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Record W4391610170 · doi:10.7759/cureus.53741

Exploring Care and Recovery for Individuals With Post-traumatic Stress Disorder: A Scoping Review

2024· review· en· W4391610170 on OpenAlexaff
Jennifer R. Smith, Kyle J. Drouillard, Angel M. Foster

Bibliographic record

VenueCureus · 2024
Typereview
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsHypervigilancePsycINFOShameIrritabilityTraumatic stressPsychologyPsychological traumaPsychological interventionMental healthPsychiatryStressorFeelingClinical psychologyPsychotherapistMEDLINEAnxietyMedicineSocial psychology

Abstract

fetched live from OpenAlex

Most people experience trauma at some point in their lives. The sources of trauma can include accidents, natural disasters, physical or sexual assault, combat, torture, or the death of a loved one. Experiencing or witnessing any of these, or other terrifying events, may make one susceptible to developing post-traumatic stress disorder (PTSD), a trauma- and stressor-related mental health condition. The common symptoms and consequences of PTSD include intrusive and distressing thoughts, memories, or flashbacks related to the traumatic event; avoidance of situations, people, or activities that remind one of the traumatic event; irritability, sleep difficulties, or hypervigilance; feelings of guilt, shame, or fear; substance use; strains on relationships; and suicidal thoughts and behaviors. These consequences can have devastating effects on the individual and their family members, friends, co-workers, peers, and communities. Effectively treating PTSD, therefore, is critical not only for the individual but also for the well-being of families, communities, and society at large. However, while treatments for PTSD exist, effectively treating patients with PTSD remains elusive. Further, despite the recognition that people's experiences are essential in understanding PTSD and provide valuable insights into what interventions are effective and how they impact recovery, patient perspectives and experiences of care and recovery have not been well-explored. We conducted a scoping review to address the following question: what is known about the experiences and perspectives of care and recovery for individuals with PTSD? We searched the Medical Literature Analysis and Retrieval System Online (MEDLINE), Embase, American Psychological Association's (APA) PsycInfo, the Cumulative Index to Nursing and Allied Health Literature (CINAHL), PTSDPubs, and Google Scholar for peer-reviewed and grey literature that used qualitative methods to report on the recovery or care experiences of adults with lived experiences of PTSD. We extracted information about study objectives, study characteristics, and key findings; reported summary statistics; and performed content and thematic analyses. We identified 14 relevant studies that provide insight into the participants' lived experiences and perspectives of PTSD care and recovery. Though limited, the body of literature sheds light on critical themes and processes in the journey of care of PTSD, which we organized into four overarching categories: pre-treatment understanding and experiences of PTSD, the experience of care or treatment, the importance of relationships and social support, and expanding the understandings of recovery. Living with and healing from PTSD are a unique and individualized human experience of developing and redeveloping relationships with oneself, with others, and with society. The recommendations for practice include educating and establishing well-informed support networks for individuals with PTSD, training healthcare practitioners in all aspects of formal and informal PTSD treatment and care needs, ensuring a continuum of care, and understanding the human experience of PTSD.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.054
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.015
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.054
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0150.018
Science and technology studies0.0020.001
Scholarly communication0.0050.005
Open science0.0020.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0040.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.308
GPT teacher head0.471
Teacher spread0.164 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2024
Admission routes1
Has abstractyes

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