Evidence map›Paper›PMID 34707881›Full record

ArticleHealth psychology open

Adverse childhood experiences predict reaction to multiple sclerosis diagnosis.

Tehila Eilam-Stock, Jon Links, Nabil Z Khan, Tamar E Bacon, Guadalupe Zuniga, Lisa Laing, Carrie Sammarco, Kathleen Sherman, Leigh Charvet

Abstract read
In one paragraph

Article in Health psychology open. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 2 pooled it
–field-weighted citation impact
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

7 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Tehila Eilam-StockNYU Grossman School of Medicine, New York, NY, USA.
Jon LinksNYU Grossman School of Medicine, New York, NY, USA.
Nabil Z KhanSUNY Downstate School of Medicine, New York, NY, USA.
Tamar E BaconNYU Grossman School of Medicine, New York, NY, USA.
Guadalupe ZunigaNYU Grossman School of Medicine, New York, NY, USA.
Lisa LaingNYU Grossman School of Medicine, New York, NY, USA.
Carrie SammarcoNYU Grossman School of Medicine, New York, NY, USA.
Kathleen ShermanNYU Grossman School of Medicine, New York, NY, USA.
Leigh CharvetNYU Grossman School of Medicine, New York, NY, USA.ORCID https://orcid.org/0000-0003-4429-9713

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveAt the time of multiple sclerosis (MS) diagnosis, identifying those at risk for poorer health-related quality of life and emotional well-being can be a critical consideration for treatment planning. This study aimed to test whether adverse childhood experiences predict MS patients' health-related quality of life and emotional functioning at time of diagnosis and initial course of disease.

methodsWe recruited patients at the time of new MS diagnosis to complete self-report surveys at baseline and a one-year follow-up. Questionnaires included the Adverse Childhood Experiences (ACEs), as well as the MS Knowledge Questionnaire (MSKQ), the 36-Item Short Form Health Survey (SF-36), and Self-Management Screening (SeMaS).

resultsA total of

conclusionsChildhood adversity predicts health-related quality of life and emotional well-being at time of MS diagnosis and over the initial course of the disease. Measured using a brief screening inventory (ACEs), routine administration may be useful for identifying patients in need of increased supportive services.

Indexed as

anxietychronic illnesscopingdepressiondiagnosisQoLrisktraumawell-being

Identifiers

PMID34707881
PMCPMC8543585

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.