Youth, mentoring, and the opioid crisis: New tools for assessing needs and tracking outcomes
By David Dubois, National Mentoring Resource Center Blog
Back in June of last year, Mike Garringer contributed an entry on this blog that addressed the ways in which mentoring for youth potentially could be useful in combating the opioid crisis (see “The Promise and Potential of Mentors in Combating the Opioid Crisis”). Mike highlighted a number of promising areas for mentors to be an asset to young people already engaged in opioid abuse (e.g., providing hope and motivation for recovery, connecting them to and supporting their engagement in treatment services). He also emphasized the potential for mentors to be helpful on the “front-end” of this issue by supporting the healthy development of young people in ways that prevent the initiation of use altogether (i.e., primary prevention). Finally, and I think this may turn out be a particularly fruitful avenue of contribution, he called attention to the potential of mentoring to be an important source of support for young people who have suffered fallout from the opioid misuse of parental or other adult support figures. As Mike noted, in fact, we already have good evidence that mentors can be beneficial to youth whose adult support systems are disrupted or otherwise compromised due to incarceration of a parent or the youth’s placement into foster care, each of which are situations often experienced by youth whose parents are struggling with opioid use.
Their promise notwithstanding, actualizing these potential contributions in the ways we all would like to see will require efforts that are both data-driven and evidence-informed. Consider, for example, a mentoring program that is looking to get an accurate handle on the number of youth it serves who have been impacted negatively by opioid use of a parent or other caregiver. Without solid data, the program would no doubt face an uphill battle when seeking funding to build in additional supports for these mentees. As another example, consider a program that develops and implements activities to facilitate conversations and information sharing within matches about the addictive potential of opioid use and its other possible harmful consequences. Systematic tracking of changes that mentees report in relevant risk factors for opioid use (e.g. believing that they are not likely to be harmful) before and after these activities could prove invaluable for gauging whether they are having the desired effect, not to mention for yielding clues as to how these supports might be improved.
A desire to help programs capitalize on these types of opportunities motivated us to include two measures relating to opioid misuse in the recently released update of the National Mentoring Resource Center’s Measurement Guidance Toolkit. One of the measures, taken from the U.S. Centers for Disease Control’s Youth Risk Behavior Surveillance System, assesses misuse of prescription pain medication as well as use of heroin. Consisting of only 3 items, it could be a practical addition to a program’s existing outcome measures. Programs may also find it informative to consult the YRBSS website for community-wide prevalence estimates derived used these same items. This data could be useful for planning purposes and to bench mark their own needs and outcomes against local trends. In Broward County, Florida, for example, it can be seen that in 2017 the percentage of youth reporting misuse of a prescription pain medication (i.e., without a doctor’s prescription or differently than how a doctor told them to use it) jumps four-fold when comparing 6th graders (2.1%) and 8th graders (8.4%). Such trends can highlight important windows for primary prevention efforts in a community of the kind that Mike envisioned in his earlier post.
The second measure added to the Toolkit asks about potential risk factors for opioid misuse (e.g., perceived availability of opioids in the youth’s environment and friends’ substance use, including opioids) as well as ways in which others’ opioid misuse may have had a negative impact on the youth (e.g., a parent or other family member being incarcerated due to opioid use, having a close friend overdose). Programs might find these questions useful to ask routinely of youth on entering their programs. In aggregate, the resulting data could provide an informative profile of the types of risk factors and negative impacts of opioid use that are most typical of the youth that the program serves, thus informing its practices (e.g., mentor training). At the level of individual mentees, these kinds of data might suggest useful goals for the match, such as risk factors to target for reduction, not to mention simply sensitizing staff and mentors alike to the myriad ways in which a given youth may have been adversely affected by opioid use in ways that are indirect and thus not as easily detected without intentional data gathering. It goes (almost) without saying, however, that whether utilizing data from these measures at the level of an entire program or particular youth, it is of paramount importance that appropriate safeguards be in place not only to address privacy concerns, but also to protect against unintended consequences such as feelings of stigma or shame.
As one might expect, just like other lines of response to the opioid crisis, measurement in this area is in an early stage of development. In doing our research to update the Toolkit, we observed that measures suitable for use with younger age groups are particularly scarce and still evolving. The YRBSS items to assess opioid misuse, for example, were first introduced into this survey only 2 years ago. We were unable, moreover, to find any appropriate measures of youths’ exposure to negative consequences of others’ opioid use (e.g., parental addiction). Accordingly, we needed to develop new survey items for this purpose ourselves. Clearly, then, users of these new Toolkit measures should be mindful that the field-testing needed to establish their reliability and validity is in a nascent state. This reality, however, should not inhibit programs from utilizing the measures. In fact, deploying them for practical purposes like those described above will generate the very kinds of data that are needed to better document their psychometric soundness and utility. Partnerships between programs and researchers are particularly likely to prove fruitful to this end. I hope to see many of these types of collaborations take root in the near future as all of us work together to realize the full potential of the mentoring field’s contribution to addressing the opioid crisis.
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