ABSTRACT
OBJECTIVE: Psychological first aid (PFA) refers to evidence-supported intervention by nonmental health professionals to assist those affected by disaster to achieve stability. This study probed the level of PFA academic discourse on three important topics (race/ethnicity, general training and delivery, and online training delivery) and explored PFA training delivery trends. METHOD: This study reviewed all available abstracts in the Web of Science database from 1975 to 2021 with keyword searches for PFA. The corpus linguistic analyses using #Lancsbox 6.0 and Sketch Engine explored the usage rate of PFA and how the PFA was used. The study also examined race/ethnicity, learning delivery except for online, and online training delivery methods. The change in online PFA training delivery with the advent of the COVID-19 pandemic was analyzed using Tau with the subcorpora (2012-2020, 2020-2021). RESULTS: The race and diversity usage rates were only 6.11 per 10,000 counts, while the substantive discourse was on PFA service and delivery. There was a significant increase in PFA online training since COVID-19 started (Tau = 0.667, p = 0.041, SETau = 0.333). CONCLUSIONS: Training and delivering online PFA is the safest method to meet the need for psychological aid during the global health crisis. Additionally, there is a significant need to address multicultural competency in PFA training and service delivery. PFA as an early critical intervention should be promoted as an early government response. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
Subject(s)
COVID-19 , Disasters , Humans , Psychological First Aid , Pandemics , First Aid/methods , First Aid/psychologyABSTRACT
Background: Psychological First Aid (PFA) is practiced worldwide. This practice in English is guided through a small collection of training manuals. Despite ubiquitous practice and formal training materials, little is known about what topics are covered and in what depth in these influential manuals. As such, we analyzed the topic structure of these training manuals.Objective: To model the PFA manuals' topics with the goal of identifying a set of topics with recurrent themes and evaluating the extent to which each manual demonstrated those themes.Method: This machine learning study employed an unsupervised topic modelling design using Latent Dirichlet Allocation. The variables are (1) the distribution of a word across documents and (2) the distribution of a word across topics. The level of measurement for all variables is continuous. The unit of analysis is words. Preprocessing and data analysis were carried out using the Orange Data Mining Toolbox (Demsar et al., 2013). This programme is a Python GUI.Results: Results indicated a ten-topic structure to the universe of the English PFA training manuals. These topics were: (1) Refugees, (2) Orientation Activities, (3) Community-Based Applications, (4) PTSD & Other Psychological Issues, (5) Training Materials, (6) Specific Helper Instructions, (7) PFA Scholarship, (8) MHPSS, (9) General Curriculum, and (10) Australian Specific Delivery. The depth of discourse on each topic varied widely between manuals.Conclusions: The Academics of the PFA topic shows a strong representation of the corpus and suggests current training manuals have stayed true to its evidence-supported practice. The topic of Community-Based Applications strongly represents the corpus and suggests that training models incorporate community-based applications. The scientific foundation and practical implementation of the training guides are essential elements. Limitations and implications were also discussed.
Little is known about what topics are covered and in what depth in the influential PFA English manuals.We conducted a topic modelling study using Latent Dirichlet Allocation, aiming to discover a set of topics with recurring themes and analyze the degree to which each manual exhibited those topics.Results indicated a 10-topic structure to the universe of the English PFA training manuals.The training manuals' scientific basis and practical application are key components, while notable gaps presented.
