Examining Changes in Coalition Dynamics to Support Opioid Fatality Reduction

Darcy A Freedman; Hannah K Knudsen; Rouba A Chahine; Timothy Hunt; Emmanuel Oga; Alison M Aldrich; Sara Roberts; LaShawn Glasgow; Bryan R Garner; Sylvia Tan; JaNae Holloway; Timothy Huerta; Carol Baden; Pamela Salsberry; Bridget Freisthler

doi:10.1016/j.focus.2025.100394

. 2025 Jul 21;4(6):100394. doi: 10.1016/j.focus.2025.100394

Examining Changes in Coalition Dynamics to Support Opioid Fatality Reduction

Darcy A Freedman ^1,^⁎, Hannah K Knudsen ^2,³, Rouba A Chahine ⁴, Timothy Hunt ⁵, Emmanuel Oga ⁶, Alison M Aldrich ⁷, Sara Roberts ¹, LaShawn Glasgow ⁶, Bryan R Garner ⁸, Sylvia Tan ⁴, JaNae Holloway ⁴, Timothy Huerta ^7,^9,¹⁰, Carol Baden ¹¹, Pamela Salsberry ¹², Bridget Freisthler ¹³

PMCID: PMC12480868 PMID: 41035942

HIGHLIGHTS

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Enhanced coalition capacity boosted community partnerships for overdose prevention.
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Coalition capacity increases sites with overdose education and naloxone distribution.
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Skill building helps opioid coalitions to shape local actions to reduce overdose risk.

Keywords: Substance-related disorders, opiate overdose, community mental health services, community health planning, implementation science

Abstract

Introduction

The goal was to evaluate how changes in coalition capacity and leadership were related to adoption and reach of overdose education and naloxone distribution in communities participating in the HEALing Communities Study.

Study Design

This was a multisite, cluster randomized waitlist-controlled trial; only analysis of Wave 1 data was performed.

Setting/Participants

Longitudinal analysis of cross-sectional surveys completed by coalition members from 33 communities in 4 states based on data collected from January 2021 to June 2022.

Intervention

Study coalitions (n=33) received the Communities That HEAL intervention to support expansion of evidence-based practices, including overdose education and naloxone distribution, to curtail opioid-related fatalities.

Main Outcomes

Coalition capacity and leadership were measured at the midpoint and end of the intervention using validated scales averaged at the community level. Community adoption and reach of overdose education and naloxone distribution were assessed as changes in the rate of community partners implementing overdose education and naloxone distribution strategies and naloxone units distributed from midpoint to the end of the intervention. Negative binomial and linear models, adjusted for baseline characteristics, were conducted in 2024.

Results

Increases in general coalition capacity, adjusted for changes in overdose education and naloxone distribution–specific coalition capacity, were significantly associated with higher rates of community partners engaged in overdose education and naloxone distribution implementation. There was a 56% increase over time in community partners engaged in overdose education and naloxone distribution implementation per unit increase in general capacity scores among coalitions receiving Communities That HEAL. Changes in coalition leadership and capacity did not significantly correlate with changes in naloxone being distributed.

Conclusions

Strengthening general coalition capacity is vital for increasing community partner engagement to expand adoption of overdose education and naloxone distribution. Findings support ongoing investment in coalition capabilities to enhance the effectiveness of public health interventions seeking to reduce opioid-related fatalities. Efforts to strengthen general capacities of coalitions, such as data-informed decision making and collective goalsetting, may accelerate implementation and scaling of evidence-based practices such as overdose education and naloxone distribution.

INTRODUCTION

In 2023, rising drug overdoses resulted in unintentional injury becoming the third leading cause of death among Americans.¹ People experiencing instability due to poverty, incarceration, other substance use disorders, and/or a prior overdose are at the highest risk for opioid-related fatality.² In response, several efforts were launched to increase adoption of evidence-based practices (EBPs), such as overdose education and naloxone distribution (OEND), to decrease these trends.³

OEND, which can reduce the risk of fatal opioid-related overdose, may be implemented in communities through active and passive implementation strategies that help people prevent, recognize, and respond to overdose in real time.4, 5, 6 Naloxone, an opioid antagonist, is a harm-reduction medication that must be administered quickly after overdose.³^,⁷ Widespread community distribution of naloxone is required to make it accessible when needed.³^,⁷

Active OEND involves proactively sharing overdose-prevention education and naloxone to high-risk groups, such as individuals leaving correctional facilities or first responders who leave behind naloxone after responding to opioid overdoses.⁵^,⁷^,⁸ Passive OEND involves referrals to OEND or availability of OEND by self-request.⁷ Examples include prescribing naloxone to high-risk individuals and making naloxone publicly available in overdose hotspots.⁹

As part of the HEAL (Helping to End Addiction Long-term) Initiative, the HEALing Communities Study (HCS) tested a community-engaged, data-driven intervention, Communities That HEAL (CTH). CTH was designed to increase adoption of OEND and 2 other EBPs (i.e., medication for opioid use disorder and safer opioid prescribing and dispensing) to reduce opioid-related fatalities in 67 communities across 4 states.¹⁰^,¹¹ During the waitlist-controlled trial, 33 intervention communities implemented a total of 615 EBP strategies, including 254 OEND-focused strategies.¹² Other HCS publications demonstrate that the CTH intervention significantly reduced opioid deaths that included a psychostimulant (other than cocaine) and resulted in 15% fewer nonfatal opioid overdoses per capita in intervention communities than in the waitlist controlled communities.¹³^,¹⁴ Communities implementing the intervention doubled the rate of naloxone distribution through community-based OEND programs compared with the comparison communities.¹⁵ These findings raise questions about the mechanisms influencing adoption and reach of OEND in HCS communities.

