Prioritizing Prevention: Difference between revisions
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[[File:Universal Prevention.mp4|thumb|Dr Peter Wyman describes the import of prioritizing universal approaches to prevention for community mental health.]] | [[File:Universal Prevention.mp4|thumb|Dr Peter Wyman describes the import of prioritizing universal approaches to prevention for community mental health.]] | ||
Prevention works best when it changes the environment people already belong to, rather than waiting to find and treat people once they are already struggling. This is the central argument behind network health approaches to suicide prevention: instead of screening individuals for risk, they strengthen the relationships and group bonds that already exist in a school, workplace, or team. | |||
[[File:Prevention or Intervention.mp4|thumb|Dr Peter Wyman explains that a "preventatative intervention" that engages a community as a whole and creates natural networks through shared experience can build protective factors into the community.|left]] | |||
[ | Wyman (2014) frames this as a shift toward "upstream" prevention, "modifying... risk and protective processes—before the emergence of suicidal behaviour," a design that "stands in contrast to current youth suicide prevention programming focused on identifying and treating individuals who are already suicidal or at high risk by training adult gatekeepers and screening" (p. S252). The case for this shift is not only conceptual. Wyman (2014) points to specific limits on identify-and-treat strategies, including "limited ability to identify specific individuals who will die by suicide" and "limited evidence that use of usual mental health treatment services will reduce suicide risk" (p. S252). Because these limits are structural, no improvement to an individual-level service resolves them; the population that needs protecting is always larger than the population any screening process will flag. | ||
' | This is why network health approaches treat the group itself, not the individual, as the target of intervention. In Wyman's (2014) words, "system-level interventions modify social-ecologic contexts, which have risk-protective effects above and beyond individual factors" (p. S252), in plain terms, making a class, team, or unit more cohesive protects everyone in it, including people no one has flagged as at risk. | ||
This logic was tested directly. A cluster randomized trial of the Wingman-Connect programme worked with intact U.S. Air Force training classes rather than individually selected trainees, aiming to "target natural organizational groups to strengthen bonds, cohesion, and adaptive coping norms" (Wyman et al., 2020, Introduction). Benefits were "distributed across personnel with different levels of those problems at baseline," evidence that "diverse personnel benefited from the program illustrates a strength of a universal prevention strategy for military populations with members at low risk and others at higher risk who may not seek mental health services" (Wyman et al., 2020, Discussion). Because the training was built into ordinary occupational skills rather than run alongside them, the authors conclude that "universal prevention programs that support operational and suicide prevention objectives are more likely to be sustained" (Wyman et al., 2020, Discussion). Mediation analysis confirmed that cohesion itself carried the effect: "participants' perceptions of being embedded in a more cohesive, healthy class accounted for significant portions of Wingman-Connect's impact on reducing suicidal ideation and depression symptoms" (Wyman et al., 2020, Results). | |||
''' | === '''Context: Prevention in Schools''' === | ||
Schools matter to prevention because childhood and adolescence are the years when most future risk takes shape. Wyman (2014) notes that "approximately one half of emotional and behavioral disorders that are well-defined risk factors for suicide have onset of symptoms by age 14 years" (p. S252). His model works in two stages: building self-regulation early through "family and school-based programs," then, in adolescence, working through "peer norms" already present in the school (Wyman, 2014, p. S253). In practice, this has meant training student peer leaders to "modify norms through their natural social networks," which "has increased schoolwide help-seeking acceptability, coping norms, and engagement of adults to help suicidal peers" (Wyman, 2014, p. S254). As a whole-school foundation for this kind of work, Positive Behavioral Interventions and Supports improves school climate and behaviour broadly (Santiago-Rosario et al., 2023), though it has not been tested as a suicide-prevention measure specifically. | |||
