Psychometric properties of Hope Scales: A systematic review
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.
Bibliographic record
Abstract
INTRODUCTION: Hope is recognised as an important factor in health, illness, and well-being. Many scales to measure hope have been developed and used in various disciplines, yet, their psychometric properties have not been systematically reviewed. AIM: To systematically review the psychometric properties of hope scales. DESIGN: Systematic review. METHODS: Four electronic databases were searched followed by a hand search. The data were extracted and qualitatively evaluated by the COSMIN checklist, an instrument designed as a quality rating tool for systematic reviews of psychometric properties. RESULTS: From 1271 retrieved abstracts, 68 papers met the inclusion criteria. The most used scale was the Snyder Hope Scale (46%) followed by the Herth Hope Index (16%). All other scales (n = 16) were evaluated in less than 10% of the papers. Structural validity (91%), internal consistency (88%), and hypothesis testing (74%) were the most reported properties. Reliability (34%), cross-cultural validity (34%), content validity (25%), and criterion validity (15%) were reported in less than 50% of the papers. Only two (3%) studies reported responsiveness, and none reported measurement error. Less than 35% of the validation studies achieved excellent or good quality for any of the measurement properties. CONCLUSION: The results show that no robust and valid scale exists for measuring hope. It highlights important gaps in psychometric properties of hope scales. Despite more than 40 years of research and development of hope scales, the currently available scales do not meet the standards of psychometric evaluation. This calls for efforts to improve the quality of hope scales.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.057 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 it