Patterns Of Self-monitoring Research Articles

Predictors of parent self-monitoring patterns in a family-based behavioral weight loss treatment program.

Self-monitoring dietary intake is a critical component of family-based intensive health behavior and lifestyle treatment for pediatric obesity, but adherence rates are often low. This study identifies predictors of parent self-monitoring rates during treatment. A secondary analysis of parent self-monitoring data from a randomized controlled trial involving 150 parent-child dyads. Patterns of self-monitoring were identified using a latent class mixed model approach. Logistic regression analyses evaluated predictors of self-monitoring patterns. Latent class models identified two trajectory groups: a high consistent self-monitoring group and a low-decreasing self-monitoring group. When compared to parents in the low group, parents in the high group lost more weight throughout treatment. Children in the high group had a similar trajectory for weight loss; however, the groups were not statistically different. Higher levels of family chaos and poorer family problem-solving skills were associated with higher odds of being in the low group. This study identified two patterns of rates of parent self-monitoring, which were associated with parent weight loss and were differentiated by family chaos and poor problem-solving. These findings suggest that families with high levels of chaos and poor problem-solving could benefit from early intervention to improve outcomes in pediatric obesity treatment programs. Clinicaltrials.gov Identifier: NCT01197443.

Profiling the pausing behaviour of EFL learners in real-time computer-aided writing: a multi-method case study

Technologically enhanced means and devices in language education and research have enabled an in-depth exploration of the dynamics of writing. This study investigated the pausing behaviour of eight Chinese English as a Foreign Language (EFL) learners at the tertiary level in performing an online writing task. Quantitative and qualitative data were collected using a combination of methods and techniques, including keystroke logging, screen recording videos, think-aloud protocols, and stimulated recall interviews to establish a profile of each learner’s pausing behaviour. The learners’ pause profiles were extensively analyzed with a comparative focus on similarities and differences in EFL learners’ pausing behaviour across writing skill levels. Overall, the findings revealed a general tendency for the learners to pause most frequently at a low text unit level, i.e., the lexical level. More specifically, less-skilled writers tended to pause more frequently than more-skilled writers at lower-level text units, whilst more-skilled writers chose to make more strategic pauses to gain overall control of their writing. Furthermore, these findings help reveal the intricate self-monitoring patterns that undergird individual writer’s pausing behaviour and relate these patterns to self-monitoring awareness, writing knowledge and experience, and writing habit. This small-scale multi-method study offers a glimpse into how EFL learners at different skill levels would respond to a real-time online writing task by using resources at their disposal and under conscious monitoring. Methodologically, it adds empirical evidence to previous literature on researching the computer-aided writing process with computer-aided tools and considers productive complementation and triangulation across research approaches and paradigms.

Defining and tracking medical student self-monitoring using multiple-choice question item certainty

BackgroundSelf-monitoring is an important component of clinical practice. It is underpinned by the framework of self-efficacy which is concerned with judgments of how well one believes one can achieve or perform a task. This research aimed to develop criteria for adequate self-monitoring, then to measure patterns of self-monitoring, and to explore how these patterns relate to a student’s year in a medical course and to patterns of knowledge.MethodsAnalysis of individuals’ levels of correctness in answering assessment items and their certainty in correctness may be used to inform assessments of ability to self-monitor. Two criteria were proposed and applied to define adequate self-monitoring. Firstly, increasing proportions correct with increasing levels of certainty. Secondly, having a proportion correct for high certainty responses that was not lower than cohort levels. Student responses in progress tests comprising multiple-choice questions (MCQs) and associated certainty were analysed. Criteria for the presence of adequate self-monitoring and for adequate knowledge were applied to the results of each of four tests conducted over 2 years, and used to categorise patterns of self-monitoring and knowledge.ResultsData from 3 year group cohorts totalling 737 students were analysed. The majority (58%) of students demonstrated adequate knowledge and met both criteria for adequate self-monitoring across all four tests. The most advanced year group cohort had the highest rates of adequate knowledge and the highest rates of meeting both self-monitoring criteria. The patterns of self-monitoring were the same as the patterns of knowledge across the four tests for 454 students, but for the remaining 283 the patterns of self-monitoring and knowledge differed.ConclusionAnalysis of responses to item level certainty has informed development of a definition of adequate self-monitoring that may be applied to individual student’s responses from a single test, and to track the adequacy of a student’s self-monitoring over time. Patterns of self-monitoring tend to match patterns of knowledge, but not in all cases, suggesting the self-monitoring measure could provide additional information about student ability.

