You will be shown an abstract from a biomedical research paper. Given this abstract, your task is to extract all unique entities of the following types: ["Outcome", "Participant", "Intervention"].

Please return the output as a JSON object of the format: {"Participant" : ["patients with COPD", ...], "Intervention" : ["Atenolol", ...], "Outcome" : ["blood pressure", ...]}. The keys should be entity types and values should be lists of extracted entities belonging to the corresponding type. If you cannot find entities belonging to a specific type, the value should be [].

Only output the JSON object and do not include any additional text.

Abstract:

Computer-delivered tailored intervention improves colon cancer screening knowledge and health beliefs of African-Americans . We conducted a randomized controlled trial among African-American patients attending a primary-care provider visit to compare efficacy of a computer-delivered tailored intervention to increase colorectal cancer ( CRC ) screening ( n = 273 ) with non-tailored print material-an American Cancer Society brochure on CRC screening ( n = 283 ) . Health Belief Model constructs were used to develop tailored messages and examined as outcomes . Analysis of covariance models were used to compare changes between CRC knowledge and health belief scores at baseline and 1 week post-intervention . At 1 week , patients who received the computer-delivered tailored intervention had greater changes in CRC knowledge scores ( P < 0.001 ) , perceived CRC risk scores ( P = 0.005 ) , FOBT barriers scores ( P = 0.034 ) and colonoscopy benefit scores ( P < 0.001 ) . Findings show that computer-delivered tailored interventions are an effective adjunct to the clinical encounter that can improve knowledge and health beliefs about CRC screening , necessary precursors to behavior change .
{"Intervention": ["computer-delivered tailored intervention", "non-tailored print material-an"], "Outcome": ["CRC knowledge scores ( P \u003c 0.001 )", "colon cancer screening knowledge", "CRC knowledge and health belief scores", "knowledge and health beliefs about CRC screening", "colonoscopy benefit scores ( P \u003c 0.001 )", "perceived CRC risk scores ( P = 0.005 )", "FOBT barriers scores ( P = 0.034 )", "colorectal cancer ( CRC ) screening"], "Participant": []}