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Hagerman CJ, Onu MC, Crane NT, Butryn ML, Forman EM. Psychological and behavioral responses to daily weight gain during behavioral weight loss treatment. J Behav Med 2024; 47:492-503. [PMID: 38407728 PMCID: PMC11026204 DOI: 10.1007/s10865-024-00476-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 01/28/2024] [Indexed: 02/27/2024]
Abstract
Self-weighing is consistently associated with more effective weight control. However, patterns show that participants disengage from their weight control behaviors following weight gain. Women with BMIs in the overweight/obese range (N = 50) enrolled in a long-term behavioral weight loss program completed ecological momentary assessment (EMA) surveys immediately after their daily weigh-ins. Nightly EMA surveys and self-monitoring data through Fitbit measured their weight control behavior that day. On days when participants gained weight (vs. lost or maintained), they reported more negative mood, more guilt/shame, and lower confidence in weight control. Motivation following daily weight gain depended on participants' overall satisfaction with their weight loss so far: more satisfied participants had marginally higher, but less satisfied participants had marginally lower motivation in response to daily weight gain. Greater guilt/shame and lower motivation after the weigh-in predicted less effective weight control behavior that day (e.g., lower likelihood of calorie tracking, fewer minutes of physical activity). Results demonstrate that even small weight gain is distressing and demoralizing for women in BWL programs, which can lead to goal disengagement. These findings have implications for future BWL interventions, including the potential utility of just-in-time adaptive interventions to promote more adaptive responses in the moments after weigh-ins.
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Affiliation(s)
- Charlotte J Hagerman
- Department of Psychological and Brain Sciences, Center for Weight, Eating and Lifestyle Sciences (WELL Center), Drexel University, Stratton Hall, 3201 Chestnut Street, Philadelphia, PA, 19104, USA.
| | - Michael C Onu
- Department of Psychological and Brain Sciences, Center for Weight, Eating and Lifestyle Sciences (WELL Center), Drexel University, Stratton Hall, 3201 Chestnut Street, Philadelphia, PA, 19104, USA
| | - Nicole T Crane
- Department of Psychological and Brain Sciences, Center for Weight, Eating and Lifestyle Sciences (WELL Center), Drexel University, Stratton Hall, 3201 Chestnut Street, Philadelphia, PA, 19104, USA
| | - Meghan L Butryn
- Department of Psychological and Brain Sciences, Center for Weight, Eating and Lifestyle Sciences (WELL Center), Drexel University, Stratton Hall, 3201 Chestnut Street, Philadelphia, PA, 19104, USA
| | - Evan M Forman
- Department of Psychological and Brain Sciences, Center for Weight, Eating and Lifestyle Sciences (WELL Center), Drexel University, Stratton Hall, 3201 Chestnut Street, Philadelphia, PA, 19104, USA
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2
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Khokhar S, Holden J, Toomer C, Del Parigi A. Weight Loss with an AI-Powered Digital Platform for Lifestyle Intervention. Obes Surg 2024; 34:1810-1818. [PMID: 38573389 DOI: 10.1007/s11695-024-07209-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2023] [Revised: 03/28/2024] [Accepted: 03/28/2024] [Indexed: 04/05/2024]
Abstract
BACKGROUND Lifestyle intervention remains the cornerstone of weight loss programs in addition to pharmacological or surgical therapies. Artificial intelligence (AI) and other digital technologies can offer individualized approaches to lifestyle intervention to enable people with obesity to reach successful weight loss. METHODS SureMediks, a digital lifestyle intervention platform using AI, was tested by 391 participants (58% women) with a broad range of BMI (20-78 kg/m2), with the aim of losing weight over 24 weeks in a multinational field trial. SureMediks consists of a mobile app, an Internet-connected scale, and a discipline of artificial intelligence called Expert system to provide individualized guidance and weight-loss management. RESULTS All participants lost body weight (average 14%, range 4-22%). Almost all (98.7%) participants lost at least 5% of body weight, 75% lost at least 10%, 43% at least 15%, and 9% at least 20%, suggesting that this AI-powered lifestyle intervention was also effective in reducing the burden of obesity co-morbidities. Weight loss was partially positively correlated with female sex, accountability circle size, and participation in challenges, while it was negatively correlated with sub-goal reassignment. The latter three variables are specific features of the SureMediks weight loss program. CONCLUSION An AI-assisted lifestyle intervention allowed people with different body sizes to lose 14% body weight on average, with 99% of them losing more than 5%, over 24 weeks. These results show that digital technologies and AI might provide a successful means to lose weight, before, during, and after pharmacological or surgical therapies.
