Strength-Based Psychotherapeutic Approaches for Relational Trauma: A Scoping Review
Bibliographic record
Abstract
Background: Psychology is increasingly adopting strength-based approaches through philosophy, research, and practice. The field recognises the need to adapt psychotherapeutic approaches for various contexts and populations; however, a universal agreed theoretical framework of strength-based psychotherapeutic approaches for relational trauma is yet to be determined. Objective: The present study undertakes a scoping review of literature to explore what is known about strength-based psychotherapeutic approaches for relational trauma and maps the findings. The review examines data from the selected literature to clarify conceptual boundaries of both relational trauma and strength-based psychotherapeutic approaches. It investigates what constitutes a strength-based psychotherapeutic approach, the kinds of relational trauma studied, the types of approaches used in the treatment of relational trauma, and the contexts in which strength-based psychotherapeutic approaches are applied. Design: A scoping review protocol were followed to identify, find, select, chart, and collate data from relevant literature. Four online databases were searched to identify literature published between 2000-2022, from which 22 publications were selected. The selected articles examined strength-based psychotherapeutic approaches for relational trauma with adult participants aged 18 or older and were from United Kingdom, the United States, Italy, Norway, Taiwan, Canada, Israel, Tanzania, Greece, Poland, Slovenia, and Australia. Results: Four key themes and 12 sub-themes were generated through reflexive thematic analysis. The key themes are healing relationships, trauma-informed, transtheoretical relevance, and balancing symptoms with wellbeing. Conclusions: While the quality or rigor of the studies were not examined, the findings informed six key conclusions: 1) there is paucity of research on the research topic, 2) evidence from the limited research was promising but not proven and future research might prioritise scientific rigor for clinical recommendations, 3) healing relationships span across relational layers relevant to the therapeutic context, 4) the research topic is transtheoretical and strengthening interdisciplinary terminology would be advantageous, 5) trauma-informed practices that include cultural competence and contextual adaptations are fundamental, and 6) a strengths-approach is a balanced approach that focuses both on symptom reduction as well as enhancing wellbeing
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".