TABLE 2.
Articles (N = 3823), No (%) | Articles With ≥ 1 Causal or Solution Explanation (n = 1164), No. (%) | Total Causal Explanationsa (n = 1267), No. (%) | Total Solution Explanationsa (n = 624), No. (%) | |
Primary racial/ethnic group mentioned | ||||
Black/African American | 2925 (76.5) | |||
Latino/Hispanic | 314 (8.2) | |||
Asian | 76 (2.0) | |||
Native American | 45 (1.2) | |||
Multiple races | 81 (2.1) | |||
Nonspecific characterization | 382 (10.0) | |||
No causal/solution explanation | 2659 (69.6) | |||
≥ 1 causal/solution explanation | 1164 (30.4) | |||
Agent providing explanationb | ||||
Academic researcher | 311 (26.7) | 284 (22.4) | 74 (11.9) | |
Media | 307 (26.4) | 243 (19.2) | 112 (17.9) | |
Health professional | 256 (22.0) | 217 (17.1) | 84 (13.5) | |
Advocacy group | 216 (18.6) | 147 (11.6) | 115 (18.4) | |
Laypeople | 154 (13.2) | 107 (8.4) | 79 (12.7) | |
Federal agency | 149 (12.8) | 117 (9.2) | 54 (8.7) | |
City/state agency | 123 (10.6) | 82 (6.5) | 67 (10.7) | |
Research institution | 57 (4.9) | 52 (4.1) | 11 (1.8) | |
Politician | 32 (2.7) | 15 (1.2) | 25 (4.0) | |
Causal explanation | 1000 (85.9) | |||
Genetic | 79 (6.2) | |||
Behavioral | 382 (30.1) | |||
Societal | 212 (16.7) | |||
Health care | 160 (12.6) | |||
Multilevel causes | 434 (34.3) | |||
Top 5 multilevel causesc | ||||
Behavioral/societal | 114 (26.3) | |||
Societal/health care | 78 (18.0) | |||
Behavioral/health care | 75 (17.3) | |||
Behavioral/societal/health care | 59 (13.6) | |||
Genetic/behavioral | 45 (10.4) | |||
Solution explanation | 536 (46.0) | |||
Genetic | 28 (4.5) | |||
Behavioral | 300 (48.1) | |||
Societal | 145 (23.2) | |||
Health care | 79 (12.7) | |||
Multilevel solutions | 72 (11.5) | |||
Top 5 multilevel solutionsc | ||||
Behavioral/societal | 28 (38.9) | |||
Societal/health care | 18 (25.0) | |||
Behavioral/health care | 10 (13.9) | |||
Behavioral/societal/health care | 7 (9.7) | |||
Genetic/behavioral | 5 (6.9) |
We coded for up to 4 causal and solution explanations per agent per article. These totals represent the number of causal and solution explanations given by all agents who provided explanations.
We coded for up to 4 agents mentioned per article. Thus, totals are greater than total number of articles and sum to more than 100%.
All other multilevel causal/solution categories made up less than 4% of the total.