This analysis explores how the dynamics of community coalitions implementing the CTH may have modulated their effectiveness in scaling OEND to reduce opioid overdose trends. Coalition dynamics have been shown to influence goal attainment among coalitions addressing other issues.16, 17, 18 These include leadership dynamics important for coalition functioning (i.e., leadership style, ability to maintain group cohesion) as well as dynamics related to increasing implementation of a specific intervention (i.e., ability of coalition leadership to gain buy-in to implement EBPs).¹⁷^,¹⁹ Although the overall study is guided by the RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) and PRISM (Practical Robust Implementation and Sustainability Model) implementation science frameworks,¹⁰^,²⁰ this analysis is informed by the Interactive Systems Framework (ISF), an implementation science framework that highlights the importance of both generalized and intervention-specific capacities to increase the adoption of EBPs.²¹ Within the ISF, general capacity refers to infrastructure and skills of groups, such as coalitions, to achieve goals as a collective.²² Intervention-specific capacity refers to attainment of motivation, skills, and resources (i.e., human, technical, fiscal) necessary to effectively implement a specific EBP, such as OEND.²²

This study sought to evaluate whether both generalized and OEND-specific changes in coalition capacity and leadership were associated with changes in OEND implementation among HCS communities. The goal was to identify coalition-level factors that can be modified to expand implementation of OEND through community distribution.

METHODS

HCS is a multisite, parallel group, cluster randomized, waitlist-controlled implementation study in 67 communities across 4 states (Kentucky, Massachusetts, New York, and Ohio) designed to test the effectiveness of implementing an integrated set of EBPs and related communication campaigns to reduce opioid-related fatalities through the CTH intervention.¹⁰ Communities were randomized to the intervention group (Wave 1, n=34 communities) or wait-list comparison group (Wave 2, n=33 communities). The present analysis is focused on Wave 1 only; it does not include a comparison group. Wave 1 implemented the CTH intervention from January 2020 through June 2022 and included 34 communities. One withdrew before the intervention started, resulting in 33 intervention communities.¹⁰

Intervention

The CTH intervention has 3 pillars developed to reduce opioid overdose deaths: (1) coalition-driven and data-informed change process¹¹; (2) Opioid-overdose Reduction Continuum of Care Approach, a menu of EBPs focused on OEND, medications for opioid use disorders, and safer opioid prescribing⁵; and (3) communication campaigns to increase awareness and demand for EBPs and reduce stigma.²³ Coalition members prioritized EBPs from the Opioid-overdose Reduction Continuum of Care Approach for implementation locally. EBP implementation occurred outside of the coalition within healthcare, behavioral health, criminal justice, and other community-based settings in communities highly affected by opioid-related fatalities. The study was approved by the single IRB, Advarra Inc. (Protocol Number Pro00038088).

Coalitions were a key component of the CTH, providing leadership to EBP selection following a community-engaged protocol, including (1) data-driven community goal setting, (2) discussion and prioritization of EBP strategies, (3) selection of EBP strategies to include in local action plans, and (4) identification of next steps for EBP implementation.²⁴ This process was supported by local implementation staff funded by the study.¹¹

Study Sample

In Wave 1, HCS engaged 33 coalitions in CTH implementation.¹¹^,²⁴ Some coalitions were pre-existing with different histories of collaboration and varied missions, including focuses on public health in general, substance use prevention, or opioid-specific treatment and recovery. Among existing coalitions, the CTH was often managed within a subcommittee or working group. Others were newly established coalitions for HCS. Coalition membership varied but often included representatives from healthcare organizations, criminal justice organizations, substance use prevention and harm-reduction settings, opioid treatment settings, government, public health settings, business, housing and recovery supports settings, people with lived experience related to opioid use disorder, and/or faith-based organizations.¹¹^,²⁴ The present analysis is focused on data collected after coalition members were able to express interest in engaging in the HCS.

A repeated cross-sectional survey of coalition members was conducted primarily using a REDCap survey.²⁵^,²⁶ Participants also had the option to complete the survey on paper or by phone. This analysis is focused on surveys administered at 2 time points—midpoint (2021) and end (2022) of the CTH intervention in Wave 1—coinciding with 15 months and 30 months, respectively, after the intervention started.²⁷ The survey included items about community perceptions related to reducing local opioid fatality trends; it was pilot tested before administration.²⁰ Survey participants were members of HCS coalitions who attended at least 2 coalition meetings during the study timeframe prior to data collection (e.g., 2 meetings before midpoint, 2 meetings before end).²⁷ A total of 781 and 591 people were invited to complete the 2 surveys with response rates of 49.6% and 42.1%, respectively. Massachusetts, New York, and Kentucky offered compensation for survey participation; Ohio did not. All participants provided free and informed consent before completing the survey.

Measures

The independent variables of general and OEND-specific coalition capacity and leadership, as reported by community coalition members, were assessed with 4 scales. Higher scores on these outcomes represented better perceived capacity and leadership. Because the main outcomes were at the community level, and survey data were collected at the individual level, coalition measures were averaged across participants within communities for the 2 time points before modeling. Change scores, likewise, were calculated after averaging the 4 scales to the community level. Participants were required to have data for at least 1 coalition measure to be included in the analysis, resulting in use of 94.8% of midpoint (n=367) and 91.2% of end of intervention (n=227) surveys. Appendix Table 1 (available online) lists all survey items.

General coalition capacity was measured using a 4-item scale assessing perceived control of the coalition to influence decisions both within the coalition and that affect the community. The scale was adapted from an existing 5-item measure about community empowerment for change.²⁸ Responses were on a 4-point Likert scale from strongly disagree (1) to strongly agree (4). A total score was calculated. The measure had acceptable reliability (Cronbach’s alpha=0.794).

OEND-specific coalition capacity was measured using an adapted scale about organizational readiness for implementing change.¹⁹ The 10-item scale assessed coalition change efficacy (i.e., shared belief in collective ability to implement OEND) and coalition change commitment (i.e., coalitions shared resolve to implement OEND). Confirmatory factor analysis found better performance when all items were combined into 1 scale with excellent reliability (Cronbach’s alpha=0.948). Responses were on a 5-point Likert scale from strongly disagree (1) to strongly agree (5). An average score was calculated.

General coalition leadership was measured using a 4-item scale about perceived coalition capacity for effectiveness. This was adapted from an existing 6-item scale designed to assess perceptions of how coalition leaders support achievement of collaborative goals.²⁹ Responses were on a 5-point Likert scale from strongly disagree (1) to strongly agree (5). An average score was calculated. The measure had excellent reliability (Cronbach’s alpha=0.917).

OEND-specific coalition leadership was measured using a 12-item scale adapted to focus on coalition versus organization leadership to implement OEND in the community.³⁰ The scale includes items about different leadership styles (i.e., proactive, knowledge based, supportive, perseverant). Responses were on a 5-point Likert scale from not at all (1) to a very great extent (5). An average score was calculated. The measure had excellent reliability (Cronbach’s alpha=0.966).

