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Schlam TR, Baker TB, Piper ME, Cook JW, Smith SS, Zwaga D, Jorenby DE, Almirall D, Bolt DM, Collins LM, Mermelstein R, Fiore MC. What to do after smoking relapse? A sequential multiple assignment randomized trial of chronic care smoking treatments. Addiction 2024; 119:898-914. [PMID: 38282258 DOI: 10.1111/add.16428] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Accepted: 11/30/2023] [Indexed: 01/30/2024]
Abstract
AIM To compare effects of three post-relapse interventions on smoking abstinence. DESIGN Sequential three-phase multiple assignment randomized trial (SMART). SETTING Eighteen Wisconsin, USA, primary care clinics. PARTICIPANTS A total of 1154 primary care patients (53.6% women, 81.2% White) interested in quitting smoking enrolled from 2015 to 2019; 582 relapsed and were randomized to relapse recovery treatment. INTERVENTIONS In phase 1, patients received cessation counseling and 8 weeks nicotine patch. Those who relapsed and agreed were randomized to a phase 2 relapse recovery group: (1) reduction counseling + nicotine mini-lozenges + encouragement to quit starting 1 month post-randomization (preparation); (2) repeated encouragement to quit starting immediately post-randomization (recycling); or (3) advice to call the tobacco quitline (control). The first two groups could opt into phase 3 new quit treatment [8 weeks nicotine patch + mini-lozenges plus randomization to two treatment factors (skill training and supportive counseling) in a 2 × 2 design]. Phase 2 and 3 interventions lasted ≤ 15 months. MEASUREMENTS The study was powered to compare each active phase 2 treatment with the control on the primary outcome: biochemically confirmed 7-day point-prevalence abstinence 14 months post initiating phase 2 relapse recovery treatment. Exploratory analyses tested for phase 3 counseling factor effects. FINDINGS Neither skill training nor supportive counseling (each on versus off) increased 14-month abstinence rates; skills on versus off 9.3% (14/151) versus 5.2% (8/153), P = 0.19; support on versus off 6.6% (10/152) versus 7.9% (12/152), P = 0.73. Phase 2 preparation did not produce higher 14-month abstinence rates than quitline referral; 3.6% (8/220) versus 2.1% [3/145; risk difference = 1.5%, 95% confidence interval (CI) = -1.8-5.0%, odds ratio (OR) = 1.8, 95% CI = 0.5-6.9]. Recycling, however, produced higher abstinence rates than quitline referral; 6.9% (15/217) versus 2.1% (three of 145; risk difference, 4.8%, 95% CI = 0.7-8.9%, OR = 3.5, 95% CI = 1.0-12.4). Recycling produced greater entry into new quit treatment than preparation: 83.4% (181/217) versus 55.9% (123/220), P < 0.0001. CONCLUSIONS Among people interested in quitting smoking, immediate encouragement post-relapse to enter a new round of smoking cessation treatment ('recycling') produced higher probability of abstinence than tobacco quitline referral. Recycling produced higher rates of cessation treatment re-engagement than did preparation/cutting down using more intensive counseling and pharmacotherapy.
