TARGETING SOCIALLY ISOLATED OLDER ADULTS: THE INTERNET-BASED CONVERSATIONAL ENGAGEMENT TRIAL (I-CONECT)
Bibliographic record
Abstract
Abstract Social isolation is a risk factor for dementia. In the recently completed randomized controlled trial named I-CONECT (www.i-conect.org; ClinicalTrials.gov: NCT02871921), we investigated the impact of frequent social interactions via webcam/internet on the cognitive function and emotional well-being, recruiting socially isolated older adults aged 75 and above. Participants in the experimental group engaged in semi-structured conversations with interviewers, prompted by daily themes and associated pictures, 4 times per week (30 minutes/session) for 6 months. The control group received only brief weekly phone check-ins. A total of 186 subjects (86 with normal cognition, 100 with mild cognitive impairment [MCI]) were randomized. We earlier reported that global cognitive function (the primary outcome), as measured by the Montreal Cognitive Assessment (MoCA), improved by nearly 2 points in the MCI experimental group compared to the control group at 6 months (effect size: Cohen’s d = 0.73) (Dodge et al., 2024, doi: 10.1093/geront/gnad147). Functional MRI data suggested a trend toward increased connectivity in the dorsal attention network favoring the experimental group. Social satisfaction improved in both groups. Our new results not reported in the topline results paper include: (1) Participants in the experimental group increased the frequency of their social interactions over time compared to the control group, and (2) Individual Treatment Response analysis showed that participants in the top 30% of responders could delay cognitive decline by 6 months or more. We will summarize all findings from this trial thus far and discuss future directions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".