Sharing data collection instrumentsBrian D Johnston

Research in injury prevention, by defin-ition, requires collection of data in someform. Thus every investigator is faced withthe challenge of identifying data collectioninstruments and deciding how best to usethese. In some cases, a researcher will beasking new questions or measuring a newconcept. If so, the researcher will need todecide how to operationalise the conceptas a measurable entity. A process of instru-ment development and validation may berequired. For example, how does onemeasure “risk taking behavior” or “paren-tal supervision?” These are not trivialquestions; getting the measures wrongrisks the integrity of the entire study.

On the other hand, many projectsinvolve measuring a behavior, attitude,belief or self-reported outcome that othershave measured in the past. Assuming thatprevious researchers have taken the time todevelop and validate a data collection tool,why should others in the field, hoping tomeasure the same entity, start from scratch?If, for example, I want to measure depres-sive symptoms, I would almost certainly bebetter off using an established data collec-tion instrument (like the CES-D1) to do so,rather than trying to develop a newmeasure for my particular study.

For a number of reasons, it is generallypreferable to use existing data collectioninstruments when these are available.Certainly, this increases research efficiency.There is no need to undertake laboriousinstrument development and validationstudies if a well-established measurementtool already exists. Such measures areoften explicitly based on a theoreticalmodel of belief or behaviour, a fact thatincreases the rigour of the investigationand may shape thinking about interpret-ation of the results. In addition, aresearcher can use not only the data col-lection forms (and the constructs theyemploy) but also data dictionaries, aggre-gate variables and data reduction techni-ques previously developed for use withthe instrument.

Whilst reuse of well-developed researchtools improves efficiency and rigour, italso facilitates data sharing,2 direct

comparison and even meta-analysis ofpublished studies. If two researchers aremeasuring the same outcome in the sameway, it is much easier to compare orcombine their findings in a productivemanner. How many studies published inthis journal alone would benefit from theuse of established and accepted measuresof home injury hazards?3 Fall risk in theelderly?4 Observed and self-reported par-ental supervision5 or child restraint use?6

The problem, of course, is that we don’talways know that such tools exist and–ifthey do–are typically challenged to obtain acopy for use in our own work. In thisdigital age, however, it is not surprising thatweb-based collections of data collectioninstruments have begun to appear. TheNational Institutes of Health toolbox offersbrief measures assessing cognitive, emo-tional, motor and sensory function (www.nihtoolbox.org); the US National CancerInstitute has Grid-Enabled Measures forconsensus-rated standard measures in onco-logic research;7 the PROMIS project pro-vides metrics for common patient reportedoutcomes (physical function, pain, distress,etc);8 and the Shared Data InstrumentLibrary ties validated instruments into theREDCap secure online data resource.9

Happily, researchers in injury and vio-lence prevention now have database andlibrary of non-proprietary data collectioninstruments and survey forms specific totheir field. The US National Center forInjury Prevention and Control at theCenters for Disease Control and Prevention(CDC) funded the Society for theAdvancement of Violence and InjuryResearch (SAVIR) to develop a system tofacilitate sharing of non-proprietary instru-ments among the research and practicecommunities. Thanks to work led by CarolRunyan and David Lawrence, that systemnow exists.Housed within the searchable–and

freely available–SafetyLit database, theSAVIR Instrument Library provides infor-mation about the development and back-ground of the instruments, how theinstruments were used to support researchpublished in peer-reviewed articles andreports, comments on the use of theinstrument, any problems encountered,and often, the instrument itself. Citationsand links to the published articles based

on the instrument are also included.Interested readers can explore the instru-ment collection here: http://www.safetylit.org/instruments.htm

The goal now is to expend the numberof data collection tools in the library. Tothat end, the journal encourages our col-leagues to make use of the collectionwhen launching new research and to con-tribute their own measures to the data-base. Study protocols, in particular,should be submitted with data collectioninstruments when available. We will alsobe inviting authors of accepted papers toshare their data forms through this mech-anism. Science is a team sport and theinjury prevention community has a longtrack record of successful collaborations.We are highly supportive of this newopportunity.

Competing interests None.

Provenance and peer review Commissioned,internally peer reviewed.

To cite Johnston BD. Inj Prev 2014;20:73.

Inj Prev 2014;20:73.doi:10.1136/injuryprev-2014-041224

REFERENCES1 Radloff LS. The CES-D Scale: A Self-Report Depression

Scale for Research in the General Population. AppliedPsychological Measurement 1977;1:385–401.

2 Johnston BD. Living in the grey area: a case for datasharing in observational epidemiology. InjuryPrevention 2012;18:358–59.

3 Kendrick D, Maula A, Stewart J, et al. Keepingchildren safe at home: protocol for three matchedcase–control studies of modifiable risk factors for falls.Injury Prevention 2012;18:e3.

4 Gleeson M, Sherrington C, Borkowski E, et al.Improving balance and mobility in people over50 years of age with vision impairments: can theAlexander Technique help? A study protocol for theVISIBILITY randomised controlled trial. InjuryPrevention 2014;20:e3.

5 Andrade C, Carita AI, Cordovil R, et al. Cross-culturaladaptation and validation of the Portuguese version ofthe Parental Supervision Attributes ProfileQuestionnaire. Injury Prevention 2013;19:421–27.

6 O’Neil J, Slaven JE, Talty J, et al. Are parents followingthe recommendations for keeping children youngerthan 2 years rear facing during motor vehicle travel?Injury Prevention Published Online First: 28 Oct 2013.doi: 10.1136/injuryprev-2013-040894.

7 Moser RP, Hesse BW, Shaikh AR, et al. Grid-EnabledMeasures: Using Science 2.0 to Standardize Measuresand Share Data. American Journal of PreventiveMedicine 2011;40(5, Supplement 2):S134–S43.

8 Cella D, Riley W, Stone A, et al. The Patient-ReportedOutcomes Measurement Information System (PROMIS)developed and tested its first wave of adultself-reported health outcome item banks: 2005–2008.Journal of Clinical Epidemiology 2010;63:1179–94.

9 Obeid JS, McGraw CA, Minor BL, et al. Procurementof shared data instruments for Research ElectronicData Capture (REDCap). Journal of BiomedicalInformatics 2013;46:259–65.

Correspondence to Dr Brian D Johnston, Departmentof Pediatrics, University of Washington, Seattle, WA98104, USA; ipeditor@bmj.com

Johnston BD. Inj Prev April 2014 Vol 20 No 2 73

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 Brian D Johnston Sharing data collection instruments

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