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Affiliation(s)
- Tanya R Schlam
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
- Department of Kinesiology, School of Education, University of Wisconsin-Madison, Madison, WI, USA
| | - Timothy B Baker
- Center for Tobacco Research and Intervention, Division of General Internal Medicine, Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Megan E Piper
- Center for Tobacco Research and Intervention, Division of General Internal Medicine, Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Jessica W Cook
- Center for Tobacco Research and Intervention, Division of General Internal Medicine, Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
- William S. Middleton Memorial Veterans Hospital, Madison, WI, USA
| | - Stevens S Smith
- Center for Tobacco Research and Intervention, Division of General Internal Medicine, Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Deejay Zwaga
- Center for Tobacco Research and Intervention, Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Douglas E Jorenby
- Center for Tobacco Research and Intervention, Division of General Internal Medicine, Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Daniel Almirall
- Institute for Social Research and Department of Statistics, University of Michigan, Ann Arbor, MI, USA
| | - Daniel M Bolt
- Department of Educational Psychology, School of Education, University of Wisconsin-Madison, Madison, WI, USA
| | - Linda M Collins
- Department of Social and Behavioral Sciences, School of Global Public Health, New York University, New York, NY, USA
| | - Robin Mermelstein
- Institute for Health Research and Policy, University of Illinois at Chicago, Chicago, IL, USA
| | - Michael C Fiore
- Center for Tobacco Research and Intervention, Division of General Internal Medicine, Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
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Lyu W, Bolt DM. Predicting response time on self-report rating scale assessments of noncognitive constructs. Behav Res Methods 2024; 56:1123-1139. [PMID: 37604960 DOI: 10.3758/s13428-023-02073-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/18/2023] [Indexed: 08/23/2023]
Abstract
Methodological studies of response time on noncognitive assessments have separately demonstrated the relevance of content trait level and response styles as predictive factors. In this paper we examine the simultaneous relevance of both factors as well as the potential for omitted predictor bias when ignoring either factor. Using response time data from several different noncognitive assessments, we demonstrate how a multilevel regression model that attends simultaneously to content and response style factors leads to consistent findings that support the simultaneous relevance of both factors. The average effects of response style consistently emerge as stronger, although also show greater respondent-level variability, possibly due to the multiple different underlying causes of response style behavior. Some implications for the use of response times in noncognitive measurement are considered.
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Affiliation(s)
- Weicong Lyu
- University of Wisconsin-Madison, Madison, WI, USA.
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Lyu W, Bolt DM. Erratum to: Rejoinder to Commentaries on Lyu, Bolt and Westby's "Exploring the Effects of Item Specific Factors in Sequential and IRTree Models". Psychometrika 2023; 88:1591. [PMID: 37668930 DOI: 10.1007/s11336-023-09928-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/06/2023]
Affiliation(s)
- Weicong Lyu
- University of Wisconsin-Madison, 880 Educational Sciences, 1025 West Johnson Street, Madison, WI, 53706, USA.
| | - Daniel M Bolt
- University of Wisconsin-Madison, 880 Educational Sciences, 1025 West Johnson Street, Madison, WI, 53706, USA
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Huang QH, Bolt DM. Unipolar IRT and the Author Recognition Test (ART). Behav Res Methods 2023:10.3758/s13428-023-02275-2. [PMID: 37973711 DOI: 10.3758/s13428-023-02275-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/17/2023] [Indexed: 11/19/2023]
Abstract
Item response theory (IRT) analyses are often used to evaluate measurement error in educational and psychological test instruments. In such contexts, the latent traits/proficiencies are typically assumed normally distributed and a cumulative normal/logistic measurement link function is applied. Such choices are consistent with constructs that are viewed as bipolar in nature and play a critical role in defining the latent proficiency metric against which the measurement error in the test is evaluated. Recently, alternative models that portray the construct as unipolar have been highlighted as being more appropriate for certain psychopathology and personality constructs. In this paper we extend consideration of unipolar IRT models for a recognition task measure, using several example datasets from various versions of the Author Recognition Test (ART), a measure of print exposure. We show how the decision between unipolar versus bipolar IRT modeling has substantial implications for the quantification and interpretation of measurement error in the ART. In sharp contrast to prior bipolar IRT analyses of the ART, under unipolar IRT measurement error in the ART is minimized at low levels of latent print exposure, and increases as latent print exposure increases. Implications for consideration of unipolar IRT with other constructs and measures (e.g., vocabulary, specialized forms of knowledge) that reflect a similar type of response process are considered in the discussion.
