| Content Provider | Springer Nature : BioMed Central |
|---|---|
| Author | Purtle, Jonathan Lê-Scherban, Félice Wang, Xi Shattuck, Paul T. Proctor, Enola K. Brownson, Ross C. |
| Abstract | Background Elected officials (e.g., legislators) are an important but understudied population in dissemination research. Audience segmentation is essential in developing dissemination strategies that are tailored for legislators with different characteristics, but sophisticated audience segmentation analyses have not been conducted with this population. An empirical clustering audience segmentation study was conducted to (1) identify behavioral health (i.e., mental health and substance abuse) audience segments among US state legislators, (2) identify legislator characteristics that are predictive of segment membership, and (3) determine whether segment membership is predictive of support for state behavioral health parity laws. Methods Latent class analysis (LCA) was used. Data were from a multi-modal (post-mail, e-mail, telephone) survey of state legislators fielded in 2017 (N = 475). Nine variables were included in the LCA (e.g., perceptions of behavioral health treatment effectiveness, mental illness stigma). Binary logistic regression tested associations between legislator characteristics (e.g., political party, gender, ideology) and segment membership. Multi-level logistic regression assessed the predictive validity of segment membership on support for parity laws. A name was developed for each segment that captured its most salient features. Results Three audience segments were identified. Budget-oriented skeptics with stigma (47% of legislators) had the least faith in behavioral health treatment effectiveness, had the most mental illness stigma, and were most influenced by budget impact. This segment was predominantly male, Republican, and ideologically conservative. Action-oriented supporters (24%) were most likely to have introduced a behavioral health bill, most likely to identify behavioral health issues as policy priorities, and most influenced by research evidence. This was the most politically and ideologically diverse segment. Passive supporters (29%) had the greatest faith in treatment effectiveness and the least stigma, but were also least likely to have introduced a behavioral health bill. Segment membership was a stronger predictor of support for parity laws than almost all other legislator characteristics. Conclusions State legislators are a heterogeneous audience when it comes to behavioral health. There is a need to develop and test behavioral health evidence dissemination strategies that are tailored for legislators in different audience segments. Empirical clustering approaches to audience segmentation are a potentially valuable tool for dissemination science. |
| Related Links | https://implementationscience.biomedcentral.com/counter/pdf/10.1186/s13012-018-0816-8.pdf |
| Ending Page | 13 |
| Page Count | 13 |
| Starting Page | 1 |
| File Format | HTM / HTML |
| ISSN | 17485908 |
| DOI | 10.1186/s13012-018-0816-8 |
| Journal | Implementation Science |
| Issue Number | 1 |
| Volume Number | 13 |
| Language | English |
| Publisher | BioMed Central |
| Publisher Date | 2018-09-19 |
| Access Restriction | Open |
| Subject Keyword | Health Services Research Public Health Health Informatics Health Policy Health Administration Health Promotion and Disease Prevention Dissemination Audience segmentation Policymaker State legislators Latent class analysis United States |
| Content Type | Text |
| Resource Type | Article |
| Subject | Health Policy Public Health, Environmental and Occupational Health Health Informatics |
| Journal Impact Factor | 8.8/2023 |
| 5-Year Journal Impact Factor | 9.2/2023 |
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