Evidence map›Paper›PMID 33642884›Full record

ReviewPsychology research and behavior management2021

To What Extent is Internet Activity Predictive of Psychological Well-Being?

Sonia Lippke, Alina Dahmen, Lingling Gao, Endi Guza, Claudio R Nigg

Abstract readReview
In one paragraph

Review in Psychology research and behavior management, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Use of social media in radiation oncology: multicenter data from the GOCO Group.Reports of practical oncology and radiotherapy : journal of Greatpoland Cancer Center in Poznan and Polish Society of Radiation Oncology · 2024
    Article
  8. Article
  9. Loneliness, health and applied psychology.Applied psychology. Health and well-being · 2023
    Article
  10. Impact of the COVID-19 Pandemic on CSR Activities of Healthcare Providers.International journal of environmental research and public health · 2022
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. 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

5 authors.

Sonia LippkeDepartment of Psychology & Methods/Focus Area Diversity, Jacobs University Bremen gGmbH, Bremen, 28759, Germany.ORCID 0000-0002-8272-0399
Alina DahmenDr. Becker Klinikgruppe, Cologne, 50968, Germany.
Lingling GaoDepartment of Psychology & Methods/Focus Area Diversity, Jacobs University Bremen gGmbH, Bremen, 28759, Germany.
Endi GuzaDepartment of Psychology & Methods/Focus Area Diversity, Jacobs University Bremen gGmbH, Bremen, 28759, Germany.
Claudio R NiggInstitute of Sport Science, University of Bern, Bern, 3012, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHealthy internet activity (eg, making use of eHealth and online therapy) is positively associated with well-being. However, unhealthy internet activity (too much online time, problematic internet use/PIU, internet dependency/ID, etc.) is associated with reduced well-being, loneliness, and other related negative aspects. While most of the evidence is correlational, some research also shows that internet activity can be predictive for well-being.

objectiveThe aim of this article is to elaborate on the question as to what extent internet activity is predictive of psychological well-being by means of (a) a scoping review and (b) theoretical understanding which model the interrelation of internet activity and psychological well-being. METHODOLOGY: We searched different electronic databases such as Web of Science by using the search terms "Internet" OR "App" OR "digital" OR "online" OR "mobile application" AND "Use" OR "Activity" OR "Behavior" OR "Engagement" AND "Well-being" OR "Loneliness" for (a, the scoping review) or CCAM for (b, the theoretical understanding).

resultsThe scoping review (a) summarizes recent findings: the extent to which internet activity is predictive for well-being depends on the internet activity itself: internet activity facilitating self-management is beneficial for well-being but too much internet activity, PIU and ID are detrimental to well-being. To understand (b) why, when and how internet activity is predictive for well-being, theoretical understanding and a model are required. While theories on either well-being or internet activity exist, not many theories take both aspects into account while also considering other behaviors. One such theory is the Compensatory Carry-Over Action Model (CCAM) which describes mechanisms on how internet use is related to other lifestyle behaviors and well-being, and that individuals are driven by the goal to adopt and maintain well-being - also called higher-level goals - in the CCAM. There are few studies testing the CCAM or selected aspects of it which include internet activity and well-being. Results demonstrate the potentials of such a multifactorial, sophisticated approach: it can help to improve health promotion in times of demographic change and in situations of lacking personnel resources in health care systems. CONCLUSION AND RECOMMENDATION: Suggestions for future research are to employ theoretical approaches like the CCAM and testing intervention effects, as well as supporting individuals in different settings. The main aim should be to perform healthy internet activities to support well-being, and to prevent unhealthy internet activity. Behavior management and learning should accordingly aim at preventing problematic internet use and internet dependency.

Indexed as

appCCAMcompensatory carry-over action modeleHealthmobile applicationsonline/digital behaviorsocial media

Identifiers

PMID33642884
PMCPMC7903968

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.