Evidence map›Paper›PMID 39279333›Full record

ArticleJournal of primary care & community health

Motivation and Use of Telehealth Among People with Depression in the United States.

Soumitra S Bhuyan, Saurabh Kalra, Asos Mahmood, Akasha Rai, Kahuwa Bordoloi, Urmi Basu, Elizabeth O'Callaghan, Marilyn Gardner

Abstract read
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Article in Journal of primary care & community health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

8 authors.

Soumitra S BhuyanThe State University of New Jersey, New Brunswick, NJ, USA.ORCID 0000-0002-7247-4438
Saurabh KalraThe State University of New Jersey, New Brunswick, NJ, USA.ORCID 0000-0002-0398-6384
Asos MahmoodUniversity of Tennessee Health Sciences Center, Memphis, TN, USA.ORCID 0000-0002-2680-9110
Akasha RaiThe State University of New Jersey, New Brunswick, NJ, USA.
Kahuwa BordoloiSt. Joseph's University, Bangalore, India.
Urmi BasuInsight Biopharma, Princeton, NJ, USA.
Elizabeth O'CallaghanRutgers University Behavioral Health Care, Piscataway, NJ, USA.
Marilyn GardnerUniversity of Wisconsin-Eau Claire, Eau Claire, WI, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe global mental health crisis, compounded by the challenges of the COVID-19 pandemic, underscores the urgent need for accessible mental health care solutions. Telehealth services have emerged as a promising technology to address barriers to access mental health services. However, population-based studies examining telehealth utilization among individuals with depression are limited.

methodsUsing data from the National Cancer Institute's Health Information National Trends Survey (HINTS) of 2022 (n = 4502), we investigated telehealth utilization among individuals diagnosed with depression in the United States. We employed multivariable logistic regression analysis to assess the association, adjusting for demographics, health behaviors, health status, trust in the medical system, and access to transportation. We also studied the factors that motivated the use of telehealth among individuals diagnosed with depression.

resultsIn the multivariable adjusted logistic regression models, individuals diagnosed with depression (AOR 2.59, 95% CI 1.96-3.42) were significantly more likely to use telehealth services relative to individuals with no depression diagnosis. Other factors associated with increased telehealth use included women (AOR 1.36, 95% CI 1.07-1.72), Hispanic ethnicity (AOR 1.78, 95% CI 1.28-2.48), being married or living with a partner (AOR 1.30, 95% CI 1.05-1.62), frequent healthcare visits (AOR 2.31, 95% CI 1.71-3.11), health insurance coverage (AOR 1.86, 95% CI 1.04-3.34), confidence in self-care (AOR 1.38, 95% CI 1.07-1.78), and lack of reliable transportation (AOR 1.57, 95% CI 1.01-2.42). Major motivation factors that influenced telehealth use among individuals with depression primarily included convenience, such as reduced travel times, as well as clinicians' recommendations.

conclusionTelehealth is a promising option for accessing mental health care, particularly for those with depression. Further research is needed to understand how well telehealth works and how it can be combined with traditional care, ensuring fair costs and keeping information safe.

Indexed as

COVID-19DepressionMotivationTelemedicineAdolescentAdultAgedFemaleHealth Services AccessibilityHumansLogistic ModelsMaleMiddle AgedPatient Acceptance of Health CareUnited StatesYoung Adultdepressionhealthcare accessmental healthtelehealth

Identifiers

PMID39279333
PMCPMC11409303

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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.