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P-63 Prospective memory and antiretroviral medication adherence in HIV

2024· article· en· W4400454336 on OpenAlexaboutno aff
Valentina Massaroni, Valentina Delle Donne, Francesca Lombardi, Silvia Lamonica, G Lenzi, Damiano Farinacci, Alberto Borghetti, Arturo Ciccullo, Carlo Torti, Simona Di Giambenedetto

Bibliographic record

VenuePoster · 2024
Typearticle
Languageen
FieldPsychology
TopicCognitive Functions and Memory
Canadian institutionsnot available
Fundersnot available
KeywordsProspective memoryMedication adherenceHuman immunodeficiency virus (HIV)Antiretroviral therapyMedicineComputer scienceViral loadPsychiatryVirologyInternal medicineCognition

Abstract

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<h3>Background</h3> Prospective Memory (ProM) is a form of episodic memory. It enables ’remembering to remember’, planning and storing intentions for the future, then executing them later. It is essential for monitoring and executing behaviours based on internal or external cues in interfering contexts. It turns out to be an important feature for functional autonomy. ProM requires activation of the medial temporal lobe and prefrontal cortex. In particular, the prefrontal cortex is the neuroanatomical substrate of executive functions. Executive functions enable us to plan, implement, and conclude goal-oriented behaviours in everyday life. People living with HIV (PLWH) may have difficulty managing daily activities. The purpose of this study was to evaluate how ProM outcomes affect the management of medical aspects in PLWH such as adherence to antiretroviral therapy (ART). <h3>Material and Methods</h3> This study assessed ProM ability in a sample of 70 PLWH with the use of the Memory for Intentions Screening Test (MIST). Cognitive domains were screened through the Montreal Cognitive Assessment (MoCA) and self-reported therapeutic adherence in the past month was collected. Exclusion criteria were age &lt;18 years and difficulties with the Italian language. <h3>Results</h3> Many of PLWH were male (91.4%, n=64), aged 46 to 55 (37.1%, n=26), with upper secondary school degree (58.6%, n=41). Most of the PLWH (68.6%, n=48) were &gt;10 years ago diagnosed with HIV and 55.7% (n=39) of them received &gt;10 years ago for the first time ART. On a scale of 1 to 10, patient-reported adherence was 7.83 (SD 1.58). The mean obtained in MoCA was 26.51 (SD 2.90). The mean obtained in MIST was 35.27 (SD 11.35). PLWH with age &gt;55 years, low education, in disease and on therapy for 1–5 years reported poor performance in ProM (p=0.023; p=0.058; p=&lt;0.001; p=&lt;0.001, respectively). A high MIST score was positively associated with high adherence to self-reported therapy (β 6.24; 95% CI 5.40/7.08; p=&lt;0.001). There was a positive correlation between MIST and MOCA (r=.286; p=0.016). The mean of the errors emerged in the MIST was 3.04 (SD 2.42). PLWH who make fewer errors reported higher adherence (p=&lt;0.001). <h3>Conclusions</h3> In conclusion, our results emphasized that ProM performance correlates with maintenance of therapeutic adherence and cognitive functioning in the normal range. Increasing age, decreasing educational attainment, and shorter time since diagnosis and shorter time on therapy seem to be factors related to lower performance in ProM. An analysis of ProM may bring out difficulties that impact with the medical management of PLWH health status. Last, assessment of ProM results should be considered in the clinical assessment of PLWH.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.020
GPT teacher head0.311
Teacher spread0.292 · 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 designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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