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Article ; Online: Optimizing Interventions for Equitability: Some Initial Ideas.

Strayhorn, Jillian C / Vanness, David J / Collins, Linda M

Prevention science : the official journal of the Society for Prevention Research

2024

Abstract: Interventions (including behavioral, biobehavioral, biomedical, and social-structural interventions) hold tremendous potential not only to improve public health overall but also to reduce health disparities and promote health equity. In this study, we ... ...

Abstract	Interventions (including behavioral, biobehavioral, biomedical, and social-structural interventions) hold tremendous potential not only to improve public health overall but also to reduce health disparities and promote health equity. In this study, we introduce one way in which interventions can be optimized for health equity in a principled fashion using the multiphase optimization strategy (MOST). Specifically, we define intervention equitability as the extent to which the health benefits provided by an intervention are distributed evenly versus concentrated among those who are already advantaged, and we suggest that, if intervention equitability is acknowledged to be a priority, then equitability should be a key criterion that is balanced with other criteria (effectiveness overall, as well as affordability, scalability, and/or efficiency) in intervention optimization. Using a hypothetical case study and simulated data, we show how MOST can be applied to achieve a strategic balance that incorporates equitability. We also show how the composition of an optimized intervention can differ when equitability is considered versus when it is not. We conclude with a vision for next steps to build on this initial foray into optimizing interventions for equitability.
Language	English
Publishing date	2024-01-31
Publishing country	United States
Document type	Journal Article
ZDB-ID	2251270-6
ISSN	1573-6695 ; 1389-4986
ISSN (online)	1573-6695
ISSN	1389-4986
DOI	10.1007/s11121-024-01644-3
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Article ; Online: A posterior expected value approach to decision-making in the multiphase optimization strategy for intervention science.

Strayhorn, Jillian C / Collins, Linda M / Vanness, David J

Psychological methods

2023

Abstract: In current practice, intervention scientists applying the multiphase optimization strategy (MOST) with a ... ...

Abstract	In current practice, intervention scientists applying the multiphase optimization strategy (MOST) with a 2
Language	English
Publishing date	2023-04-13
Publishing country	United States
Document type	Journal Article
ZDB-ID	2103345-6
ISSN	1939-1463 ; 1082-989X
ISSN (online)	1939-1463
ISSN	1082-989X
DOI	10.1037/met0000569
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Article ; Online: Optimization Methods and Implementation Science: An Opportunity for Behavioral and Biobehavioral Interventions.

Guastaferro, Kate / Collins, Linda M

Implementation research and practice

2021 Volume 2, Page(s) 26334895211054363

Abstract: This editorial introduces the multiphase optimization strategy (MOST), a principled framework for the development, optimization and evaluation of multicomponent interventions, to the field of implementation science. We suggest that MOST may be integrated ...

Abstract	This editorial introduces the multiphase optimization strategy (MOST), a principled framework for the development, optimization and evaluation of multicomponent interventions, to the field of implementation science. We suggest that MOST may be integrated with implementation science to advance the field, moving closer towards the ultimate goal of disseminating effective interventions to those in need. We offer three potential ways MOST may advance implementation science: (1) development of an effective and immediately scalable intervention; (2) adaptation of interventions to local contexts; and (3) optimization of the implementation of an intervention itself. Our goal is to inspire the integration of MOST with implementation science across a number of public health contexts.
Language	English
Publishing date	2021-10-29
Publishing country	United States
Document type	Journal Article
ISSN	2633-4895
ISSN (online)	2633-4895
DOI	10.1177/26334895211054363
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Book: Measurement and design issues in tobacco and drug use research

Collins, Linda M.

(Drug and alcohol dependence ; 68, Suppl. 1)

2002

Author's details	guest ed.: Linda M. Collins
Series title	Drug and alcohol dependence ; 68, Suppl. 1
Collection
Language	English
Size	S96 S. : graph. Darst.
Publisher	Elsevier
Publishing place	Amsterdam u.a.
Publishing country	Netherlands
Document type	Book
HBZ-ID	HT013516186
Database	Catalogue ZB MED Medicine, Health

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Article ; Online: Achieving the Goals of Translational Science in Public Health Intervention Research: The Multiphase Optimization Strategy (MOST).

