Essential 10

6. Outcome measures Clearly define all outcome measures assessed (e.g. cell death, molecular markers, or behavioural changes). explanation

6a Clearly define all outcome measures assessed (e.g. cell death, molecular markers, or behavioural changes).
6b For hypothesis-testing studies, specify the primary outcome measure, i.e. the outcome measure that was used to determine the sample size.
Explanation
Examples

An outcome measure (also known as a dependent variable or a response variable) is any variable recorded during a study (e.g. volume of damaged tissue, number of dead cells, specific molecular marker) to assess the effects of a treatment or experimental intervention. Outcome measures may be important for characterising a sample (e.g. baseline data) or for describing complex responses (e.g. ‘haemodynamic’ outcome measures including heart rate, blood pressure, central venous pressure, and cardiac output). Failure to disclose all the outcomes that were measured introduces bias in the literature as positive outcomes (e.g. those statistically significant) are reported more often [1-4].

Explicitly describe what was measured, especially when measures can be operationalised in different ways. For example, activity could be recorded as time spent moving or distance travelled. Where possible, the recording of outcome measures should be made in an unbiased manner (e.g. blinded to the treatment allocation of each experimental group; see item 5 – Blinding). Specify how the outcome measure(s) assessed are relevant to the objectives of the study. 

 

References

  1. John LK, Loewenstein G and Prelec D (2012). Measuring the Prevalence of Questionable Research Practices With Incentives for Truth Telling. Psychological Science. doi: 10.1177/0956797611430953
  2. Dwan K, Altman DG, Arnaiz JA, Bloom J, Chan AW, Cronin E, Decullier E, Easterbrook PJ, Von Elm E, Gamble C, Ghersi D, Ioannidis JP, Simes J and Williamson PR (2008). Systematic review of the empirical evidence of study publication bias and outcome reporting bias. PLoS One. doi: 10.1371/journal.pone.0003081
  3. Tsilidis KK, Panagiotou OA, Sena ES, Aretouli E, Evangelou E, Howells DW, Al-Shahi Salman R, Macleod MR and Ioannidis JP (2013). Evaluation of excess significance bias in animal studies of neurological diseases. PLoS Biol. doi: 10.1371/journal.pbio.1001609
  4. Sena ES, van der Worp HB, Bath PM, Howells DW and Macleod MR (2010). Publication bias in reports of animal stroke studies leads to major overstatement of efficacy. PLoS Biol. doi: 10.1371/journal.pbio.1000344