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Affiliation(s)
| | - John Holden
- Rockford-College of Medicine, University of Illinois, Rockford, IL, 6110, USA
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3
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Butryn ML, Kerrigan S, Hagerman CJ, Crane NT, Godfrey K. Do monthly coaching calls influence proximal participant adherence in a behavioral weight loss program? J Behav Med 2023; 46:699-706. [PMID: 36723730 DOI: 10.1007/s10865-023-00394-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Accepted: 01/11/2023] [Indexed: 02/02/2023]
Abstract
Participants who receive continued coach contact following behavioral weight loss treatment are more successful in maintaining their weight loss long-term. The current study examines whether these contacts have dynamic effects, such that participants are most adherent to the prescribed weight loss behaviors in the days after the call, when motivation and goal salience may be heightened, than they are as time goes on. The current study examined the trajectory of calorie intake, physical activity, weight, and self-monitoring behavior in the fourteen days after a monthly coaching call among participants completing the maintenance phase of a behavioral weight loss trial. For physical activity outcomes, caloric intake, and weight, there were no changes across time. Participants did have the highest adherence and quality of dietary self-monitoring immediately after the call, which diminished over time. Coach contact may continually renew commitment to this burdensome but critical behavior. Likelihood of self-weighing showed an opposite trend, where participants were more likely to weigh themselves in the days more distal from the coach call. Results can inform the timing and content of future coach contact to promote weight control.
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Affiliation(s)
- Meghan L Butryn
- Department of Psychological and Brain Sciences and Center for Weight, Eating and Lifestyle Sciences (WELL Center), Drexel University, 3141 Chestnut St., Stratton 286, Philadelphia, PA, 19104, USA.
| | | | - Charlotte J Hagerman
- Department of Psychological and Brain Sciences and Center for Weight, Eating and Lifestyle Sciences (WELL Center), Drexel University, 3141 Chestnut St., Stratton 286, Philadelphia, PA, 19104, USA
| | - Nicole T Crane
- Department of Psychological and Brain Sciences and Center for Weight, Eating and Lifestyle Sciences (WELL Center), Drexel University, 3141 Chestnut St., Stratton 286, Philadelphia, PA, 19104, USA
| | - Kathryn Godfrey
- Center for WorkLife Wellbeing, ChristianaCare, Wilmington, DE, USA
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Wren GM, Koutoukidis DA, Scragg J, Whitman M, Jebb S. The Association Between Goal Setting and Weight Loss: Prospective Analysis of a Community Weight Loss Program. J Med Internet Res 2023; 25:e43869. [PMID: 37405833 DOI: 10.2196/43869] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 05/05/2023] [Accepted: 06/06/2023] [Indexed: 07/06/2023] Open
Abstract
BACKGROUND Goal setting aids health-related behavior changes; however, the influence of different types of goals on weight loss remains unclear. OBJECTIVE We aimed to investigate the association of 3 aspects of goal setting with weight and program dropout over a 24-week period. METHODS This study was a prospective longitudinal analysis of participants in a 12-week digital behavioral weight loss program. Weight and engagement data for eligible participants (N=36,794) were extracted from the database. Eligible participants were adults in the United Kingdom who had enrolled in the program, had a BMI ≥25 kg/m2, and a weight reading recorded at baseline. Three aspects of goal setting were self-reported at enrollment: weight loss motivation (appearance, health, fitness, or self-efficacy), overall goal preference (low, medium, or high), and percentage weight loss goal (<5%, 5%-10%, or >10%). Weight was measured at 4, 12, and 24 weeks. Mixed models for repeated measures were used to explore the association between goals and weight across the 24-week period. To measure sustained weight change, the primary outcome was weight at 24 weeks. We explored dropout rates over the 24-week period by goal and whether engagement mediated the association between goals and weight loss. RESULTS Of the 36,794 participants (mean 46.7, SD 11.1 years; 33,902/36,794, 92.14% female) included in the cohort, 13.09% (n=4818) reported weight at 24 weeks. Most participants set goals of 5%-10% weight loss (23,629/36,794, 64.22%), but setting goals for >10% was associated with greater weight loss (mean difference 5.21 kg, 95% CI 5.01-5.41; P<.001). There was no difference between goals of 5%-10% and <5% (mean difference 0.59 kg, 95% CI 0.00-1.18; P=.05). Appearance was the most prevalent motivational factor (14,736/36,794, 40.05%), but health and fitness were associated with greater weight losses (mean difference health vs appearance 1.40 kg, 95% CI 1.15-1.65; P<.001 and mean difference fitness vs appearance 0.38 kg, 95% CI 0.05-0.70; P=.03). Goal preference had no association with weight. Engagement was an independent predictor of weight loss but not a mediator of the effect of goal setting. At 24 weeks, those who set goals of >10% were less likely to drop out compared with 5%-10% goals (odds ratio [OR] 0.40, 95% CI 0.38-0.42; P<.001); those who liked to set overall high goals were more likely to drop out compared with medium goals (OR 1.20, 95% CI 1.11-1.29; P<.001); and those motivated by fitness or health were less likely to drop out compared with appearance (OR 0.92, 95% CI 0.85-0.995; P=.04 and OR 0.84, 95% CI 0.78-0.89; P<.001, respectively). CONCLUSIONS Setting higher weight loss goals and being motivated by health or fitness were associated with greater weight loss and lower likelihood of dropout. Randomized trials for setting these types of goals are required to confirm causality.