Guastaferro, Kate / Collins, Linda M

American journal of public health

2019 Volume 109, Issue S2, Page(s) S128–S129

MeSH term(s)	Health Services Research/organization & administration ; Humans ; Organizational Objectives ; Public Health Administration ; Translational Medical Research/organization & administration ; United States
Language	English
Publishing date	2019-02-20
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	121100-6
ISSN	1541-0048 ; 0090-0036 ; 0002-9572
ISSN (online)	1541-0048
ISSN	0090-0036 ; 0002-9572
DOI	10.2105/AJPH.2018.304874
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Article ; Online: Intervention Optimization: A Paradigm Shift and Its Potential Implications for Clinical Psychology.

Collins, Linda M / Nahum-Shani, Inbal / Guastaferro, Kate / Strayhorn, Jillian C / Vanness, David J / Murphy, Susan A

Annual review of clinical psychology

2024

Abstract: To build a coherent knowledge base about what psychological intervention strategies work, develop interventions that have positive societal impact, and maintain and increase this impact over time, it is necessary to replace the classical treatment ... ...

Abstract	To build a coherent knowledge base about what psychological intervention strategies work, develop interventions that have positive societal impact, and maintain and increase this impact over time, it is necessary to replace the classical treatment package research paradigm. The multiphase optimization strategy (MOST) is an alternative paradigm that integrates ideas from behavioral science, engineering, implementation science, economics, and decision science. MOST enables optimization of interventions to strategically balance effectiveness, affordability, scalability, and efficiency. In this review we provide an overview of MOST, discuss several experimental designs that can be used in intervention optimization, consider how the investigator can use experimental results to select components for inclusion in the optimized intervention, discuss the application of MOST in implementation science, and list future issues in this rapidly evolving field. We highlight the feasibility of adopting this new research paradigm as well as its potential to hasten the progress of psychological intervention science. Expected final online publication date for the
Language	English
Publishing date	2024-02-05
Publishing country	United States
Document type	Journal Article ; Review
ZDB-ID	2194815-X
ISSN	1548-5951 ; 1548-5943
ISSN (online)	1548-5951
ISSN	1548-5943
DOI	10.1146/annurev-clinpsy-080822-051119
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Article: The multiphase optimization strategy (MOST) in child maltreatment prevention research.

Guastaferro, Kate / Strayhorn, Jillian C / Collins, Linda M

Journal of child and family studies

2021 Volume 30, Issue 10, Page(s) 2481–2491

Abstract: Each year hundreds of thousands of children and families receive behavioral interventions designed to prevent child maltreatment; yet rates of maltreatment have not declined in over a decade. To reduce the prevalence and prevent the life-long negative ... ...

Abstract	Each year hundreds of thousands of children and families receive behavioral interventions designed to prevent child maltreatment; yet rates of maltreatment have not declined in over a decade. To reduce the prevalence and prevent the life-long negative consequences of child maltreatment, behavioral interventions must not only be effective, but also affordable, scalable, and efficient to meet the demand for these services. An innovative approach to intervention science is needed. The purpose of this article is to introduce the multiphase optimization strategy (MOST) to the field of child maltreatment prevention. MOST is an engineering-inspired framework for developing, optimizing, and evaluating multicomponent behavioral interventions. MOST enables intervention scientists to empirically examine the performance of each intervention component, independently and in combination. Using a hypothetical example of a home visiting intervention and artificial data, this article demonstrates how MOST may be used to optimize the
Language	English
Publishing date	2021-08-05
Publishing country	United States
Document type	Journal Article
ZDB-ID	2016750-7
ISSN	1573-2843 ; 1062-1024
ISSN (online)	1573-2843
ISSN	1062-1024
DOI	10.1007/s10826-021-02062-7
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: One view of the next decade of research on behavioral and biobehavioral approaches to cancer prevention and control: intervention optimization.