=== '''Context: Prevention among Remote Workers in IT and Technology''' === | |||
No trial has tested a network-cohesion prevention programme with software teams, so this extends the same logic to a population studied only for its risk, not its remedy. Distributed software development shows what erodes when a team splits across sites: work spanning more than one location "take about two and one-half times as long to complete" as collocated work (Herbsleb & Mockus, 2003, Abstract), and separated developers report markedly less "teamness," a gap the authors link to distance disrupting "the usual stages by which individuals become coherent groups or teams" (Herbsleb & Mockus, 2003, Discussion). A large study of Microsoft staff found remote work "caused larger increases for engineers than non-engineers" in messaging and calls, "reflective of the fact that software development teams are particularly reliant on informal communication" once carried face to face (Yang et al., 2022, Results), the cohesion Wingman-Connect targets, untested here. | |||
=== '''References''' === | |||
Herbsleb, J. D., & Mockus, A. (2003). An empirical study of speed and communication in globally distributed software development. ''IEEE Transactions on Software Engineering, 29''(6), 481–494. <nowiki>https://doi.org/10.1109/TSE.2003.1205177</nowiki> | |||
Santiago-Rosario, M. R., McIntosh, K., Izzard, S., Cohen Lissman, D., & Calhoun, E. (2023). ''Is positive behavioral interventions and supports (PBIS) an evidence-based practice?'' Center on PBIS, University of Oregon. <nowiki>https://www.researchgate.net/publication/375487373_Is_Positive_Behavioral_Interventions_and_Supports_PBIS_an_Evidence-Based_Practice</nowiki> | |||
Wyman, P. A. (2014). Developmental approach to prevent adolescent suicides: Research pathways to effective upstream preventive interventions. ''American Journal of Preventive Medicine, 47''(3, Suppl. 2), S251–S256. <nowiki>https://doi.org/10.1016/j.amepre.2014.05.039</nowiki> | |||
Wyman, P. A., Pisani, A. R., Brown, C. H., Yates, B., Morgan-DeVelder, L., Schmeelk-Cone, K., Gibbons, R. D., Caine, E. D., Petrova, M., Neal-Walden, T., Linkh, D. J., Matteson, A., Simonson, J., & Pflanz, S. E. (2020). Effect of the Wingman-Connect upstream suicide prevention program for Air Force personnel in training: A cluster randomized clinical trial. ''JAMA Network Open, 3''(11), e2022532. <nowiki>https://doi.org/10.1001/jamanetworkopen.2020.22532</nowiki> | |||
Yang, L., Holtz, D., Jaffe, S., Suri, S., Sinha, S., Weston, J., Joyce, C., Shah, N., Sherman, K., Hecht, B., & Teevan, J. (2022). The effects of remote work on collaboration among information workers. ''Nature Human Behaviour, 6'', 43–54. <nowiki>https://doi.org/10.1038/s41562-021-01196-4</nowiki> | |||
Latest revision as of 13:53, 22 July 2026
Prevention works best when it changes the environment people already belong to, rather than waiting to find and treat people once they are already struggling. This is the central argument behind network health approaches to suicide prevention: instead of screening individuals for risk, they strengthen the relationships and group bonds that already exist in a school, workplace, or team.
Wyman (2014) frames this as a shift toward "upstream" prevention, "modifying... risk and protective processes—before the emergence of suicidal behaviour," a design that "stands in contrast to current youth suicide prevention programming focused on identifying and treating individuals who are already suicidal or at high risk by training adult gatekeepers and screening" (p. S252). The case for this shift is not only conceptual. Wyman (2014) points to specific limits on identify-and-treat strategies, including "limited ability to identify specific individuals who will die by suicide" and "limited evidence that use of usual mental health treatment services will reduce suicide risk" (p. S252). Because these limits are structural, no improvement to an individual-level service resolves them; the population that needs protecting is always larger than the population any screening process will flag.
This is why network health approaches treat the group itself, not the individual, as the target of intervention. In Wyman's (2014) words, "system-level interventions modify social-ecologic contexts, which have risk-protective effects above and beyond individual factors" (p. S252), in plain terms, making a class, team, or unit more cohesive protects everyone in it, including people no one has flagged as at risk.
