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Efficacy of an Internet-Based Behavioral Intervention for Adults With Insomnia

2009· article· en· W2126133436 on OpenAlexaff
Lee M. Ritterband, Frances P. Thorndike, Linda Gonder‐Frederick, Joshua C. Magee, Elaine T. Bailey, Drew K. Saylor, Charles M. Morin

Bibliographic record

VenueArchives of General Psychiatry · 2009
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsUniversité Laval
FundersNational Institute of Mental Health
KeywordsInsomniaSleep hygieneCognitive behavioral therapy for insomniaSleep restrictionCognitive behavioral therapyMedicinePhysical therapySleep onsetCognitionPsychologyPsychiatryClinical psychologySleep deprivation

Abstract

fetched live from OpenAlex

CONTEXT: Insomnia is a major health problem with significant psychological, health, and economic consequences. However, availability of one of the most effective insomnia treatments, cognitive behavioral therapy, is significantly limited. The Internet may be a key conduit for delivering this intervention. OBJECTIVE: To evaluate the efficacy of a structured behavioral Internet intervention for adults with insomnia. DESIGN, SETTING, AND PARTICIPANTS: Forty-five adults were randomly assigned to an Internet intervention (n = 22) or wait-list control group (n = 23). Forty-four eligible participants (mean [SD] age, 44.86 [11.03] years; 34 women) who had a history of sleep difficulties longer than 10 years on average (mean [SD], 10.59 [8.89] years) were included in the analyses. INTERVENTION: The Internet intervention is based on well-established face-to-face cognitive behavioral therapy incorporating the primary components of sleep restriction, stimulus control, sleep hygiene, cognitive restructuring, and relapse prevention. MAIN OUTCOME MEASURES: The Insomnia Severity Index and daily sleep diary data were used to determine changes in insomnia severity and the main sleep variables, including wake after sleep onset and sleep efficiency. RESULTS: Intention-to-treat analyses showed that scores on the Insomnia Severity Index significantly improved from 15.73 (95% confidence interval [CI], 14.07 to 17.39) to 6.59 (95% CI, 4.73 to 8.45) for the Internet group but did not change for the control group (16.27 [95% CI, 14.61 to 17.94] to 15.50 [95% CI, 13.64 to 17.36]) (F(1,42) = 29.64; P < .001). The Internet group maintained their gains at the 6-month follow-up. Internet participants also achieved significant decreases in wake after sleep onset (55% [95% CI, 34% to 76%]) and increases in sleep efficiency (16% [95% CI, 9% to 22%]) compared with the nonsignificant control group changes of wake after sleep onset (8% [95% CI, -17% to 33%) and sleep efficiency (3%; 95% CI, -4% to 9%). CONCLUSIONS: Participants who received the Internet intervention for insomnia significantly improved their sleep, whereas the control group did not have a significant change. The Internet appears to have considerable potential in delivering a structured behavioral program for insomnia. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT00328250.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.010
GPT teacher head0.305
Teacher spread0.295 · 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 designRandomized trial
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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Citations488
Published2009
Admission routes1
Has abstractyes

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