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A systematic review and meta-analysis of digital application use in clinical research in pain medicine

Shetty, A; Delanerolle, G; Zeng, Y; Shi, JQ; Ebrahim, R; Pang, J; Hapangama, D; ... Phiri, P; + view all (2022) A systematic review and meta-analysis of digital application use in clinical research in pain medicine. Frontiers in Digital Health , 4 , Article 850601. 10.3389/fdgth.2022.850601. Green open access

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Abstract

IMPORTANCE: Pain is a silent global epidemic impacting approximately a third of the population. Pharmacological and surgical interventions are primary modes of treatment. Cognitive/behavioural management approaches and interventional pain management strategies are approaches that have been used to assist with the management of chronic pain. Accurate data collection and reporting treatment outcomes are vital to addressing the challenges faced. In light of this, we conducted a systematic evaluation of the current digital application landscape within chronic pain medicine. OBJECTIVE: The primary objective was to consider the prevalence of digital application usage for chronic pain management. These digital applications included mobile apps, web apps, and chatbots. DATA SOURCES: We conducted searches on PubMed and ScienceDirect for studies that were published between 1st January 1990 and 1st January 2021. STUDY SELECTION: Our review included studies that involved the use of digital applications for chronic pain conditions. There were no restrictions on the country in which the study was conducted. Only studies that were peer-reviewed and published in English were included. Four reviewers had assessed the eligibility of each study against the inclusion/exclusion criteria. Out of the 84 studies that were initially identified, 38 were included in the systematic review. DATA EXTRACTION AND SYNTHESIS: The AMSTAR guidelines were used to assess data quality. This assessment was carried out by 3 reviewers. The data were pooled using a random-effects model. MAIN OUTCOME(S) AND MEASURE(S): Before data collection began, the primary outcome was to report on the standard mean difference of digital application usage for chronic pain conditions. We also recorded the type of digital application studied (e.g., mobile application, web application) and, where the data was available, the standard mean difference of pain intensity, pain inferences, depression, anxiety, and fatigue. RESULTS: 38 studies were included in the systematic review and 22 studies were included in the meta-analysis. The digital interventions were categorised to web and mobile applications and chatbots, with pooled standard mean difference of 0.22 (95% CI: −0.16, 0.60), 0.30 (95% CI: 0.00, 0.60) and −0.02 (95% CI: −0.47, 0.42) respectively. Pooled standard mean differences for symptomatologies of pain intensity, depression, and anxiety symptoms were 0.25 (95% CI: 0.03, 0.46), 0.30 (95% CI: 0.17, 0.43) and 0.37 (95% CI: 0.05, 0.69), respectively. A sub-group analysis was conducted on pain intensity due to the heterogeneity of the results (I2 = 82.86%; p = 0.02). After stratifying by country, we found that digital applications were more likely to be effective in some countries (e.g., United States, China) than others (e.g., Ireland, Norway). CONCLUSIONS AND RELEVANCE: The use of digital applications in improving pain-related symptoms shows promise, but further clinical studies would be needed to develop more robust applications. SYSTEMATIC REVIEW REGISTRATION: https://www.crd.york.ac.uk/prospero/, identifier: CRD42021228343.

Type: Article
Title: A systematic review and meta-analysis of digital application use in clinical research in pain medicine
Location: Switzerland
Open access status: An open access version is available from UCL Discovery
DOI: 10.3389/fdgth.2022.850601
Publisher version: https://doi.org/10.3389/fdgth.2022.850601
Language: English
Additional information: © 2022 Shetty, Delanerolle, Zeng, Shi, Ebrahim, Pang, Hapangama, Sillem, Shetty, Shetty, Hirsch, Raymont, Majumder, Chong, Goodison, O'hara, Hull, Pluchino, Shetty, Elneil, Fernandez, Brownstone and Phiri. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Keywords: Chronic pain, digital app, digital medicine, mHealth, pain management
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Surgery and Interventional Sci
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL EGA Institute for Womens Health
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Department of Neuromuscular Diseases
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Surgery and Interventional Sci > Department of Targeted Intervention
URI: https://discovery.ucl.ac.uk/id/eprint/10172957
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