Evidence map›Paper›PMID 30135826›Full record

ReviewInternet interventions2017

Effective use of technology in clinical supervision.

Priya Martin, Saravana Kumar, Lucylynn Lizarondo

Abstract readReview
In one paragraph

Review in Internet interventions, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Virtual supervision in ophthalmology: a scoping review.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2023
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. 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.

Priya MartinAllied Health, Cunningham Centre, Darling Downs Hospital and Health Service, Toowoomba, Queensland 4350, Australia.
Saravana KumarSchool of Health Sciences, Sansom Institute for Health Research, University of South Australia, Adelaide, South Australia 5001, Australia.
Lucylynn LizarondoJoanna Briggs Institute, University of Adelaide, Adelaide, South Australia 5001, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clinical supervision is integral to continuing professional development of health professionals. With advances in technology, clinical supervision too can be undertaken using mediums such as videoconference, email and teleconference. This mode of clinical supervision is termed as telesupervision. While telesupervision could be useful in any context, its value is amplified for health professionals working in rural and remote areas where access to supervisors within the local work environment is often diminished. While telesupervision offers innovative means to undertake clinical supervision, there remain gaps in the literature in terms of its parameters of use in clinical practice. This article outlines ten evidence-informed, practical tips stemming from a review of the literature that will enable health care stakeholders to use technology effectively and efficiently while undertaking clinical supervision. By highlighting the "how to" aspect, telesupervision can be delivered in the right way, to the right health professional, at the right time.

Indexed as

Clinical supervisionContinuing professional developmentTelesupervisionWorkforce development/issues

Identifiers

PMID30135826
PMCPMC6096199

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.