CoChat
Sign Up
Cited by 53Anxiety, Depression, Psychometrics, Treatment, Cognitive ProcessesPsychometric Methodologies and TestingTreatment of Major Depression

The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.

The development and psychometric evaluation of the motivation and energy inventory (MEI)

Fehnel, S.E., Bann, C.M., Hogue, S.L., Kwong, W.J., Mahajan, S.S.·2004·Quality of Life Research
DOI 10.1023/b:qure.0000037502.64077.4d
Open this paper in CoChat — free account

Abstract

Because depressed patients commonly experience reductions in motivation and energy, both as symptoms of their disorder and as side effects of pharmacotherapy, it is important to identify interventions that can restore their vitality. The Motivation and Energy Inventory (MEI) was recently developed to facilitate the evaluation of such efforts both in depression research, as well as in other therapeutic areas where vitality is an important issue. The constructs addressed by the MEI were identified through a combination of literature review, consultation with experts, and patient focus groups. Potential problems identified during cognitive testing and addressed in subsequent revisions related to the instructions, reference period, response scale sizes, and response scale labels, as well as a number of item-specific issues. Most recently, the data from two randomized, placebo-controlled clinical trials were utilized to evaluate the psychometric properties of the new questionnaire. In general, the data collected during the first and second trial were used for exploratory and confirmatory analysis, respectively. Consistent with the measurement model of the MEI, the psychometric results confirm that the instrument has three factors generally addressing physical energy, mental energy, and social motivation. Furthermore, these results provide evidence for the internal consistency, construct validity, and responsiveness of all three MEI subscales. Additional work is currently underway to examine test-retest reliability and establish minimal clinically important difference values for the MEI subscales.

Overview

Integrity signals

Registry

Crossref · 10.1023/b:qure.0000037502.64077.4d

Cites

36 of 36 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • The MEI was designed to be responsive to treatment effects and able to discriminate among patient populations with differing clinical characteristics.

    “It was designed to be responsive to treatment effects and able to discriminate among patient populations with differing clinical characteristics.”

    From Patient-reported outcome measures for life engagement in mental health: a systematic review (2022) · cites this paper as [35]

  • In depression, the three MEI subscales each showed good internal consistency (Cronbach's α = 0.75-0.89), construct validity (moderate correlation with quality of life, r = −0.42 to −0.64, and modest correlation with depressive symptoms, r = −0.15 to −0.26), and could detect changes over time.

    “In depression, the three MEI subscales each showed good internal consistency (Cronbach’s α = 0.75–0.89), construct validity (moderate correlation with quality of life, r = − 0.42 to − 0.64, and modest correlation with depressive symptoms, r = − 0.15 to − 0.26), and could detect changes over time [35].”

    From Patient-reported outcome measures for life engagement in mental health: a systematic review (2022) · cites this paper as [35]

  • The Motivation and Energy Inventory (MEI) measures vitality in the past 4 weeks.

    “The MEI [35] measures vitality in the past 4 weeks.”

    From Patient-reported outcome measures for life engagement in mental health: a systematic review (2022) · cites this paper as [35]

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 1

  1. Medical Outcomes Trust Depression in primary care: Improving diagnosis and treatment at Kaiser-Permanente Colorado. Med Outcomes Trust Monit 1997; 2: 2–4.

Cited by

Sorted by citations

Related

Metadata

Authors
Fehnel, S. E., Bann, C. M., Hogue, S. L., Kwong, W. J., & Mahajan, S. S.
Affiliations
  • RTI International (US)
  • GlaxoSmithKline (United States) (US)
Corresponding author
Fehnel, S.E.
ORCID
Venue
Quality of Life Research
Publisher
Springer Science and Business Media LLC
Published
2004-09
Volume
13
Issue
7
Pages
1321-1336
ISSN
  • 0962-9343 (ISSN-L)
  • 1573-2649
DOI
10.1023/b:qure.0000037502.64077.4d
OpenAlex
W2009337441
Cited by
53
References
36
Citations by year
2026: 2 · 2025: 2 · 2024: 3 · 2023: 5 · 2022: 4 · 2021: 1 · 2020: 4 · 2018: 3 · 2017: 4 · 2016: 4 · 2015: 3 · 2014: 3 · 2013: 2
FWCI
1.88
Type
journal article
Language
en
Open access
closed
Licence
Locations
  • Quality of Life Research (publishedVersion)
  • PubMed (publishedVersion)
Funders
GlaxoSmithKline
Topics
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
  • Health Sciences › Medicine › Pharmacology (medical) › Treatment of Major Depression
Keywords
motivation, energy, depression, vitality, psychometric properties, questionnaire development, physical energy, mental energy, social motivation, construct validity, responsiveness, internal consistency, minimal clinically important difference
MeSH terms
Adolescent, Adult, Aged, Antidepressive Agents, Depression, Factor Analysis, Statistical, Fatigue, Female, Humans, Male, Middle Aged, Motivation, Personality Inventory, Psychometrics, Reproducibility of Results, Randomized Controlled Trials as Topic

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review