Feedback Messages Research Articles

Feedback literacy as a model to explore how learners respond to feedback.

Clinicians spend a considerable part of their time while supervising trainees providing feedback. It is generally accepted that feedback can play a major role in subsequent academic performance. Traditionally it was thought that all feedback was good feedback, that inevitably improved learner outcomes. This has been challenged and it is now understood that feedback can have a beneficial or deleterious effect on the student. A number of factors can affect a learner's response to feedback. The concept of feedback literacy is helpful to understanding these responses - this describes the processes by which a learner makes sense of feedback and subsequently uses it to enhance learning. A learner who is feedback literate can recognise when they are getting feedback and understand how it relates to their progress; they can process it effectively both cognitively and emotionally, and they can put it in to action in ways which benefit their learning. Modifiable and non-modifiable factors can influence feedback literacy, with modifiable factors including feedback standards and supervisor behaviours. Providing clear feedback expectations, ensuring accuracy of feedback messages and focusing on the relationship between the teacher and learner have the most evidence for their effect on facilitating feedback literacy.

Better with GPs as managers? – Variation in perceptions of feedback messages, goal-clarity and performance across manager´s in Swedish primary care

BackgroundPrimary care in several countries is developing towards team-based and multi-professional care, requiring leadership and management capabilities at the primary care practice level. This article reports findings from a study of primary care managers in Sweden, focusing variation in performance and perceptions of feedback messages and goal-clarity, depending on managers’ professional background.MethodsThe study was designed as a cross-sectional analysis of primary care practice managers’ perceptions combined with registered data on patient-reported performance. Managers perceptions was collected through a survey to all 1 327 primary care practice managers in Sweden. Data about patient-reported performance was collected from the 2021 National Patient Survey in primary care. We used bivariate (Pearson correlation) and multivariate (ordinary least square regression analysis) statistical methods to describe and analyse the possible association between managers’ background, responses to survey statements and patient-reported performance.ResultsBoth GP and non-GP managers had positive perceptions of the quality and support of feedback messages from professional committees focusing medical quality indicators, although managers perceived that the feedback facilitated improvement work to a lower degree. Feedback from the regions as payers scored consistently lower in all dimensions, especially among GP-managers. Results from regression analysis indicate that GP-managers correlate with better patient-reported performance when controlling for selected primary care practice and managerial characteristics. A significant positive relationship with patient-reported performance was also found for female managers, a smaller size of the primary care practice and a good staffing situation of GPs.ConclusionsBoth GP and non-GP managers rated the quality and support of feedback messages from professional committees higher than feedback from regions as payers. Differences in perceptions were especially striking among GP-managers. Patient-reported performance was significantly better in primary care practices managed by GPs and female managers. Variables reflecting structural and organizational, rather than managerial, characteristics contributed with additional explanations behind the variation in patient-reported performance across primary care practices. As we cannot exclude reversed causality, the findings may reflect that GPs are more likely to accept being a manager of a primary care practice with favourable characteristics.

Characteristics of productive feedback encounters in online learning

ABSTRACT Understanding how students engage with feedback is often reduced to a study of feedback messages that sheds little light on effects. Using the emerging notion of feedback encounters as an analytical lens, this study examines what characterizes productive feedback encounters when learning online. Drawing from a cross-national digital ethnographic dataset, a qualitative analysis categorized feedback encounters within this dataset: While most encounters led to instrumental impacts without any significant reflections, students also engaged in encounters with more substantive impact on learning. The latter took place under two conditions. First, the encounter must challenge the student’s assumptions about their work, and they must be able and willing to accept this challenge. Second, the encounter must take place at a time which is appropriate in relation to whichever task the student is currently working on. This highlights design considerations, such as importance of social interactions, and the instrumental enactments of self-generated feedback.

