Experiences of Self-Monitoring in Self-Directed Weight Loss and Weight Loss Maintenance: Systematic Review of Qualitative Studies

Hartmann‐Boyce, Jamie; Boylan, Anne‐Marie; Jebb, Susan A.; Aveyard, Paul

doi:10.1177/1049732318784815

Cited by 40 publications

(27 citation statements)

References 42 publications

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“…Interalia, this has potential implications on data interpretation that we have identified as a recurring concept across studies. Previous research demonstrated the importance of PGHD interpretation and its wider implications [46], with missing sense-making skills and the fear of self-interpretation mentioned as key challenges to personal health information use. Our findings reflected that importance, as a major proportion of the literature directly or indirectly addressed interpretability by describing various approaches to fostering correct data understanding.…”

Section: Discussionmentioning

confidence: 99%

Electronic Patient-Generated Health Data to Facilitate Disease Prevention and Health Promotion: Scoping Review

Nittas¹,

Lun²,

Ehrler³

et al. 2019

J Med Internet Res

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BackgroundDigital innovations continue to shape health and health care. As technology socially integrates into daily living, the lives of health care consumers are transformed into a key source of health information, commonly referred to as patient-generated health data (PGHD). With chronic disease prevalence signaling the need for a refocus on primary prevention, electronic PGHD might be essential in strengthening proactive and person-centered health care.ObjectiveThis study aimed to review and synthesize the existing literature on the utilization and implications of electronic PGHD for primary disease prevention and health promotion purposes.MethodsGuided by a well-accepted methodological framework for scoping studies, we screened MEDLINE, CINAHL, PsycINFO, Scopus, Web of Science, EMBASE, and IEEE Digital Library. We hand-searched 5 electronic journals and 4 gray literature sources, additionally conducted Web searches, reviewed relevant Web pages, manually screened reference lists, and consulted authors. Screening was based on predefined eligibility criteria. Data extraction and synthesis were guided by an adapted PGHD-flow framework. Beyond initial quantitative synthesis, we reported narratively, following an iterative thematic approach. Raw data were coded, thematically clustered, and mapped, allowing for the identification of patterns.ResultsOf 183 eligible studies, targeting knowledge and self-awareness, behavior change, healthy environments, and remote monitoring, most literature (125/183, 68.3%) addressed weight reduction, either through physical activity or nutrition, applying a range of electronic tools from socially integrated to full medical devices. Participants generated their data actively (100/183, 54.6%), in combination with passive sensor-based trackers (63/183, 34.4%) or entirely passively (20/183, 10.9%). The proportions of active and passive data generation varied strongly across prevention areas. Most studies (172/183, 93.9%) combined electronic PGHD with reflective, process guiding, motivational and educational elements, highlighting the role of PGHD in multicomponent digital prevention approaches. Most of these interventions (110/183, 60.1%) were fully automatized, underlining broader trends toward low-resource and efficiency-driven care. Only a fraction (47/183, 25.6%) of studies provided indications on the impact of PGHD on prevention-relevant outcomes, suggesting overall positive trends, especially on vitals (eg, blood pressure) and body composition measures (eg, body mass index). In contrast, the impact of PGHD on health equity remained largely unexplored. Finally, our analysis identified a list of barriers and facilitators clustered around data collection and use, technical and design considerations, ethics, user characteristics, and intervention context and content, aiming to guide future PGHD research.ConclusionsThe large, heterogeneous volume of the PGHD literature underlines the topic’s emerging nature. Utilizing electronic PGHD to prevent diseases and promote health is a complex m...

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Section: Discussionmentioning

confidence: 99%

Electronic Patient-Generated Health Data to Facilitate Disease Prevention and Health Promotion: Scoping Review

Nittas¹,

Lun²,

Ehrler³

et al. 2019

J Med Internet Res

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“…Overall, adherence to self‐monitoring of weight was lower than that of eating or physical activity. There may be unique challenges for self‐monitoring of weight that need to be addressed clinically, such as a sense of shame regarding one's weight (regardless of recent progress) or avoidance that results when one fears that recent weight change will be disappointing . However, it is difficult to interpret the decline in adherence to weight self‐monitoring because the prescription for frequency of weight self‐monitoring changed from weekly to daily during the final weeks of the programme, and thus, the change in frequency prescribed is confounded with the timing of the initial weight loss phase of treatment coming to an end.…”

Section: Discussionmentioning

confidence: 99%

Digital self‐monitoring: Does adherence or association with outcomes differ by self‐monitoring target?