This logic was tested directly. A cluster randomized trial of the Wingman-Connect programme worked with intact U.S. Air Force training classes rather than individually selected trainees, aiming to "target natural organizational groups to strengthen bonds, cohesion, and adaptive coping norms" (Wyman et al., 2020, Introduction). Benefits were "distributed across personnel with different levels of those problems at baseline," evidence that "diverse personnel benefited from the program illustrates a strength of a universal prevention strategy for military populations with members at low risk and others at higher risk who may not seek mental health services" (Wyman et al., 2020, Discussion). Because the training was built into ordinary occupational skills rather than run alongside them, the authors conclude that "universal prevention programs that support operational and suicide prevention objectives are more likely to be sustained" (Wyman et al., 2020, Discussion). Mediation analysis confirmed that cohesion itself carried the effect: "participants' perceptions of being embedded in a more cohesive, healthy class accounted for significant portions of Wingman-Connect's impact on reducing suicidal ideation and depression symptoms" (Wyman et al., 2020, Results).
Context: Prevention in Schools
Schools matter to prevention because childhood and adolescence are the years when most future risk takes shape. Wyman (2014) notes that "approximately one half of emotional and behavioral disorders that are well-defined risk factors for suicide have onset of symptoms by age 14 years" (p. S252). His model works in two stages: building self-regulation early through "family and school-based programs," then, in adolescence, working through "peer norms" already present in the school (Wyman, 2014, p. S253). In practice, this has meant training student peer leaders to "modify norms through their natural social networks," which "has increased schoolwide help-seeking acceptability, coping norms, and engagement of adults to help suicidal peers" (Wyman, 2014, p. S254). As a whole-school foundation for this kind of work, Positive Behavioral Interventions and Supports improves school climate and behaviour broadly (Santiago-Rosario et al., 2023), though it has not been tested as a suicide-prevention measure specifically.
Context: Prevention among Remote Workers in IT and Technology
No trial has tested a network-cohesion prevention programme with software teams, so this extends the same logic to a population studied only for its risk, not its remedy. Distributed software development shows what erodes when a team splits across sites: work spanning more than one location "take about two and one-half times as long to complete" as collocated work (Herbsleb & Mockus, 2003, Abstract), and separated developers report markedly less "teamness," a gap the authors link to distance disrupting "the usual stages by which individuals become coherent groups or teams" (Herbsleb & Mockus, 2003, Discussion). A large study of Microsoft staff found remote work "caused larger increases for engineers than non-engineers" in messaging and calls, "reflective of the fact that software development teams are particularly reliant on informal communication" once carried face to face (Yang et al., 2022, Results), the cohesion Wingman-Connect targets, untested here.
References
Herbsleb, J. D., & Mockus, A. (2003). An empirical study of speed and communication in globally distributed software development. IEEE Transactions on Software Engineering, 29(6), 481–494. https://doi.org/10.1109/TSE.2003.1205177
Santiago-Rosario, M. R., McIntosh, K., Izzard, S., Cohen Lissman, D., & Calhoun, E. (2023). Is positive behavioral interventions and supports (PBIS) an evidence-based practice? Center on PBIS, University of Oregon. https://www.researchgate.net/publication/375487373_Is_Positive_Behavioral_Interventions_and_Supports_PBIS_an_Evidence-Based_Practice
Wyman, P. A. (2014). Developmental approach to prevent adolescent suicides: Research pathways to effective upstream preventive interventions. American Journal of Preventive Medicine, 47(3, Suppl. 2), S251–S256. https://doi.org/10.1016/j.amepre.2014.05.039
Wyman, P. A., Pisani, A. R., Brown, C. H., Yates, B., Morgan-DeVelder, L., Schmeelk-Cone, K., Gibbons, R. D., Caine, E. D., Petrova, M., Neal-Walden, T., Linkh, D. J., Matteson, A., Simonson, J., & Pflanz, S. E. (2020). Effect of the Wingman-Connect upstream suicide prevention program for Air Force personnel in training: A cluster randomized clinical trial. JAMA Network Open, 3(11), e2022532. https://doi.org/10.1001/jamanetworkopen.2020.22532
Yang, L., Holtz, D., Jaffe, S., Suri, S., Sinha, S., Weston, J., Joyce, C., Shah, N., Sherman, K., Hecht, B., & Teevan, J. (2022). The effects of remote work on collaboration among information workers. Nature Human Behaviour, 6, 43–54. https://doi.org/10.1038/s41562-021-01196-4