Modeling the Mental Health Practice Change Preferences of Educators: A Discrete-Choice Conjoint Experiment

Effective Teacher Professional Development for School-Based Mental Health Promotion: A Review of the Literature

Teachers are critically involved in the delivery of school-based mental health promotion (SMHP) interventions in school, though pre-service teacher education often leaves teachers feeling underprepared in this area. Thus, understanding how best to build teachers' capacity for delivery through effective professional development (PD) is essential for teachers to fulfill their role as delivery agents to achieve SMHP outcomes. This systematized review focuses on identifying components of high-quality teacher PD for SMHP and examining the empirical support for these components. In a two-phase analysis, we examined the descriptive literature regarding teacher PD for SMHP to identify common elements. This resulted in the identification of components relevant to training (interactive, guided by staff input) and technical assistance (TA), including the goals (skill development, motivation, generalization/adaptation), approach (collaborative, individualized, data-driven, strengths-based), and activities (modeling, performance feedback, reflection, problem solving) involved. A second phase focused on the examination of empirical evidence for these PD components. While the empirical evidence for these components was limited, the identified components represent a current standard of practice in teacher PD for SMHP, based on the existing research. These components may provide a framework for practical use in planning teacher PD related to SMHP and for designing future research into effective capacity building in this area.

Development of attributes and levels of mental health insurance services using a discrete choice experiment

BACKGROUND

Despite the fact that mental illness is among the ten top diseases with the highest burden, the health services required by these patients do not have adequate insurance coverage. The purpose of this study is to develop the attributes and levels of mental health insurance services using a discrete choice experiment (DCE).

MATERIALS AND METHOD

This study involved a qualitative phase of the DCE that was conducted in Iran in 2020-2021 and included several stages. First, during a literature review, the attributes and levels were determined. Then, the attributes of health insurance were identified and weighed through virtual and in-person interviews with 16 mental health insurance professionals and policymakers in this field who were selected by purposive sampling. Finally, after a few sessions, through review studies, interviews, and a group of the expert panel, attributes and levels were finalized.

RESULTS

This study showed that coverage of inpatient services, outpatient services, place of receiving services, use of online internet services, limitation of services, and monthly premiums were the most important attributes of mental health insurance services.

CONCLUSION

To promote mental health insurance, policymakers and health insurance organizations should pay attention to premiums to be commensurate with the payment of people, packages of mental health services, and the ability of people to pay in appropriation with inflation. Identifying these attributes can determine people's willingness to pay and preferences for mental health insurance and lead to better planning for more comprehensive coverage for patients and increase the desirability of individuals in receiving services.

Current Practices for Accounting for Preference Heterogeneity in Health-Related Discrete Choice Experiments: A Systematic Review

BACKGROUND

Accounting for preference heterogeneity is a growing analytical practice in health-related discrete choice experiments (DCEs). As heterogeneity may be examined from different stakeholder perspectives with different methods, identifying the breadth of these methodological approaches and understanding the differences are major steps to provide guidance on good research practices.

OBJECTIVES

Our objective was to systematically summarize current practices that account for preference heterogeneity based on the published DCEs related to healthcare.

METHODS

This systematic review is part of the project led by the Professional Society for Health Economics and Outcomes Research (ISPOR) health preference research special interest group. The systematic review conducted systematic searches on the PubMed, OVID, and Web of Science databases, as well as on two recently published reviews, to identify articles. The review included health-related DCE articles published between 1 January 2000 and 30 March 2020. All the included articles also presented evidence on preference heterogeneity analysis based on either explained or unexplained factors or both.

RESULTS

Overall, 342 of the 2202 (16%) articles met the inclusion/exclusion criteria for extraction. The trend showed that analyses of preference heterogeneity increased substantially after 2010 and that such analyses mainly examined heterogeneity due to observable or unobservable factors in individual characteristics. Heterogeneity through observable differences (i.e., explained heterogeneity) is identified among 131 (40%) of the 342 articles and included one or more interactions between an attribute variable and an observable characteristic of the respondent. To capture unobserved heterogeneity (i.e., unexplained heterogeneity), the studies largely estimated either a mixed logit (n = 205, 60%) or a latent-class logit (n = 112, 32.7%) model. Few studies (n = 38, 11%) explored scale heterogeneity or heteroskedasticity.