The first outcome variable was the number of community partner organizations (e.g., jails, homeless shelters, emergency departments) engaged in OEND implementation through HCS, including active OEND, passive OEND, and naloxone administration. This outcome was calculated on the basis of data recorded monthly using the Opioid-overdose Reduction Continuum of Care Approach Tracker, a REDCap tool designed to capture community-selected EBPs implemented during HCS.⁸ It includes duplicates for partners engaged in more than 1 OEND strategy. Data were aggregated to the community level for analysis. The study required coalitions to select at least 1 active OEND strategy to reach those at high risk of overdose or in venues where these individuals may be.⁵^,⁸ Coalitions had the option of including passive OEND strategies to indirectly reach these populations as well as to support naloxone administration by first responders.⁵^,⁸

The second outcome variable, the number of naloxone units distributed by community partner organizations, was obtained through administrative data in each state.¹⁵ For Kentucky, naloxone units were measured on the basis of the recipient's location within 1 of the HCS communities. New York, Massachusetts, and Ohio used the location of the organization to determine the number of units distributed within HCS communities.

Both outcome measures were analyzed as a rate per community population size. Two databases were used to calculate community population denominators for rate calculations for coalitions located in either counties³¹ or areas smaller than counties.³² Rates were calculated per 100,000 population.

Statistical Analysis

All models were estimated at the community level. Owing to the study’s use of covariate-constraint randomization, models were adjusted for baseline (2019) opioid overdose death rate, rural/urban status, and state.¹⁰ Community population size was used as either an offset or weight in adjusted models.

Results were considered statistically significant for 2-sided p<0.05. Analyses were conducted in SAS (Cary, NC, Version 9.4). Because 1 community had extreme values for changes in general capacity, innovation-specific capacity, and general coalition leadership (Figure 1), posthoc sensitivity analyses were conducted to assess the impact of these values.

Changes in coalition dynamics from midpoint to the end of the Communities That HEAL intervention.^a

^aMidpoint of intervention is July 2021; end of intervention is June 2022. Sample size for midpoint surveys was n=367, and that for end-point surveys was n=227.

OEND, overdose education and naloxone distribution.

For coalition capacity, the joint association between changes in general coalition capacity and OEND-specific coalition capacity and the rate of partners engaged in OEND implementation from the midpoint to the end of the intervention were tested using a negative binomial model with robust, empirical, sandwich SEs, and log link. A similar model was used to test the joint association of changes in general coalition leadership and OEND-specific coalition leadership. Because the models are on a log scale, the results were exponentiated for interpretation. Joint associations were used to align analyses, with the ISF recognizing the interdependent role of generalized and intervention-specific capacities and leadership to support implementation of EBPs.²¹

Two communities had a decline in the number of naloxone units distributed. Therefore, a linear model was used to test the joint association between changes in general coalition capacity and OEND-specific coalition capacity and rate of naloxone units distributed. Models were adjusted for each community’s baseline (2019) rate of naloxone distribution; population was used as a weight. A similar model was used to assess the joint association of changes in general coalition leadership and OEND-specific leadership.

RESULTS

The 33 coalitions were distributed across the 4 states with 8 coalitions each in Kentucky, Massachusetts, and New York and 9 in Ohio. Coalitions represented both urban (54.5%) and rural (45.5%) communities. In 2019, the study communities had an average rate of 38.2 opioid overdose deaths per 100,000 adult residents (range=8.9–127.6) (Table 1). Demographic characteristics of survey participants are in Appendix Table 2 (available online).

Table 1.

Descriptive Statistics for Coalition Dynamics and OEND Outcomes in Wave 1 Communities Over Time (n=33)

Descriptive characteristics	Baseline^a	Midpoint of intervention^a	End of intervention^a	Change^b
Rate of partner organizations implementing OEND strategies^c^,^d
Mean (SD)	N/A	17.1 (22.6)	31.7 (33.3)	14.5 (16.4)
Median (Q1, Q3)	N/A	7.8 (0.3, 24.0)	26.5 (13.2, 42.8)	11.3 (4.7, 19.1)
Range	N/A	0.0–108.8	1.1–175.3	0.0–72.2
Rate of naloxone units distributed through community-based programs^c^,^d^,^e
Mean (SD)	820.4 (909.8)	2,107.6 (2,553.1)	3,870.9 (3,898.8)	1,763.3 (1,985.4)
Median (Q1, Q3)	482.4 (293.1, 941.8)	1,129.8 (700.3; 2,453.7)	2,358.3 (1,152.7; 5,054.7)	1,131.1 (333.2; 2,557.7)
Range	0.0–3,535.6	0.0–12,865.1	0.0–17,302.5	−232.4 to 8382.1
General coalition capacity^f
Mean (SD)	N/A	13.6 (0.8)	14.0 (1.1)	0.4 (1.3)
Median (Q1, Q3)	N/A	13.8 (13.2, 14.1)	14.0 (13.3, 14.9)	0.2 (−0.3, 1.0)
Range	N/A	11.3–15.8	11.8–16.0	−2.1 to 4.7
OEND-specific coalition capacity^g
Mean (SD)	N/A	4.5 (0.3)	4.6 (0.2)	0.1 (0.4)
Median (Q1, Q3)	N/A	4.5 (4.3, 4.7)	4.6 (4.5, 4.8)	0.0 (−0.1, 0.3)
Range	N/A	3.5–5.0	4.1–4.9	−0.6 to 1.4
General coalition leadership^g
Mean (SD)	N/A	4.5 (0.3)	4.6 (0.3)	0.1 (0.5)
Median (Q1, Q3)	N/A	4.5 (4.4, 4.7)	4.7 (4.4, 4.9)	0.1 (0.0, 0.3)
Range	N/A	3.3–5.0	3.8–5.0	−0.7 to 1.8
OEND-specific coalition leadership^g
Mean (SD)	N/A	4.2 (0.4)	4.4 (0.4)	0.2 (0.5)
Median (Q1, Q3)	N/A	4.2 (4.0, 4.5)	4.4 (4.3, 4.6)	0.2 (0.0, 0.4)
Range	N/A	2.8–4.9	3.5–5.0	−1.1 to 1.2

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Baseline is measured from January 2019 to December 2019, midpoint of intervention is July 2021, and end of intervention is June 2022. Sample size for midpoint surveys was n=367, and that for end point surveys was n=227.

