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  1. Article ; Online: The Effectiveness of eHealth Interventions for Weight Loss and Weight Loss Maintenance in Adults with Overweight or Obesity: A Systematic Review of Systematic Reviews.

    Kupila, Sakris K E / Joki, Anu / Suojanen, Laura-U / Pietiläinen, Kirsi H

    Current obesity reports

    2023  Volume 12, Issue 3, Page(s) 371–394

    Abstract: PURPOSE OF REVIEW: The purpose of this study is to evaluate the effectiveness of eHealth interventions for weight loss and weight loss maintenance among adults with overweight or obesity through a systematic review of systematic reviews. RECENT FINDINGS: ...

    Abstract PURPOSE OF REVIEW: The purpose of this study is to evaluate the effectiveness of eHealth interventions for weight loss and weight loss maintenance among adults with overweight or obesity through a systematic review of systematic reviews. RECENT FINDINGS: This study included 26 systematic reviews, covering a total of 338 original studies, published between 2018 and 2023. The review indicates that eHealth interventions are more effective than control interventions or no care and comparable to face-to-face interventions. The effect sizes remain relatively small when comparing eHealth interventions to any control conditions, with mean differences of weight loss results from - 0.12 kg (95% CI - 0.64 to 0.41 kg) in a review comparing eHealth interventions to face-to-face care to - 4.32 kg (- 5.08 kg to - 3.57 kg) in a review comparing eHealth interventions to no care. The methodological quality of the included studies varies considerably. However, it can be concluded that interventions with human contact work better than those that are fully automated. In conclusion, this systematic review of systematic reviews provides an updated understanding of the development of digital interventions in recent years and their effectiveness for weight loss and weight loss maintenance among adults with overweight or obesity. The findings suggest that eHealth interventions can be a valuable tool for delivering obesity care to more patients economically. Further research is needed to determine which specific types of eHealth interventions are most effective and how to best integrate them into clinical practice.
    MeSH term(s) Humans ; Adult ; Overweight ; Systematic Reviews as Topic ; Obesity ; Weight Loss ; Telemedicine
    Language English
    Publishing date 2023-06-24
    Publishing country United States
    Document type Journal Article ; Review
    ISSN 2162-4968
    ISSN (online) 2162-4968
    DOI 10.1007/s13679-023-00515-2
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Correction: The Effectiveness of eHealth Interventions for Weight Loss and Weight Loss Maintenance in Adults with Overweight or Obesity: A Systematic Review of Systematic Reviews.

    Kupila, Sakris K E / Joki, Anu / Suojanen, Laura-U / Pietiläinen, Kirsi H

    Current obesity reports

    2023  Volume 12, Issue 4, Page(s) 544–545

    Language English
    Publishing date 2023-10-13
    Publishing country United States
    Document type Published Erratum
    ISSN 2162-4968
    ISSN (online) 2162-4968
    DOI 10.1007/s13679-023-00530-3
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Development and validation of a weight-loss predictor to assist weight loss management.

    Biehl, Alexander / Venäläinen, Mikko S / Suojanen, Laura U / Kupila, Sakris / Ahola, Aila J / Pietiläinen, Kirsi H / Elo, Laura L

    Scientific reports

    2023  Volume 13, Issue 1, Page(s) 20661

    Abstract: This study aims to develop and validate a modeling framework to predict long-term weight change on the basis of self-reported weight data. The aim is to enable focusing resources of health systems on individuals that are at risk of not achieving their ... ...

    Abstract This study aims to develop and validate a modeling framework to predict long-term weight change on the basis of self-reported weight data. The aim is to enable focusing resources of health systems on individuals that are at risk of not achieving their goals in weight loss interventions, which would help both health professionals and the individuals in weight loss management. The weight loss prediction models were built on 327 participants, aged 21-78, from a Finnish weight coaching cohort, with at least 9 months of self-reported follow-up weight data during weight loss intervention. With these data, we used six machine learning methods to predict weight loss after 9 months and selected the best performing models for implementation as modeling framework. We trained the models to predict either three classes of weight change (weight loss, insufficient weight loss, weight gain) or five classes (high/moderate/insufficient weight loss, high/low weight gain). Finally, the prediction accuracy was validated with an independent cohort of overweight UK adults (n = 184). Of the six tested modeling approaches, logistic regression performed the best. Most three-class prediction models achieved prediction accuracy of > 50% already with half a month of data and up to 97% with 8 months. The five-class prediction models achieved accuracies from 39% (0.5 months) to 89% (8 months). Our approach provides an accurate prediction method for long-term weight loss, with potential for easier and more efficient management of weight loss interventions in the future. A web application is available: https://elolab.shinyapps.io/WeightChangePredictor/ .The trial is registered at clinicaltrials.gov/ct2/show/NCT04019249 (Clinical Trials Identifier NCT04019249), first posted on 15/07/2019.
    MeSH term(s) Adult ; Humans ; Obesity/therapy ; Overweight ; Self Report ; Weight Loss ; Weight Gain
    Language English
    Publishing date 2023-11-24
    Publishing country England
    Document type Journal Article
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-023-47930-y
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Effectiveness of a web-based real-life weight management program: Study design, methods, and participants' baseline characteristics.