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Affiliation(s)
- Qi Helen Huang
- Educational Psychology, University of Wisconsin-Madison, Madison, WI, USA.
| | - Daniel M Bolt
- Educational Psychology, University of Wisconsin-Madison, Madison, WI, USA
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Gorney K, Wollack JA, Bolt DM. Using Item Scores and Distractors to Detect Test Speededness. Appl Psychol Meas 2023; 47:386-401. [PMID: 37810541 PMCID: PMC10552735 DOI: 10.1177/01466216231182149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
Test speededness refers to a situation in which examinee performance is inadvertently affected by the time limit of the test. Because speededness has the potential to severely bias both person and item parameter estimates, it is crucial that speeded examinees are detected. In this article, we develop a change-point analysis (CPA) procedure for detecting test speededness. Our procedure distinguishes itself from existing CPA procedures by using information from both item scores and distractors. Using detailed simulations, we show that under most conditions, the new CPA procedure improves the detection of speeded examinees and produces more accurate change-point estimates. It therefore seems there is a considerable amount of information to be gained from the item distractors, which, quite notably are available in all multiple-choice data. A real data example is also provided.
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Affiliation(s)
- Kylie Gorney
- Department of Educational Psychology, University of Wisconsin-Madison, Madison, WI, USA
| | - James A. Wollack
- Department of Educational Psychology, University of Wisconsin-Madison, Madison, WI, USA
| | - Daniel M. Bolt
- Department of Educational Psychology, University of Wisconsin-Madison, Madison, WI, USA
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6
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Lyu W, Bolt DM. Rejoinder to Commentaries on Lyu, Bolt and Westby's "Exploring the Effects of Item Specific Factors in Sequential and IRTree Models". Psychometrika 2023; 88:1026-1031. [PMID: 37326910 DOI: 10.1007/s11336-023-09913-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Indexed: 06/17/2023]
Abstract
We respond to the commentaries on Lyu, Bolt and Westby's "Exploring the effects of item specific factors in sequential and IRTree models." The commentaries raise important points that allow us to clarify our theoretical expectation for item specific factors in many educational and psychological test items. At the same time, we agree with the commentaries in acknowledging challenges associated with providing empirical evidence for their presence and reflect on strategies that might support their estimation. We maintain that the principal concern is the ambiguity item specific factors create in attempting to interpret or use the parameters beyond the first node.
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Affiliation(s)
- Weicong Lyu
- University of Wisconsin-Madison, 880 Educational Sciences, 1025 West Johnson Street, Madison, WI, 53706, USA.
| | - Daniel M Bolt
- University of Wisconsin-Madison, 880 Educational Sciences, 1025 West Johnson Street, Madison, WI, 53706, USA
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7
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Lyu W, Bolt DM, Westby S. Exploring the Effects of Item-Specific Factors in Sequential and IRTree Models. Psychometrika 2023; 88:745-775. [PMID: 37326911 DOI: 10.1007/s11336-023-09912-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Indexed: 06/17/2023]
Abstract
Test items for which the item score reflects a sequential or IRTree modeling outcome are considered. For such items, we argue that item-specific factors, although not empirically measurable, will often be present across stages of the same item. In this paper, we present a conceptual model that incorporates such factors. We use the model to demonstrate how the varying conditional distributions of item-specific factors across stages become absorbed into the stage-specific item discrimination and difficulty parameters, creating ambiguity in the interpretations of item and person parameters beyond the first stage. We discuss implications in relation to various applications considered in the literature, including methodological studies of (1) repeated attempt items; (2) answer change/review, (3) on-demand item hints; (4) item skipping behavior; and (5) Likert scale items. Our own empirical applications, as well as several examples published in the literature, show patterns of violations of item parameter invariance across stages that are highly suggestive of item-specific factors. For applications using sequential or IRTree models as analytical models, or for which the resulting item score might be viewed as outcomes of such a process, we recommend (1) regular inspection of data or analytic results for empirical evidence (or theoretical expectations) of item-specific factors; and (2) sensitivity analyses to evaluate the implications of item-specific factors for the intended inferences or applications.