Change from midpoint to end of the Communities That HEAL intervention.

Two databases were used to calculate community population denominators for rate calculations for coalitions in either counties³¹ or areas smaller than counties.³²

Rate per 100,000 individuals, all ages.

Models of naloxone units distributed are adjusted for the baseline rate of naloxone units distributed.

Total score has possible range of 4–16.

Total score has possible range of 1–5.

N/A, not applicable; OEND, overdose education and naloxone distribution; Q1, Quartile 1; Q3, Quartile 3.

At the midpoint of the intervention, coalition measures of capacity and leadership were relatively high for all scales, although the range in scores varied across the communities, indicating heterogeneity in coalition capacity and leadership among the coalitions. Figure 1 shows average community-level changes in the coalition measures from midpoint to the end of the intervention, highlighting both improvements and declines over time.

The average change in the rate of partners engaged in OEND implementation in each community from the midpoint to the end of the intervention was 14.5 partners (range=0–72.2) per 100,000 population. The average change in the rate of naloxone units distributed through community-based programs from the midpoint to the end of the intervention was 1,763.3 units (range= −232.4 to 8,382.1) per 100,000 population.

Table 2 provides results for the joint associations between changes in coalition capacity and leadership and the 2 outcomes. An increase in general coalition capacity, after adjusting for OEND-specific coalition capacity, was associated with an increase in the number of partner organizations implementing OEND strategies (β=1.56 [1.11, 2.19], p=0.013). A 1-unit increase in the general coalition capacity score, adjusted for OEND-specific capacity, was associated with a 56% increase in the rate of OEND partners per 100,000 population. There were no other statistically significant findings. Results from posthoc sensitivity analyses, conducted to assess the effect of removing extreme values in the predictors, remained consistent with the original analysis (Appendix Table 3, available online).

Table 2.

Changes in Coalition Dynamics and Rates of OEND Adoption and Reach (n=33 Coalitions)

Outcomes	Change in coalition capacity				Change in leadership
	General		OEND specific		General		OEND specific
	Beta (95% CI)	p-value	Beta (95% CI)	p-value	Beta (95% CI)	p-value	Beta (95% CI)	p-value
Change in rate of partner organizations implementing OEND strategies^a^,^b	1.56 (1.11, 2.19)	0.013	0.50 (0.15, 1.65)	0.244	1.62 (0.47, 5.60)	0.430	1.03 (0.23, 4.58)	0.968
Change in rate of naloxone units distributed through community-based programs^b^,^c	274.6 (−69.5, 618.8)	0.113	305.5 (−817.8, 1428.7)	0.580	1263.0 (−615.6, 3141.6)	0.178	−567.8 (−1930.8, 795.3)	0.398

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Note: Boldface indicates statistical significance (p<0.05).

A generalized linear model was fitted, adjusting for the baseline opioid overdose death, urban/rural status, and research site. The beta coefficient reflects the percent increase (>1) or decrease (<1) per unit change in the predictor.

Change in rate was defined as the difference in rates between middle and end of intervention period.

A general linear model was fitted, adjusting for the baseline rate of naloxone units distributed, baseline opioid overdose death rate, urban/rural status, and research site, using the community population as weight. The beta coefficient reflects the change in the outcome per unit change in the predictor.

OEND, overdose education and naloxone distribution.

DISCUSSION

Results offer insights about the importance of general coalition capacity as a modifiable lever for expanding adoption of OEND among partners within diverse communities. These findings build on prior evidence about the extent to which capabilities of community health coalitions modulate their effectiveness.¹⁷

Building on insights from the ISF for implementation science,²¹ improvements in general coalition capacity were associated with significantly more partners adopting OEND. This was within the context of the CTH intervention that centered community coalitions to increase implementation of EBPs, including OEND.⁵^,¹¹^,²³ General coalition capacity reflects the extent that coalition members believed that they had the skills and abilities to achieve coalition goals, leverage the coalition to influence decisions within the community, and influence decisions made within the coalition.²⁸ Members who reported that their coalition improved its general capacity were able to engage more partners to adopt OEND. This aligns with findings from other research demonstrating that general capacity versus EBP-specific capacities positively influence EBP implementation.³³^,³⁴

The relationship between improvements in general coalition capacity and increased engagement of partners adopting OEND aligns with the CTH intervention approach. As described previously, the intervention included multiple steps to expand general capacity of coalitions for data-driven action planning to accelerate adoption and reach of OEND.¹¹^,²⁴ The 7 phases of the CTH guided community coalitions through a systematic process of strengthening partnerships to increase support for EBPs locally. The CTH included supports for community coalitions to develop charters; deepen understandings of EBPs available to reduce opioid-related fatalities; access data to describe the local crisis; identify resources and gaps; and develop and implement data-driven community action plans to support OEND implementation, technical assistance for implementation, and sustainability planning.

None of the coalition dynamics examined were associated with changes in the reach of naloxone distribution within community-based settings, which may be due to several factors. First, the scales used to assess OEND-specific capacity and leadership were adapted from measures originally developed for organizations.¹⁹^,³⁰ It may be that these EBP-specific dynamics are more relevant at the organizational level because OEND implementation typically occurs within organizations. Second, although coalitions prioritized different OEND strategies for their communities, implementation required additional steps by organizations. For example, organizations must integrate implementation processes into their workflows, identify and train staff, and allocate resources to obtain naloxone. Third, increasing the number of units of naloxone distributed may not be the best indicator of success because the study’s goal was to reach high-risk groups, which may require dissemination of fewer units to targeted groups. Fourth, although the CTH intervention effectively reduced community-level stigma related to carrying naloxone among those who saw the study’s social marketing campaigns,³⁵ there is far more complexity related to this harm-reduction strategy, especially for people seeking to abstain from opioids who may associate naloxone with drug use culture. Thus, stigma may have been a barrier to naloxone reach.³⁶ Finally, state-level administrative data on naloxone distribution include both HCS-supported initiatives and ongoing work that was independent of HCS, making it more difficult to detect associations between coalition-level measures and community-level naloxone distribution.

