Abstract

Objectives: a) Assess the psychosocial impact of predictive testing. b) Check the effect of variables: gender, cancer diagnosis, cancer treatment, first proband, the type of hereditary syndrome: breast/ovarian or colorectal cancer, result of genetic testing, and time since the communication of results. c) To study the psychometric properties and replicate the factor structure of the Spanish version of MICRA. Method: We studied 122 subjects who had genetic testing done at an interval of 1 month to 5 years. They were administrated the Multidimensional Impact of Cancer Risk Assessment (MICRA) Questionnaire. Sample data: 95 women and 27 men; mean age: 50.48 years; with high education; 93 (72.2%) were diagnosed with cancer; 45 (36.9%) were receiving cancer treatment; 89 (73%) consulted for breast/ovarian cancer risk and 33 (27%) for colorectal cancer risk; 50 (41%) were negative for the mutation test, 37(30.3%) positive and 35 (28.7%) non-informative. The average time elapsed since the communication of results: 401 days. We calculated the internal consistency of MICRA, took out a multitrait scaling analysis and a confirmatory factor analysis. Results: The genetic test did not cause a negative psychological impact. The variables of sex, cancer diagnosis, cancer treatment, first proband, type of syndrome (breast/ovarian-colorectal) or time elapsed do not influence the impact of genetic testing. The result type (positive, negative and non-informative) was significant in the ANOVA, Tukey test showed differences in distress subscale of the positive vs. negative (p=0.00), with Cohen’s d=1,16), and positive vs. non-informative (p=0.00), Cohen’s d = 0.84, on the subscale positive experiences the differences are between positive vs. negative (p=0.01), Cohen’s d=0.68, and positive vs. non-informative (p=0.02), Cohen’s d=0.67, in the total are the differences between the positive vs. negative (p=0.000), Cohen’s d=0.96, and between positive vs. non-informative (p=0.00), Cohen’s d = 1.00. The MICRA showed satisfactory internal consistency. The convergent and discriminant validity were adequate for the distress and positive experience subscales, but not for the uncertainty subscale. Factor analysis confirms the distress and positive experiences subscales but not uncertainty subscale. Conclusions: Genetic testing did not cause a negative psychological impact. Mutation carriers showed a greater negative impact than participants with negative and uninformative. The MICRA showed good psychometric properties, but the Spanish version needs significant improvements.

Highlights

  • Método: se evaluó a 122 sujetos que habían realizado test genético en un intervalo de 1 mes a 5 años, mediante el cuestionario de evaluación multidimensional del impacto de riesgo de cáncer (MICRA)

  • We studied 122 subjects who had genetic testing done at an interval of 1 month to 5 years

  • We calculated the internal consistency of Multidimensional Impact of Cancer Risk Assessment (MICRA), took out a multitrait scaling analysis and a confirmatory factor analysis

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Summary

Introduction

Método: se evaluó a 122 sujetos que habían realizado test genético en un intervalo de 1 mes a 5 años, mediante el cuestionario de evaluación multidimensional del impacto de riesgo de cáncer (MICRA). Datos de la muestra: 95 mujeres y 27 hombres; media de edad: 50,48 años; con nivel educativo alto; 93 (72,2%) fueron diagnosticados de cáncer; 45 (36,9%) recibían tratamiento oncológico; 89 (73%) consultaban por SHCMO y 33 (27%) por SHCC; 50 (41%) eran negativos para la mutación, 37 (30,3%) positivos y 35 (28,7%) no informativos. La media del tiempo que ha transcurrido desde la comunicación de los resultados: 401 días. Se calculó la consistencia interna del MICRA, se llevó a cabo un análisis de la validez convergente y discriminante de los ítems de Objectives: a) Assess the psychosocial impact of predictive testing. Se calculó la consistencia interna del MICRA, se llevó a cabo un análisis de la validez convergente y discriminante de los ítems de Objectives: a) Assess the psychosocial impact of predictive testing. b) Check the effect of variables: gender, cancer diagnosis, cancer treatment, first proband, the type of hereditary syndrome: breast/ovarian or colorectal cancer, result of genetic testing, and time since the communication of results. c) To study the psychometric properties and replicate the factor structure of the Spanish version of MICRA

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