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Affiliation(s)
- Gina M Wren
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Dimitrios A Koutoukidis
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Jadine Scragg
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | | | - Susan Jebb
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
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Delrieu L, Hamy AS, Coussy F, Kassara A, Asselain B, Antero J, De Villèle P, Dumas E, Forstmann N, Guérin J, Hotton J, Jouannaud C, Milder M, Leopold A, Sedeaud A, Soibinet P, Toussaint JF, Vercamer V, Laas E, Reyal F. Digital phenotyping in young breast cancer patients treated with neoadjuvant chemotherapy (the NeoFit Trial): protocol for a national, multicenter single-arm trial. BMC Cancer 2022; 22:493. [PMID: 35509030 PMCID: PMC9069776 DOI: 10.1186/s12885-022-09608-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Accepted: 03/22/2022] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND Breast cancer (BC) has particular characteristics in young women, with diagnosis at more advanced stages, a poorer prognosis and highly aggressive tumors. In NeoFit, we will use an activity tracker to identify and describe various digital profiles (heart rate, physical activity, and sleep patterns) in women below the age of 45 years on neoadjuvant chemotherapy for BC. METHODS NeoFit is a prospective, national, multicenter, single-arm open-label study. It will include 300 women below the age of 45 years treated with neoadjuvant chemotherapy for BC. Participants will be asked to wear a Withing Steel HR activity tracker round the clock for 12 months. The principal assessments will be performed at baseline, at the end of neoadjuvant chemotherapy and at 12 months. We will evaluate clinical parameters, such as toxicity and the efficacy of chemotherapy, together with quality of life, fatigue, and parameters relating to lifestyle and physical activity. The women will complete REDCap form questionnaires via a secure internet link. DISCUSSION In this study, the use of an activity tracker will enable us to visualize changes in the lifestyle of young women on neoadjuvant chemotherapy for BC, over the course of a one-year period. This exploratory study will provide crucial insight into the digital phenotypes of young BC patients on neoadjuvant chemotherapy and the relationship between these phenotypes and the toxicity and efficacy of treatment. This trial will pave the way for interventional studies involving sleep and physical activity interventions. TRIAL REGISTRATION Clinicaltrials.gov identifier: NCT05011721 . Registration date: 18/08/2021.
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Affiliation(s)
- Lidia Delrieu
- Residual Tumor & Response To Treatment Laboratory, RT2Lab, Translational Research Department, INSERM, U932 Immunity and Cancer, Institut Curie, University Paris, Paris, France
| | - Anne-Sophie Hamy
- Residual Tumor & Response To Treatment Laboratory, RT2Lab, Translational Research Department, INSERM, U932 Immunity and Cancer, Institut Curie, University Paris, Paris, France
- Department of Medical Oncology, Institut Curie, University Paris, Paris, France
| | - Florence Coussy
- Residual Tumor & Response To Treatment Laboratory, RT2Lab, Translational Research Department, INSERM, U932 Immunity and Cancer, Institut Curie, University Paris, Paris, France
- Department of Medical Oncology, Institut Curie, University Paris, Paris, France
| | - Amyn Kassara
- Residual Tumor & Response To Treatment Laboratory, RT2Lab, Translational Research Department, INSERM, U932 Immunity and Cancer, Institut Curie, University Paris, Paris, France
| | | | - Juliana Antero
- Institute for Biomedical and Epidemiological Research in Sport, France University, EA7329, Paris, France
- Institut National du Sport de L'Expertise Et de La Performance, INSEP, Paris, France
| | | | - Elise Dumas
- Residual Tumor & Response To Treatment Laboratory, RT2Lab, Translational Research Department, INSERM, U932 Immunity and Cancer, Institut Curie, University Paris, Paris, France
| | - Nicolas Forstmann
- Institute for Biomedical and Epidemiological Research in Sport, France University, EA7329, Paris, France
- Institut National du Sport de L'Expertise Et de La Performance, INSEP, Paris, France
| | | | - Judicael Hotton
- Department of Surgical Oncology, Institut de Cancérologie Jean-Godinot, Reims, France
| | - Christelle Jouannaud
- Department of Medical Oncology, Institut de Cancérologie Jean-Godinot, Reims, France
| | | | | | - Adrien Sedeaud
- Institute for Biomedical and Epidemiological Research in Sport, France University, EA7329, Paris, France
- Institut National du Sport de L'Expertise Et de La Performance, INSEP, Paris, France
| | - Pauline Soibinet
- Department of Medical Oncology, Institut de Cancérologie Jean-Godinot, Reims, France
| | - Jean-François Toussaint
- Institute for Biomedical and Epidemiological Research in Sport, France University, EA7329, Paris, France
- Institut National du Sport de L'Expertise Et de La Performance, INSEP, Paris, France
- Center for Sports Medicine Research, Hôtel-Dieu, Publics Assistance Hospitals of Paris, Paris, France
| | | | - Enora Laas
- Residual Tumor & Response To Treatment Laboratory, RT2Lab, Translational Research Department, INSERM, U932 Immunity and Cancer, Institut Curie, University Paris, Paris, France
- Department of Surgical Oncology, Institut Curie, University Paris, Paris, France
| | - Fabien Reyal
- Residual Tumor & Response To Treatment Laboratory, RT2Lab, Translational Research Department, INSERM, U932 Immunity and Cancer, Institut Curie, University Paris, Paris, France.