The Effect of Automated Error Message Feedback on Undergraduate Physics Students Learning Python: Reducing Anxiety and Building Confidence

STEM fields, such as physics, increasingly rely on complex programs to analyse large datasets, thus teaching students the required programming skills is an important component of all STEM curricula. Since undergraduate students often have no prior coding experience, they are reliant on error messages as the primary diagnostic tool to identify and correct coding mistakes. However, such messages are notoriously cryptic and often undecipherable for novice programmers, presenting a significant learning hurdle that leads to frustration, discouragement, and ultimately a loss of confidence. Addressing this, we developed a tool to enhance error messages for the popular Python language, translating them into plain English to empower students to resolve the underlying error independently. We used a mixed methods approach to study the tool’s effect on first-year physics students undertaking an introductory programming course. We find a broadly similar distribution of the most common error types to previous studies in other contexts. Our results show a statistically significant reduction in negative student emotions, such as frustration and anxiety, with the mean self-reported intensity of these emotions reducing by (73 ± 12)% and (55 ± 18)%, respectively. This led to a corresponding decrease in discouragement and an increase in student confidence. We conclude that enhanced error messages provide an effective way to alleviate negative student emotions and promote confidence. However, further longer-term investigations are necessary to confirm if this translates into improved learning outcomes. To our knowledge, this is the first physics-specific investigation of the effect of Python error message enhancement on student learning.

Engaging Students in Retrieval Practice Over Academic Breaks

Students lose valuable ground over breaks from school, and this issue is even more problematic given the detrimental effects of the COVID-19 pandemic on student progress and learning. The Keep in School Shape (KiSS) Program represents a way of engaging students in reviewing previously learned material that they need to maintain over academic breaks. The KiSS program repurposes existing online survey software to nudge students to engage in daily retrieval practice opportunities via text message or email, together with supporting resources, including hints, solutions, and empowering feedback messages. This paper describes the design of the KiSS Program and presents select results for a run of the KiSS Program during the 2022 winter break involving introductory level Calculus students at a large university. Findings indicate that such a program can get students to voluntarily rehearse previously learned material over breaks from school, and that students use the program in ways that are consistent with a growth mindset.

The Importance of Instructor Affirming Messages in Business Communication Students’ Writing Apprehension

Through the guidance of social presence theory, this study sought to understand how instructors’ affirming messages and social presence behaviors affect students’ writing apprehension in online business communication courses. The data were consistent with two models, both of which indicate that instructor affirming messages indirectly affect students’ writing apprehension in the business communication classroom. Both models also indicate that students’ burnout mediates that indirect effect. The results show how important it is for instructors to take the time to leave affirming message feedback when teaching business communication online.

One-of-a-kind products: Leveraging strict uniqueness in mass customization

This research examines product uniqueness in its most pure form—products that are literally one of a kind. It does so in mass customization (MC) settings where consumers configure their own products. Due to extremely large solution spaces that are typically available in MC, a specific product configured by a consumer is often one of a kind in that it has never been produced before. How might firms leverage such strict product uniqueness to enhance consumer value? A natural way of doing so is to simply inform consumers that the product they have configured is one of a kind—through a feedback message that is either present-oriented (e.g., “this specific product has never been produced before”) or future-oriented (e.g., “this product will remain one of a kind in perpetuity”). Evidence from five experiments, including a large-scale field experiment, shows that one-of-a-kind feedback can cause a substantial increase in consumers’ product valuation. This value-enhancing effect of one-of-a-kind feedback specifically occurs in product domains that are primarily matters of subjective taste. By contrast, such feedback tends to reduce consumers’ product valuation in domains that are primarily matters of objective quality. These findings advance our understanding of the concept of product uniqueness, and of how firms can harness the one-of-a-kindness of mass-customized products to unlock consumer value.

Developing Writing Self-Efficacy: Perspectives from Agricultural Communications Students

While there is mounting consensus writing is an essential skill required of agricultural communications graduates, there are opposing views as to what educators can do to improve students’ writing education and performance. Self-efficacy research provides one perspective for exploring the relationship between students’ performance and their beliefs in their writing abilities. The purpose of this study was to qualitatively explore how agricultural communications students perceive their writing self-efficacy and what underlying sources shape their self-efficacy beliefs. The findings confirmed agricultural communications students use a variety of sources to inform their self-efficacy beliefs including their interpretations of their writing performance and education; interactions with modeling and assignment expectations; feedback messages and their perceived value of writing; feelings of anxiety and optimism; self-regulated learning strategies, such as prewriting and drafting processes; different types of writing, such as academic writing versus industry writing; and different types of courses, including agricultural science and communications courses. Overall, the results were consistent with previous writing self-efficacy studies, however the differentiation between the types of courses students enroll in provided a new direction for self-efficacy research. Recommendations for practice are provided on enhancing agricultural communications students’ writing self-efficacy and improving writing instruction. Future research is needed to determine how other cognitive, behavioral, and environmental influences impact writing development.