Collins, Linda M / Strayhorn, Jillian C / Vanness, David J

Translational behavioral medicine

2021 Volume 11, Issue 11, Page(s) 1998–2008

Abstract: As a new decade begins, we propose that the time is right to reexamine current methods and procedures and look for opportunities to accelerate progress in cancer prevention and control. In this article we offer our view of the next decade of research on ... ...

Abstract	As a new decade begins, we propose that the time is right to reexamine current methods and procedures and look for opportunities to accelerate progress in cancer prevention and control. In this article we offer our view of the next decade of research on behavioral and biobehavioral interventions for cancer prevention and control. We begin by discussing and questioning several implicit conventions. We then briefly introduce an alternative research framework: the multiphase optimization strategy (MOST). MOST, a principled framework for intervention development, optimization, and evaluation, stresses not only intervention effectiveness, but also intervention affordability, scalability, and efficiency. We review some current limitations of MOST along with future directions for methodological work in this area, and suggest some changes in the scientific environment we believe would permit wider adoption of intervention optimization. We propose that wider adoption of intervention optimization would have a positive impact on development and successful implementation of interventions for cancer prevention and control and on intervention science more broadly, including accumulation of a coherent base of knowledge about what works and what does not; establishment of an empirical basis for adaptation of interventions to different settings with different levels and types of resources; and, in the long run, acceleration of progress from Stage 0 to Stage V in the National Institutes of Health Model of Stages of Intervention Development.
MeSH term(s)	Humans ; Neoplasms/prevention & control ; United States
Language	English
Publishing date	2021-12-01
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Review
ZDB-ID	2586893-7
ISSN	1613-9860 ; 1869-6716
ISSN (online)	1613-9860
ISSN	1869-6716
DOI	10.1093/tbm/ibab087
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Article ; Online: Using decision analysis for intervention value efficiency to select optimized interventions in the multiphase optimization strategy.

Strayhorn, Jillian C / Cleland, Charles M / Vanness, David J / Wilton, Leo / Gwadz, Marya / Collins, Linda M

Health psychology : official journal of the Division of Health Psychology, American Psychological Association

2023 Volume 43, Issue 2, Page(s) 89–100

Abstract: Objective: Optimizing multicomponent behavioral and biobehavioral interventions presents a complex decision problem. To arrive at an intervention that is both effective and readily implementable, it may be necessary to weigh effectiveness against ... ...

Abstract	Objective: Optimizing multicomponent behavioral and biobehavioral interventions presents a complex decision problem. To arrive at an intervention that is both effective and readily implementable, it may be necessary to weigh effectiveness against implementability when deciding which components to select for inclusion. Different components may have differential effectiveness on an array of outcome variables. Moreover, different decision-makers will approach this problem with different objectives and preferences. Recent advances in decision-making methodology in the multiphase optimization strategy (MOST) have opened new possibilities for intervention scientists to optimize interventions based on a wide variety of decision-maker preferences, including those that involve multiple outcome variables. In this study, we introduce decision analysis for intervention value efficiency (DAIVE), a decision-making framework for use in MOST that incorporates these new decision-making methods. We apply DAIVE to select optimized interventions based on empirical data from a factorial optimization trial. Method: We define various sets of hypothetical decision-maker preferences, and we apply DAIVE to identify optimized interventions appropriate to each case. Results: We demonstrate how DAIVE can be used to make decisions about the composition of optimized interventions and how the choice of optimized intervention can differ according to decision-maker preferences and objectives. Conclusions: We offer recommendations for intervention scientists who want to apply DAIVE to select optimized interventions based on data from their own factorial optimization trials. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
MeSH term(s)	Humans ; Decision Support Techniques
Language	English
Publishing date	2023-08-03
Publishing country	United States
Document type	Journal Article
ZDB-ID	226369-5
ISSN	1930-7810 ; 0278-6133
ISSN (online)	1930-7810
ISSN	0278-6133
DOI	10.1037/hea0001318
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Article ; Online: Investigation of Active Ingredients Within Internet-Delivered Cognitive Behavioral Therapy for Depression: A Randomized Optimization Trial.

