Evidence map›Paper›PMID 41595284›Full record

ReviewHealthcare (Basel, Switzerland)2026

Digital Approaches to Pain Assessment Across Older Adults: A Scoping Review.

Leanne McGaffin, Gary Mitchell, Tara Anderson, Arnelle Gillis, Stephanie Craig

Abstract readReview
In one paragraph

Review in Healthcare (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

3 citing papers in PubMed.

  1. Review
  2. The Need for Continued Investment in Digital Pain Assessment.Journal of medical Internet research · 2026
    Article
  3. 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

5 authors.

Leanne McGaffinSchool of Nursing and Midwifery, Queen's University Belfast, Belfast BT9 7BL, UK.ORCID 0009-0002-6401-4076
Gary MitchellSchool of Nursing and Midwifery, Queen's University Belfast, Belfast BT9 7BL, UK.ORCID 0000-0003-2133-2998
Tara AndersonSchool of Nursing and Midwifery, Queen's University Belfast, Belfast BT9 7BL, UK.ORCID 0009-0005-3611-3431
Arnelle GillisSchool of Nursing and Midwifery, Queen's University Belfast, Belfast BT9 7BL, UK.ORCID 0009-0001-6512-1212
Stephanie CraigSchool of Nursing and Midwifery, Queen's University Belfast, Belfast BT9 7BL, UK.ORCID 0000-0003-0783-4975

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEffectively managing pain in adults remains challenging, particularly in individuals with cognitive impairment or communication difficulties. Digital technologies, including artificial intelligence (AI)-enabled facial recognition and mobile applications, are emerging as innovative tools to improve the objectivity and consistency of pain evaluation. This scoping review aimed to map the current evidence on digital pain-assessment tools used with adult and older populations, focusing on validity, reliability, usability, and contributions to person-centred care.

methodsThe review followed the Joanna Briggs Institute methodology and Arksey and O'Malley framework and was reported in accordance with PRISMA-ScR guidelines. Systematic searches were conducted in PubMed, CINAHL Complete, Medline (ALL), and PsycINFO for English-language studies published from 2010 onwards. Eligible studies included adults (≥18 years) using digital tools for pain assessment. Data extraction and synthesis were performed using Covidence, and findings were analyzed thematically.

resultsOf 1160 records screened, ten studies met inclusion criteria. Most research was quantitative and conducted in high-income clinical settings. Five tools were identified: ePAT/PainChek

conclusionsEmerging evidence suggests that facial-recognition-based digital pain-assessment tools may demonstrate acceptable psychometric performance and usability within dementia care settings in high-income countries. However, evidence relating to broader adult populations, diverse care contexts, and low-resource settings remains limited, highlighting important gaps for future research.

Indexed as

dementiadigital pain assessmentePATfacial recognitionnursingolder adultsPainChekscoping review

Identifiers

PMID41595284
PMCPMC12841086

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.