The Use of Evaluation Panels During the Development of a Digital Intervention for Veterans Based on Cognitive Behavioral Therapy for Insomnia: Qualitative Evaluation Study.

Individuals enrolling in the Veterans Health Administration frequently report symptoms consistent with insomnia disorder. Cognitive behavioral therapy for insomnia (CBT-I) is a gold standard treatment for insomnia disorder. While the Veterans Health Administration has successfully implemented a large dissemination effort to train providers in CBT-I, the limited number of trained CBT-I providers continues to restrict the number of individuals who can receive CBT-I. Digital mental health intervention adaptations of CBT-I have been found to have similar efficacy as traditional CBT-I. To help address the unmet need for insomnia disorder treatment, the VA commissioned the creation of a freely available, internet-delivered digital mental health intervention adaptation of CBT-I known as Path to Better Sleep (PTBS). We aimed to describe the use of evaluation panels composed of veterans and spouses of veterans during the development of PTBS. Specifically, we report on the methods used to conduct the panels, the feedback they provided on elements of the course relevant to user engagement, and how their feedback influenced the design and content of PTBS. A communications firm was contracted to recruit 3 veteran (n=27) and 2 spouse of veteran (n=18) panels and convene them for three 1-hour meetings. Members of the VA team identified key questions for the panels, and the communications firm prepared facilitator guides to elicit feedback on these key questions. The guides provided a script for facilitators to follow while convening the panels. The panels were telephonically conducted, with visual content displayed via remote presentation software. The communications firm prepared reports summarizing the panelists' feedback during each panel meeting. The qualitative feedback described in these reports served as the raw material for this study. The panel members provided markedly consistent feedback on several elements of PTBS, including recommendations to emphasize the efficacy of CBT-I techniques; clarify and simplify written content as much as possible; and ensure that content is consistent with the lived experiences of veterans. Their feedback was congruent with previous studies on the factors influencing user engagement with digital mental health interventions. Panelist feedback influenced multiple course design decisions, including reducing the effort required to use the course's sleep diary function, making written content more concise, and selecting veteran testimonial videos that emphasized the benefits of treating chronic insomnia symptoms. The veteran and spouse evaluation panels provided useful feedback during the design of PTBS. This feedback was used to make concrete revisions and design decisions consistent with existing research on improving user engagement with digital mental health interventions. We believe that many of the key feedback messages provided by these evaluation panels could prove useful to other digital mental health intervention designers.

Abstract P235: The Association Between Neighborhood Walkability and Physical Activity in a Behavioral Weight Loss Trial Testing the Addition of Remotely Delivered Feedback Messages to Self-Monitoring