Findings provide guidance for future research and practice designed to leverage community coalitions to accelerate the adoption and reach of OEND. Results reinforce the value of investing in general coalition capacity to accentuate coalition effectiveness in expanding partner engagement in EBP implementation.³⁷ Findings highlight the need for coalitions to engage organizations implementing OEND. The unique needs related to OEND implementation, such as addressing workflow or naloxone-sourcing issues, may be addressed collectively within the coalition if more implementing organizations are present. Determining what is needed to engage these implementing partners is a key step for future coalition-based strategies focused on OEND expansion. This may be a particularly important task for coalitions that were originally formed for primary prevention yet are now engaging in harm-reduction efforts due to evolving trends of the opioid crisis.

Limitations

To the authors’ knowledge, this is the largest coalition-based implementation science study.³⁸^,³⁹ However, the sample size of 33 communities limits the statistical power available to detect effects. Moreover, there was variability in both the community context and coalition structures across study sites, which resulted in wide CIs in some models. Because the study was conducted in states with high rates of opioid overdose deaths, coalitions may have been more motivated to engage partners to implement OEND strategies. Thus, the findings may not be generalizable to coalitions in other states or those that were originally formed to address other health issues. Response rates for the surveys were low, possibly affecting estimates of coalition measures.

CONCLUSIONS

Findings from the largest community-engaged, implementation science addiction study conducted to date reinforce the value of coalitions for increasing the number of partners adopting OEND within diverse community settings. Findings provide support for investing in coalition infrastructure to mitigate one of the most pressing public health challenges of the time.

Acknowledgments

ACKNOWLEDGMENTS

The authors wish to acknowledge the participation of the HEALing Communities Study communities, community coalitions, community partner organizations and agencies, community advisory boards, and state government officials who partnered with the authors on this study. This study protocol (Pro00038088) was approved by Advarra Inc., the HEALing Communities Study single IRB.

Disclaimer: The content of this paper is solely the responsibility of the authors and does not necessarily represent the official views of the NIH, the Substance Abuse and Mental Health Services Administration, or the NIH HEAL Initiative.

Funding: This research was supported by the NIH and the Substance Abuse and Mental Health Services Administration through the NIH HEAL (Helping to End Addiction Long-term) Initiative under award Numbers UM1DA049394, UM1DA049406, UM1DA049412, UM1DA049415, and UM1DA049417 (ClinicalTrials.gov Identifier: NCT04111939).

Declaration of interest: None.

CRediT AUTHOR STATEMENT

Darcy A. Freedman: Conceptualization, Methodology, Supervision, Writing - original draft, Writing - review & editing. Hannah K. Knudsen: Conceptualization, Methodology, Writing - original draft, Writing - review & editing. Rouba A. Chahine: Formal analysis, software, Writing - original draft, Writing - review & editing. Timothy Hunt: Conceptualization, Methodology, Supervision, Writing - original draft, Writing - review & editing. Emmanuel Oga: Funding acquisition, Conceptualization, Methodology, Formal analysis, Supervision, Writing - original draft, Writing - review & editing. Alison M. Aldrich: Investigation, Data curation, Writing - original draft, Writing - review & editing. Sara Roberts: Investigation, Data curation, Supervision, Writing - original draft, Writing - review & editing. LaShawn Glasgow: Conceptualization, Methodology, Writing - original draft, Writing - review & editing. Bryan R. Garner: Conceptualization, Methodology, Writing - original draft, Writing - review & editing. Sylvia Tan: Formal analysis, Writing - review & editing. JaNae Holloway: Formal analysis, Software, Writing - review & editing. Timothy Huerta: Conceptualization, Methodology, Data curation, Writing - original draft, Writing - review & editing. Carol Baden: Conceptualization, Writing - review & editing. Pamela Salsberry: Supervision, Writing - review & editing. Freisthler: Funding acquisition, Conceptualization, Methodology, Supervision, Writing - original draft, Writing - review & editing.

Footnotes

Supplementary material associated with this article can be found in the online version at doi:10.1016/j.focus.2025.100394.

