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Pain Assessment–Can it be Done with a Computerised System? A Systematic Review and Meta-Analysis

Author

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  • Nuno Pombo

    (Instituto de Telecomunicações (Telecommunications Institute), University of Beira Interior, Covilhã 6200-001, Portugal
    Department of Informatics, University of Beira Interior, Covilhã 6200-001, Portugal
    ALLab—Assisted Living Computing and Telecommunications Laboratory, University of Beira Interior, Covilhã 6200-001, Portugal)

  • Nuno Garcia

    (Instituto de Telecomunicações (Telecommunications Institute), University of Beira Interior, Covilhã 6200-001, Portugal
    Department of Informatics, University of Beira Interior, Covilhã 6200-001, Portugal
    ALLab—Assisted Living Computing and Telecommunications Laboratory, University of Beira Interior, Covilhã 6200-001, Portugal)

  • Kouamana Bousson

    (Department of Aerospace Sciences, University of Beira Interior, Covilhã 6200-001, Portugal)

  • Susanna Spinsante

    (Dipartimento di Ingegneria dell’Informazione, Università Politecnica delle Marche, Ancona 60121, Italy)

  • Ivan Chorbev

    (Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University Skopje, Skopje 1000, Macedonia)

Abstract

Background : Mobile and web technologies are becoming increasingly used to support the treatment of chronic pain conditions. However, the subjectivity of pain perception makes its management and evaluation very difficult. Pain treatment requires a multi-dimensional approach (e.g., sensory, affective, cognitive) whence the evidence of technology effects across dimensions is lacking. This study aims to describe computerised monitoring systems and to suggest a methodology, based on statistical analysis, to evaluate their effects on pain assessment. Methods : We conducted a review of the English-language literature about computerised systems related to chronic pain complaints that included data collected via mobile devices or Internet, published since 2000 in three relevant bibliographical databases such as BioMed Central, PubMed Central and ScienceDirect. The extracted data include: objective and duration of the study, age and condition of the participants, and type of collected information (e.g., questionnaires, scales). Results : Sixty-two studies were included, encompassing 13,338 participants. A total of 50 (81%) studies related to mobile systems, and 12 (19%) related to web-based systems. Technology and pen-and-paper approaches presented equivalent outcomes related with pain intensity. Conclusions : The adoption of technology was revealed as accurate and feasible as pen-and-paper methods. The proposed assessment model based on data fusion combined with a qualitative assessment method was revealed to be suitable. Data integration raises several concerns and challenges to the design, development and application of monitoring systems applied to pain.

Suggested Citation

  • Nuno Pombo & Nuno Garcia & Kouamana Bousson & Susanna Spinsante & Ivan Chorbev, 2016. "Pain Assessment–Can it be Done with a Computerised System? A Systematic Review and Meta-Analysis," IJERPH, MDPI, vol. 13(4), pages 1-27, April.
    • Handle: RePEc:gam:jijerp:v:13:y:2016:i:4:p:415-:d:68121
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    References listed on IDEAS

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    1. Shin, Vladimir & Shevlyakov, Georgy & Kim, Kiseon, 2007. "A new fusion formula and its application to continuous-time linear systems with multisensor environment," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 840-854, October.
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