Background: Adding feedback messages (FB) to self-monitoring (SM) may reinforce behavior change. However, socio-environmental conditions (e.g., limited access to parks and low walkability) may limit one’s ability to respond to FB focused on physical activity (PA). Hypothesis: Residents of high walkability neighborhoods will achieve higher PA levels at 12 months than those in low walkability neighborhoods regardless of whether FB was randomly assigned. Methods: This is a secondary analysis of a 12-month behavioral weight loss trial, where adults with overweight or obesity were randomized to SM+FB (n=251) or SM alone (n=251). The SM+FB group received a smartphone pop-up message every other day tailored to their PA data. Assessment included neighborhood walkability via Smart Walk Score (low [<50] vs. high [≥50]), moderate to vigorous PA (MVPA) minutes and step count via Fitbit Charge 2™, and weight via digital smart scales. We report adjusted regression coefficients (b) with 95% confidence intervals from linear mixed modeling. To normalize the residual distribution, we applied a natural log transformation (ln) to MVPA. Results: Participants (N=502) were primarily white (82.5%), female (79.5%), well-educated (16.4±2.8 years), mean age of 45±14.4 years with a body mass index (BMI) of 33.10±3.93 kg/m 2 . Compared to those from neighborhoods with high walkability, participants from neighborhoods with low walkability were more likely to be White (75.3% vs. 87.8%, P ==.0003) and older (41.4±14.7 vs. 47.7±13.6 years, P <.0001) at baseline. After adjusting for these characteristics, baseline BMI and exercise self-efficacy, neighborhood walkability did not moderate the effect of treatment assignment on lnMVPA (b±SE=-0.20±0.15, P =.170) or steps (b±SE=-816.48±484.83, P =.092) over 12 months. lnMVPA (b±SE=0.12±0.10, P =.244) and steps (b±SE=415.05±344.50, P =.228) were on average similar between walkability groups. Both lnMVPA (b 6mo ±SE=0.003±0.07, P =.968; b 12mo ±SE=-0.23±0.08, P =.009) and steps (b 6mo ±SE=-416.18±195.68, P =.034; b 12mo ±SE=-1443.75±227.49, P <.0001) declined over time. On average, the SM+FB group had greater lnMVPA (b±SE=0.23±0.12, P =.047) and marginally greater number of steps (b±SE=674.84±392.91, P =.086) than SM group. There were no significant interactions for group and time or group, time, and walkability ( P ≥.05). Conclusion: On average, FB had a small but significant positive impact on PA over 12 months, but neighborhood walkability did not moderate the treatment effect of FB on PA. The small effect of FB on PA may have limited our ability to detect moderation of neighborhood walkability on the treatment effects of FB on PA. Future studies need to replicate this analysis in a trial with larger treatment effects and a more diverse sample.

Abstract P399: The Effect of Self-Monitoring of Diet, Weight and Steps and Adherence to Diet, Fat and Physical Activity Goals on Weight Loss at 12 Months: Smarter RCT

Introduction: Self-monitoring (SM) is the core of behavioral weight loss. Efficacy evidence for mHealth to improve SM adherence and impact weight loss outcomes is limited. Purpose: Examine associations among diet, weight, and physical activity (PA) SM and adherence to diet, fat and PA goals on weight loss at 12 mos in adults with overweight or obesity. Methods: SMARTER was a single-site, 2-arm weight loss trial. We randomized adults with (BMI) 27-43 kg/m 2 to diet, weight, and PA SM plus tailored feedback messages (SM+FB, n=251) or SM alone (n=251). The SM+FB group received feedback messages via the SMARTER app on diet daily, PA every other day and weight weekly. The study provided Fitbit Charge 2™ for PA, smart scales for weight and Fitbit app for diet. Participants received individualized daily calorie/fat goals (based on sex & weight) and incremental weekly PA goals to reach ≥300 min/wk of moderate- and vigorous-intensity PA. Staff measured weight at baseline, 6 and 12 mos. Diet SM was the % of days with ≥50% of calorie goal recorded. Weight SM was the % of days with weight recorded. PA SM was % of days with ≥500 steps. Calorie goal adherence was % of days with ≥85% and <115% of calorie goals and fat goals as ≤25% of calorie goals. PA goal adherence was the average % of weekly MVPA meeting the PA goal for ≥4 days/wk. Weight loss at 12 mos was computed as the % of change in weight from baseline to 12 mos relative to baseline weight. We compared diet, weight and PA SM and adherence to calorie, fat and PA goals by treatment assignment using Wilcoxon rank-sum tests. The effect of diet, weight and PA SM and adherence to calorie, fat and PA goals on weight loss at 12 mos was examined using separate linear regression models considering treatment assignment and interaction effects. Results: The sample (N=502) was 82% white (n=414), 79% female (n=399), on average 45.0±14.4 years of age with a mean BMI of 33.7±4.0 kg/m 2 . Treatment arms were similar on % days of weight and PA SM and % days adherent to calorie, fat and PA goals (p≥.05); however, the SM+FB group had greater % days of SM diet than the SM group (58.9 [24.7, 84.9] vs. 41.1 [14.0, 81.9]; P=.01). Weight loss at 12 mos was significantly associated (reported as b [95% CI]) with higher % of days of SM diet (-0.10 [-0.13, -0.08]), weight (-0.12 [-0.14, -0.09]) and PA (-0.10 [-0.13, -0.07]) and % days adherent to calorie (-0.06 [-0.11, -0.01]) and fat goals (-0.11 [-0.20, -0.02]) and average % days adherent to PA goals (-0.04 [-0.06, -0.02]). The effect of treatment assignment and its interactions with SM of diet, weight and PA and adherence to calorie, fat and PA goals on weight loss at 12 mos were not significant. Conclusions: In this study, SM of lifestyle behaviors and adherence to diet and PA goals were associated with better weight loss at 12 months and did not depend on treatment group assignment, suggesting that the mHealth intervention did not enhance adherence sufficiently to affect weight loss outcomes.

