Evidence map›Paper›PMID 33372897›Full record

ArticleJMIR mental health2020

The Digital Therapeutic Alliance and Human-Computer Interaction.

Simon D'Alfonso, Reeva Lederman, Sandra Bucci, Katherine Berry

Open access · goldAbstract read
In one paragraph

Article in JMIR mental health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed
4.6field-weighted citation impact, top 5% 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

40 citing papers in PubMed, 84 citations in OpenAlex.

  1. Trial
  2. Trial
  3. Trial
  4. Trial
  5. Trial
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

4 authors at 2 institutions in 2 countries.

Simon D'AlfonsoSchool of Computing and Information Systems, University of Melbourne, Parkville, Australia.ORCID https://orcid.org/0000-0001-7407-8730
Reeva LedermanSchool of Computing and Information Systems, University of Melbourne, Parkville, Australia.ORCID https://orcid.org/0000-0003-4005-329X
Sandra BucciDivision of Psychology and Mental Health, School of Health Sciences, University of Manchester, Manchester, United Kingdom.ORCID https://orcid.org/0000-0002-6197-5333
Katherine BerryDivision of Psychology and Mental Health, School of Health Sciences, University of Manchester, Manchester, United Kingdom.ORCID https://orcid.org/0000-0002-7399-5462
Manchester Academic Health Science Centre · GBThe University of Melbourne · AU

Funding

Medical Research Council MR/P026664/1
6 · The paper itself

Abstract

The therapeutic alliance (TA), the relationship that develops between a therapist and a client/patient, is a critical factor in the outcome of psychological therapy. As mental health care is increasingly adopting digital technologies and offering therapeutic interventions that may not involve human therapists, the notion of a TA in digital mental health care requires exploration. To date, there has been some incipient work on developing measures to assess the conceptualization of a digital TA for mental health apps. However, the few measures that have been proposed have more or less been derivatives of measures from psychology used to assess the TA in traditional face-to-face therapy. This conceptual paper explores one such instrument that has been proposed in the literature, the Mobile Agnew Relationship Measure, and examines it through a human-computer interaction (HCI) lens. Through this process, we show how theories from HCI can play a role in shaping or generating a more suitable, purpose-built measure of the digital therapeutic alliance (DTA), and we contribute suggestions on how HCI methods and knowledge can be used to foster the DTA in mental health apps.

Indexed as

affective computingdigital mental healthmHealthmobile phonepersuasive computingpositive computingtherapeutic alliance

Identifiers

PMID33372897
PMCPMC7803473
OpenAlexW3113891030

What OpenQuestion 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 OpenQuestion graph.