Evidence map›Paper›PMID 30558610›Full record

ArticleBiomedical engineering online2018

Review of cognitive behavioural therapy mobile apps using a reference architecture embedded in the patient-provider relationship.

Alice Lan, Alexandra Lee, Kristin Munroe, Cameron McRae, Linda Kaleis, Karim Keshavjee, Aziz Guergachi

Abstract read
In one paragraph

Article in Biomedical engineering online, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. NoFumo+: A Clinical Trial of an mHealth for Smoking Cessation with Hospitalized Patients.International journal of environmental research and public health · 2021
    Trial
  4. Patient and therapist experiences of using a smartphone application monitoring anxiety symptoms.International journal of qualitative studies on health and well-being · 2022
    Article
  5. Review
  6. Article
  7. 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

7 authors.

Alice LanUniversity of Toronto, Health Sciences Bldg, 155 College St, 4th Floor, Toronto, ON, M5T 1P8, Canada.
Alexandra LeeUniversity of Toronto, Health Sciences Bldg, 155 College St, 4th Floor, Toronto, ON, M5T 1P8, Canada.
Kristin MunroeUniversity of Toronto, Health Sciences Bldg, 155 College St, 4th Floor, Toronto, ON, M5T 1P8, Canada.
Cameron McRaeUniversity of Toronto, Health Sciences Bldg, 155 College St, 4th Floor, Toronto, ON, M5T 1P8, Canada.
Linda KaleisUniversity of Toronto, Health Sciences Bldg, 155 College St, 4th Floor, Toronto, ON, M5T 1P8, Canada.
Karim KeshavjeeUniversity of Toronto, Health Sciences Bldg, 155 College St, 4th Floor, Toronto, ON, M5T 1P8, Canada. karim@infoclin.ca.ORCID http://orcid.org/0000-0003-1317-7035
Aziz GuergachiRyerson University, 350 Victoria Street, Toronto, ON, M5B 2K3, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMobile health apps (mHealth apps) are increasing in popularity and utility for the management of many chronic diseases. Although the current reimbursement structure for mHealth apps is lagging behind the rapidly improving functionality, more clinicians will begin to recommend these apps as they prove their clinical worth. Payors such as the government or private insurance companies will start to reimburse for the use of these technologies, especially if they add value to patients by providing timely support, a more streamlined patient experience, and greater patient convenience. Payors are likely to see benefits for providers, as these apps could help increase productivity between in-office encounters without having to resort to expensive in-person visits when patients are having trouble managing their disease. KEY

findingsTo guide and perhaps speed up adoption of mHealth apps by patients and providers, analysis and evaluation of existing apps needs to be carried out and more feedback must be provided to app developers. In this paper, an evaluation of 35 mHealth apps claiming to provide cognitive behavioural therapy was conducted to assess the quality of the patient-provider relationship and evidence-based practices embedded in these apps. The mean score across the apps was 4.9 out of 20 functional criteria all of which were identified as important to the patient-provider relationship. The median score was 5 out of these 20 functional criteria.

conclusionOverall, the apps reviewed were mostly stand-alone apps that do not enhance the patient-provider relationship, improve patient accountability or help providers support patients more effectively between visits. Large improvements in patient experience and provider productivity can be made through enhanced integration of mHealth apps into the healthcare system.

Indexed as

Cognitive Behavioral TherapyMobile ApplicationsPhysician-Patient RelationsTelemedicineAnxietyDepressionHumansQuality ControlCognitive behavioural therapyMental healthmHealthMobile appVirtual care

Identifiers

PMID30558610
PMCPMC6296144

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.