Probabilistic and distributed traffic control in LPWANs

Low-power, low data transmission rates, and long-range wireless networks, also known as LPWANs, are intended to work best with equipment that uses few resources and can be used for many years thanks to their long battery life operation. This type of networks can handle traffic from nearly 1,000 nodes while maintaining a duty cycle of less than 1%. However, as the nodes become denser, the number of collisions increases and network traffic management becomes mandatory. To address this concern, we propose a Distributed and Probabilistic Traffic Control algorithm (DiPTC) that allows nodes to change their traffic in response to the application requirements (e.g., acquiring K measurements over a period of time) while being agnostic to the number of nodes or the network topology. When this requirement is not achieved, the gateway sends a feedback message to all the nodes so that they may adapt their traffic. We compare the proposed solution to LoRaWAN and to a Centralized Optimal Traffic Control solution (COTraC), in simulation. Compared to LoRaWAN, our algorithm proved successful in achieving the objective while minimizing collisions and extending the network lifetime threefold.

Leveraging natural language processing to support automated assessment and feedback for student open responses in mathematics

AbstractBackgroundTeachers often rely on the use of open‐ended questions to assess students' conceptual understanding of assigned content. Particularly in the context of mathematics; teachers use these types of questions to gain insight into the processes and strategies adopted by students in solving mathematical problems beyond what is possible through more close‐ended problem types. While these types of problems are valuable to teachers, the variation in student responses to these questions makes it difficult, and time‐consuming, to evaluate and provide directed feedback. It is a well‐studied concept that feedback, both in terms of a numeric score but more importantly in the form of teacher‐authored comments, can help guide students as to how to improve, leading to increased learning. It is for this reason that teachers need better support not only for assessing students' work but also in providing meaningful and directed feedback to students.ObjectivesIn this paper, we seek to develop, evaluate, and examine machine learning models that support automated open response assessment and feedback.MethodsWe build upon the prior research in the automatic assessment of student responses to open‐ended problems and introduce a novel approach that leverages student log data combined with machine learning and natural language processing methods. Utilizing sentence‐level semantic representations of student responses to open‐ended questions, we propose a collaborative filtering‐based approach to both predict student scores as well as recommend appropriate feedback messages for teachers to send to their students.Results and ConclusionWe find that our method outperforms previously published benchmarks across three different metrics for the task of predicting student performance. Through an error analysis, we identify several areas where future works may be able to improve upon our approach.

Evaluating the Use and Interpretation of the TOEIC® Listening and Reading Test Score Report: Perspectives of Test Takers in Japan

Researchers suggest that claims about the meaningfulness of test score interpretations and consequences of test use should be backed by evidence that stakeholders understand the definition of the construct assessed (meaningfulness) and score reports (consequences). Evaluation of stakeholders' actual uses and interpretations of score reports in large‐scale standardized language proficiency tests, however, remains limited in the score reporting literature. This study investigates how test takers, as an important stakeholder group, use and interpret the score report of the TOEIC® Listening and Reading (TOEIC L&R) test. Data were collected from 834 TOEIC L&R test takers in Japan, who represented a wide range of English language proficiency based on their TOEIC L&R total scores. The participants responded to an online survey that asked about their uses and interpretations of the test results and their comprehension of the performance feedback presented in the score report. The results showed that the participants used the test results largely as intended, providing an important piece of validity evidence to support the proposed uses of the TOEIC L&R test. Some of the score reporting elements such as the performance feedback and footnote message, however, were not easy to understand for all participants, revealing a need to improve the interpretability of the score report. The study findings have implications for designing informative score reports and the usefulness around reporting test performance feedback.