Appendix. Supplementary materials

mmc1.docx^{(33.6KB, docx)}

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5.Winhusen T., Walley A., Fanucchi L.C., et al. The Opioid-Overdose Reduction Continuum of Care Approach (ORCCA): evidence-based practices in the HEALing Communities Study. Drug Alcohol Depend. 2020;217 doi: 10.1016/j.drugalcdep.2020.108325. [DOI] [PMC free article] [PubMed] [Google Scholar]
6.Messinger J.C., Beletsky L., Kesselheim A.S., Barenie RE. Moving naloxone over the counter is necessary but not sufficient. Ann Intern Med. 2023;176(8):1109–1112. doi: 10.7326/M23-0852. [DOI] [PubMed] [Google Scholar]
7.Substance Abuse and Mental Health Services Administration, Opioid-Overdose Reduction Continuum of Care Approach (ORCCA) Practice Guide, 2023, National Mental Health and Substance Use Policy Laboratory. Substance Abuse and Mental Health Services Administration. https://www.samhsa.gov/resource/ebp/opioid-overdose-reduction-continuum-care-approach-orcca-practice-guide-2023. Accessed October 1, 2024.
8.Chandler R., Nunes E.V., Tan S., et al. Community selected strategies to reduce opioid-related overdose deaths in the HEALing (Helping to End Addiction Long-term SM) communities study. Drug Alcohol Depend. 2023;245 doi: 10.1016/j.drugalcdep.2023.109804. [DOI] [PMC free article] [PubMed] [Google Scholar]
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10.HEALing Communities Study Consortium The HEALing (Helping to End Addiction Long-term SM) Communities Study: protocol for a cluster randomized trial at the community level to reduce opioid overdose deaths through implementation of an integrated set of evidence-based practices. Drug Alcohol Depend. 2020;217 doi: 10.1016/j.drugalcdep.2020.108335. [DOI] [PMC free article] [PubMed] [Google Scholar]
11.Sprague Martinez L., Rapkin B.D., Young A., et al. Community engagement to implement evidence-based practices in the HEALing communities study. Drug Alcohol Depend. 2020;217 doi: 10.1016/j.drugalcdep.2020.108326. [DOI] [PMC free article] [PubMed] [Google Scholar]
12.HEALing Communities Study Consortium. Samet J.H., El-Bassel N., et al. Community-based cluster-randomized trial to reduce opioid overdose deaths. N Engl J Med. 2024;391(11):989–1001. doi: 10.1056/NEJMoa2401177. [DOI] [PMC free article] [PubMed] [Google Scholar]
13.Freisthler B., Chahine R.A., Villani J., et al. Communities that HEAL intervention and mortality including polysubstance overdose deaths: a randomized clinical trial. JAMA Netw Open. 2024;7(10) doi: 10.1001/jamanetworkopen.2024.40006. [DOI] [PMC free article] [PubMed] [Google Scholar]
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15.Freeman P.R., Walley A.Y., Winhusen T.J., et al. Effect of the communities that HEAL intervention on overdose education and naloxone distribution: a cluster-randomized, wait-list controlled trial. Am J Public Health. 2025;115(1):83–94. doi: 10.2105/AJPH.2024.307845. [DOI] [PMC free article] [PubMed] [Google Scholar]
16.Ken-Opurum J., Darbishire L., Miller D.K., Savaiano D. Assessing rural health coalitions using the public health logic model: a systematic review. Am J Prev Med. 2020;58(6):864–878. doi: 10.1016/j.amepre.2020.01.015. [DOI] [PubMed] [Google Scholar]
17.Zakocs R.C., Edwards EM. What explains community coalition effectiveness?: a review of the literature. Am J Prev Med. 2006;30(4):351–361. doi: 10.1016/j.amepre.2005.12.004. [DOI] [PubMed] [Google Scholar]
18.Shapiro V.B., Oesterle S., Abbott R.D., Arthur M.W., Hawkins JD. Measuring dimensions of coalition functioning for effective and participatory community practice. Soc Work Res. 2013;37(4):349–359. doi: 10.1093/swr/svt028. [DOI] [PMC free article] [PubMed] [Google Scholar]
19.Shea C.M., Jacobs S.R., Esserman D.A., Bruce K., Weiner BJ. Organizational readiness for implementing change: a psychometric assessment of a new measure. Implement Sci. 2014;9(1):7. doi: 10.1186/1748-5908-9-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
20.Knudsen H.K., Drainoni M.L., Gilbert L., et al. Model and approach for assessing implementation context and fidelity in the HEALing Communities Study. Drug Alcohol Depend. 2020;217 doi: 10.1016/j.drugalcdep.2020.108330. [DOI] [PMC free article] [PubMed] [Google Scholar]
21.Wandersman A., Duffy J., Flaspohler P., et al. Bridging the gap between prevention research and practice: the interactive systems framework for dissemination and implementation. Am J Community Psychol. 2008;41(3–4):171–181. doi: 10.1007/s10464-008-9174-z. [DOI] [PubMed] [Google Scholar]
22.Flaspohler P., Duffy J., Wandersman A., Stillman L., Maras MA. Unpacking prevention capacity: an intersection of research-to-practice models and community-centered models. Am J Community Psychol. 2008;41(3–4):182–196. doi: 10.1007/s10464-008-9162-3. [DOI] [PubMed] [Google Scholar]
23.Lefebvre R.C., Chandler R.K., Helme D.W., et al. Health communication campaigns to drive demand for evidence-based practices and reduce stigma in the HEALing communities study. Drug Alcohol Depend. 2020;217 doi: 10.1016/j.drugalcdep.2020.108338. [DOI] [PMC free article] [PubMed] [Google Scholar]
24.Young A.M., Brown J.L., Hunt T., et al. Protocol for community-driven selection of strategies to implement evidence-based practices to reduce opioid overdoses in the HEALing Communities Study: a trial to evaluate a community-engaged intervention in Kentucky, Massachusetts, New York and Ohio. BMJ Open. 2022;12(9) doi: 10.1136/bmjopen-2021-059328. [DOI] [PMC free article] [PubMed] [Google Scholar]
25.Harris P.A., Taylor R., Minor B.L., et al. The REDCap consortium: building an international community of software platform partners. J Biomed Inform. 2019;95 doi: 10.1016/j.jbi.2019.103208. [DOI] [PMC free article] [PubMed] [Google Scholar]
26.Harris P.A., Taylor R., Thielke R., Payne J., Gonzalez N., Conde JG. Research Electronic Data Capture (REDCap)–a metadata-driven methodology and workflow process for providing translational research informatics support - PubMed. J Biomed Inform. 2009;42(2):377–381. doi: 10.1016/j.jbi.2008.08.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
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28.Israel B.A., Checkoway B., Schulz A., Zimmerman M. Health education and community empowerment: conceptualizing and measuring perceptions of individual, organizational, and community control. Health Educ Q. 1994;21(2):149–170. doi: 10.1177/109019819402100203. [DOI] [PubMed] [Google Scholar]
29.Hays C.E., Hays S.P., DeVille J.O., Mulhall PF. Capacity for effectiveness: the relationship between coalition structure and community impact. Eval Program Plann. 2000;23(3):373–379. doi: 10.1016/S0149-7189(00)00026-4. [DOI] [Google Scholar]
30.Aarons G.A., Ehrhart M.G., Farahnak LR. The implementation leadership scale (ILS): development of a brief measure of unit level implementation leadership. Implement Sci. 2014;9(1):45. doi: 10.1186/1748-5908-9-45. [DOI] [PMC free article] [PubMed] [Google Scholar]
31.National Center for Health Statistics. Vintage 2020 postcensal estimates of the resident population of the United States April 1, 2010, July 1, 2010-July 1, 2020), by year, county, single-year of age (0, 1, 2, .., 85 years and over), bridged race, Hispanic origin, and sex. Prepared under a collaborative arrangement with the U.S. Census Bureau. Accessed February 13, 2024. https://www.census.gov/programs-surveys/popest/technical-documentation/research/evaluation-estimates/2020-evaluation-estimates/2010s-county-detail.html.
32.American community survey 5-year estimates, 2017–2021. U.S. Census Bureau. https://www.census.gov/newsroom/press-kits/2022/acs-5-year.html. Updated August 6, 2025. Accessed December 9, 2024.
33.Collins CB, Sapiano TN. Lessons learned from dissemination of evidence-based interventions for HIV prevention. Am J Prev Med. 2016;51(4)(suppl 2):S140–S147. 10.1016/j.amepre.2016.05.017. [DOI] [PubMed]
34.Halgunseth L.C., Carmack C., Childs S.S., Caldwell L., Craig A., Smith EP. Using the interactive systems framework in understanding the relation between general program capacity and implementation in afterschool settings. Am J Community Psychol. 2012;50(3–4):311–320. doi: 10.1007/s10464-012-9500-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
35.Lewis N., Eggleston B., Chandler R.K., et al. Stigma and efficacy beliefs regarding opioid use disorder treatment and naloxone in communities participating in the HEALing Communities Study intervention. PLoS One. 2024;19(12) doi: 10.1371/journal.pone.0308965. [DOI] [PMC free article] [PubMed] [Google Scholar]
36.Bowles J.M., Smith L.R., Mittal M.L., et al. “I wanted to close the chapter completely … and I feel like that [carrying naloxone] would keep it open a little bit”: refusal to carry naloxone among newly-abstinent opioid users and 12-step identity. Int J Drug Policy. 2021;94 doi: 10.1016/j.drugpo.2021.103200. [DOI] [PMC free article] [PubMed] [Google Scholar]
37.Butterfoss F.D., Kegler MC. In: Community Organizing and Community Building for Health and Social Equity. 4th Edition. Minkler M., Wakimoto P., editors. Rutgers University Press; New Brunswick, NJ: 2022. 18. Community coalition action theory: designing and evaluating community collaboratives; pp. 307–324. [DOI] [Google Scholar]
38.Chilenski S.M., Gayles J., Luneke A., et al. Understanding community- and system-capacity change over time: a close look at changing social capital in Evidence2Success communities. J Community Psychol. 2023;51(7):2989–3011. doi: 10.1002/jcop.23034. [DOI] [PMC free article] [PubMed] [Google Scholar]
39.Brown E.C., Hawkins J.D., Arthur M.W., Briney J.S., Abbott RD. Effects of communities that care on prevention services systems: findings from the community youth development study at 1.5 years. Prev Sci. 2007;8(3):180–191. doi: 10.1007/s11121-007-0068-3. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

