Evidence map›Paper›PMID 37880473›Full record

ArticleAdministration and policy in mental health2024

Leveraging Novel Technologies and Artificial Intelligence to Advance Practice-Oriented Research.

Dana Atzil-Slonim, Juan Martin Gomez Penedo, Wolfgang Lutz

Abstract read
PubMed Publisher
In one paragraph

Article in Administration and policy in mental health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Targeting mechanisms of change as a path to precision psychotherapy for community settings.Psychotherapy research : journal of the Society for Psychotherapy Research · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. 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

3 authors.

Dana Atzil-SlonimDepartment of Psychology, Bar-Ilan University, Ramat-Gan, Israel. dana.slonim@gmail.com.ORCID 0000-0001-6958-1200
Juan Martin Gomez PenedoDepartment of Psychology, University of Buenos Aires, Buenos Aires, Argentina.
Wolfgang LutzDepartment of Psychology, University of Trier, Trier, Germany.

Funding

Israel Science Foundation ISF #2466/21
6 · The paper itself

Abstract

Mental health services are experiencing notable transformations as innovative technologies and artificial intelligence (AI) are increasingly utilized in a growing number of studies and services.These cutting-edge technologies carry the promise of substantial improvements in the field of mental health. Nevertheless, questions emerge about the alignment of novel technologies and AI systems with human needs, especially in the context of vulnerable populations receiving mental healthcare. The practice-oriented research (POR) model is pivotal in seamlessly integrating these emerging technologies into clinical research and practice. It underscores the importance of tight collaboration between clinicians and researchers, all driven by the central goal of ensuring and elevating client well-being. This paper focuses on how novel technologies can enhance the POR model and highlights its pivotal role in integrating these technologies into clinical research and practice. We discuss two key phases: pre-treatment, and during treatment. For each phase, we describe the challenges, present the major technological innovations, describe recent studies exemplifying technology use, and suggest future directions. Ethical concerns and the importance of aligning humans and technology are also considered, in addition to implications for practice and training.

Indexed as

Artificial IntelligenceMental Health ServicesHumansArtificial intelligenceMachine learningPractice-oriented researchPsychotherapy research

Identifiers

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.