Butryn

Godfrey

Martinelli

et al. 2019

Obesity Science & Practice

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Objective: Digital self-monitoring of eating, physical activity, and weight is increasingly prescribed in behavioural weight loss programmes. This study determined if adherence rates or associations with outcomes differed according to self-monitoring target (ie, self-monitoring of eating versus physical activity versus weight).Methods: Participants in a 3-month, group-based weight loss programme were instructed to use an app to record food intake, wear a physical activity sensor, and use a wireless body weight scale. At post-treatment, weight loss was measured in clinic and moderate-to-vigorous physical activity (MVPA) was measured by research-grade accelerometer.Results: Adherence to self-monitoring decreased significantly over time for eating and weight but not physical activity. Overall, adherence to self-monitoring of weight was lower than that of eating or physical activity. Greater adherence to selfmonitoring of eating, physical activity, and weight each predicted greater weight loss.Only greater adherence to self-monitoring of eating was associated with greater bouted minutes of MVPA.Conclusions: Findings from this study suggest that self-monitoring should be considered a target-specific behaviour rather than a unitary construct when conceptualizing adherence and association with treatment outcomes.

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“…Indeed, a review of just-in-time interventions suggested that portable devices may be useful to enhance cognitive behavioral therapy for weight loss programs [12]. Mobile phones also provide an avenue for regular self-monitoring, which have been strongly linked with successful behavior change, particularly in weight management [13,14].…”

Section: Introductionmentioning

confidence: 99%

A Mobile Phone App Designed to Support Weight Loss Maintenance and Well-Being (MotiMate): Randomized Controlled Trial

Brindal¹,

Hendrie²,

Freyne³

et al. 2019

JMIR Mhealth Uhealth

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BackgroundFew people successfully maintain lost weight over the longer term. Mobile phones have the potential to deliver weight loss management programs that can encourage self-monitoring while also providing some behavioral therapy to assist users in developing personal skills that may be necessary for improved longer term weight loss maintenance.ObjectiveThe aim of this study was to evaluate a program supporting weight maintenance, which uses a behaviorally based mobile phone app to manage weight, food, exercise, mood, and stress.MethodsIn a randomized controlled trial over 24 weeks, the full version of the app (MotiMate) was compared with a control app (monitoring only; excluding mood and stress) for its effect on weight, diet, and psychological well-being. Both apps had the same visual appearance and were designed to deliver all intervention content without face-to-face contact. The control version included features to track weight, food intake, and exercise with limited feedback and no encouraging/persuasive features. The intervention app included more persuasive and interactive features to help users track their weight, food intake, and physical activity and prompted users to enter data each day through notifications and included a mood and stress workshopping tool. Participants were recruited through advertising and existing databases. Clinic visits occurred at baseline, 4 weeks, 8 weeks, 12 weeks, and 24 weeks. At all visits, the clinical trial manager recorded body weight, and participants then completed a computer-delivered survey, which measured psychological and lifestyle outcomes. Objective app usage data were recorded throughout the trial.ResultsA total of 88 adults who had lost and maintained at least 5% of their body weight within the last 2 years were randomized (45 MotiMate and 43 control). Overall, 75% (66/88) were female, and 69% (61/88) completed week 24 with no differences in dropout by condition (χ21,87=0.7, P=.49). Mixed models suggested no significant changes in weight or psychological outcomes over 24 weeks regardless of condition. Of 61 completers, 53% (32/61) remained within 2% of their starting weight. Significant increases occurred over 24 weeks for satisfaction with life and weight loss self-efficacy regardless of app condition. Diet and physical activity behaviors did not vary by app or week. Negative binomial models indicated that those receiving the full app remained active users of the app for 46 days longer than controls (P=.02). Users of the full version of the app also reported that they felt more supported than those with the control app (P=.01).ConclusionsAlthough some aspects of the intervention app such as usage and user feedback showed promise, there were few observable effects on behavioral and psychological outcomes. Future evaluation of the app should implement alternative research methods or target more specific populations to better understand the utility of the coping interface.Trial RegistrationAustralia New Zealand Clinical Trials Registry ACTRN12614000474651; htt...

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Experiences of Self-Monitoring in Self-Directed Weight Loss and Weight Loss Maintenance: Systematic Review of Qualitative Studies

Cited by 40 publications

References 42 publications

Electronic Patient-Generated Health Data to Facilitate Disease Prevention and Health Promotion: Scoping Review

Electronic Patient-Generated Health Data to Facilitate Disease Prevention and Health Promotion: Scoping Review

Digital self‐monitoring: Does adherence or association with outcomes differ by self‐monitoring target?

A Mobile Phone App Designed to Support Weight Loss Maintenance and Well-Being (MotiMate): Randomized Controlled Trial

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