- Department of Surgical Oncology, Institut Curie, University Paris, Paris, France.
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6
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Huhn S, Axt M, Gunga HC, Maggioni MA, Munga S, Obor D, Sié A, Boudo V, Bunker A, Sauerborn R, Bärnighausen T, Barteit S. The Impact of Wearable Technologies in Health Research: Scoping Review. JMIR Mhealth Uhealth 2022; 10:e34384. [PMID: 35076409 PMCID: PMC8826148 DOI: 10.2196/34384] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 11/23/2021] [Accepted: 12/17/2021] [Indexed: 12/23/2022] Open
Abstract
Background Wearable devices hold great promise, particularly for data generation for cutting-edge health research, and their demand has risen substantially in recent years. However, there is a shortage of aggregated insights into how wearables have been used in health research. Objective In this review, we aim to broadly overview and categorize the current research conducted with affordable wearable devices for health research. Methods We performed a scoping review to understand the use of affordable, consumer-grade wearables for health research from a population health perspective using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) framework. A total of 7499 articles were found in 4 medical databases (PubMed, Ovid, Web of Science, and CINAHL). Studies were eligible if they used noninvasive wearables: worn on the wrist, arm, hip, and chest; measured vital signs; and analyzed the collected data quantitatively. We excluded studies that did not use wearables for outcome assessment and prototype studies, devices that cost >€500 (US $570), or obtrusive smart clothing. Results We included 179 studies using 189 wearable devices covering 10,835,733 participants. Most studies were observational (128/179, 71.5%), conducted in 2020 (56/179, 31.3%) and in North America (94/179, 52.5%), and 93% (10,104,217/10,835,733) of the participants were part of global health studies. The most popular wearables were fitness trackers (86/189, 45.5%) and accelerometer wearables, which primarily measure movement (49/189, 25.9%). Typical measurements included steps (95/179, 53.1%), heart rate (HR; 55/179, 30.7%), and sleep duration (51/179, 28.5%). Other devices measured blood pressure (3/179, 1.7%), skin temperature (3/179, 1.7%), oximetry (3/179, 1.7%), or respiratory rate (2/179, 1.1%). The wearables were mostly worn on the wrist (138/189, 73%) and cost <€200 (US $228; 120/189, 63.5%). The aims and approaches of all 179 studies revealed six prominent uses for wearables, comprising correlations—wearable and other physiological data (40/179, 22.3%), method evaluations (with subgroups; 40/179, 22.3%), population-based research (31/179, 17.3%), experimental outcome assessment (30/179, 16.8%), prognostic forecasting (28/179, 15.6%), and explorative analysis of big data sets (10/179, 5.6%). The most frequent strengths of affordable wearables were validation, accuracy, and clinical certification (104/179, 58.1%). Conclusions Wearables showed an increasingly diverse field of application such as COVID-19 prediction, fertility tracking, heat-related illness, drug effects, and psychological interventions; they also included underrepresented populations, such as individuals with rare diseases. There is a lack of research on wearable devices in low-resource contexts. Fueled by the COVID-19 pandemic, we see a shift toward more large-sized, web-based studies where wearables increased insights into the developing pandemic, including forecasting models and the effects of the pandemic. Some studies have indicated that big data extracted from wearables may potentially transform the understanding of population health dynamics and the ability to forecast health trends.
