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The effect of personalized intelligent digital systems for self-care training on type II diabetes: a systematic review and meta-analysis of clinical trials

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A Correction to this article was published on 15 September 2023

This article has been updated

Abstract

Aims

Type 2 diabetes (T2D) is rising worldwide. Self-care prevents diabetic complications. Lack of knowledge is one reason patients fail at self-care. Intelligent digital health (IDH) solutions have a promising role in training self-care behaviors based on patients’ needs. This study reviews the effects of RCTs offering individualized self-care training systems for T2D patients.

Methods

PubMed, Web of Science, Scopus, Cochrane Library, and Science Direct databases were searched. The included RCTs provided data-driven, individualized self-care training advice for T2D patients. Due to the repeated studies measurements, an all-time-points meta-analysis was conducted to analyze the trends over time. The revised Cochrane risk-of-bias tool (RoB 2.0) was used for quality assessment.

Results

In total, 22 trials met the inclusion criteria, and 19 studies with 3071 participants were included in the meta-analysis. IDH interventions led to a significant reduction of HbA1c level in the intervention group at short-term (in the third month: SMD = − 0.224 with 95% CI − 0.319 to − 0.129, p value < 0.0; in the sixth month: SMD = − 0.548 with 95% CI − 0.860 to − 0.237, p value < 0.05). The difference in HbA1c reduction between groups varied based on patients’ age and technological forms of IDH services delivery. The descriptive results confirmed the impact of M-Health technologies in improving HbA1c levels.

Conclusions

IDH systems had significant and small effects on HbA1c reduction in T2D patients. IDH interventions’ impact needs long-term RCTs. This review will help diabetic clinicians, self-care training system developers, and researchers interested in using IDH solutions to empower T2D patients.

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Acknowledgements

The authors would like to express their sincere gratitude to Dr. Abbas Ali Keshtkar for his valuable courses to train the systematic review and meta-analysis principles and his expert advice.

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Author notes

  1. Mozhgan Tanhapour and Maryam Peimani should be considered joint first authors.

Authors and Affiliations

  1. Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran

    Mozhgan Tanhapour, Sharareh Rostam Niakan Kalhori & Niloofar Mohammadzadeh

  2. Diabetes Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Science, Tehran, Iran

    Maryam Peimani & Ensieh Nasli Esfahani

  3. Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School, 38106, Braunschweig, Germany

    Sharareh Rostam Niakan Kalhori

  4. Department of Computer Engineering, Faculty of Engineering, Alzahra University, Tehran, Iran

    Hadi Shakibian

  5. Non-communicable Disease Research Center, Alborz University of Medical Sciences, Karaj, Iran

    Mostafa Qorbani

Authors
  1. Mozhgan Tanhapour
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  2. Maryam Peimani
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  6. Niloofar Mohammadzadeh
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Contributions

Conceptualization: MT, MP, SRNK, ENE, HS, NM, MQ Design: MT, MP, SRNK, ENE, HS, NM, MQ Literature search: MT, MP, NM Analysis and interpretation of data: MT, MQ Supervision: MP, SRNK, ENE, HS, NM, MQ Writing manuscript draft: MT Writing–review & editing: MT, MP, SRNK, ENE, HS, NM, MQ Project administration: NM.

Corresponding author

Correspondence to Niloofar Mohammadzadeh.

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This article belongs to the topical collection Health Education and Psycho-Social Aspects, managed by Massimo Porta and Marina Trento.

The original online version of this article was revised: Numbers in the “Result” Section and “Search Results” sub-section corrected.

Appendix

Appendix

See Table 3 and Figs. 8, 9, 10.

Fig. 8
figure 8

One-out-remove method result at three months after intervention. The standard mean difference and p value in each row indicated the effect size of remaining studies after removing the related RCT

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Fig. 9
figure 9

One-out-remove method result at six months after intervention. The standard mean difference and p value in each row indicated the effect size of remaining studies after removing the related RCT

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Fig. 10
figure 10

One-out-remove method result at twelve months after intervention. The standard mean difference and p value in each row indicated the effect size of remaining studies after removing the related RCT

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Table 3 Characteristics of included randomized controlled trials
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Tanhapour, M., Peimani, M., Rostam Niakan Kalhori, S. et al. The effect of personalized intelligent digital systems for self-care training on type II diabetes: a systematic review and meta-analysis of clinical trials. Acta Diabetol 60, 1599–1631 (2023). https://doi.org/10.1007/s00592-023-02133-9

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