Evidence map›Paper›PMID 35536347›Full record

Trial reportJournal of medical systems2022

Within Clinic Reliability and Usability of a Voice-Based Amazon Alexa Administration of the Patient Health Questionnaire 9 (PHQ 9).

Jason Beaman, Luke Lawson, Ashley Keener, Michael L Mathews

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Journal of medical systems, 2022. 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. 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

4 authors.

Jason BeamanCenter for Health Sciences, Oklahoma State University, Tulsa, USA.
Luke LawsonCenter for Health Sciences, Oklahoma State University, Tulsa, USA. luke.lawson@okstate.edu.ORCID http://orcid.org/0000-0003-0442-2617
Ashley KeenerCenter for Health Sciences, Oklahoma State University, Tulsa, USA.
Michael L MathewsOral Roberts University, Tulsa, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over the last two decades, metric-based instruments have garnered popularity in mental health. Self-administered surveys, such as the Patient Health Questionnaire 9 (PHQ 9), have been leveraged to inform treatment practice of Major Depressive Disorder (MDD). The aim of this study was to measure the reliability and usability of a novel voice-based delivery system of the PHQ 9 using Amazon Alexa within a patient population. Forty-one newly admitted patients to a behavioral medicine clinic completed the PHQ 9 at two separate time points (first appointment and one-month follow up). Patients were randomly assigned to a version (voice vs paper) completing the alternate format at the next appointment. Patients additionally completed a 26-item User Experience Questionnaire (UEQ) and open-ended questionnaire at each session. Assessments between PHQ 9 total scores for the Alexa and paper version showed a high degree of reliability (α = .86). Quantitative UEQ results showed significantly higher overall positive attitudes towards the Alexa format with higher subscale scores on attractiveness, stimulation, and novelty. Further qualitative responses supported these findings with 85.7% of participants indicating a willingness to use the device at home. With the benefit of user instruction in a clinical environment, the novel Alexa delivery system was shown to be consistent with the paper version giving evidence of reliability between the two formats. User experience assessments further showed a preference for the novel version over the traditional format. It is our hope that future studies may examine the efficacy of the Alexa format in improving the at-home clinical treatment of depression.

Indexed as

Major Depressive DisorderPatient Health QuestionnaireHumansPsychometricsReproducibility of ResultsSurveys and QuestionnairesAmazon AlexaDepressive disorder, majorIoTMental healthPatient health questionnaireVoice recognition

Identifiers

PMID35536347
PMCPMC9086138

What Socratic 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 Socratic graph.