Evidence map›Paper›PMID 30683106›Full record

ArticleBMC medical informatics and decision making2019

Development and validation of a pain monitoring app for patients with musculoskeletal conditions (The Keele pain recorder feasibility study).

John Bedson, Jonathon Hill, David White, Ying Chen, Simon Wathall, Stephen Dent, Kendra Cooke, Danielle van der Windt

Registry-linked trialOpen access · goldAbstract readValidation Study
In one paragraph

Article in BMC medical informatics and decision making, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04975568 (Effectiveness of Therapeutic Exercise Controlled Through App Adding Face-to-face Supervision Executed by Physical Therapist in the Subacute and Chronic Low Back Pain), which is not on this map. Cited by 15 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 3 pooled it
3.6field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT04975568 nacompletednot on this mapstarted 2021, after this paper: background citation

Effectiveness of Therapeutic Exercise Controlled Through App Adding Face-to-face Supervision Executed by Physical Therapist in the Subacute and Chronic Low Back Pain

TypeinterventionalSponsorUniversidad Complutense de MadridRan2021 to 2022Enrolled90ConditionsLow Back PainArmsApp and face-to-face physical therapy, App physical therapy
3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 3 syntheses or guidelines pooled it, 36 citations in OpenAlex.

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  9. The Effect of Everyday-Life Social Contact on Pain.Journal of medical Internet research · 2024
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 1 institution in 1 country.

John BedsonArthritis Research UK Primary Care Centre, Research Institute for Primary Care & Health Sciences, Keele University, Keele, Staffordshire, ST5 5BG, UK. j.bedson@keele.ac.uk.ORCID 0000-0001-9521-210X
Jonathon HillArthritis Research UK Primary Care Centre, Research Institute for Primary Care & Health Sciences, Keele University, Keele, Staffordshire, ST5 5BG, UK.
David WhiteArthritis Research UK Primary Care Centre, Research Institute for Primary Care & Health Sciences, Keele University, Keele, Staffordshire, ST5 5BG, UK.
Ying ChenArthritis Research UK Primary Care Centre, Research Institute for Primary Care & Health Sciences, Keele University, Keele, Staffordshire, ST5 5BG, UK.
Simon WathallArthritis Research UK Primary Care Centre, Research Institute for Primary Care & Health Sciences, Keele University, Keele, Staffordshire, ST5 5BG, UK.
Stephen DentArthritis Research UK Primary Care Centre, Research Institute for Primary Care & Health Sciences, Keele University, Keele, Staffordshire, ST5 5BG, UK.
Kendra CookeArthritis Research UK Primary Care Centre, Research Institute for Primary Care & Health Sciences, Keele University, Keele, Staffordshire, ST5 5BG, UK.
Danielle van der WindtArthritis Research UK Primary Care Centre, Research Institute for Primary Care & Health Sciences, Keele University, Keele, Staffordshire, ST5 5BG, UK.
Keele University · GB

Funding

Department of Health
6 · The paper itself

Abstract

backgroundAssessing daily change in pain and related symptoms help in diagnosis, prognosis, and monitoring response to treatment. However, such changes are infrequently assessed, and usually reviewed weeks or months after the start of treatment. We therefore developed a smartphone application (Keele Pain Recorder) to record information on the severity and impact of pain on daily life. Specifically, the study goal was to assess face, content and construct validity of data collection using the Pain Recorder in primary care patients receiving new analgesic prescriptions for musculoskeletal pain, as well as to assess its acceptability and clinical utility.

methodsThe app was developed with Keele's Research User Group (RUG), a clinical advisory group (CAG) and software developer for use on Android devices. The app recorded pain levels, interference, sleep disturbance, analgesic use, mood and side effects. In a feasibility study, patients aged > 18 attending their general practitioner (GP) with a painful musculoskeletal condition were recruited to use the app twice per day for 28 days. Face and construct validity were assessed through baseline and post-study questionnaires (Spearman's rank correlation coefficient). Usability and acceptability were determined through post-study questionnaires, and patient, GP, RUG and CAG interviews.

resultsAn app was developed which was liked by both patients and GPs. It was felt that it offered the opportunity for GPs to discuss pain control with their patients in a new way. All participants found the app easy to use (it did not interfere with their activities) and results easy to interpret. Strong associations existed between the first 3 days (Spearman r = 0.79) and last 3 days (r = 0.60) of pain levels and intensity scores on the app with the validated questionnaires.

conclusionsCollaborating with patient representatives and clinical stakeholders, we developed an app which can be used to help clinicians and patients monitor painful musculoskeletal conditions in response to analgesic prescribing. Recordings were accurate and valid, especially, for pain intensity ratings, and it was easy to use. Future work needs to examine how pain trajectories can help manage changes in a patient's condition, ultimately assisting in self-management.

Indexed as

Mobile ApplicationsPatient Acceptance of Health CareSoftware DesignAgedData CollectionFeasibility StudiesFemaleHumansMaleMiddle AgedMonitoring, PhysiologicMusculoskeletal PainPain ManagementPrimary Health CareSmartphoneTelemedicineAppApplicationAssessmenteHealthMusculoskeletalPainPrimary careSmartphoneTelehealth

Identifiers

PMID30683106
PMCPMC6347830
OpenAlexW2913179615

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.