CONCLUSIONS

Providing preference heterogeneity evidence in health-related DCEs has been found as an increasingly used practice among researchers. In recent studies, controlling for unexplained preference heterogeneity has been seen as a common practice rather than explained ones (e.g., interactions), yet a lack of providing methodological details has been observed in many studies that might impact the quality of analysis. As heterogeneity can be assessed from different stakeholder perspectives with different methods, researchers should become more technically pronounced to increase confidence in the results and improve the ability of decision makers to act on the preference evidence.

Understanding the value of adhering to or adapting evidence-based interventions: a study protocol of a discrete choice experiment

Background

Whereas the value of an evidence-based intervention (EBI) is often determined by its effect on clinical outcomes, the value of implementing and using EBIs in practice is broader, reflecting qualities such as appropriateness, equity, costs, and impact. Reconciling these value conflicts involves a complicated decision process that has received very limited scholarly attention. Inspired by studies on decision-making, the objective of this project is to explore how practitioners appraise the values of different outcomes and to test how this appraisal influences their decisions surrounding the so-called fidelity–adaptation dilemma. This dilemma is related to the balance between using an EBI as it was designed (to ensure its effectiveness) and making appropriate adaptations (to ensure alignment with constraints and possibilities in the local context).

Methods

This project consists of three sub-studies. The participants will be professionals leading evidence-based parental programs in Sweden and, in Sub-study 1, parents and decision-makers. Sub-study 1 will use sequential focus groups and individual interviews to explore parameters that influence fidelity and adaptation decisions—the dilemmas encountered, available options, how outcomes are valued by practitioners as well as other stakeholders, and value trade-offs. Sub-study 2 is a discrete choice experiment that will test how value appraisals influence decision-making using data from Sub-study 1 as input. Sub-study 3 uses a mixed-method design, with findings from the two preceding sub-studies as input in focus group interviews to investigate how practitioners make sense of findings from optimal decision situations (experiment) and constrained, real-world decision situations.

Discussion

The project will offer unique insights into decision-making processes that influence how EBIs are used in practice. Such knowledge is needed for a more granular understanding of how practitioners manage the fidelity–adaptation dilemma and thus, ultimately, how the value of EBI implementation can be optimized. This study contributes to our knowledge of what happens once EBIs are adopted—that is, the gap between the way in which EBIs are intended to be used and the way in which they are used in practice.

Community stakeholder preferences for evidence-based practice implementation strategies in behavioral health: a best-worst scaling choice experiment

BACKGROUND

Community behavioral health clinicians, supervisors, and administrators play an essential role in implementing new psychosocial evidence-based practices (EBP) for patients receiving psychiatric care; however, little is known about these stakeholders' values and preferences for implementation strategies that support EBP use, nor how best to elicit, quantify, or segment their preferences. This study sought to quantify these stakeholders' preferences for implementation strategies and to identify segments of stakeholders with distinct preferences using a rigorous choice experiment method called best-worst scaling.

METHODS

A total of 240 clinicians, 74 clinical supervisors, and 29 administrators employed within clinics delivering publicly-funded behavioral health services in a large metropolitan behavioral health system participated in a best-worst scaling choice experiment. Participants evaluated 14 implementation strategies developed through extensive elicitation and pilot work within the target system. Preference weights were generated for each strategy using hierarchical Bayesian estimation. Latent class analysis identified segments of stakeholders with unique preference profiles.