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Affiliation(s)
- Sophie Huhn
- Heidelberg Institute of Global Health, Heidelberg University Hospital, Heidelberg University, Heidelberg, Germany
| | - Miriam Axt
- Heidelberg Institute of Global Health, Heidelberg University Hospital, Heidelberg University, Heidelberg, Germany
| | - Hanns-Christian Gunga
- Charité - Universitätsmedizin Berlin, Institute of Physiology, Center for Space Medicine and Extreme Environment, Berlin, Germany
| | - Martina Anna Maggioni
- Charité - Universitätsmedizin Berlin, Institute of Physiology, Center for Space Medicine and Extreme Environment, Berlin, Germany.,Department of Biomedical Sciences for Health, Università degli Studi di Milano, Milano, Italy
| | | | - David Obor
- Kenya Medical Research Institute, Kisumu, Kenya
| | - Ali Sié
- Heidelberg Institute of Global Health, Heidelberg University Hospital, Heidelberg University, Heidelberg, Germany.,Centre de Recherche en Santé Nouna, Nouna, Burkina Faso
| | | | - Aditi Bunker
- Heidelberg Institute of Global Health, Heidelberg University Hospital, Heidelberg University, Heidelberg, Germany
| | - Rainer Sauerborn
- Heidelberg Institute of Global Health, Heidelberg University Hospital, Heidelberg University, Heidelberg, Germany
| | - Till Bärnighausen
- Heidelberg Institute of Global Health, Heidelberg University Hospital, Heidelberg University, Heidelberg, Germany.,Harvard Center for Population and Development Studies, Cambridge, MA, United States.,Africa Health Research Institute, KwaZulu-Natal, South Africa
| | - Sandra Barteit
- Heidelberg Institute of Global Health, Heidelberg University Hospital, Heidelberg University, Heidelberg, Germany
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7
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Encantado J, Palmeira AL, Silva C, Sniehotta FF, Stubbs RJ, Gouveia MJ, Teixeira PJ, Heitmann BL, Marques MM. What goes on in digital behaviour change interventions for weight loss maintenance targeting physical activity: A scoping review. Digit Health 2022; 8:20552076221129089. [PMID: 36386250 PMCID: PMC9643762 DOI: 10.1177/20552076221129089] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Accepted: 09/10/2022] [Indexed: 09/06/2023] Open
Abstract
OBJECTIVE To identify the core components of digital behaviour change interventions for weight loss maintenance targeting physical activity, in terms of: (i) behaviour change techniques, (ii) mechanisms of action, (iii) modes of delivery, (iv) dose and (v) tailoring/personalization. In addition, the links between these components were investigated. METHODS A literature search was performed in five electronic databases: PubMed, Embase, CINHAL, PsycINFO and Web of Science. Two reviewers independently screened the identified articles and extracted data related with the study characteristics and behaviour change techniques, mechanism of action, mode of delivery, dose, and tailoring, using standardized classifications whenever available (e.g. behaviour change techniques taxonomy). RESULTS Seventeen articles reporting 11 original studies were selected. Two studies were protocols, 9 studies presented results for weight change and all but one showed no significant differences between the intervention and control groups. Eight studies (73%) provided adequate information on behaviour change techniques. Five studies (45%) provided partial information about how the behaviour change techniques were linked to mechanisms of action, and only one study (0.9%) described these links for all the techniques. Around half of the studies reported the modes through which behaviour change techniques were delivered. Descriptions of dose were present in most studies, but with minimal information. The use of tailoring or personalization approaches was mentioned in eight studies (73%), but descriptions of what was tailored and how were minimal. CONCLUSIONS The compilation of information regarding intervention components was difficult due to the lack of information and systematization in reporting across papers. This is particularly true for the reporting of the links between behaviour change techniques and the other core intervention components. This information is crucial to help us understand in the context of behaviour change interventions what works or does not work, how it works and why.
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Affiliation(s)
- Jorge Encantado
- Centro Interdisciplinar para o Estudo da Performance Humana (CIPER),
Faculdade de Motricidade Humana, Universidade de Lisboa, Cruz Quebrada, Portugal
- APPsyCI – Applied Psychology Research Center Capabilities &
Inclusion, ISPA – Instituto Universitário, Lisboa, Portugal
| | - António L Palmeira
- Centro de Investigação em Desporto, Educação Física, Exercício e
Saúde (CIDEFES), Universidade Lusófona, Lisboa, Portugal
| | - Carolina Silva
- Trinity College Dublin, ADAPT SFI Research Centre & Trinity Centre for Practice and
Healthcare Innovation, College Green, Dublin, Ireland
| | - Falko F Sniehotta
- NIHR Policy Research Unit Behavioural Science, Faculty of Medical
Sciences, Institute of Health & Society, Newcastle University, Newcastle,
UK
- Department of Public Health, Preventive and Social Medicine Center
for Preventive Medicine and Digital Health, Heidelberg University, Mannheim Medical
Faculty, Mannheim, Germany
| | - R James Stubbs
- School of Psychology, Faculty of Medicine and Health, University of Leeds, Leeds, UK
| | - Maria João Gouveia
- APPsyCI – Applied Psychology Research Center Capabilities &
Inclusion, ISPA – Instituto Universitário, Lisboa, Portugal
| | - Pedro J Teixeira
- Centro Interdisciplinar para o Estudo da Performance Humana (CIPER),
Faculdade de Motricidade Humana, Universidade de Lisboa, Cruz Quebrada, Portugal
| | - Berit L Heitmann
- Research Unit for Dietary Studies at The Parker Institute Bispebjerg and Frederiksberg
Hospital, part of the Copenhagen University Hospital – The Capital
Region, Copenhagen, Denmark
- The Department of Public Health, Section for General Medicine,
University of Copenhagen, Copenhagen, Denmark
| | - Marta M Marques
- Trinity College Dublin, ADAPT SFI Research Centre & Trinity Centre for Practice and
Healthcare Innovation, College Green, Dublin, Ireland
- Comprehensive Health Research Centre, NOVA Medical School,
Universidade Nova de Lisboa, Lisbon, Portugal