Affective-motivational effects of performance feedback in computer-based assessment: Does error message complexity matter?

The impact of computer-based performance feedback on students’ affective-motivational state may be very different, depending on the positive or negative direction of the feedback message and its specific content. This experiment investigated whether more elaborated error messages improve students’ affective-motivational response to negative (i.e., corrective) feedback. We systematically varied the presence and complexity of corrective feedback messages (1 × 4 between-subjects design) and analyzed the effects of the provided feedback on students’ emotions, task-related perceived usefulness, and expectancy-value beliefs. University students (N = 439) worked on a low-stakes test with 12 constructed-response geometry tasks. They received either no feedback or different complexities of immediate corrective feedback after incorrect responses (i.e., Knowledge of Results [KR], Knowledge of Correct Response [KCR], or Elaborated Feedback [EF]), paired with immediate confirmatory KCR feedback after correct responses (i.e., confirming their response). Our data showed that students’ task-level performance moderated the emotional impact of feedback (i.e., beneficial effects after correct responses; detrimental effects after incorrect responses). Students’ performance further moderated several feedback effects on students’ expectancy-value beliefs. Regarding error message complexity, we found that students reported higher levels of positive emotions after receiving EF or KCR compared to KR, while only EF decreased students' level of negative emotions compared to KR and increased students' task-related perceived usefulness compared to all other groups. Overall, our results suggest that performance feedback is likely to improve students’ affective-motivational state when the feedback confirms a correct response. Moreover, when reporting an error, EF (or KCR messages) were more beneficial to affective-motivational outcomes than simple KR notifications.

Identifying Predictors of Adherence to the Physical Activity Goal: A Secondary Analysis of the SMARTER Weight Loss Trial.

Research is needed to inform tailoring supportive strategies for promoting physical activity (PA) in the context of behavioral treatment of obesity. We aimed to identify baseline participant characteristics and short-term intervention response predictors associated with adherence to the study-defined PA goal in a mobile health (mHealth) weight loss trial. A secondary analysis was conducted of a 12-month weight loss trial (SMARTER) that randomized 502 adults with overweight or obesity to either self-monitoring of diet, PA, and weight with tailored feedback messages ( n = 251) or self-monitoring alone ( n = 251). The primary outcome was average adherence to the PA goal of ≥150 min·wk -1 of moderate- and vigorous-intensity aerobic activities (MVPA) from Fitbit Charge 2™ trackers over 52 wk. Twenty-five explanatory variables were considered. Machine learning methods and linear regression were used to identify predictors of adherence to the PA goal. The sample ( N = 502) was mostly female (80%), White (82%) with the average age of 45 ± 14.4 yr and body mass index of 33.7 ± 4.0 kg·m -2 . Machine learning methods identified PA goal adherence for the first week as the most important predictor of long-term PA goal adherence. In the parsimonious linear regression model, higher PA goal adherence for the first week, greater PA FB messages opened, older age, being male, higher education, being single and not having obstructive sleep apnea were associated with higher long-term PA goal adherence. To our knowledge, this is the first study using machine learning approaches to identify predictors of long-term PA goal adherence in a mHealth weight loss trial. Future studies focusing on facilitators or barriers to PA among young and middle-age adults and women with low PA goal adherence are warranted.

