{"title":"利用统计技术了解有心理健康问题的军人的独特需求:从假设病人的同质性转向了解异质性。","authors":"Laura Josephine Hendrikx, D Murphy","doi":"10.1136/military-2022-002253","DOIUrl":null,"url":null,"abstract":"<p><p>Gold standard treatments for military personnel seeking support for mental health difficulties are often standardised and manualised to ensure high levels of treatment fidelity. While manualised treatments are preferable to less evidence-based idiosyncratic approaches, they may not fully account for the differences in symptom profiles present in patients with the same psychological diagnosis. Indeed, recent findings have highlighted that a significant proportion of individuals do not benefit from the 'gold standard' treatments. This brief report discusses the utility of statistical techniques, specifically latent profile analysis and network analysis, to support the transition to more evidence-based idiosyncratic, personalised care for clinical military, and general, populations. Further incorporation of such analysis methods may support arriving at a framework to support the personalisation of care in terms of the selection and adaption of evidence-based approach treatments based on individual clinical need.</p>","PeriodicalId":48485,"journal":{"name":"Bmj Military Health","volume":null,"pages":null},"PeriodicalIF":1.4000,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Using statistical techniques to understand the unique needs of military personnel experiencing mental health difficulties: moving away from assuming patient homogeneity to understanding heterogeneity.\",\"authors\":\"Laura Josephine Hendrikx, D Murphy\",\"doi\":\"10.1136/military-2022-002253\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Gold standard treatments for military personnel seeking support for mental health difficulties are often standardised and manualised to ensure high levels of treatment fidelity. While manualised treatments are preferable to less evidence-based idiosyncratic approaches, they may not fully account for the differences in symptom profiles present in patients with the same psychological diagnosis. Indeed, recent findings have highlighted that a significant proportion of individuals do not benefit from the 'gold standard' treatments. This brief report discusses the utility of statistical techniques, specifically latent profile analysis and network analysis, to support the transition to more evidence-based idiosyncratic, personalised care for clinical military, and general, populations. Further incorporation of such analysis methods may support arriving at a framework to support the personalisation of care in terms of the selection and adaption of evidence-based approach treatments based on individual clinical need.</p>\",\"PeriodicalId\":48485,\"journal\":{\"name\":\"Bmj Military Health\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2024-09-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Bmj Military Health\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1136/military-2022-002253\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MEDICINE, GENERAL & INTERNAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bmj Military Health","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1136/military-2022-002253","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
Using statistical techniques to understand the unique needs of military personnel experiencing mental health difficulties: moving away from assuming patient homogeneity to understanding heterogeneity.
Gold standard treatments for military personnel seeking support for mental health difficulties are often standardised and manualised to ensure high levels of treatment fidelity. While manualised treatments are preferable to less evidence-based idiosyncratic approaches, they may not fully account for the differences in symptom profiles present in patients with the same psychological diagnosis. Indeed, recent findings have highlighted that a significant proportion of individuals do not benefit from the 'gold standard' treatments. This brief report discusses the utility of statistical techniques, specifically latent profile analysis and network analysis, to support the transition to more evidence-based idiosyncratic, personalised care for clinical military, and general, populations. Further incorporation of such analysis methods may support arriving at a framework to support the personalisation of care in terms of the selection and adaption of evidence-based approach treatments based on individual clinical need.