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8
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Sheng Y, Doyle J, Bond R, Jaiswal R, Gavin S, Dinsmore J. Home-based digital health technologies for older adults to self-manage multiple chronic conditions: A data-informed analysis of user engagement from a longitudinal trial. Digit Health 2022; 8:20552076221125957. [PMID: 36171962 PMCID: PMC9511338 DOI: 10.1177/20552076221125957] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Accepted: 08/25/2022] [Indexed: 11/18/2022] Open
Abstract
Background Ageing populations are resulting in higher prevalence of people with multiple chronic conditions (multimorbidity). Digital health platforms have great potential to support self-management of multimorbidity, increasing a person's awareness of their health and well-being, supporting a better understanding of diseases and encouraging behaviour change. However, little research has explored the long-term engagement of older adults with such digital interventions. Methods The aim of this study is to analyse how 60 older adults with multimorbidity engaged with digital symptom and well-being monitoring through a digital health platform over a period of approximately 12 months. Data analysis focused on user retention, frequency of monitoring, intervals in monitoring and patterns of daily engagement. Results Our findings show that the overall engagement with the digital health platform was high, with more than 80% of participants using the technology devices for over 200 days. The submission frequency for symptom parameters (e.g. blood glucose (BG), blood pressure (BP), etc.) was between three and four times per week which was higher than that of self-report (2.24) and weight (2.84). Submissions of exercise (6.12) and sleep (5.67) were more frequent. The majority of interactions happened in the morning time. The most common time of submission for symptom parameters was 10 am, whereas 8 am was the most common time for weight measurements. Conclusions The findings indicate the patterns of engagement of older adults with complex chronic diseases with digital home-based self-management systems.
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Affiliation(s)
- Yiyang Sheng
- NetwellCASALA, Dundalk Institute of Technology, Dundalk, Co. Louth, Ireland
- Yiyang Sheng, NetwellCASALA, Dundalk Institute of Technology, Dublin Rd, Dundalk, Co. Louth A91 K584, Ireland.
| | - Julie Doyle
- NetwellCASALA, Dundalk Institute of Technology, Dundalk, Co. Louth, Ireland
| | - Raymond Bond
- School of Computing, Ulster University, Jordanstown, UK
| | - Rajesh Jaiswal
- School of Computing, Dundalk Institute of Technology, Dundalk, Co. Louth, Ireland
| | - Shane Gavin
- NetwellCASALA, Dundalk Institute of Technology, Dundalk, Co. Louth, Ireland
| | - John Dinsmore
- Trinity Centre for Practice and Healthcare Innovation, School of Nursing and Midwifery, Trinity College Dublin, Dublin, Ireland
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Eisenhauer CM, Brito F, Kupzyk K, Yoder A, Almeida F, Beller RJ, Miller J, Hageman PA. Mobile health assisted self-monitoring is acceptable for supporting weight loss in rural men: a pragmatic randomized controlled feasibility trial. BMC Public Health 2021; 21:1568. [PMID: 34407782 PMCID: PMC8375071 DOI: 10.1186/s12889-021-11618-7] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Accepted: 08/07/2021] [Indexed: 12/02/2022] Open
Abstract
BACKGROUND Addressing overweight and obesity among men at-risk for obesity-related diseases and disability in rural communities is a public health issue. Commercial smartphone applications (apps) that promote self-monitoring for weight loss are widely available. Evidence is lacking regarding what support is required to enhance user engagement with and effectiveness of those technologies. Pragmatically comparing these apps effectiveness, including rural men's desired forms of support when using them, can lead to greater weight loss intervention impact and reach. This study assessed the feasibility and acceptability of a mobile technology application applied differently across two groups for weight loss. METHODS In a two-armed, pragmatic pilot feasibility study, 80 overweight and obese men aged 40-69 were randomized using a 1:1 ratio to either an enhanced Mobile Technology Plus (MT+) intervention or a basic Mobile Technology (MT) intervention. The MT+ group had an enhanced smartphone app for self-monitoring (text messaging, discussion group, Wi-Fi scale) whereas the MT group received a basic app that allowed self-monitoring logging only. Assessments were collected at baseline, 3 and 6 months. App logs were analyzed to track engagement and adherence to self-monitoring. Acceptability was assessed via focus groups. Analysis included descriptive statistics and qualitative content analysis. RESULTS Of 80 men recruited, forty were allocated to each arm. All were included in the primary analysis. Recruitment ended after 10 months with a 97.5 and 92.5% (3 month, 6 month) retention rate. Over 90% of men reported via survey and focus groups that Lose-It app and smart scale (MT+) was an acceptable way to self-monitor weight, dietary intake and physical activity. Adherence to daily app self-monitoring of at least 800 dietary calories or more (reported respectively as MT+, MT) was positive with 73.4, 51.6% tracking at least 5 days a week. Adherence to tracking activity via recorded steps four or more days weekly was positive, 87.8, 64.6%. Men also adhered to self-weighing at least once weekly, 64, 46.3%. At 6 months, an observed mean weight loss was 7.03 kg (95% CI: 3.67, 10.39) for MT+ group and 4.14 kg (95% CI: 2.22, 6.06) for MT group, with 42.9 and 34.2% meeting ≥5% weight loss, respectively. No adverse events were reported. CONCLUSIONS This National Institutes of Health-funded pilot study using mobile technologies to support behavior change for weight loss was found to be feasible and acceptable among midlife and older rural men. The interventions demonstrated successful reductions in weight, noting differing adherence to lifestyle behaviors of eating, monitoring and activity between groups, with men in the MT+ having more favorable results. These findings will be used to inform the design of a larger scale, clinical trial. TRIAL REGISTRATION The trial was prospectively registered with ClinicalTrials NCT03329079 . 11/1/2017.
