Evidence map›Paper›PMID 34914841›Full record

ArticleJournal of clinical psychology2022

Using interpersonal reconstructive therapy to address comorbid problems organized by attachment-based learning: The case of Don.

Kenneth L Critchfield, Priyata Thapa, Mariafé T Panizo, Nuno Conceição

Abstract readCase Reports
PubMed Publisher
In one paragraph

Article in Journal of clinical psychology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.9field-weighted citation impact, top 22% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 7 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 4 institutions in 2 countries.

Kenneth L CritchfieldFerkauf Graduate School of Psychology, Yeshiva University, New York City, New York, USA.ORCID 0000-0002-6797-1763
Priyata ThapaDepartment of Graduate Psychology, James Madison University, Harrisonburg, Virginia, USA.ORCID 0000-0001-8754-6126
Mariafé T PanizoStudent Health and Counseling Services, California State University, Sacramento, California, USA.
Nuno ConceiçãoResearch Center for Psychological Science (CICPSI), Faculdade de Psicologia, Universidade de Lisboa, Lisbon, Portugal.ORCID 0000-0001-8038-5841
California Department of Health Care Services · USJames Madison University · USUniversity of Lisbon · PTYeshiva University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Feature heterogeneity and diagnostic overlap occur regularly among patients in clinical settings. In interpersonal reconstructive therapy (IRT), a case formulation focused on patterns learned in close attachment relationships guides intervention choices. This study illustrates how IRT formulation and treatment proceed, and how it may also fail when there is not close adherence to underlying principles. Don is a music professor in his 40's with a significant trauma history and complex diagnostic profile that includes many hospitalizations and suicide attempts. He qualified for several diagnostic and statistical manual of mental disorders personality disorders via formal diagnostic interviews (obsessive-compulsive, avoidant, passive-aggressive, narcissistic), as well as major depression, generalized anxiety, and substance abuse. Don's formulation demonstrates how self-destruction can function as a "gift of love" to internalized representations of important caregivers. Data from work with patients like Don confirm the usefulness of Benjamin's IRT lens for navigating comorbidity, as well as the importance of underlying principles of change.

Indexed as

Major Depressive DisorderPersonality DisordersAdultComorbidityDiagnostic and Statistical Manual of Mental DisordersHumansMaleSuicide, AttemptedattachmentinterpersonalmechanismsSASB

Identifiers

PMID34914841
OpenAlexW4200230573

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.