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Trauma Recovery from a Positive Psychology and Post-Traumatic Growth Perspective

2024· book-chapter· en· W4396614925 on OpenAlexaff
Kathleen Stephany

Bibliographic record

VenueBENTHAM SCIENCE PUBLISHERS eBooks · 2024
Typebook-chapter
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsDouglas College
Fundersnot available
KeywordsPerspective (graphical)PsychologyPsychoanalysisPositive psychologyPsychotherapistEmotional traumaClinical psychologyApplied psychologyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

The aim of Chapter Four is to demonstrate that living a better life after adversity is possible when adequate support is offered. Therefore, positive psychology and post-traumatic growth are two recovery-focused trauma-informed approaches that are highly recommended to help people who have experienced adversity. Positive psychology studies human well-being and optimal functioning. Post-traumatic growth refers to positive changes in someone’s coping that occur from sorting through their experience of trauma. Three different responses to traumatic stress are explained. For instance, certain people bounce right back after an adverse event, others develop maladaptive functioning, and a third reaction results in post-traumatic growth. The particular response that a person experiences is somewhat context-dependent. After trauma occurs, positive changes in brain function are made possible through neuroplasticity. Positive Psychology and trauma-informed care share the common goal of helping people to live better lives, but they also differ. For instance, positive psychology strategies are designed to be used by everyone and are therefore not limited to those who have experienced trauma. The five key elements of well-being theory called PERMA are presented, such as positive emotions, engagement, relationships, meaning, and accomplishment. Positive emotions are deemed essential for life satisfaction. Work-related well-being was later developed and called PERMA+4 and is associated with physical health, mindset, work environment, and economic security. Flourishing is a central component of well-being theory and consists of the capacity to be satisfied with one’s life achievements and being involved in something that is meaningful. The following strategies are known to facilitate well-being, being grateful, a positive attitude, random acts of kindness, and positive psychotherapy. Positive psychotherapy is an effective method to treat trauma because it focuses on a person’s strengths and weaknesses but also uses a person’s character signature strengths to help them move forward. Appreciation for life, new possibilities, relating to others, personal strength, and spiritual change are the five domains of post-traumatic growth. Meaningmaking, instillation of hope, and self-compassion are identified as additional lifeenhancing responses to adversity. Two Narrative Case Studies are presented. The first one identifies how a student nurse felt unprepared to discuss spiritual issues with her patient. The second case study demonstrates how nurturing mindful self-compassion helps a teen to heal from childhood trauma. The following three learning activities are suggested, debating the value of positive emotions, understanding the 24 signature strengths of positive psychotherapy, and lessons learned from those who have experienced post-traumatic growth. The chapter ends by recommending specific gratitude-enhancing self-care strategies.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.163
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.003
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.028
GPT teacher head0.346
Teacher spread0.318 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations1
Published2024
Admission routes1
Has abstractyes

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