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Affiliation(s)
- Christine M Eisenhauer
- College of Nursing-Northern Division, University of Nebraska Medical Center, 801 East Benjamin Avenue, Norfolk, NE, 68701, USA.
| | - Fabiana Brito
- College of Public Health, University of Nebraska Medical Center, 984355 Medical Center, Omaha, NE, 68198-4355, USA
| | - Kevin Kupzyk
- College of Nursing-Omaha Division, University of Nebraska Medical Center, 985330 Nebraska Medical Center, Omaha, NE, 68198-5330, USA
| | - Aaron Yoder
- Department of Environmental, Agricultural & Occupational Health, College of Public Health, University of Nebraska Medical Center, 984388 Nebraska Medical Center, Omaha, NE, 68198-4388, USA
| | - Fabio Almeida
- Department of Health Promotion, College of Public Health, University of Nebraska Medical Center, 984365 Nebraska Medical Center, Omaha, NE, 68198-4365, USA
| | - Rebecca Johnson Beller
- College of Nursing-Northern Division, University of Nebraska Medical Center, 801 East Benjamin Avenue, Norfolk, NE, 68701, USA
| | - Jessica Miller
- College of Nursing-Northern Division, University of Nebraska Medical Center, 801 East Benjamin Avenue, Norfolk, NE, 68701, USA
| | - Patricia A Hageman
- Department of Health and Rehabilitation Sciences, College of Allied Health Professions, University of Nebraska Medical Center, 984420 Nebraska Medical Center, Omaha, NE, 68198-4420, USA
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10
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Vuorinen AL, Helander E, Pietilä J, Korhonen I. Frequency of Self-Weighing and Weight Change: Cohort Study With 10,000 Smart Scale Users. J Med Internet Res 2021; 23:e25529. [PMID: 34075879 PMCID: PMC8277333 DOI: 10.2196/25529] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Revised: 12/20/2020] [Accepted: 05/17/2021] [Indexed: 01/20/2023] Open
Abstract
Background Frequent self-weighing is associated with successful weight loss and weight maintenance during and after weight loss interventions. Less is known about self-weighing behaviors and associated weight change in free-living settings. Objective This study aimed to investigate the association between the frequency of self-weighing and changes in body weight in a large international cohort of smart scale users. Methods This was an observational cohort study with 10,000 randomly selected smart scale users who had used the scale for at least 1 year. Longitudinal weight measurement data were analyzed. The association between the frequency of self-weighing and weight change over the follow-up was investigated among normal weight, overweight, and obese users using Pearson’s correlation coefficient and linear models. The association between the frequency of self-weighing and temporal weight change was analyzed using linear mixed effects models. Results The eligible sample consisted of 9768 participants (6515/9768, 66.7% men; mean age 41.5 years; mean BMI 26.8 kg/m2). Of the participants, 4003 (4003/9768, 41.0%), 3748 (3748/9768, 38.4%), and 2017 (2017/9768, 20.6%) were normal weight, overweight, and obese, respectively. During the mean follow-up time of 1085 days, the mean weight change was –0.59 kg, and the mean percentage of days with a self-weigh was 39.98%, which equals 2.8 self-weighs per week. The percentage of self-weighing days correlated inversely with weight change, r=–0.111 (P<.001). Among normal weight, overweight, and obese individuals, the correlations were r=–0.100 (P<.001), r=–0.125 (P<.001), and r=–0.148 (P<.001), respectively. Of all participants, 72.5% (7085/9768) had at least one period of ≥30 days without weight measurements. During the break, weight increased, and weight gains were more pronounced among overweight and obese individuals: 0.58 kg in the normal weight group, 0.93 kg in the overweight group, and 1.37 kg in the obese group (P<.001). Conclusions Frequent self-weighing was associated with favorable weight loss outcomes also in an uncontrolled, free-living setting, regardless of specific weight loss interventions. The beneficial associations of regular self-weighing were more pronounced for overweight or obese individuals.