RESULTS

On average, stakeholders preferred two strategies significantly more than all others-compensation for use of EBP per session and compensation for preparation time to use the EBP (P < .05); two strategies were preferred significantly less than all others-performance feedback via email and performance feedback via leaderboard (P < .05). However, latent class analysis identified four distinct segments of stakeholders with unique preferences: Segment 1 (n = 121, 35%) strongly preferred financial incentives over all other approaches and included more administrators; Segment 2 (n = 80, 23%) preferred technology-based strategies and was younger, on average; Segment 3 (n = 52, 15%) preferred an improved waiting room to enhance client readiness, strongly disliked any type of clinical consultation, and had the lowest participation in local EBP training initiatives; Segment 4 (n = 90, 26%) strongly preferred clinical consultation strategies and included more clinicians in substance use clinics.

CONCLUSIONS

The presence of four heterogeneous subpopulations within this large group of clinicians, supervisors, and administrators suggests optimal implementation may be achieved through targeted strategies derived via elicitation of stakeholder preferences. Best-worst scaling is a feasible and rigorous method for eliciting stakeholders' implementation preferences and identifying subpopulations with unique preferences in behavioral health settings.

Investigating physiotherapy stakeholders' preferences for the development of performance-based assessment in practice education

OBJECTIVES

Discrete choice experiments (DCEs) are used in healthcare to measure the relative importance that stakeholders give to different features (or attributes) of medical treatments or services. They may also help to address research questions in health professional education. Several challenges exist regarding the performance-based assessment process (PBA) employed in physiotherapy practice-based education, a process which determines students' readiness for independent practice. Evidence highlights many commonalities among these challenges, but it is unknown which factors are the most important to stakeholders. The use of DCE methodology may provide answers and help to prioritise areas for development. Thus, this study employed DCE to identify clinical educators', practice tutors and physiotherapy students' preferences for developing the PBA process in physiotherapy.

DESIGN

Attributes (aspects of the PBA process known to be important to stakeholders) were derived from focus group interviews conducted with three groups; physiotherapy students, clinical educators (practising clinicians) and practice tutors (dedicated educational roles in the workplace). These attributes included the PBA tool, grading mechanisms, assessors involved, and, feedback mechanisms. Preferences for each group were calculated using a logistic regression model.

RESULTS

Seventy-two students, 124 clinical educators and 49 practice tutors (n=245) participated. Priorities identified centred primarily on the mandatory inclusion of two assessors in the PBA process and on refinement of the PBA tool.

CONCLUSION

Employment of DCE enabled the prioritisation of stakeholder-informed challenges related to PBA in physiotherapy practice-based education. This corroborates findings from previous qualitative work and facilitates a prioritised pathway for development of this process.

What Influences Educators' Design Preferences for Bullying Prevention Programs? Multi-level Latent Class Analysis of a Discrete Choice Experiment

We used a discrete choice conjoint experiment to model the anti-bullying (AB) program preferences of 1080 junior kindergarten to Grade 8 educators. Participants chose between hypothetical AB programs that varied combinations of 12 design attributes. Multi-level latent class analysis yielded three classes: All-in Supervisors (21.5%) preferred that all teaching staff supervise playgrounds and hallways; Facilitators (61.6%) preferred that students take ownership of AB activities with 25% of educators supervising playgrounds and hallways; and Reluctant Delegators (16.9%) preferred delegating the supervision of playgrounds and hallways to non-teaching staff. This class reported higher dispositional reactance, more implementation barriers, and more psychological reactance to these initiatives. They were less sensitive to social influences and less intent on participating in AB activities. Multi-level analysis showed a greater proportion of Reluctant Delegators clustered in one of the two groups of schools. The program choices of all classes were sensitive to the support of principals, colleagues, students, and, to a lesser extent, parents. All classes preferred programs conducted from kindergarten through Grade 12 that addressed the problems underlying bullying while valuing firm and consistent consequences for all students. Educators preferred AB programs selected by individual schools, rather than governments.

Modeling the Decision of Mental Health Providers to Implement Evidence-Based Children's Mental Health Services: A Discrete Choice Conjoint Experiment

Using an online, cross sectional discrete choice experiment, we modeled the influence of 14 implementation attributes on the intention of 563 providers to adopt hypothetical evidence-based children’s mental health practices (EBPs). Latent class analysis identified two segments. Segment 1 (12%) would complete 100% of initial training online, devote more time to training, make greater changes to their practices, and introduce only minor modifications to EBPs. Segment 2 (88%) preferred fewer changes, more modifications, less training, but more follow-up. Simulations suggest that enhanced supervisor support would increase the percentage of participants choosing the intensive training required to implement EBPs. The dissemination of EBPs needs to consider the views of segments of service providers with differing preferences regarding EBPs and implementation process design.