Patient Experience Connecting Mobile-Based Self-Monitoring of Diet and Physical Activity to Diabetes Educators through a Connected Interface in an Electronic System for Diabetes Education

Background: Smartphone applications and wearable activity trackers have become popular tools in recent years in managing chronic diseases such as diabetes. More recently, studies have focused on connecting patient-generated health data from mobile devices directly to health care providers and educators. However, not much is known regarding the patient experience in using these mobile devices for diabetes management, particularly the implications of allowing educators direct access to patients’ diet and exercise data. Objective: The objective of this study was to identify patients’ perceived benefits and concerns about using a smartphone application and wristband activity tracker to monitor diet and physical activity, as well as the perceived benefits and concerns of allowing educators access to such data. Methods: We conducted a qualitative, descriptive study as an axillary study to a clinical trial testing a connected interface to link patient self-monitoring diet and physical activity to a nationally used electronic diabetes education system. Our axillary study examined 13 type 2 diabetes patients’ views on perceived benefits and concerns about using a smartphone application and wristband activity tracker to monitor diet and physical activity for three months. A focus group interview was administered to obtain general and specific understanding of the use of smartphone applications and activity trackers during the study period. The central interview questions guiding the discussion included “What did you think about the UP24 wristband and app?”, “What are your thoughts about the connection of UP24 data with Chronicle, the Web-based diabetes education system, so that your diabetes educators can see your behavior?”, and “Has knowing that someone else has access to your diet and exercise data affected your behavior and self-monitoring?” The interviewer also asked specific questions to gain deeper understanding of the following topics: (1) the app and wristband features used to record and monitor diet and physical activity, (2) materials used for intervention orientation, (3) additional data (eg, weight and blood glucose) that participants would like to share with educators, and (4) suggestions for improvement in diabetes self-management and communication with educators and physicians. The focus group sessions were audio-recorded and transcribed. Transcribed data were analyzed to identify key themes based on interpretive coding procedures. Results: We identified 11 key themes under three major categories and described these themes with illustrative quotations. The three major categories of themes covered (1) self-monitoring themes: varied experience and self-monitoring patterns and adherence exist among patients using the wearable tracker and its companion smartphone application; (2) themes related to sharing self-monitoring of diet and physical activity data with diabetes educators: sharing self-monitoring diet influences patient self-monitoring adherence and dietary and activity changes, and communication with educators; and (3) research study-related themes: technical barriers, utilization of manuals and tutorial videos in beginning use of the connected health tools, and desired features on combining lifestyle data with glucose data and caregiver access. Conclusions: Connected technology aiming to incorporate patient-generated health lifestyle data into clinical workflow should consider patient perspectives in terms of their experience and motivation for generating and sharing such data and technical barriers in using such tools.

Weight Loss Associated With Different Patterns of Self-Monitoring Using the Mobile Phone App My Meal Mate.

BackgroundObesity is a major global public health issue due to its association with a number of serious chronic illnesses and its high economic burden to health care providers. Self-monitoring of diet has been consistently linked to weight loss. However, there is limited evidence about how frequently individuals need to monitor their diet for optimal weight loss.ObjectiveThe aim of this paper is to describe app usage frequency and pattern in the mobile phone arm of a previously conducted randomized controlled trial. The relationship between frequency and pattern of electronic dietary self-monitoring and weight loss is also investigated.MethodsA randomized pilot trial comparing three methods of self-monitoring (mobile phone app, paper diary, Web-based) was previously conducted. Trial duration was 6 months. The mobile phone app My Meal Mate features an electronic food diary and encourages users to self-monitor their dietary intake. All food consumption data were automatically uploaded with a time and date stamp. Post hoc regression analysis of app usage patterns was undertaken in the My Meal Mate group (n=43; female: 77%, 33/43; white: 100%, 43/43; age: mean 41, SD 9 years; body mass index: mean 34, SD 4 kg/m2) to explore the relationship between frequency and pattern of electronic dietary self-monitoring and weight loss. Baseline characteristics of participants were also investigated to identify any potential predictors of dietary self-monitoring.ResultsRegression analysis showed that those in the highest frequency-of-use category (recorded ≥129 days on the mobile phone app) had a −6.4 kg (95% CI −10.0 to −2.9) lower follow-up weight (adjusted for baseline weight) than those in the lowest frequency-of-use category (recorded ≤42 days; P<.001). Long-term intermittent monitoring over 6 months appeared to facilitate greater mean weight loss than other patterns of electronic self-monitoring (ie, monitoring over the short or moderate term and stopping and consistently monitoring over consecutive days). Participant characteristics such as age, baseline weight, sex, ethnicity, conscientiousness, and consideration of future consequences were not statistically associated with extent of self-monitoring.ConclusionsThe results of this post hoc exploratory analysis indicate that duration and frequency of app use is associated with improved weight loss, but further research is required to identify whether there are participant characteristics that would reliably predict those who are most likely to regularly self-monitor their diet.ClinicalTrialClinicalTrials.gov NCT01744535; http://clinicaltrials.gov/ct2/show/NCT01744535 (Archived by WebCite at http://www.webcitation.org/6FEtc3PVB)