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Affiliation(s)
- Anna-Leena Vuorinen
- VTT Technical Research Centre of Finland, Tampere, Finland.,Health Sciences, Faculty of Social Sciences, Tampere University, Tampere, Finland
| | - Elina Helander
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Julia Pietilä
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Ilkka Korhonen
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
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11
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Komarzynski S, Wreglesworth NI, Griffiths D, Pecchia L, Subbe CP, Hughes SF, Davies EH, Innominato PF. Embracing Change: Learnings From Implementing Multidimensional Digital Remote Monitoring in Oncology Patients at a District General Hospital During the COVID-19 Pandemic. JCO Clin Cancer Inform 2021; 5:216-220. [PMID: 33606562 DOI: 10.1200/cci.20.00136] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Affiliation(s)
| | - Nicholas I Wreglesworth
- Oncology Department, Ysbyty Gwynedd, Betsi Cadwaladr University Health Board, Bangor, UK.,School of Medical Sciences, Bangor University, Bangor, UK
| | - Dawn Griffiths
- Oncology Department, Ysbyty Gwynedd, Betsi Cadwaladr University Health Board, Bangor, UK
| | | | - Christian P Subbe
- School of Medical Sciences, Bangor University, Bangor, UK.,Acute and Critical Care Medicine, Ysbyty Gwynedd, Betsi Cadwaladr University Health Board, Bangor, UK
| | - Stephen F Hughes
- North Wales Clinical Research Centre, Betsi Cadwaladr University Health Board, Wrexham, UK
| | | | - Pasquale F Innominato
- Oncology Department, Ysbyty Gwynedd, Betsi Cadwaladr University Health Board, Bangor, UK.,Cancer Chronotherapy Team, Warwick Medical School, University of Warwick, Coventry, UK.,European Laboratory U935, Institut National de la Santé et de la Recherche Médicale (INSERM), Paris-Saclay University, Villejuif, France
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12
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Pépin JL, Bruno RM, Yang RY, Vercamer V, Jouhaud P, Escourrou P, Boutouyrie P. Wearable Activity Trackers for Monitoring Adherence to Home Confinement During the COVID-19 Pandemic Worldwide: Data Aggregation and Analysis. J Med Internet Res 2020; 22:e19787. [PMID: 32501803 PMCID: PMC7307323 DOI: 10.2196/19787] [Citation(s) in RCA: 79] [Impact Index Per Article: 19.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Revised: 06/03/2020] [Accepted: 06/04/2020] [Indexed: 01/23/2023] Open
Abstract
Background In the context of home confinement during the coronavirus disease (COVID-19) pandemic, objective, real-time data are needed to assess populations’ adherence to home confinement to adapt policies and control measures accordingly. Objective The aim of this study was to determine whether wearable activity trackers could provide information regarding users' adherence to home confinement policies because of their capacity for seamless and continuous monitoring of individuals’ natural activity patterns regardless of their location. Methods We analyzed big data from individuals using activity trackers (Withings) that count the wearer’s average daily number
of steps in a number of representative nations that adopted different modalities of restriction of citizens’ activities. Results Data on the number of steps per day from over 740,000 individuals around the world were analyzed. We demonstrate the physical activity patterns in several representative countries with total, partial, or no home confinement. The decrease in steps per day in regions with strict total home confinement ranged from 25% to 54%. Partial lockdown (characterized by social distancing measures such as school closures, bar and restaurant closures, and cancellation of public meetings but without strict home confinement) does not appear to have a significant impact on people’s activity compared to the pre-pandemic period. The absolute level of physical activity under total home confinement in European countries is around twofold that in
China. In some countries, such as France and Spain, physical activity started to gradually decrease even before official commitment
to lockdown as a result of initial less stringent restriction orders or self-quarantine. However, physical activity began to increase
again in the last 2 weeks, suggesting a decrease in compliance with confinement orders. Conclusions Aggregate analysis of activity tracker data with the potential for daily updates can provide information regarding adherence to home confinement policies.
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Affiliation(s)
- Jean Louis Pépin
- HP2 (Hypoxia and Physio-Pathologies) Laboratory, Inserm (French National Institute of Health and Medical Research) U1042, University Grenoble Alpes, Grenoble, France.,EFCR (Cardiovascular and Respiratory Function) Laboratory, Grenoble Alpes University Hospital, Grenoble, France
| | - Rosa Maria Bruno
- Inserm (French National Institute of Health and Medical Research) U970, Hôpital Européen Georges Pompidou, Assistance Publique Hôpitaux de Paris, Paris, France.,Université de Paris, Paris, France
| | | | | | | | - Pierre Escourrou
- Hôpital Béclère, Assistance Publique Hôpitaux de Paris, Paris, France.,Université Paris Saclay, Paris, France
| | - Pierre Boutouyrie
- Inserm (French National Institute of Health and Medical Research) U970, Hôpital Européen Georges Pompidou, Assistance Publique Hôpitaux de Paris, Paris, France.,Université de Paris, Paris, France
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