scholarly journals Barriers to Building More Effective Treatments: Negative Interactions Among Smoking-Intervention Components

2021 ◽  
pp. 216770262199455
Author(s):  
Timothy B. Baker ◽  
Daniel M. Bolt ◽  
Stevens S. Smith

Meaningfully improved mental and behavioral health treatment is an unrealized dream. Across three factorial experiments, inferential tests in prior studies showed a pattern of negative interactions, suggesting that better clinical outcomes may be obtained when participants receive fewer rather than more intervention components. Furthermore, relatively few significant main effects were found in these experiments. Modeling suggested that negative interactions among components may account for these patterns. In this article, we evaluate factors that may contribute to such declining benefit: increased attentional or effort burden; components that produce their effects via the same capacity-limited mechanisms, making their effects subadditive; and a tipping-point phenomenon in which people near a hypothesized tipping point for change will benefit markedly from weak intervention and people far from the tipping point will benefit little from even strong intervention. New research should explore factors that cause negative interactions among components and constrain the development of more effective treatments.

2019 ◽  
Vol 28 (11) ◽  
pp. 3110-3120
Author(s):  
Angela A. Robertson ◽  
Matthew Hiller ◽  
Richard Dembo ◽  
Michael Dennis ◽  
Christy Scott ◽  
...  

2019 ◽  
Vol 15 (1) ◽  
pp. 22-42
Author(s):  
Fredrick Butcher ◽  
Krystel Tossone ◽  
Maureen Kishna ◽  
Jeff M. Kretschmar ◽  
Daniel J. Flannery

2017 ◽  
Vol 27 (4) ◽  
pp. 449-455 ◽  
Author(s):  
Megan Shepherd-Banigan ◽  
Marisa E. Domino ◽  
Rebecca Wells ◽  
Regina Rutledge ◽  
Marianne M. Hillemeier ◽  
...  

2017 ◽  
Vol 23 (1) ◽  
pp. e20-e27 ◽  
Author(s):  
Irene Falgas ◽  
Zorangeli Ramos ◽  
Lizbeth Herrera ◽  
Adil Qureshi ◽  
Ligia Chavez ◽  
...  

1992 ◽  
Vol 42 (3-4) ◽  
pp. 237-246
Author(s):  
U. Batra ◽  
M.L. Aggarwal

This paper deals with construction of plans for s-level factorial experiments in which there are p response variables and each respose is affected by one or more factors. The plans are orthogonal for each response variable. Estimates of the parameters in the models for such plans are obtained when Σ, the dispersion matrix of an observation vector is known. The properties of these estimates can be of help in designing the experiment so that the variances of estimates of the parameters can be influenced by their relative importance.


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