Psychometric Properties of the Coma Near-Coma Scale for Adults in Disordered States of Consciousness: A Rasch Analysis

Published:November 04, 2020DOI:



      To examine the construct validity and measurement precision of the Coma Near-Coma scale (CNC) in measuring neurobehavioral function (NBF) in patients with disorders of consciousness receiving postacute care rehabilitation.


      Rasch analysis of retrospective data.


      Participants (N=48) with disordered consciousness who were admitted to postacute care rehabilitation.


      Not applicable.

      Main Outcome Measure



      Assessment with CNC repeated weekly until the participant was conscious or discharged from the postacute care facility (451 participant records). Rating scale steps were ordered for all items. Eight of the 10 CNC items evaluated in this study fit the measurement model (χ2=5332.58; df=11; P=.17); pain items formed a distinct construct. The ordering of the 8 items from most to least challenging makes clinical sense and compares favorably with other published hierarchies of NBF. Tactile items are more easily responded to. Visual and auditory items requiring higher cognitive processing were more challenging. In the full sample, the CNC achieved good measurement precision, with a person separation reliability of 0.87.


      The items of the CNC reflect good construct validity and acceptable interrater reliability. The measurement precision achieved indicates that the CNC may be used to make decisions about groups of individuals but that these items may not be sufficiently precise for individual patient treatment decision-making.


      List of abbreviations:

      BI (brain injury), CNC (Coma Near-Coma), CI (confidence interval), DoC (disorders of consciousness), DOCS-25 (Disorders of Consciousness Scale), KA (Krippendorff’s alpha), LID (local item dependency), MnSq (mean square), MCS (minimally conscious state), NBF (neurobehavioral function), PCAR (Principal Component Analysis of Residuals), PSR (person separation reliability), SI (Separation Index), UWS (unresponsive wakefulness syndrome), VS (vegetative state)
      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'


      Subscribe to Archives of Physical Medicine and Rehabilitation
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect


        • American Academy of Neurology (AAN)
        Practice parameters: assessment and management of patients in the persistent vegetative state (summary statement). The Quality Standards Subcommittee of the American Academy of Neurology.
        Neurology. 1995; 45: 1015-1018
        • Jennett B.
        • Plum F.
        Persistent vegetative state after brain damage.
        RN. 1972; 35: ICU1-ICU4
        • Jennett B.
        A quarter century of the vegetative state: an international perspective.
        J Head Trauma Rehabil. 1997; 12: 1-12
        • Laureys S.
        • Celesia G.G.
        • Cohadon F.
        • et al.
        Unresponsive wakefulness syndrome: a new name for the vegetative state or apallic syndrome.
        BMC Med. 2010; 8: 68
        • Boly M.
        • Seth A.K.
        • Wilke M.
        • et al.
        Consciousness in humans and non-human animals: recent advances and future directions.
        Front Psychol. 2013; 4: 625
        • Giacino J.T.
        • Ashwal S.
        • Childs N.
        • et al.
        The minimally conscious state: definition and diagnostic criteria.
        Neurology. 2002; 58: 349-353
        • Laureys S.
        • Boly M.
        • Moonen G.
        • Maquet P.
        in: Squire L. Encyclopedia of Neuroscience. Academic Press, Oxford, UK2009: 1133-1142
        • Rappaport M.
        • Dougherty A.M.
        • Kelting D.L.
        Evaluation of coma and vegetative states.
        Arch Phys Med Rehabil. 1992; 73: 628-634
        • Rappaport M.
        The Disability Rating and Coma/Near-Coma scales in evaluating severe head injury.
        Neuropsychol Rehabil. 2005; 15: 442-453
        • Seel R.T.
        • Sherer M.
        • Whyte J.
        • et al.
        Assessment scales for disorders of consciousness: evidence-based recommendations for clinical practice and research.
        Arch Phys Med Rehabil. 2010; 91: 1795-1813
        • Gosseries O.
        • Thibaut A.
        • Boly M.
        • Rosanova M.
        • Massimini M.
        • Laureys S.
        Assessing consciousness in coma and related states using transcranial magnetic stimulation combined with electroencephalography.
        Ann Fr Anesth Reanim. 2014; 33: 65-71
        • Pape T.L.
        • Rosenow J.M.
        • Harton B.
        • et al.
        Preliminary framework for Familiar Auditory Sensory Training (FAST) provided during coma recovery.
        J Rehabil Res Dev. 2012; 49: 1137-1152
        • Pape T.L.
        • Rosenow J.M.
        • Steiner M.
        • et al.
        Placebo-controlled trial of familiar auditory sensory training for acute severe traumatic brain injury: a preliminary report.
        Neurorehabil Neural Repair. 2015; 29: 537-547
        • Rasch G.
        A mathematical theory of objectivity and its consequences for model construction.
        Institute of Mathematical Statistics, Amsterdam1968
        • Linacre J.M.
        Sample size and item calibrations stability.
        RMT. 1994; 7: 328
        • Linacre J.M.
        What do infit and outfit, mean-square and standardized mean?.
        RMT. 2002; 16: 878
        • Wright B.D.
        • Linacre J.M.
        • Gustafson J.E.
        • Martin-Lof P.
        Reasonable mean-square fit values.
        RMT. 1994; 8: 370
        • Linacre J.M.
        Table 23.99 Largest residual correlations for items.
        (Available at:)
        • Wright B.D.
        Separation, reliability and skewed distributions: statistically different sample-independent levels of performance.
        RMT. 2001; 14: 786
      1. Linacre JM. WINSTEPS Help. Available at: Accessed April 1, 2020.

