RESUMO
PURPOSE: To overcome literacy-related barriers in the collection of electronic family health histories, we developed an animated Virtual Counselor for Knowing your Family History, or VICKY. This study examined the acceptability and accuracy of using VICKY to collect family histories from underserved patients as compared with My Family Health Portrait (MFHP). METHODS: Participants were recruited from a patient registry at a safety net hospital and randomized to use either VICKY or MFHP. Accuracy was determined by comparing tool-collected histories with those obtained by a genetic counselor. RESULTS: A total of 70 participants completed this study. Participants rated VICKY as easy to use (91%) and easy to follow (92%), would recommend VICKY to others (83%), and were highly satisfied (77%). VICKY identified 86% of first-degree relatives and 42% of second-degree relatives; combined accuracy was 55%. As compared with MFHP, VICKY identified a greater number of health conditions overall (49% with VICKY vs. 31% with MFHP; incidence rate ratio (IRR): 1.59; 95% confidence interval (95% CI): 1.13-2.25; P = 0.008), in particular, hypertension (47 vs. 15%; IRR: 3.18; 95% CI: 1.66-6.10; P = 0.001) and type 2 diabetes (54 vs. 22%; IRR: 2.47; 95% CI: 1.33-4.60; P = 0.004). CONCLUSION: These results demonstrate that technological support for documenting family history risks can be highly accepted, feasible, and effective.
Assuntos
Saúde da Família , Aconselhamento Genético , Anamnese , Aceitação pelo Paciente de Cuidados de Saúde , Interface Usuário-Computador , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Sistema de Registros , Reprodutibilidade dos Testes , Inquéritos e Questionários , Adulto JovemRESUMO
BACKGROUND: Obesity rates in the United States have escalated in recent decades and present a major challenge in public health prevention efforts. Currently, testing to identify genetic risk for obesity is readily available through several direct-to-consumer companies. Despite the availability of this type of testing, there is a paucity of evidence as to whether providing people with personal genetic information on obesity risk will facilitate or impede desired behavioral responses. PURPOSE: We describe the key issues in the design and implementation of a randomized controlled trial examining the clinical utility of providing genetic risk information for obesity. METHODS: Participants are being recruited from the Coriell Personalized Medicine Collaborative, an ongoing, longitudinal research cohort study designed to determine the utility of personal genome information in health management and clinical decision making. The primary focus of the ancillary Obesity Risk Communication Study is to determine whether genetic risk information added value to traditional communication efforts for obesity, which are based on lifestyle risk factors. The trial employs a 2 × 2 factorial design in order to examine the effects of providing genetic risk information for obesity, alone or in combination with lifestyle risk information, on participants' psychological responses, behavioral intentions, health behaviors, and weight. RESULTS: The factorial design generated four experimental arms based on communication of estimated risk to participants: (1) no risk feedback (control), (2) genetic risk only, (3) lifestyle risk only, and (4) both genetic and lifestyle risk (combined). Key issues in study design pertained to the selection of algorithms to estimate lifestyle risk and determination of information to be provided to participants assigned to each experimental arm to achieve a balance between clinical standards and methodological rigor. Following the launch of the trial in September 2011, implementation challenges pertaining to low enrollment and differential attrition became apparent and required immediate attention and modifications to the study protocol. Although monitoring of these efforts is ongoing, initial observations show a doubling of enrollment and reduced attrition. LIMITATIONS: The trial is evaluating the short-term impact of providing obesity risk information as participants are followed for only 3 months. This study is built upon the structure of an existing personalized medicine study wherein participants have been provided with genetic information for other diseases. This nesting in a larger study may attenuate the effects of obesity risk information and has implications for the generalizability of study findings. CONCLUSIONS: This randomized trial examines value of obesity genetic information, both when provided independently and when combined with lifestyle risk assessment, to motivate individuals to engage in healthy lifestyle behaviors. Study findings will guide future intervention efforts to effectively communicate genetic risk information.
Assuntos
Predisposição Genética para Doença , Testes Genéticos , Obesidade/genética , Seleção de Pacientes , Projetos de Pesquisa , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Algoritmos , Protocolos Clínicos , Seguimentos , Comportamentos Relacionados com a Saúde , Conhecimentos, Atitudes e Prática em Saúde , Humanos , Estilo de Vida , Perda de Seguimento , Pessoa de Meia-Idade , Obesidade/etiologia , Obesidade/prevenção & controle , Avaliação de Resultados em Cuidados de Saúde , Medição de Risco , Fatores de Risco , Adulto JovemRESUMO
OBJECTIVE: Genetic testing for obesity is available directly to consumers, yet little is understood about its behavioral impact and its added value to nongenetic risk communication efforts based on lifestyle factors. METHODS: A randomized trial examined the short-term impact of providing personalized obesity risk information, using a 2 × 2 factorial design. Participants were recruited from the Coriell Personalized Medicine Collaborative (CPMC) and randomized to receive (1) no risk information (control), (2) genetic risk, (3) lifestyle risk, or (4) combined genetic/lifestyle risks. Baseline and 3-month follow-up survey data were collected. Analyses examined the impact of risk feedback on intentions to lose weight and self-reported weight. RESULTS: A total of 696 participants completed the study. A significant interaction effect was observed for genetic and lifestyle information on intent to lose weight (P = 0.0150). Those who received genetic risk alone had greater intentions at follow-up, compared with controls (P = 0.0034). The impact of receiving elevated risk information on intentions varied by source and combination of risks presented. Non-elevated genetic risk did not lower intentions. No group differences were observed for self-reported weight. CONCLUSIONS: Genetic risk information for obesity may add value to lifestyle risk information depending on the context in which it is presented.