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Record W4210792459 · doi:10.31083/j.jin2101028

Digital dementia in the internet generation: excessive screen time during brain development will increase the risk of Alzheimer's disease and related dementias in adulthood

2022· review· en· W4210792459 on OpenAlexaff
Laurie Manwell, Merelle Tadros, Tiana M. Ciccarelli, Roelof Eikelboom

Bibliographic record

VenueJournal of Integrative Neuroscience · 2022
Typereview
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsDementiaPsychologyDiseaseCognitionAmnesiaCognitive declineNeuroscienceAudiologyMedicinePsychiatryInternal medicine

Abstract

fetched live from OpenAlex

Converging evidence from biopsychosocial research in humans and animals demonstrates that chronic sensory stimulation (via excessive screen exposure) affects brain development increasing the risk of cognitive, emotional, and behavioural disorders in adolescents and young adults. Emerging evidence suggests that some of these effects are similar to those seen in adults with symptoms of mild cognitive impairment (MCI) in the early stages of dementia, including impaired concentration, orientation, acquisition of recent memories (anterograde amnesia), recall of past memories (retrograde amnesia), social functioning, and self-care. Excessive screen time is known to alter gray matter and white volumes in the brain, increase the risk of mental disorders, and impair acquisition of memories and learning which are known risk factors for dementia. Chronic sensory overstimulation (i.e., excessive screen time) during brain development increases the risk of accelerated neurodegeneration in adulthood (i.e., amnesia, early onset dementia). This relationship is affected by several mediating/moderating factors (e.g., IQ decline, learning impairments and mental illness). We hypothesize that excessive screen exposure during critical periods of development in Generation Z will lead to mild cognitive impairments in early to middle adulthood resulting in substantially increased rates of early onset dementia in later adulthood. We predict that from 2060 to 2100, the rates of Alzheimer's disease and related dementias (ADRD) will increase significantly, far above the Centres for Disease Control (CDC) projected estimates of a two-fold increase, to upwards of a four-to-six-fold increase. The CDC estimates are based entirely on factors related to the age, sex, race and ethnicity of individuals born before 1950 who did not have access to mobile digital technology during critical periods of brain development. Compared to previous generations, the average 17-19-year-old spends approximately 6 hours a day on mobile digital devices (MDD) (smartphones, tablets, and laptop computers) whereas individuals born before 1950 at the same age spent zero. Our estimates include the documented effects of excessive screen time on individuals born after 1980, Millennials and Generation Z, who will be the majority of individuals ≥65 years old. An estimated 4-to-6-fold increase in rates of ADRD post-2060 will result in widespread societal and economic distress and the complete collapse of already overburdened healthcare systems in developed countries. Preventative measures must be set in place immediately including investments and interventions in public education, social policy, laws, and healthcare.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.305
Teacher spread0.275 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations107
Published2022
Admission routes1
Has abstractyes

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