OBJECTIVE: To develop and validate a simplified, easy to interpret scoring system based on the health profile-types taxonomy for the Spanish version of the Child Health and Illness Profile-Adolescent Edition (CHIP-AE). METHODS: The CHIP-AE was administered to a 1453 Spanish adolescents. Hierarchic and nonhierarchical cluster analyses, as well as conceptual considerations, were used to identify exhaustive, mutually exclusive health profile-types based in four CHIP-AE domain scores: Satisfaction, Discomfort, Resilience, and Risks. Validity of the health profile-types was assessed by testing expected differences among adolescents according to sex, age, socioeconomic status, and self-reported conditions. Logistic models were built. RESULTS: A total of 13 health profile-types (10 that best fitted the data and three additional considered conceptually necessary) were identified. The largest group of adolescents was in the "Excellent health" or "Good health" types (43.4%), although 11.2% were in the "Worst health" profile. According to a priori hypotheses, being a girl (OR = 1.81; 95% CI = 1.26-2.60), older age (OR = 1.80; 1.26-2.57), and self-reported recurrent (OR = 2.49; 1.72-3.60) and psychosocial disorders (OR = 4.38; 2.92-6.56) were associated to the likelihood of a "Worst health" profile-type. CONCLUSIONS: The Spanish CHIP-AE health profile-types offer a simplified method to describe adolescents' patterns of health, which is valid and similar to the original US taxonomy. This can facilitate interpreting the instrument scores and using it for needs assessment, although additional research is required.
OBJECTIVE: To develop and validate a simplified, easy to interpret scoring system based on the health profile-types taxonomy for the Spanish version of the Child Health and Illness Profile-Adolescent Edition (CHIP-AE). METHODS: The CHIP-AE was administered to a 1453 Spanish adolescents. Hierarchic and nonhierarchical cluster analyses, as well as conceptual considerations, were used to identify exhaustive, mutually exclusive health profile-types based in four CHIP-AE domain scores: Satisfaction, Discomfort, Resilience, and Risks. Validity of the health profile-types was assessed by testing expected differences among adolescents according to sex, age, socioeconomic status, and self-reported conditions. Logistic models were built. RESULTS: A total of 13 health profile-types (10 that best fitted the data and three additional considered conceptually necessary) were identified. The largest group of adolescents was in the "Excellent health" or "Good health" types (43.4%), although 11.2% were in the "Worst health" profile. According to a priori hypotheses, being a girl (OR = 1.81; 95% CI = 1.26-2.60), older age (OR = 1.80; 1.26-2.57), and self-reported recurrent (OR = 2.49; 1.72-3.60) and psychosocial disorders (OR = 4.38; 2.92-6.56) were associated to the likelihood of a "Worst health" profile-type. CONCLUSIONS: The Spanish CHIP-AE health profile-types offer a simplified method to describe adolescents' patterns of health, which is valid and similar to the original US taxonomy. This can facilitate interpreting the instrument scores and using it for needs assessment, although additional research is required.
Authors: Maria-Dolors Estrada; Luis Rajmil; Michael Herdman; Vicky Serra-Sutton; Cristian Tebé; Jordi Alonso; Anne W Riley; Christopher B Forrest; Barbara Starfield Journal: Qual Life Res Date: 2011-08-14 Impact factor: 4.147
Authors: Maria-Dolors Estrada; Luis Rajmil; Vicky Serra-Sutton; Cristian Tebé; Jordi Alonso; Michael Herdman; Anne W Riley; Christopher B Forrest; Barbara Starfield Journal: Health Qual Life Outcomes Date: 2010-08-02 Impact factor: 3.186