Evidence map›Paper›PMID 30104183›Full record

ArticleJMIR mHealth and uHealth2018

mHealth Self-Report Monitoring in Competitive Middle- and Long-Distance Runners: Qualitative Study of Long-Term Use Intentions Using the Technology Acceptance Model.

Sara Rönnby, Oscar Lundberg, Kristina Fagher, Jenny Jacobsson, Bo Tillander, Håkan Gauffin, Per-Olof Hansson, Örjan Dahlström, Toomas Timpka

Open access · goldAbstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.4field-weighted citation impact, top 19% 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

9 citing papers in PubMed, 19 citations in OpenAlex.

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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

9 authors at 1 institution in 1 country.

Sara RönnbyAthletics Research Center, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.ORCID http://orcid.org/0000-0002-4807-0257
Oscar LundbergAthletics Research Center, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.ORCID http://orcid.org/0000-0001-6479-1938
Kristina FagherAthletics Research Center, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.ORCID http://orcid.org/0000-0002-9524-7553
Jenny JacobssonAthletics Research Center, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.ORCID http://orcid.org/0000-0002-1551-1722
Bo TillanderAthletics Research Center, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.ORCID http://orcid.org/0000-0001-5795-5447
Håkan GauffinAthletics Research Center, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.ORCID http://orcid.org/0000-0003-3565-4461
Per-Olof HanssonAthletics Research Center, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.ORCID http://orcid.org/0000-0003-3174-5956
Örjan DahlströmAthletics Research Center, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.ORCID http://orcid.org/0000-0002-3955-0443
Toomas TimpkaAthletics Research Center, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.ORCID http://orcid.org/0000-0001-6049-5402
Linköping University · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInternational middle- and long-distance running competitions attract millions of spectators in association with city races, world championships, and Olympic Games. It is therefore a major concern that ill health and pain, as a result of sports overuse, lead to numerous hours of lost training and decreased performance in competitive runners. Despite its potential for sustenance of performance, approval of mHealth self-report monitoring (mHSM) in this group of athletes has not been investigated.

objectiveThe objective of our study was to explore individual and situational factors associated with the acceptance of long-term mHSM in competitive runners.

methodsThe study used qualitative research methods with the Technology Acceptance Model as the theoretical foundation. The study population included 20 middle- and long-distance runners competing at national and international levels. Two mHSM apps asking for health and training data from track and marathon runners were created on a platform for web survey development (Briteback AB). Data collection for the technology acceptance analysis was performed via personal interviews before and after a 6-week monitoring period. Preuse interviews investigated experience and knowledge of mHealth monitoring and thoughts on benefits and possible side effects. The postuse interviews addressed usability and usefulness, attitudes toward nonfunctional issues, and intentions to adhere to long-term monitoring. In addition, the runners' trustworthiness when providing mHSM data was discussed. The interview data were investigated using a deductive thematic analysis.

resultsThe mHSM apps were considered technically easy to use. Although the runners read the instructions and entered data effortlessly, some still perceived mHSM as problematic. Concerns were raised about the selection of items for monitoring (eg, recording training load as running distance or time) and about interpretation of concepts (eg, whether subjective well-being should encompass only the running context or daily living on the whole). Usefulness of specific mHSM apps was consequently not appraised on the same bases in different subcategories of runners. Regarding nonfunctional issues, the runners competing at the international level requested detailed control over who in their sports club and national federation should be allowed access to their data; the less competitive runners had no such issues. Notwithstanding, the runners were willing to adhere to long-term mHSM, provided the technology was adjusted to their personal routines and the output was perceived as contributing to running performance.

conclusionsAdoption of mHSM by competitive runners requires clear definitions of monitoring purpose and populations, repeated in practice tests of monitoring items and terminology, and meticulousness regarding data-sharing routines. Further naturalistic studies of mHSM use in routine sports practice settings are needed with nonfunctional ethical and legal issues included in the evaluation designs.

Indexed as

diagnostic self-evaluationhealth technologymHealthqualitative researchremote sensing technologyrunningself-evaluation programs

Identifiers

PMID30104183
PMCPMC6111145
OpenAlexW2808315047

What OpenQuestion 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 OpenQuestion graph.