Methods to Improve the Selection and Tailoring of Implementation Strategies

Implementing behavioral health interventions is a complicated process. It has been suggested that implementation strategies should be selected and tailored to address the contextual needs of a given change effort; however, there is limited guidance as to how to do this. This article proposes four methods (concept mapping, group model building, conjoint analysis, and intervention mapping) that could be used to match implementation strategies to identified barriers and facilitators for a particular evidence-based practice or process change being implemented in a given setting. Each method is reviewed, examples of their use are provided, and their strengths and weaknesses are discussed. The discussion includes suggestions for future research pertaining to implementation strategies and highlights these methods' relevance to behavioral health services and research.

Using Latent Class Analysis to Model Preference Heterogeneity in Health: A Systematic Review

BACKGROUND

Latent class analysis (LCA) has been increasingly used to explore preference heterogeneity, but the literature has not been systematically explored and hence best practices are not understood.

OBJECTIVE

We sought to document all applications of LCA in the stated-preference literature in health and to inform future studies by identifying current norms in published applications.

METHODS

We conducted a systematic review of the MEDLINE, EMBASE, EconLit, Web of Science, and PsycINFO databases. We included stated-preference studies that used LCA to explore preference heterogeneity in healthcare or public health. Two co-authors independently evaluated titles, abstracts, and full-text articles. Abstracted key outcomes included segmentation methods, preference elicitation methods, number of attributes and levels, sample size, model selection criteria, number of classes reported, and hypotheses tests. Study data quality and validity were assessed with the Purpose, Respondents, Explanation, Findings, and Significance (PREFS) quality checklist.

RESULTS

We identified 2560 titles, 99 of which met the inclusion criteria for the review. Two-thirds of the studies focused on the preferences of patients and the general population. In total, 80% of the studies used discrete choice experiments. Studies used between three and 20 attributes, most commonly four to six. Sample size in LCAs ranged from 47 to 2068, with one-third between 100 and 300. Over 90% of the studies used latent class logit models for segmentation. Bayesian information criterion (BIC), Akaike information criterion (AIC), and log-likelihood (LL) were commonly used for model selection, and class size and interpretability were also considered in some studies. About 80% of studies reported two to three classes. The number of classes reported was not correlated with any study characteristics or study population characteristics (p > 0.05). Only 30% of the studies reported using statistical tests to detect significant variations in preferences between classes. Less than half of the studies reported that individual characteristics were included in the segmentation models, and 30% reported that post-estimation analyses were conducted to examine class characteristics. While a higher percentage of studies discussed clinical implications of the segmentation results, an increasing number of studies proposed policy recommendations based on segmentation results since 2010.

CONCLUSIONS

LCA is increasingly used to study preference heterogeneity in health and support decision-making. However, there is little consensus on best practices as its application in health is relatively new. With an increasing demand to study preference heterogeneity, guidance is needed to improve the quality of applications of segmentation methods in health to support policy development and clinical practice.

Application of discrete choice experiments to enhance stakeholder engagement as a strategy for advancing implementation: a systematic review

Background

One of the key strategies to successful implementation of effective health-related interventions is targeting improvements in stakeholder engagement. The discrete choice experiment (DCE) is a stated preference technique for eliciting individual preferences over hypothetical alternative scenarios that is increasingly being used in health-related applications. DCEs are a dynamic approach to systematically measure health preferences which can be applied in enhancing stakeholder engagement. However, a knowledge gap exists in characterizing the extent to which DCEs are used in implementation science.

Methods

We conducted a systematic literature search (up to December 2016) of the English literature to identify and describe the use of DCEs in engaging stakeholders as an implementation strategy. We searched the following electronic databases: MEDLINE, Econlit, PsychINFO, and the CINAHL using mesh terms. Studies were categorized according to application type, stakeholder(s), healthcare setting, and implementation outcome.

