Health Impact Assessments (HIA) for Healthy Alcohol and Drug Policies and Programs
Bibliographic record
Abstract
Health impact assessment (HIA) has been defined as, combination of procedures, methods, and tools that systematically judges the potential, and sometimes unintended, effects of a policy, plan, programme or project on the health of a and the distribution of those effects within the population (Quigley et al., 2006). HIAs are quite popular in Western Europe, Canada and other countries but are not that popular in the United States (Collins, & Koplan, 2009; Metcalfe & Higgins, 2009). HIAs have been preceded by environmental impact assessments (EIA) that were created in 1969 under the National Environmental Policy Act to assess the environmental effects of federal projects and policies such as designing highways (Collins, & Koplan, 2009; Mindell, Boltong, & Forde, 2008). Metcalfe and Higgins (2009) contend that HIA is really important for healthier public policies, assistance toward achieving health as a right for all, and better decision making through use of quantitative assessment on environmental and health issues. MacNaughton and Hunt (2009) point out that there is a growing demand for governments to carry out HIAs toward achieving health as a right. HIAs can detect policies or activities that may have detrimental and sometimes unanticipated or undesired effects on health (Douglas, Conway, Gorman, Gavin & Hanlon, 2001). Collins and Koplan (2009) cite the example of the No Child Left Behind Act in the United States which had disastrous effects on health and physical education curricula, and these could have been prevented had a HIA been done on that policy. HIAs are quite useful as these systematically assess the effects of the policy or the program on various subgroups of the population. HIAs are usually commissioned by local, regional, and national governments/health authorities/planning authorities/donors or private industry (Quigley et al., 2006). The actual professionals conducting these HIAs can have a variety of backgrounds. World Health Organization (1999, 2001) has developed a set of guiding principles for HIAs. These state that HIAs should be democratic and must entail the right of all people to participate in them; HIAs must study the impact on all subgroups of populations particularly the vulnerable subpopulations; HIAs must pay attention to impacts on present generation as well as future generations; HIAs must use transparent and rigorous methods; and, finally, HIAs must be comprehensive, covering physical, mental and social spheres. Douglas and colleagues (2001) have also developed a set of 16 principles for HIAs and the interested reader can consult their paper. Mindell and colleagues (2008) conducted a systematic review of HIAs and found that there is considerable variation in terms of participation of the community. Some people consider involvement in focus groups, interviews, etc as participation, while others believe that community should take the leadership in the process. There is need for more clarity and consensus in this regard. HIA consists of six steps (Kemm, 2008): (a) screening or decision to undertake HIA; (b) scoping or deciding areas to focus; (c) appraisal or gathering evidence; (d) recommendations and reporting; (e) decision making; and (f) implementation and monitoring. An example of a HIA is the Greater Christchurch Urban Development Strategy health impact assessment in New Zealand that was implemented as a partnership between public health and local government authorities (Mathias, & Harris-Roxas, 2009). Various qualitative methods such as key informant interviews, focus groups, document reviews, and surveys were used in the HIA. Recommendations with regard to air quality, water quality, social connectedness, housing, transport, and engagement with Maori were the result of the HIA. …
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".