Page 205 - Encyclopedia of Nursing Research
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172  n  FAILurE TO THrIVE (AduLT)



           then models from two to six factors should   Factors are interpreted by examining the
           also be tested to verify the factor structures.   pattern  and  magnitude  of  the  factor  load-
   F       Problematic items usually appear across the   ings in the rotated factor matrix (orthogonal
           various factor solutions. remove items with   rotation)  or  pattern  matrix  (oblique  rota-
           primary  factor  loadings  of  less  than  .40  or   tion). Ideally, there are one or more marker
           with secondary factor loadings of more than   variables,  variables  with  a  very  high  load-
           .30. remove items one at a time and rerun the   ing on one and only one factor (Nunnally &
           factor analyses with solutions for two to six   Bernstein, 1994), which can help in the inter-
           factors after each item removal until a “clean”   pretation and naming of factors. replication
           solution is identified. No factor should have   of  factor  solutions  in  subsequent  analyses
           less than two variables.                 with  different  populations  gives  increased
              Factor  extraction  results  in  a  factor   credibility  to  the  findings.  Comparisons
           matrix that shows the relationship between   between  factor-analytic  solutions  can  be
           the  original  variables  and  the  factors  by   made by visual inspection of the factor load-
           means of factor loadings. The factor loadings,   ings or by using formal statistical procedures,
           when squared, equal the variance in the var-  such  as  the  computation  of  Cattell’s  salient
           iable  accounted  for  by  the  factor.  For  all  of   similarity index and the use of confirmatory
           the extracted factors, the sum of the squared   factor analysis (Gorsuch, 1983).
           loadings for a single variable across all fac-
           tors represents the communality (shared var-                 Christopher J. Burant
           iance) of that variable. The sum of a factor’s             Jaclene A. Zauszniewski
           squared loadings for all variables is equiva-
           lent to that factor’s eigenvalue (Nunnally &
           Bernstein, 1994).
              Factor  rotation  is  commonly  used  when   Failure to thrive (adult)
           more  than  one  factor  emerges.  Factor  rota-
           tion  involves  the  movement  of  the  reference
           axes within the factor space so that the vari-  Adult  failure  to  thrive  (FTT)  syndrome  is
           ables align with a single factor (Nunnally &   defined  as  a  lower-than-expected  level  of
           Bernstein, 1994). Orthogonal rotation keeps the   functioning associated with nutritional defi-
           reference axes at right angles and results in fac-  cits,  depressed  mood  state,  and  cognitive
           tors that are uncorrelated. Orthogonal rotation   impairment  (Newbern  &  Krowchuk,  1994;
           is usually performed through a method known   Verdery, 1996). Clinically, FTT has been used
           as varimax, but other methods (quartimax and   interchangeably  with  the  terms  cachexia,
           equimax) are also available. Oblique rotation   frailty,  dwindling,  nonspecific  presentation
           allows the reference axes to rotate into acute or   of  illness,  and  decompensation.  Although
           oblique angles, thereby resulting in correlated   it  has  been  discussed  primarily  in  relation
           factors (Nunnally & Bernstein). When oblique   to the elderly (Egbert, 1996), on the basis of
           rotation is used, there are two resulting matri-  the above definition, it is likely that the syn-
           ces: a pattern matrix that reveals partial regres-  drome  crosses  age  boundaries  and  exists
           sion coefficients between variables and factors,   in  other  chronically  ill  patient  populations,
           and  a  structure  matrix  that  shows  variable–  for  example,  adults  with  multiple  sclerosis,
           factor correlations. The pattern matrix is easier   AIdS, or diabetes.
           to interpret. The recommended rotation tech-  In  the  International  Classification  of
           nique is to use oblique rotation because this   diseases,  10th  revision,  FTT  is  most  fre-
           represents the correlation of factors that occur   quently  classified  as  a  pediatric  diagnosis.
           in real life (Fabrigar, Wegener, MacCallum, &   In children, FTT is very broadly defined as
           Strahan, 1999).                          deviation from an expected growth pattern
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