        • Luppescu S.
        Comparing measures.
        RMT. 1995; 9: 410-411
        • Hayes A.F.
        • Krippendorff K.
        Answering the call for a standard reliability measure for coding data.
        Commun Methods Meas. 2007; 1: 77-89
        • Schnakers C.
        • Chatelle C.
        • Vanhaudenhuyse A.
        • et al.
        The Nociception Coma Scale: a new tool to assess nociception in disorders of consciousness.
        Pain. 2010; 148: 215-219
        • Smith R.M.
        • Schumacker R.E.
        • Bush M.J.
        Using item mean squares to evaluate fit to the Rasch model.
        J Outcome Meas. 1998; 2: 66-78
        • Linacre J.M.
        Simulated file specifications.
        (Available at:)
        • Linacre J.M.
        Displacement measures.
        (Available at:)
        • Linacre J.M.
        Dimensionality Investigation--An Example.
        (Available at:)
        • Linacre J.M.
        Table 23.1, 23.11, ...Principal Components/contrast plots of item loadings.
        (Available at:)
        • Giacino J.T.
        • Schnakers C.
        • RodriguezMoreno D.
        • Kalmar K.
        • Schiff N.
        • Hirsch J.
        Behavioral assessment in patients with disorders of consciousness: gold standard or fool's gold?.
        Prog Brain Res. 2009; 177: 33-48
        • Plum F.
        • Posner J.B.
        The diagnosis of stupor and coma.
        FA Davis Co., Philadelphia1980
        • Schiff N.D.
        Recovery of consciousness after brain injury: a mesocircuit hypothesis.
        Trends Neurosci. 2010; 33: 1-9
        • Wannez S.S.
        • Gosseries O.
        • Azzolini D.
        • et al.
        Prevalence of coma-recovery scale-revised signs of consciousness in patients in minimally conscious state.
        Neuropsychol Rehabil. 2018; 28: 1350-1359
        • Giacino J.T.
        The minimally conscious state: defining the borders of consciousness.
        Prog Brain Res. 2005; 150: 381-395
        • Schnakers C.
        • Zasler N.
        Assessment and management of pain in patients with disorders of consciousness.
        PM R. 2015; 7: S270-S277
        • Bond T.G.
        • Fox C.M.
        Applying the Rasch model fundamental measurement in the human sciences.
        3rd ed. Taylor & Francis, New York2015

      CHORUS Manuscript

      View Open Manuscript