Results

Seventy-five publications were selected for analysis in this systematic review. Studies were categorized by application type: (1) characterizing demand for therapies and treatment technologies (n = 32), (2) comparing implementation strategies (n = 22), (3) incentivizing workforce participation (n = 11), and (4) prioritizing interventions (n = 10). Stakeholders included providers (n = 27), patients (n = 25), caregivers (n = 5), and administrators (n = 2). The remaining studies (n = 16) engaged multiple stakeholders (i.e., combination of patients, caregivers, providers, and/or administrators). The following implementation outcomes were discussed: acceptability (n = 75), appropriateness (n = 34), adoption (n = 19), feasibility (n = 16), and fidelity (n = 3).

Conclusions

The number of DCE studies engaging stakeholders as an implementation strategy has been increasing over the past decade. As DCEs are more widely used as a healthcare assessment tool, there is a wide range of applications for them in stakeholder engagement. The DCE approach could serve as a tool for engaging stakeholders in implementation science.

Electronic supplementary material

The online version of this article (10.1186/s13012-017-0675-8) contains supplementary material, which is available to authorized users.

Educator Burnout and Compassion Fatigue: A Pilot Study

Sixty-four Canadian educators from Southwestern Ontario took part in a 2-hr voluntary workshop about the emotional labor and consequences that may be experienced by educators. A focus on both burnout and teacher compassion fatigue (CF), an underresearched area with respect to Canadian educators, was taken. The current study hypothesized that this professional development would positively influence educators’ knowledge, skills, and awareness regarding burnout, CF, and self-care; furthermore, it was predicted there would be a positive correlation between burnout and CF. Results supported the efficacy of professional development and partial support was detected for the relationship between burnout and CF. Implications and future research are discussed.

Fertility Desires among Women Living with HIV

OBJECTIVE

Rates of pregnancy among women living with HIV (WLHIV) have increased with the availability of effective HIV treatment. Planning for pregnancy and childbirth is an increasingly important element of HIV care. Though rates of unintended pregnancies are high among women in general, among couples affected by HIV, significant planning and reproductive decisions must be considered to prevent negative health consequences for WLHIV and their neonates. To gain insight into this reproductive decision-making process among WLHIV, this study explored women's knowledge, attitudes and practices regarding fertility planning, reproductive desires, and safer conception practices. It was hypothesized that pregnancy desires would be influenced by partners, families, the potential risk of HIV transmission to infants, and physicians' recommendations.

METHODS

WLHIV of childbearing age were recruited from urban South Florida, and completed an assessment of demographics (N = 49), fertility desires and a conjoint survey of factors associated with reproductive decision-making.

RESULTS

Using conjoint analysis, we found that different decision paths exist for different types of women: Younger women and those with less education desired children if their partners wanted children; reproductive desires among those with less education, and with less HIV pregnancy-related knowledge, displayed a trend toward additional emphasis on their family's desires. Conversely, older women and those with more education appeared to place more importance on physician endorsement in their plans for childbearing.

CONCLUSIONS

Results of this study highlight the importance of ongoing preconception counselling for all women of reproductive age during routine HIV care. Counselling should be tailored to patient characteristics, and physicians should consider inclusion of families and/or partners in the process.

Methods to Improve the Selection and Tailoring of Implementation Strategies

Implementing behavioral health interventions is a complicated process. It has been suggested that implementation strategies should be selected and tailored to address the contextual needs of a given change effort; however, there is limited guidance as to how to do this. This article proposes four methods (concept mapping, group model building, conjoint analysis, and intervention mapping) that could be used to match implementation strategies to identified barriers and facilitators for a particular evidence-based practice or process change being implemented in a given setting. Each method is reviewed, examples of their use are provided, and their strengths and weaknesses are discussed. The discussion includes suggestions for future research pertaining to implementation strategies and highlights these methods' relevance to behavioral health services and research.