Using Health Intervention Messages to Reduce Intentions to Spend Time on Social Networks

Abstract: This study examined the efficacy of using behavioral feedback and social norms health message interventions to reduce social networking site (SNS) use. A total of 107 participants reported their current SNS use and attitude through endorsement of the statement “I spend too much time on social media” before being randomly assigned to read a message (control, generic consequences, social norms, or behavioral feedback). After reading the message, participants reported their future intentions to use social media and responded to the statement again. The results demonstrated a relationship between the social norms message and future intended SNS use, such that those who read information about the norm for SNS use were more likely to report that they intended to reduce their SNS use in the future. An interaction suggested that the higher the current use, the more effective it was to expose the user to the social norm. Additionally, an association was found between the behavioral feedback message and the belief that they were currently using SNSs too much, such that those who saw tailored consequences of their use were more likely to endorse the statement more strongly. Overall, using these health messages as an intervention to reduce SNS use is a promising avenue that should be explored further.

Managing in Writing: Recommendations from Textual Patterns in Managers’ Email Communication

This study draws from personality psychology and linguistics of written communication to explore the characteristics of self-selected well-written email communications (N=273) solicited from Polish managers who organized and supervised the (remote) work of their units during the COVID-19 period. The focus is on the writing of managers with above-average levels of conscientiousness and agreeableness, as these personality factors are predictors of efficacy in the completion of two work-related goals, Achievement and Communion, according to the Theory of Purposeful Work Behavior. The linguistic patterns responsible for effective email communication are identified through both automated and qualitative textual analyses of the email sample. The study has implications for management training via the assumption that linguistic patterns that a reflexive manager uses in writing are subjected to monitoring and can be modeled and adapted to. Specific recommendations for managerial writing styles concern informational, instructional, explanatory, feedback, and query messages.

PP40 Health Apps To Manage Depression: Can We Separate The Grain From The Chaff? EvalDepApps Project

IntroductionThe use of mobile applications in the treatment of health issues is more frequently becoming common practice. Apps are fast, versatile, and manageable tools that allow the empowerment of patients and professionals, and can reduce the possible stigmatization suffered by some patients, mainly in mental health. There are more than 325,000 health apps on the market, but their impact remains unclear. There are several initiatives to define how health applications should be assessed, however, all of them address only partial aspects of the evaluation. The theoretical frameworks existing to date highlight the need to develop new tools and methodologies to assess mobile applications whose objective is the management of specific pathologies.MethodsThe primary goal of the EvalDepApps project is to develop and pilot an assessment tool for mobile applications whose main objectives are the treatment, monitoring or social support of people suffering from depression. The project is inspired by the results and lessons learnt from a previous project, EVALAPPS, whose central aim was to develop a tool to assess health apps targeted toward the management of overweight and obesity. The first steps of the EvalDepApps project are: (i) to explore and characterize the current landscape of mobile applications available in the market to treat depression through a systematic appraisal, and (ii) to review the existing evidence about the effectiveness and safety of these applications through systematic research of the existing evidence.ResultsPreliminary results show that all the depression management studies were by design based on cognitive-behavioral therapy (CBT) interventions (n=17) and the main management tools included in the services (web or apps) are psychoeducation and coaching (14), together with self-monitoring and feedback messaging (13).ConclusionsMoreover, although health apps seem to be an interesting strategy to treat depression, there are very few apps available on the markets (30) and the supporting evidence is very limited. This result uncovers a need for further systematic and clinically oriented validation and testing of such apps.

The Area Enclosed by a Function Is Not Always the Definite Integral: Relearning Through Collaborative Transitioning Within a Learning-Support Module

Learning-support system is an umbrella term that we use for digital resources that assign students with mathematical questions and give automatic feedback on the inserted answers. Transitioning between questions and feedback is characteristic to students’ work with such systems. We apply the commognitive framework to explore the role of within-system transitions in students’ mathematics learning, with a special interest in what we term as “reroutinization”—a process of repeated development of conventional routines to be implemented in already familiar mathematical tasks. The study revolves around a digital module in integral calculus, which was designed to support undergraduates with finding areas enclosed by functions. The data comes from dyads and triads of first-year university students, who collaboratively interacted with the module. The analyses cast light on how transitioning within the module aided students to review familiar routines, amend them, confirm, and solidify the amendments. The transition process was not always linear and contained instances of students cycling back and forth between the assigned questions and feedback messages. We conclude with the discussion on the module’s design that afforded reroutinization and suggest paths for further research.