Systematic Review of Qualitative and Quantitative Studies on Attitudes and Barriers to Percutaneous Endoscopic Gastrostomy Feeding
Bibliographic record
Abstract
Percutaneous endoscopic gastrostomy (PEG) is now widely used for long-term enteral feeding in long-term care and community settings. However, regional variations exist in the acceptability of PEG tube feeding with long-term nasogastric feeding still commonplace in many Asian nations.To evaluate the evidence relating to attitudes towards PEG feeding and to determine potential barriers to the acceptance of PEG tube feeding.We searched Ovid MEDLINE, EMBASE, the Cochrane Library, Web of Science and CINAHL databases using the terms “PEG”, “percutaneous endoscopic gastrostomy”, “enteral feeding”, “attitude”, “perception” and “opinion”. We included qualitative and quantitative studies which quality of studies was assessed with the Alberta checklists.From 981 articles, 17 articles were included in the final analysis. Twelve qualitative and four quantitative studies were considered of good quality except for one quantitative study which was considered of moderate quality. Seven of the 14 studies reported positive attitudes towards PEG. Factors influencing the choice of PEG feeding included financial problems, lack of information given to patients and carers, lack of competency and skills, and knowledge among healthcare professionals (HCPs). In terms of barriers, three major themes were identified: lack of choice, confronting mortality and weighing alternatives.Only half of our articles reported positive perceptions towards PEG feeding. Acceptance of PEG feeding is influenced by financial factors, knowledge of HCPs and client involvement in decision-making. The themes identified in our systematic review will guide the development of interventions to alter the current attitudes and barriers towards PEG tube feeding.
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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 | 0.081 | 0.235 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.006 |
| Bibliometrics | 0.019 | 0.024 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".