mmc1.docx^{(33.6KB, docx)}

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[bib0007] 7.Substance Abuse and Mental Health Services Administration, Opioid-Overdose Reduction Continuum of Care Approach (ORCCA) Practice Guide, 2023, National Mental Health and Substance Use Policy Laboratory. Substance Abuse and Mental Health Services Administration. https://www.samhsa.gov/resource/ebp/opioid-overdose-reduction-continuum-care-approach-orcca-practice-guide-2023. Accessed October 1, 2024.

[bib0008] 8.Chandler R., Nunes E.V., Tan S., et al. Community selected strategies to reduce opioid-related overdose deaths in the HEALing (Helping to End Addiction Long-term SM) communities study. Drug Alcohol Depend. 2023;245 doi: 10.1016/j.drugalcdep.2023.109804. [DOI] [PMC free article] [PubMed] [Google Scholar]

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[bib0010] 10.HEALing Communities Study Consortium The HEALing (Helping to End Addiction Long-term SM) Communities Study: protocol for a cluster randomized trial at the community level to reduce opioid overdose deaths through implementation of an integrated set of evidence-based practices. Drug Alcohol Depend. 2020;217 doi: 10.1016/j.drugalcdep.2020.108335. [DOI] [PMC free article] [PubMed] [Google Scholar]

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[bib0013] 13.Freisthler B., Chahine R.A., Villani J., et al. Communities that HEAL intervention and mortality including polysubstance overdose deaths: a randomized clinical trial. JAMA Netw Open. 2024;7(10) doi: 10.1001/jamanetworkopen.2024.40006. [DOI] [PMC free article] [PubMed] [Google Scholar]

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[bib0015] 15.Freeman P.R., Walley A.Y., Winhusen T.J., et al. Effect of the communities that HEAL intervention on overdose education and naloxone distribution: a cluster-randomized, wait-list controlled trial. Am J Public Health. 2025;115(1):83–94. doi: 10.2105/AJPH.2024.307845. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib0016] 16.Ken-Opurum J., Darbishire L., Miller D.K., Savaiano D. Assessing rural health coalitions using the public health logic model: a systematic review. Am J Prev Med. 2020;58(6):864–878. doi: 10.1016/j.amepre.2020.01.015. [DOI] [PubMed] [Google Scholar]

[bib0017] 17.Zakocs R.C., Edwards EM. What explains community coalition effectiveness?: a review of the literature. Am J Prev Med. 2006;30(4):351–361. doi: 10.1016/j.amepre.2005.12.004. [DOI] [PubMed] [Google Scholar]

[bib0018] 18.Shapiro V.B., Oesterle S., Abbott R.D., Arthur M.W., Hawkins JD. Measuring dimensions of coalition functioning for effective and participatory community practice. Soc Work Res. 2013;37(4):349–359. doi: 10.1093/swr/svt028. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib0019] 19.Shea C.M., Jacobs S.R., Esserman D.A., Bruce K., Weiner BJ. Organizational readiness for implementing change: a psychometric assessment of a new measure. Implement Sci. 2014;9(1):7. doi: 10.1186/1748-5908-9-7. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib0020] 20.Knudsen H.K., Drainoni M.L., Gilbert L., et al. Model and approach for assessing implementation context and fidelity in the HEALing Communities Study. Drug Alcohol Depend. 2020;217 doi: 10.1016/j.drugalcdep.2020.108330. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib0021] 21.Wandersman A., Duffy J., Flaspohler P., et al. Bridging the gap between prevention research and practice: the interactive systems framework for dissemination and implementation. Am J Community Psychol. 2008;41(3–4):171–181. doi: 10.1007/s10464-008-9174-z. [DOI] [PubMed] [Google Scholar]

[bib0022] 22.Flaspohler P., Duffy J., Wandersman A., Stillman L., Maras MA. Unpacking prevention capacity: an intersection of research-to-practice models and community-centered models. Am J Community Psychol. 2008;41(3–4):182–196. doi: 10.1007/s10464-008-9162-3. [DOI] [PubMed] [Google Scholar]

