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Record W2753080726 · doi:10.2196/jmir.7487

Web-Based Mindfulness Interventions for People With Physical Health Conditions: Systematic Review

2017· review· en· W2753080726 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Medical Internet Research · 2017
Typereview
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsSouth Health CampusAlberta Health ServicesUniversity of Calgary
FundersAlberta Cancer Foundation
KeywordsPsychological interventionMindfulnessWeb applicationSystematic reviewPsychologyMedicineMEDLINEWorld Wide WebComputer sciencePsychotherapistPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Mindfulness-based interventions (MBIs) are becoming increasingly popular for helping people with physical health conditions. Expanding from traditional face-to-face program delivery, there is growing interest in Web-based application of MBIs, though Web-based MBIs for people with physical health conditions specifically have not been thoroughly reviewed to date. OBJECTIVE: The objective of this paper was to review Web-based MBIs for people with physical health conditions and to examine all outcomes reported (eg, efficacy or effectiveness for physical changes or psychological changes; feasibility). METHODS: Databases PubMed, PsycINFO, Science Direct, CINAHL Plus, and Web of Science were searched. Full-text English papers that described any Web-based MBI, examining any outcome, for people with chronic physical health conditions were included. Randomized, nonrandomized, controlled, and uncontrolled trials were all included. Extracted data included intervention characteristics, population characteristics, outcomes, and quality indicators. Intervention characteristics (eg, synchronicity and guidance) were examined as potential factors related to study outcomes. RESULTS: Of 435 publications screened, 19 published papers describing 16 studies were included. They examined Web-based MBIs for people with cancer, chronic pain or fibromyalgia, irritable bowel syndrome (IBS), epilepsy, heart disease, tinnitus, and acquired brain injury. Overall, most studies reported positive effects of Web-based MBIs compared with usual care on a variety of outcomes including pain acceptance, coping measures, and depressive symptoms. There were mixed results regarding the effectiveness of Web-based MBIs compared with active control treatment conditions such as cognitive behavioral therapy. Condition-specific symptoms (eg, cancer-related fatigue and IBS symptoms) targeted by treatment had the largest effect size improvements following MBIs. Results are inconclusive regarding physical variables. CONCLUSIONS: Preliminary evidence suggests that Web-based MBIs may be helpful in alleviating symptom burden that those with physical health conditions can experience, particularly when interventions are tailored for specific symptoms. There was no evidence of differences between synchronous versus asynchronous or facilitated versus self-directed Web-based MBIs. Future investigations of Web-based MBIs should evaluate the effects of program adherence, effects on mindfulness levels, and whether synchronous or asynchronous, or facilitated or self-directed interventions elicit greater improvements.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.093
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0060.004
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0030.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0150.000

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 head0.291
GPT teacher head0.582
Teacher spread0.291 · 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