Evidence map›Paper›PMID 34805388›Full record

ArticlemHealth2021

"It depends:" a qualitative study on digital health academic-industry collaboration.

Kelsey L Ford, Jenn Leiferman, Bruno Sobral, John K Bennett, Susan L Moore, Sheana Bull

Abstract read
In one paragraph

Article in mHealth, 2021. 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. Article
  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

6 authors.

Kelsey L FordColorado School of Public Health, University of Colorado, Aurora, CO, USA.
Jenn LeifermanColorado School of Public Health, University of Colorado, Aurora, CO, USA.
Bruno SobralColorado School of Public Health, University of Colorado, Aurora, CO, USA.
John K BennettUniversity of Colorado Denver, Denver, CO, USA.
Susan L MooreColorado School of Public Health, University of Colorado, Aurora, CO, USA.
Sheana BullColorado School of Public Health, University of Colorado, Aurora, CO, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAcademic-industry collaborations (AICs) are endorsed to alleviate challenges in digital health, but partnership experiences remain understudied. The qualitative study's objective investigated collaboration experiences between academic institutions and digital health companies.

methodsA phenomenology methodology captured experiences of AICs, eliciting perspectives from academic researchers and industry affiliates (e.g., leadership, company investigators). Semi-structured interviews probed eligible collaborators about their experiences in digital health. Analysts coded and organized data into significant statements reaching thematic saturation.

resultsParticipants (N=20) were interviewed from 6 academic institutions and 14 unique industry partners. Seven themes emerged: (I) Collaboration evolves with time, relationships, funding, and evidence; (II) Collaboration demands strong relationships and interpersonal dynamics; (III) Operational processes vary across collaborations; (IV) Collaboration climate and context matters; (V) Shared expectations lead to a better understanding of success; (VI) Overcoming challenges with recommendations; (VII) Collaboration may help navigate the global pandemic.

conclusionsDigital health academic industry collaboration demands strong relationships, requiring flexible mechanisms of collaboration and cultural fit. Diverse models of collaboration exist and remain dependent on contextual factors. While no collaboration conquers all challenges in digital health, AICs may serve as a facilitator for improved digital health products, thus advancing science, promoting public health, and benefiting the economy.

Indexed as

academic-industry collaboration (AIC)digital healthmHealthPublic-private sector partnerships

Identifiers

PMID34805388
PMCPMC8572752

What OpenQuestion holds

Textmetadata
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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.