[bib0023] 23.Lefebvre R.C., Chandler R.K., Helme D.W., et al. Health communication campaigns to drive demand for evidence-based practices and reduce stigma in the HEALing communities study. Drug Alcohol Depend. 2020;217 doi: 10.1016/j.drugalcdep.2020.108338. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib0024] 24.Young A.M., Brown J.L., Hunt T., et al. Protocol for community-driven selection of strategies to implement evidence-based practices to reduce opioid overdoses in the HEALing Communities Study: a trial to evaluate a community-engaged intervention in Kentucky, Massachusetts, New York and Ohio. BMJ Open. 2022;12(9) doi: 10.1136/bmjopen-2021-059328. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib0025] 25.Harris P.A., Taylor R., Minor B.L., et al. The REDCap consortium: building an international community of software platform partners. J Biomed Inform. 2019;95 doi: 10.1016/j.jbi.2019.103208. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib0026] 26.Harris P.A., Taylor R., Thielke R., Payne J., Gonzalez N., Conde JG. Research Electronic Data Capture (REDCap)–a metadata-driven methodology and workflow process for providing translational research informatics support - PubMed. J Biomed Inform. 2009;42(2):377–381. doi: 10.1016/j.jbi.2008.08.010. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib0027] 27.Davis A., Knudsen H.K., Walker D.M., et al. Effects of the Communities that Heal (CTH) intervention on perceived opioid-related community stigma in the HEALing Communities Study: results of a multi-site, community-level, cluster-randomized trial. Lancet Reg Health Am. 2024;32 doi: 10.1016/j.lana.2024.100710. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib0028] 28.Israel B.A., Checkoway B., Schulz A., Zimmerman M. Health education and community empowerment: conceptualizing and measuring perceptions of individual, organizational, and community control. Health Educ Q. 1994;21(2):149–170. doi: 10.1177/109019819402100203. [DOI] [PubMed] [Google Scholar]

[bib0029] 29.Hays C.E., Hays S.P., DeVille J.O., Mulhall PF. Capacity for effectiveness: the relationship between coalition structure and community impact. Eval Program Plann. 2000;23(3):373–379. doi: 10.1016/S0149-7189(00)00026-4. [DOI] [Google Scholar]

[bib0030] 30.Aarons G.A., Ehrhart M.G., Farahnak LR. The implementation leadership scale (ILS): development of a brief measure of unit level implementation leadership. Implement Sci. 2014;9(1):45. doi: 10.1186/1748-5908-9-45. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib0031] 31.National Center for Health Statistics. Vintage 2020 postcensal estimates of the resident population of the United States April 1, 2010, July 1, 2010-July 1, 2020), by year, county, single-year of age (0, 1, 2, .., 85 years and over), bridged race, Hispanic origin, and sex. Prepared under a collaborative arrangement with the U.S. Census Bureau. Accessed February 13, 2024. https://www.census.gov/programs-surveys/popest/technical-documentation/research/evaluation-estimates/2020-evaluation-estimates/2010s-county-detail.html.

[bib0032] 32.American community survey 5-year estimates, 2017–2021. U.S. Census Bureau. https://www.census.gov/newsroom/press-kits/2022/acs-5-year.html. Updated August 6, 2025. Accessed December 9, 2024.

[bib0033] 33.Collins CB, Sapiano TN. Lessons learned from dissemination of evidence-based interventions for HIV prevention. Am J Prev Med. 2016;51(4)(suppl 2):S140–S147. 10.1016/j.amepre.2016.05.017. [DOI] [PubMed]

[bib0034] 34.Halgunseth L.C., Carmack C., Childs S.S., Caldwell L., Craig A., Smith EP. Using the interactive systems framework in understanding the relation between general program capacity and implementation in afterschool settings. Am J Community Psychol. 2012;50(3–4):311–320. doi: 10.1007/s10464-012-9500-3. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib0035] 35.Lewis N., Eggleston B., Chandler R.K., et al. Stigma and efficacy beliefs regarding opioid use disorder treatment and naloxone in communities participating in the HEALing Communities Study intervention. PLoS One. 2024;19(12) doi: 10.1371/journal.pone.0308965. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib0036] 36.Bowles J.M., Smith L.R., Mittal M.L., et al. “I wanted to close the chapter completely … and I feel like that [carrying naloxone] would keep it open a little bit”: refusal to carry naloxone among newly-abstinent opioid users and 12-step identity. Int J Drug Policy. 2021;94 doi: 10.1016/j.drugpo.2021.103200. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib0037] 37.Butterfoss F.D., Kegler MC. In: Community Organizing and Community Building for Health and Social Equity. 4th Edition. Minkler M., Wakimoto P., editors. Rutgers University Press; New Brunswick, NJ: 2022. 18. Community coalition action theory: designing and evaluating community collaboratives; pp. 307–324. [DOI] [Google Scholar]

[bib0038] 38.Chilenski S.M., Gayles J., Luneke A., et al. Understanding community- and system-capacity change over time: a close look at changing social capital in Evidence2Success communities. J Community Psychol. 2023;51(7):2989–3011. doi: 10.1002/jcop.23034. [DOI] [PMC free article] [PubMed] [Google Scholar]

[bib0039] 39.Brown E.C., Hawkins J.D., Arthur M.W., Briney J.S., Abbott RD. Effects of communities that care on prevention services systems: findings from the community youth development study at 1.5 years. Prev Sci. 2007;8(3):180–191. doi: 10.1007/s11121-007-0068-3. [DOI] [PubMed] [Google Scholar]

PERMALINK

Examining Changes in Coalition Dynamics to Support Opioid Fatality Reduction

Darcy A Freedman, PhD

Hannah K Knudsen, PhD

Rouba A Chahine, PhD

Timothy Hunt, PhD

Emmanuel Oga, MD, MPH

Alison M Aldrich, MPH

Sara Roberts, MSSA

LaShawn Glasgow, DrPH

Bryan R Garner, PhD

Sylvia Tan, MS

JaNae Holloway, MSPH

Timothy Huerta, PhD

Carol Baden

Pamela Salsberry, PhD

Bridget Freisthler, PhD

HIGHLIGHTS

Abstract

Introduction

Study Design

Setting/Participants

Intervention

Main Outcomes

Results

Conclusions

INTRODUCTION

METHODS

Intervention

Study Sample

Measures

Statistical Analysis

Figure 1.

RESULTS

Table 1.

Table 2.

DISCUSSION

Limitations

CONCLUSIONS

Acknowledgments

ACKNOWLEDGMENTS

CRediT AUTHOR STATEMENT

Footnotes

Appendix. Supplementary materials

REFERENCES

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

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