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Affiliation(s)
- Weicong Lyu
- University of Wisconsin-Madison, 880 Educational Sciences, 1025 West Johnson Street, Madison, WI, 53706, USA.
| | - Daniel M Bolt
- University of Wisconsin-Madison, 1082 A Educational Sciencesz, 1025 West Johnson Street, Madison, WI, 53706, USA
| | - Samuel Westby
- Northeastern University, 177 Huntington Ave Desk 232O, Boston, MA, 02115, USA
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Huang Q(H, Bolt DM. Relative Robustness of CDMs and (M)IRT in Measuring Growth in Latent Skills. Educ Psychol Meas 2023; 83:808-830. [PMID: 37398840 PMCID: PMC10311955 DOI: 10.1177/00131644221117194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Previous studies have demonstrated evidence of latent skill continuity even in tests intentionally designed for measurement of binary skills. In addition, the assumption of binary skills when continuity is present has been shown to potentially create a lack of invariance in item and latent ability parameters that may undermine applications. In this article, we examine measurement of growth as one such application, and consider multidimensional item response theory (MIRT) as a competing alternative. Motivated by prior findings concerning the effects of skill continuity, we study the relative robustness of cognitive diagnostic models (CDMs) and (M)IRT models in the measurement of growth under both binary and continuous latent skill distributions. We find CDMs to be a less robust way of quantifying growth under misspecification, and subsequently provide a real-data example suggesting underestimation of growth as a likely consequence. It is suggested that researchers should regularly attend to the assumptions associated with the use of latent binary skills and consider (M)IRT as a potentially more robust alternative if unsure of their discrete nature.
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Nolan MB, Piasecki TM, Smith SS, Baker TB, Fiore MC, Adsit RT, Bolt DM, Conner KL, Bernstein SL, Eng OD, Lazuk D, Gonzalez A, Hayes-Birchler T, Jorenby DE, D'Angelo H, Kirsch JA, Williams BS, Kent S, Kim H, Lubanski SA, Yu M, Suk Y, Cai Y, Kashyap N, Mathew J, McMahan G, Rolland B, Tindle HA, Warren GW, Abu-el-rub N, An LC, Boyd AD, Brunzell DH, Carrillo VA, Chen LS, Davis JM, Deshmukh VG, Dilip D, Goldstein AO, Ha PK, Iturrate E, Jose T, Khanna N, King A, Klass E, Lui M, Mermelstein RJ, Poon C, Tong E, Wilson KM, Theobald WE, Slutske WS. Relations of Current and Past Cancer with Severe Outcomes among 104,590 Hospitalized COVID-19 Patients: The COVID EHR Cohort at the University of Wisconsin. Cancer Epidemiol Biomarkers Prev 2023; 32:12-21. [PMID: 35965473 PMCID: PMC9827105 DOI: 10.1158/1055-9965.epi-22-0500] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Revised: 06/29/2022] [Accepted: 08/08/2022] [Indexed: 01/12/2023] Open
Abstract
BACKGROUND There is mixed evidence about the relations of current versus past cancer with severe COVID-19 outcomes and how they vary by patient and cancer characteristics. METHODS Electronic health record data of 104,590 adult hospitalized patients with COVID-19 were obtained from 21 United States health systems from February 2020 through September 2021. In-hospital mortality and ICU admission were predicted from current and past cancer diagnoses. Moderation by patient characteristics, vaccination status, cancer type, and year of the pandemic was examined. RESULTS 6.8% of the patients had current (n = 7,141) and 6.5% had past (n = 6,749) cancer diagnoses. Current cancer predicted both severe outcomes but past cancer did not; adjusted odds ratios (aOR) for mortality were 1.58 [95% confidence interval (CI), 1.46-1.70] and 1.04 (95% CI, 0.96-1.13), respectively. Mortality rates decreased over the pandemic but the incremental risk of current cancer persisted, with the increment being larger among younger vs. older patients. Prior COVID-19 vaccination reduced mortality generally and among those with current cancer (aOR, 0.69; 95% CI, 0.53-0.90). CONCLUSIONS Current cancer, especially among younger patients, posed a substantially increased risk for death and ICU admission among patients with COVID-19; prior COVID-19 vaccination mitigated the risk associated with current cancer. Past history of cancer was not associated with higher risks for severe COVID-19 outcomes for most cancer types. IMPACT This study clarifies the characteristics that modify the risk associated with cancer on severe COVID-19 outcomes across the first 20 months of the COVID-19 pandemic. See related commentary by Egan et al., p. 3.
