Evidence map›Paper›PMID 28887592›Full record

Trial reportCommunity mental health journal2018

The (Surprising) Impact of Televised Antidepressant Direct-to-Consumer Advertising on the Stigmatization of Mental Illness.

Nicolette Rainone, Reshma Oodal, Jeff Niederdeppe

Abstract readRandomized Controlled Trial
PubMed Publisher
In one paragraph

Trial report in Community mental health journal, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Multilevel Opportunities to Address Lung Cancer Stigma across the Cancer Control Continuum.Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer · 2018
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Nicolette RainoneCollege of Human Ecology, Cornell University, Martha Van Rensselaer Hall, Ithaca, NY, 14850, USA. nar57@cornell.edu.
Reshma OodalCollege of Agriculture and Life Sciences, Cornell University, Ithaca, NY, 14850, USA.
Jeff NiederdeppeCollege of Agriculture and Life Sciences, Cornell University, Ithaca, NY, 14850, USA.

Funding

Merck Company Foundation Unrestricted educational grantNIH HHS No. 1 R01 CA113407-01A1Robert Wood Johnson Foundation Grant from the Substance Abuse Policy Research Program
6 · The paper itself

Abstract

This study tests the effect of pharmaceutical Direct-to-Consumer Advertising (DTCA) for antidepressants on perceived stigma surrounding mental disorders. We randomly assigned participants into one of three experimental conditions: antidepressant DTCA with portrayals of discrimination, cognitive separation, and stereotyping (DCSS), antidepressant DTCA without these representations, or a no-exposure control. Contrary to study hypotheses, participants who viewed ads containing portrayals of DCSS were significantly less likely to want to socially distance themselves from those with mental illnesses than those assigned to the no-exposure control condition, even when controlling for demographics and personal experience with mental illness. We discuss plausible explanations for the unexpected pattern of effects and resulting implications for future research on the topic.

Indexed as

Antidepressive AgentsDirect-to-Consumer AdvertisingPsychological DistanceStereotypingAdolescentAdultAnxiety DisordersDepressionEthnicityFemaleHumansMaleMental DisordersNew EnglandRegression AnalysisSocial StigmaAntidepressive AgentsAntidepressantsDepressionDTCAMental illnessStigma

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.