Evidence map›Paper›PMID 37283228›Full record

Observational studyJMIR mHealth and uHealth2023

Exploring the Feasibility and Usability of Smartphones for Monitoring Physical Activity in Orthopedic Patients: Prospective Observational Study.

Arash Ghaffari, Rikke Emilie Kildahl Lauritsen, Michael Christensen, Trine Rolighed Thomsen, Harshit Mahapatra, Robert Heck, Søren Kold, Ole Rahbek

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in JMIR mHealth and uHealth, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.9field-weighted citation impact, top 27% 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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Trial
  2. Review
  3. Observational
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 3 institutions in 1 country.

Arash Ghaffari *Interdisciplinary Orthopaedics, Aalborg University Hospital, Aalborg, Denmark.ORCID 0000-0002-6901-0763
Rikke Emilie Kildahl LauritsenInterdisciplinary Orthopaedics, Aalborg University Hospital, Aalborg, Denmark.ORCID 0000-0003-2906-8909
Michael ChristensenAlexandra Institute, Aarhus, Denmark.ORCID 0000-0003-2649-6967
Trine Rolighed ThomsenDanish Technological Institute, Aarhus, Denmark.ORCID 0000-0002-7393-9372
Harshit MahapatraAlexandra Institute, Aarhus, Denmark.ORCID 0000-0002-4608-7637
Robert HeckDanish Technological Institute, Aarhus, Denmark.ORCID 0000-0003-4511-7731
Søren KoldInterdisciplinary Orthopaedics, Aalborg University Hospital, Aalborg, Denmark.ORCID 0000-0002-3387-1473
Ole RahbekInterdisciplinary Orthopaedics, Aalborg University Hospital, Aalborg, Denmark.ORCID 0000-0002-5602-4533
Aalborg University Hospital · DKAlexandra Institute (Denmark) · DKDanish Technological Institute · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSmartphones are often equipped with inertial sensors that measure individuals' physical activity (PA). However, their role in remote monitoring of the patients' PAs in telemedicine needs to be adequately explored.

objectiveThis study aimed to explore the correlation between a participant's actual daily step counts and the daily step counts reported by their smartphone. In addition, we inquired about the usability of smartphones for collecting PA data.

methodsThis prospective observational study was conducted among patients undergoing lower limb orthopedic surgery and a group of nonpatients as control. The data from the patients were collected from 2 weeks before surgery until 4 weeks after the surgery, whereas the data collection period for the nonpatients was 2 weeks. The participant's daily step count was recorded by PA trackers worn 24/7. In addition, a smartphone app collected the number of daily steps registered by the participants' smartphones. We compared the cross-correlation between the daily steps time series obtained from the smartphones and PA trackers in different groups of participants. We also used mixed modeling to estimate the total number of steps, using smartphone step counts and the characteristics of the patients as independent variables. The System Usability Scale was used to evaluate the participants' experience with the smartphone app and the PA tracker.

resultsOverall, 1067 days of data were collected from 21 patients (n=11, 52% female patients) and 10 nonpatients (n=6, 60% female patients). The median cross-correlation coefficient on the same day was 0.70 (IQR 0.53-0.83). The correlation in the nonpatient group was slightly higher than that in the patient group (median 0.74, IQR 0.60-0.90 and median 0.69, IQR 0.52-0.81, respectively). The likelihood ratio tests on the models fitted by mixed effects methods demonstrated that the smartphone step count was positively correlated with the PA tracker's total number of steps (χ

conclusionsConsidering the ubiquity, convenience, and practicality of smartphones, the high correlation between the smartphones and the total daily step count time series highlights the potential usefulness of smartphones in detecting changes in the number of steps in remote monitoring of a patient's PA.

Indexed as

Mobile ApplicationsSmartphoneData CollectionExerciseFeasibility StudiesFemaleHumansMalemixed effects modelingmobile phonephysical activityremote monitoringsmartphone applicationstep countstep count predictionwearable sensors

Identifiers

PMID37283228
PMCPMC10354652
OpenAlexW4379600112

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.