Evidence map›Paper›PMID 33059955›Full record

ArticleThe International journal on drug policy2021

Enacting 'more-than-human' care: Clients' and counsellors' views on the multiple affordances of chatbots in alcohol and other drug counselling.

Anthony Barnett, Michael Savic, Kiran Pienaar, Adrian Carter, Narelle Warren, Emma Sandral, Victoria Manning, Dan I Lubman

Open access · greenAbstract read
In one paragraph

Article in The International journal on drug policy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 3 pooled it
3.2field-weighted citation impact, top 8% 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

17 citing papers in PubMed, 3 syntheses or guidelines pooled it, 47 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Article
  5. Review
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
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

8 authors at 4 institutions in 1 country.

Anthony BarnettMonash Addiction Research Centre, Eastern Health Clinical School, Monash University, VIC and Turning Point, Eastern Health, Richmond, VIC, Australia. Electronic address: anthony.barnett@monash.edu.
Michael SavicMonash Addiction Research Centre, Eastern Health Clinical School, Monash University, VIC and Turning Point, Eastern Health, Richmond, VIC, Australia.
Kiran PienaarSchool of Humanities and Social Sciences, Deakin University, Melbourne, VIC, Australia; and School of Social Sciences, Monash University, Melbourne, VIC, Australia.
Adrian CarterSchool of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia and University of Queensland Centre of Clinical Research, University of Queensland, Brisbane, QLD, Australia.
Narelle WarrenSchool of Social Sciences, Faculty of Arts, Monash University, Melbourne, VIC, Australia.
Emma SandralMonash Addiction Research Centre, Eastern Health Clinical School, Monash University, VIC and Turning Point, Eastern Health, Richmond, VIC, Australia.
Victoria ManningMonash Addiction Research Centre, Eastern Health Clinical School, Monash University, VIC and Turning Point, Eastern Health, Richmond, VIC, Australia.
Dan I LubmanMonash Addiction Research Centre, Eastern Health Clinical School, Monash University, VIC and Turning Point, Eastern Health, Richmond, VIC, Australia.
Eastern Health · AUDeakin University · AUMonash University · AUUniversity of Queensland · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Forms of artificial intelligence (AI), such as chatbots that provide automated online counselling, promise to revolutionise alcohol and other drug treatment. Although the replacement of human counsellors remains a speculative prospect, chatbots for 'narrow AI' tasks (e.g., assessment and referral) are increasingly being used to augment clinical practice. Little research has addressed the possibilities for care that chatbots may generate in the future, particularly in the context of alcohol and other drug counselling. To explore these issues, we draw on the concept of technological 'affordances' and identify the range of possibilities for care that emerging chatbot interventions may afford and foreclose depending on the contexts in which they are implemented. Our analysis is based on qualitative data from interviews with clients (n=20) and focus group discussions with counsellors (n=8) conducted as part of a larger study of an Australian online alcohol and other drug counselling service. Both clients and counsellors expressed a concern that chatbot interventions lacked a 'human' element, which they valued in empathic care encounters. Most clients reported that they would share less information with a chatbot than a human counsellor, and they viewed this as constraining care. However, clients and counsellors suggested that the use of narrow AI might afford possibilities for performing discrete tasks, such as screening, triage or referral. In the context of what we refer to as 'more-than-human' care, our findings reveal complex views about the types of affordances that chatbots may produce and foreclose in online care encounters. We conclude by discussing implications for the potential 'addiction futures' and care trajectories that AI technologies offer, focussing on how they might inform alcohol and other drug policy, and the design of digital healthcare.

Indexed as

CounselorsPharmaceutical PreparationsArtificial IntelligenceAustraliaCounselingHumansPharmaceutical PreparationsAddictionAffordancesArtificial intelligenceAustraliaChatbotsOnline care

Identifiers

PMID33059955
PMCPMC7550115
OpenAlexW3092841162

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.