Do individual, online motivational interviewing chat sessions enhance weight loss in a group-based, online weight control program?

To examine whether the addition of online motivational interviewing (MI) chats to a Web-based, group behavioral obesity treatment program augments weight loss outcomes relative to the Web-based weight control program alone. Healthy individuals (N = 398, 24% minority) with overweight/obesity were randomized to a 36-session group Internet behavioral weight control treatment (BT) or the same group Internet treatment plus six individual MI chat sessions (BT + MI). Both conditions received weekly synchronous online chat group sessions for 6 months followed by 12 monthly group chats. Participants in both groups received identical behavioral lessons and individualized therapist feedback on progress toward meeting exercise and calorie goals. BT + MI also received six individual MI sessions delivered by a separate MI counselor via Web chat. Weight loss was measured at 6 and 18 months. There were no significant differences in weight loss between BT (-5.5 ± 6.0 kg) and BT + MI (-5.1 ± 6.3 kg) at 6 months or at 18 months (-3.3 ± 7.1 kg vs. -3.5 ± 7.7 kg for BT and BT + MI, respectively). Attendance at group chats did not differ between groups, nor did self-monitoring patterns, suggesting comparable engagement in the weight control program in both conditions. Online MI chat sessions were not a viable strategy to enhance Web-based weight control treatment outcomes.

Data Mining of a Remote Behavioral Tracking System for Type 2 Diabetes Patients: A Prospective Cohort Study.

BackgroundComplications from type 2 diabetes mellitus can be prevented when patients perform health behaviors such as vigorous exercise and glucose-regulated diet. The use of smartphones for tracking such behaviors has demonstrated success in type 2 diabetes management while generating repositories of analyzable digital data, which, when better understood, may help improve care. Data mining methods were used in this study to better understand self-monitoring patterns using smartphone tracking software.ObjectiveAssociations were evaluated between the smartphone monitoring of health behaviors and HbA1c reductions in a patient subsample with type 2 diabetes who demonstrated clinically significant benefits after participation in a randomized controlled trial.MethodsA priori association-rule algorithms, implemented in the C language, were applied to app-discretized use data involving three primary health behavior trackers (exercise, diet, and glucose monitoring) from 29 participants who achieved clinically significant HbA1c reductions. Use was evaluated in relation to improved HbA1c outcomes.ResultsAnalyses indicated that nearly a third (9/29, 31%) of participants used a single tracker, half (14/29, 48%) used two primary trackers, and the remainder (6/29, 21%) of the participants used three primary trackers. Decreases in HbA1c were observed across all groups (0.97-1.95%), but clinically significant reductions were more likely with use of one or two trackers rather than use of three trackers (OR 0.18, P=.04).ConclusionsData mining techniques can reveal relevant coherent behavior patterns useful in guiding future intervention structure. It appears that focusing on using one or two trackers, in a symbolic function, was more effective (in this sample) than regular use of all three trackers.

BeWell24: development and process evaluation of a smartphone "app" to improve sleep, sedentary, and active behaviors in US Veterans with increased metabolic risk.

Lifestyle behaviors across the 24-h spectrum (i.e., sleep, sedentary, and active behaviors) drive metabolic risk. We describe the development and process evaluation of BeWell24, a multicomponent smartphone application (or "app") that targets behavior change in these interdependent behaviors. A community-embedded iterative design framework was used to develop the app. An 8-week multiphase optimization strategy design study was used to test the initial efficacy of the sleep, sedentary, and exercise components of the app. Process evaluation outcomes included objectively measured app usage statistics (e.g., minutes of usage, self-monitoring patterns), user experience interviews, and satisfaction ratings. Participants (N = 26) logged approximately 60% of their sleep, sedentary, and exercise behaviors, which took 3-4min/day to complete. Usage of the sleep and sedentary components peaked at week 2 and remained high throughout the intervention. Exercise component use was low. User experiences were mixed, and overall satisfaction was modest.