    Suojanen, L-U / Ahola, A J / Kupila, S / Korpela, R / Pietiläinen, K H

    Contemporary clinical trials communications

    2020  Volume 19, Page(s) 100638

    Abstract: Obesity is an important public health concern with limited effective treatment options. Internet-based technologies offer a cost-effective means to treat obesity. However, most of the online programs have been of short duration, have focused on a limited ...

    Abstract Obesity is an important public health concern with limited effective treatment options. Internet-based technologies offer a cost-effective means to treat obesity. However, most of the online programs have been of short duration, have focused on a limited number of treatment modalities, and have not utilized the potential of coaching as part of the intervention. In this paper, we present the design, methods and participants' baseline characteristics in a real-life internet-based weight management program. Healthy Weight Coaching (HWC) is a 12-month web-based intervention for the management of obesity. The program is based on the Acceptance and Commitment Therapy and includes themes important for weight loss, including diet, physical activity, psychological factors, and sleep. In addition to the automated, interactive program, a personal coach is allocated to each participant. The participants are nationally enrolled through referrals from primary care, occupational health, hospitals, and private health care units. Adult individuals with BMI ≥25 kg/m
    Trial registration: The trial is registered at clinicaltrials.cov (Clinical Trials Identifier NCT04019249).
    Language English
    Publishing date 2020-08-13
    Publishing country Netherlands
    Document type Journal Article
    ISSN 2451-8654
    ISSN (online) 2451-8654
    DOI 10.1016/j.conctc.2020.100638
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Effectiveness of a web-based real-life weight management program

    L-U. Suojanen / A.J. Ahola / S. Kupila / R. Korpela / K.H. Pietiläinen

    Contemporary Clinical Trials Communications, Vol 19, Iss , Pp 100638- (2020)

    Study design, methods, and participants’ baseline characteristics

    2020  

    Abstract: Obesity is an important public health concern with limited effective treatment options. Internet-based technologies offer a cost-effective means to treat obesity. However, most of the online programs have been of short duration, have focused on a limited ...

    Abstract Obesity is an important public health concern with limited effective treatment options. Internet-based technologies offer a cost-effective means to treat obesity. However, most of the online programs have been of short duration, have focused on a limited number of treatment modalities, and have not utilized the potential of coaching as part of the intervention. In this paper, we present the design, methods and participants’ baseline characteristics in a real-life internet-based weight management program. Healthy Weight Coaching (HWC) is a 12-month web-based intervention for the management of obesity. The program is based on the Acceptance and Commitment Therapy and includes themes important for weight loss, including diet, physical activity, psychological factors, and sleep. In addition to the automated, interactive program, a personal coach is allocated to each participant. The participants are nationally enrolled through referrals from primary care, occupational health, hospitals, and private health care units. Adult individuals with BMI ≥25 kg/m2 without severe complications are included. On a weekly basis, participants submit their weight logs, training sessions, and lifestyle targets to the internet portal and are scheduled to have online discussions with their coaches 26 times over the course of a year. Questionnaires on lifestyle, diet, physical activity, psychological factors, sleep, and quality of life are completed at baseline, 3, 6, 9, and 12 months, and thereafter yearly until 5 years. Additionally, log data on the use of the service and discussions with the coach are collected. The main outcome is weight change from baseline to 12 months. Recruitment to the HWC is ongoing. Baseline data of the participants recruited between Oct 2016 and Mar 2019 (n = 1189) are provided. This research will bring insight into how internet-based technologies can be implemented in the virtual management of obesity. Trial registration: The trial is registered at clinicaltrials.cov (Clinical Trials Identifier NCT04019249).
    Keywords Obesity ; Web-based intervention ; Weight management ; Acceptance and commitment therapy ; Medicine (General) ; R5-920
    Subject code 796
    Language English
    Publishing date 2020-09-01T00:00:00Z
    Publisher Elsevier
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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