-monitoring of their errors, as indexed by enhanced Pe amplitudes, when compared to controls. Importantly, greater number of years of meditation experience was linked to larger Pe amplitudes, providing evidence that more practice with meditation was associated with greater error awareness. At the same time, meditators showed greater levels of mindfulness and self-compassion when compared to controls. Importantly, each of the neural indices was linked to greater levels of mindfulness and self-compassion. Specifically, self-kindness was correlated with each of these ERP components and to percentage of alpha power during meditation, and the mindfulness facet of observing fully mediated the relationship between meditation experience and P1 amplitudes. These findings suggest that the qualities that are enhanced with meditation are associated with enhancements in attentional control and awareness of errors. This study is an exciting step toward future intervention studies that combine multiple sources of information (self-report, neural measures, and behavior) to clarify the nature of the associations among these variables so that the mechanisms of mindfulness can be more fully understood.

Multi-tiered systems of behavioral support are a promising approach for schools looking to maximize their resources while at the same time ensuring that every student's social and behavioral needs are being met. A commonly used Tier II intervention is Check-in/Check-out (CICO), wherein students check in with an adult before and after school and then receive feedback from their teachers throughout the day using a point card. Although CICO has been well supported through previous research, the intervention does require a fair amount of teacher time after each class period, and it also leaves students entirely reliant on the teacher for feedback regarding their behavioral performance throughout the day. The current study therefore examined the effectiveness and feasibility of integrating self-monitoring into CICO, called Student-Guided CICO (SG-CICO). Three elementary students were taught how to self-monitor their behavior after each class and then compare their ratings to those provided by the teacher. Teacher accuracy checks were faded back once students became consistently accurate with their self-ratings. An ABABC single subject design was used to evaluate the effect SG-CICO had on each participant's on-task and disruptive behavior. Each participant displayed (to varying degrees) increased on-task responding and reductions in disruptive behavior following implementation of SG-CICO. Students reported enjoying their participation in SG-CICO, however the acceptability of SG-CICO was met with mixed reactions from staff. Conceptual implications of these results along with a description of study limitations and directions for future research are provided.

abstract: Nutrition instruction has become more accessible; it is no longer relegated to the doctor’s office, dietitian briefing, outpatient clinic, or hospital. Now it is available in people’s hands, pockets, and purses via their smartphone. Since nutrition instruction has become more accessible, health professionals and members of the general public are increasingly interested in using smartphone apps to assist with health-related dietary changes. With more and more of the population required to follow certain dietary recommendations and/or monitor specific nutrient intake, commercially available apps may be a useful and cost-effective resource for the public. The purpose of this four-week intervention was to determine if the popular calorie counter app, MyFitnessPal, can be used to reduce sodium intake to ≤ 2,300 mg/day compared to the traditional paper-and-pencil method. This four-week randomized parallel trial enrolled 30 generally healthy adults who were 18 to 80 years of age. Participants were randomly assigned to the MyFitnessPal (“APP”) group or to the paper (“PAP”) group and required to meet three times with the researcher for screening, baseline (start), and completion of the study. There was a significant difference in the mean urinary sodium change between the APP group and the PAP group from the start of the intervention to the completion (-24.0±32.6 and 8.5±41.9 mmol/g creatinine respectively, p = 0.027). Other positive trends that resulted from the intervention included a decline in dietary sodium in both groups and a higher adherence in the APP group compared to the PAP group regarding recording method. The MyFitnessPal app proved to be a useful tool in reducing and/or monitoring sodium intake. Thus, this trial reinforces the potential of this app to be used for monitoring other nutrients, but further research needs to be conducted. / Dissertation/Thesis / Masters Thesis Nutrition 2016

The ability to diagnose deviations and predict faults effectively is an important task in various industrial domains for minimizing costs and productivity loss and also conserving environmental resources. However, the majority of the efforts for diagnostics are still carried out by human experts in a time-consuming and expensive manner. Automated data-driven solutions are needed for continuous monitoring of complex systems over time. On the other hand, domain expertise plays a significant role in developing, evaluating, and improving diagnostics and monitoring functions. Therefore, automatically derived solutions must be able to interact with domain experts by taking advantage of available a priori knowledge and by incorporating their feedback into the learning process. This thesis and appended papers tackle the problem of generating a real-world self-monitoring system for continuous monitoring of machines and operations by developing algorithms that can learn data streams and their relations over time and detect anomalies using joint-human machine learning. Throughout this thesis, we have described a number of different approaches, each designed for the needs of a self-monitoring system, and have composed these methods into a coherent framework. More specifically, we presented a two-layer meta-framework, in which the first layer was concerned with learning appropriate data representations and detectinganomalies in an unsupervised fashion, and the second layer aimed at interactively exploiting available expert knowledge in a joint human-machine learning fashion. Furthermore, district heating has been the focus of this thesis as the application domain with the goal of automatically detecting faults and anomalies by comparing heat demands among different groups of customers. We applied and enriched different methods on this domain, which then contributed to the development and improvement of the meta-framework. The contributions that result from the studies included in this work can be summarized into four categories: (1) exploring different data representations that are suitable for the self-monitoring task based on data characteristics and domain knowledge, (2) discovering patterns and groups in data that describe normal behavior of the monitored system/systems, (3) implementing methods to successfully discriminate anomalies from the normal behavior, and (4) incorporating domain knowledge and expert feedback into self-monitoring.

This research explores the relationship of self-monitoring with team leader behavior and work environment preference. Those who are high on self-monitoring demonstrate flexibility in their actions with others and are socially perceptive. They perform well in a variety of leadership positions and are viewed as leaders by group members. High self-monitoring types choose "socially" based careers, including teacher and psychologist, in which they adapt their interaction styles to effectively meet the demands of clients. The demands placed on a team leader appear to require similar characteristics to those that high self-monitoring individuals possess. As a team matures through different stages of development, the role of the leader ranges from director to facilitator to consultant. In order to effectively meet team needs, a leader must be socially sensitive to interpersonal cues and have the ability to assume various roles. In addition, given the fact that the position of team leader is a highly social type of career that requires behaviors similar to careers chosen by high self-monitoring individuals, it is likely that high self-monitors would prefer working in a team work environment over a traditional one. A survey methodology was used to assess the characteristics of 100 team members. No relationship was found between self-monitoring and flexible team leader behavior. However, when a job relevant version of a traditional self-monitoring scale was used, some of the data suggested that flexible people prefer a team work environment over a traditional one. Also, individuals who demonstrated ineffective team leader behaviors tended to show a preference towards traditional work environments.

Undergraduate male and female students enrolled in an introductory behavior analysis course with minimal instruction on self-management were given modified exploratory logs to use in a self-management project. Students self-monitored behavior via the log, constructed their own interventions, and reported changes in behavior and extent of success in a write up at course end. Changes in self-reported descriptions in the logs as well as the written results of a pre and post survey of emotional responses were counted. Successful self-management project interventions were reported by most students. Correspondence between planned and actual events increased. Negative reinforcement procedures characterized most students' intervention. Correspondence between events at pre and post and actual log reports was highest at post.