Patterns of success: online self-monitoring in a web-based behavioral weight control program.

Online weight control technologies could reduce barriers to treatment, including increased ease and convenience of self-monitoring. Self-monitoring consistently predicts outcomes in behavioral weight loss programs; however, little is known about patterns of self-monitoring associated with success. The current study examines 161 participants (92% women; 31% African American; mean body mass index = 35.7 ± 5.7) randomized to a 6-month online behavioral weight control program that offered weekly group "chat" sessions and online self-monitoring. Self-monitoring log-ins were continuously monitored electronically during treatment and examined in association with weight change and demographics. Weekend and weekday log-ins were examined separately and length of periods of continuous self-monitoring were examined. We found that 91% of participants logged in to the self-monitoring webpage at least once. Over 6 months, these participants monitored on an average of 28% of weekdays and 17% of weekend days, with most log-ins earlier in the program. Women were less likely to log-in, and there were trends for greater self-monitoring by older participants. Race, education, and marital status were not significant predictors of self-monitoring. Both weekday and weekend log-ins were significant independent predictors of weight loss. Patterns of consistent self-monitoring emerged early for participants who went on to achieve greater than a 5% weight loss. Patterns of online self-monitoring were strongly associated with weight loss outcomes. These results suggest a specific focus on consistent self-monitoring early in a behavioral weight control program might be beneficial for achieving clinically significant weight losses.

PMD83 The Cost Impact of Modifying Patterns of Self-Monitoring of Blood Glucose in an Irish Type 2 Diabetes Cohort

PMD83 The Cost Impact of Modifying Patterns of Self-Monitoring of Blood Glucose in an Irish Type 2 Diabetes Cohort

SMART trial: A randomized clinical trial of self-monitoring in behavioral weight management-design and baseline findings

Background The primary form of treatment for obesity today is behavioral therapy. Self-monitoring diet and physical activity plays an important role in interventions targeting behavior and weight change. The SMART weight loss trial examined the impact of replacing the standard paper record used for self-monitoring with a personal digital assistant (PDA). This paper describes the design, methods, intervention, and baseline sample characteristics of the SMART trial. Methods The SMART trial used a 3-group design to determine the effects of different modes of self-monitoring on short- and long-term weight loss and on adherence to self-monitoring in a 24-month intervention. Participants were randomized to one of three conditions (1) use of a standard paper record (PR); (2) use of a PDA with dietary and physical activity software (PDA); or (3), use of a PDA with the same software plus a customized feedback program (PDA + FB). Results We screened 704 individuals and randomized 210. There were statistically but not clinically significant differences among the three cohorts in age, education, HDL cholesterol, blood glucose and systolic blood pressure. At 24 months, retention rate for the first of three cohorts was 90%. Conclusions To the best of our knowledge, the SMART trial is the first large study to compare different methods of self-monitoring in a behavioral weight loss intervention and to compare the use of PDAs to conventional paper records. This study has the potential to reveal significant details about self-monitoring patterns and whether technology can improve adherence to this vital intervention component.

Using instrumented paper diaries to document self-monitoring patterns in weight loss

Self-monitoring of eating is associated with successful weight loss, but adherence is imperfect and deteriorates over time. Moreover, intentionally or not, many individuals have difficulty keeping faithful records. We used instrumented paper diaries (IPDs) to study self-monitoring in randomly chosen participants in the PREFER trial, a behavioral treatment for weight-loss study. The diaries they used to self-report eating were periodically replaced with IPDs at various times during an 18-month weight-loss program, consisting of three successive phases: intense treatment ( n = 35), less-intense treatment ( n = 13), and maintenance ( n = 16). We compared electronically documented self-monitoring data, showing when and how often IPDs were used, with self-reported data, then compared the electronically validated adherence and weight loss. Self-reported diary usage exceeded IPD-documented usage while the electronic data demonstrated a significant decline in self-monitoring over time. Diary recording often was not timely. Percentage weight lost correlated significantly with frequency of IPD use ( p = .001) and the number of diary entries made within 15 min of opening the IPD ( p = .002). This is the first study to document patterns of self-monitoring among participants in a weight-loss program, which demonstrated that individuals may falsify the times and frequency of self-monitoring. Furthermore, our results showed that adherence to self-monitoring and the timeliness of recording significantly correlate with improved weight loss.