Watkins, Edward / Newbold, Alexandra / Tester-Jones, Michelle / Collins, Linda M / Mostazir, Mohammod

JAMA psychiatry

2023 Volume 80, Issue 9, Page(s) 942–951

Abstract: Importance: There is limited understanding of how complex evidence-based psychological interventions such as cognitive behavioral therapy (CBT) for depression work. Identifying active ingredients may help to make therapy more potent, brief, and scalable. ...

Abstract	Importance: There is limited understanding of how complex evidence-based psychological interventions such as cognitive behavioral therapy (CBT) for depression work. Identifying active ingredients may help to make therapy more potent, brief, and scalable. Objective: To test the individual main effects and interactions of 7 treatment components within internet-delivered CBT for depression to investigate its active ingredients. Design, setting, and participants: This randomized optimization trial using a 32-condition, balanced, fractional factorial optimization experiment (IMPROVE-2) recruited adults with depression (Patient Health Questionnaire-9 [PHQ-9] score ≥10) from internet advertising and the UK National Health Service Improving Access to Psychological Therapies service. Participants were randomized from July 7, 2015, to March 29, 2017, with follow-up for 6 months after treatment until December 29, 2017. Data were analyzed from July 2018 to April 2023. Interventions: Participants were randomized with equal probability to 7 experimental factors within the internet CBT platform, each reflecting the presence vs absence of specific treatment components (activity scheduling, functional analysis, thought challenging, relaxation, concreteness training, absorption, and self-compassion training). Main outcomes and measures: The primary outcome was depression symptoms (PHQ-9 score). Secondary outcomes include anxiety symptoms and work, home, and social functioning. Results: Among 767 participants (mean age [SD] age, 38.5 [11.62] years; range, 18-76 years; 635 women [82.8%]), 506 (66%) completed the 6-month posttreatment follow-up. On average, participants receiving internet-delivered CBT had reduced depression (pre-to-posttreatment difference in PHQ-9 score, -7.79 [90% CI, -8.21 to -7.37]; 6-month follow-up difference in PHQ-9 score, -8.63 [90% CI, -9.04 to -8.22]). A baseline score-adjusted analysis of covariance model using effect-coded intervention variables (-1 or +1) found no main effect on depression symptoms for the presence vs absence of activity scheduling, functional analysis, thought challenging, relaxation, concreteness training, or self-compassion training (posttreatment: largest difference in PHQ-9 score [functional analysis], -0.09 [90% CI, -0.56 to 0.39]; 6-month follow-up: largest difference in PHQ-9 score [relaxation], -0.18 [90% CI, -0.61 to 0.25]). Only absorption training had a significant main effect on depressive symptoms at 6-month follow-up (posttreatment difference in PHQ-9 score, 0.21 [90% CI, -0.27 to 0.68]; 6-month follow-up difference in PHQ-9 score, -0.54, [90% CI, -0.97 to -0.11]). Conclusions and relevance: In this randomized optimization trial, all components of internet-delivered CBT except absorption training did not significantly reduce depression symptoms relative to their absence despite an overall average reduction in symptoms. The findings suggest that treatment benefit from internet-delivered CBT probably accrues from spontaneous remission, factors common to all CBT components (eg, structure, making active plans), and nonspecific therapy factors (eg, positive expectancy), with the possible exception of absorption focused on enhancing direct contact with positive reinforcers. Trial registration: isrctn.org Identifier: ISRCTN24117387.
MeSH term(s)	Adult ; Humans ; Female ; Child ; Depression/psychology ; State Medicine ; Cognitive Behavioral Therapy ; Anxiety/therapy ; Patient Health Questionnaire ; Treatment Outcome ; Internet
Language	English
Publishing date	2023-06-27
Publishing country	United States
Document type	Randomized Controlled Trial ; Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2701203-7
ISSN	2168-6238 ; 2168-622X
ISSN (online)	2168-6238
ISSN	2168-622X
DOI	10.1001/jamapsychiatry.2023.1937
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