4.3 Article

Prospective outcomes of injury study

Journal

INJURY PREVENTION
Volume 15, Issue 5, Pages -

Publisher

BMJ PUBLISHING GROUP
DOI: 10.1136/ip.2009.022558

Keywords

-

Funding

  1. Health Research Council of New Zealand
  2. Accident Compensation Corporation, Wellington, New Zealand

Ask authors/readers for more resources

Background: In New Zealand (NZ), 20% of adults report a disability, of which one-third is caused by injury. No prospective epidemiological studies of predictors of disability following all-cause injury among New Zealanders have been undertaken. Internationally, studies have focused on a limited range of predictors or specific injuries. Although these studies provide useful insights, applicability to NZ is limited given the importance of NZ's unique macro-social factors, such as NZ's no-fault accident compensation and rehabilitation scheme, the Accident Compensation Corporation (ACC). Objectives: (1) To quantitatively determine the injury, rehabilitation, personal, social and economic factors leading to disability outcomes following injury in NZ. (2) To qualitatively explore experiences and perceptions of injury-related outcomes in face-to-face interviews with 15 Maori and 15 other New Zealanders, 6 and 12 months after injury. Setting: Four geographical regions within NZ. Design: Prospective cohort study with telephone interviews 1, 4 and 12 months after injury. Participants: 2500 people (including 460 Maori), aged 18-64 years, randomly selected from ACC's entitlement claims register (people likely to be off work for at least 1 week or equivalent). Data: Telephone interviews, electronic hospital and ACC injury data. Exposures include demographic, social, economic, work-related, health status, participation and/or environmental factors. Outcome measures: Primary: disability (including WHODAS II) and health-related quality of life (including EQ-5D). Secondary: participation (paid and unpaid activities), life satisfaction and costs. Analysis: Separate regression models will be developed for each of the outcomes. Repeated measures outcomes will be modelled using general estimating equation models and generalised linear mixed models.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.3
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available