Ancillary study to the PREFER trial: A descriptive study of participants' patterns of self-monitoring — rationale, design and preliminary experiences

Background The treatment of obesity, marked by a high rate of recidivism, lacks strategies that sustain the improved lifestyle behaviors that led to the weight loss. Self-monitoring, a behavioral strategy to increase awareness of one's behavior, is the cornerstone of behavioral treatment in weight loss management. However, adherence to self-monitoring is less than ideal. The actual patterns of self-monitoring of eating behaviors in weight loss treatment programs have not been studied previously; if done, these data could provide information on how self-monitoring patterns affect weight loss and if interventions can be developed that address deficits in self-monitoring. Technology now permits an instrumented paper-and-pencil diary to record the real time of individuals' self-monitoring behaviors (invivodata, inc.), thus providing more information about self-reported behaviors. This technology differs from PDA based products (ex. e-diary, e-trials, logpad, PICS) because, to the user, it is no different from a standard paper-and-pencil diary. Methods The purposes of this ancillary study are: (1) to describe the electronically recorded patterns of self-monitoring of eating behaviors by weight-loss study participants; (2) compare reported vs. electronically recorded self-monitoring; and (3) examine the relationship between the electronically validated adherence to self-monitoring goals and success in weight loss in a sub-sample of participants in the PREFER study. This paper describes the design, methods and preliminary 6-month results. Results Preliminary results reveal that participants frequently report recording their eating behavior during times when the binder was not opened. Two examples of data are shown that demonstrate the lack of concordance between the self-reported and the electronically recorded data. Conclusions These unobtrusively collected electronic data can lead to the development of strategies that can promote improved adherence to self-monitoring.

Frequency of blood glucose monitoring in relation to glycaemic control: observational study with diabetes database

Objectives: To investigate patterns of self monitoring of blood glucose concentration in diabetic patients who use insulin and to determine whether frequency of self monitoring is related to glycaemic control.Setting:...

FEES OF PHYSICIANS AND SURGEONS

<h3>Abstract</h3> <b>Objectives:</b> To investigate patterns of self monitoring of blood glucose concentration in diabetic patients who use insulin and to determine whether frequency of self monitoring is related to glycaemic control. <b>Setting:</b> Diabetes database, Tayside, Scotland. <b>Subjects:</b> Patients resident in Tayside in 1993-5 who were using insulin and were registered on the database and diagnosed with insulin dependent (type 1) or non-insulin dependent (type 2) diabetes before 1993. <b>Main outcome measures:</b> Number of glucose monitoring reagent strips dispensed (reagent strip uptake) derived from records of prescriptions. First recorded haemoglobin A_1c concentration in the study period, and reagent strips dispensed in the previous 6 months. <b>Results:</b> Among 807 patients with type 1 diabetes, 128 (16%) did not redeem any prescriptions for glucose monitoring reagent strips in the 3 year study period. Only 161 (20%) redeemed prescriptions for enough reagent strips to test glucose daily. The corresponding figures for the 790 patients with type 2 diabetes who used insulin were 162 (21%; no strips) and 131 (17%; daily tests). Reagent strip uptake was influenced both by age and by deprivation category. There was a direct relation between uptake and glycaemic control for 258 patients (with recorded haemoglobin A_1c concentrations) with type 1 diabetes. In a linear regression model the decrease in haemoglobin A_1c concentration for every extra 180 reagent strips dispensed was 0.7%. For the 290 patients with type 2 diabetes who used insulin there was no such relation. <b>Conclusions:</b> Self monitoring of blood glucose concentration is associated with improved glycaemic control in patients with type 1 diabetes. Regular self monitoring in patients with type 1 and type 2 diabetes is uncommon. <h3>Key messages</h3> Several studies have indicated the importance of self monitoring of blood glucose concentration for prevention of complications in patients with diabetes Uptake of reagent strips for self monitoring of blood glucose among diabetic patients who used insulin was low, with only 20% of patients with type 1 diabetes and 17% of those with type 2 diabetes obtaining enough strips to test blood glucose concentration once daily Reagent strip uptake depends on characteristics such as age and social deprivation category, and patient groups with low uptake should be identified and targeted There was a direct association between strip uptake in the previous 6 months and glycaemic control in patients with type 1 diabetes but not in those with type 2 diabetes