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Affiliation(s)
- Margaret B. Nolan
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin
| | - Thomas M. Piasecki
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin
| | - Stevens S. Smith
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin
| | - Timothy B. Baker
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin
| | - Michael C. Fiore
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin
| | - Robert T. Adsit
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin
| | - Daniel M. Bolt
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin
- Department of Educational Psychology, University of Wisconsin-Madison, Madison, Wisconsin
| | - Karen L. Conner
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin
| | - Steven L. Bernstein
- Department of Emergency Medicine, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire
| | - Oliver D. Eng
- Institute for Clinical and Translational Research, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin
| | - David Lazuk
- Yale-New Haven Health System, New Haven, Connecticut
| | - Alec Gonzalez
- BlueTree Network, a Tegria Company, Madison, Wisconsin
| | - Todd Hayes-Birchler
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin
| | - Douglas E. Jorenby
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin
| | - Heather D'Angelo
- Carbone Cancer Center, University of Wisconsin-Madison, Madison, Wisconsin
| | - Julie A. Kirsch
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin
- Department of Family Medicine and Community Health, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin
| | - Brian S. Williams
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin
- Department of Pediatrics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin
| | - Sean Kent
- Department of Statistics, University of Wisconsin-Madison, Madison, Wisconsin
| | - Hanna Kim
- Department of Educational Psychology, University of Wisconsin-Madison, Madison, Wisconsin
| | | | - Menggang Yu
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin
| | - Youmi Suk
- School of Data Science, University of Virginia, Charlottesville, Virginia
| | - Yuxin Cai
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin
| | - Nitu Kashyap
- Yale-New Haven Health System, New Haven, Connecticut
- Yale School of Medicine, New Haven, Connecticut
| | - Jomol Mathew
- Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin
| | - Gabriel McMahan
- Department of Statistics, University of Wisconsin-Madison, Madison, Wisconsin
| | - Betsy Rolland
- Institute for Clinical and Translational Research, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin
- Carbone Cancer Center, University of Wisconsin-Madison, Madison, Wisconsin
| | - Hilary A. Tindle
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Graham W. Warren
- Department of Radiation Oncology, Medical University of South Carolina, Charleston, South Carolina
| | - Noor Abu-el-rub
- Center for Medical Informatics and Enterprise Analytics, University of Kansas Medical Center, Kansas City, Kansas
| | - Lawrence C. An
- Division of General Medicine, Rogel Cancer Center, University of Michigan, Ann Arbor, Michigan
| | - Andrew D. Boyd
- Department of Biomedical and Health Information Sciences, College of Applied Health Sciences, University of Illinois at Chicago, Chicago, Illinois
| | | | - Victor A. Carrillo
- Hackensack Meridian Health, Hackensack University Medical Center, Hackensack, New Jersey
| | - Li-Shiun Chen
- Washington University in St. Louis School of Medicine, St. Louis, Missouri
| | - James M. Davis
- Duke Cancer Institute and Duke University Department of Medicine, Durham, North Carolina
| | | | - Deepika Dilip
- Memorial Sloan Kettering Cancer Center, New York, New York
| | - Adam O. Goldstein
- Department of Family Medicine and Lineberger Comprehensive Cancer Center, University of North Carolina School of Medicine, Chapel Hill, North Carolina
| | - Patrick K. Ha
- Division of Head and Neck Surgical Oncology, University of California San Francisco, San Francisco, California
| | | | - Thulasee Jose
- Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, Minnesota
| | - Niharika Khanna
- University of Maryland School of Medicine, Baltimore, Maryland
| | - Andrea King
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago Comprehensive Cancer Center, Chicago, Illinois
| | - Elizabeth Klass
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Michelle Lui
- Memorial Sloan Kettering Cancer Center, New York, New York
| | - Robin J. Mermelstein
- Department of Psychology and Institute for Health Research and Policy, University of Illinois at Chicago, Chicago, Illinois
| | - Chester Poon
- Memorial Sloan Kettering Cancer Center, New York, New York
| | - Elisa Tong
- Department of Internal Medicine, University of California Davis, Davis, California
| | - Karen M. Wilson
- Department of Pediatrics, University of Rochester School of Medicine and Dentistry, Rochester, New York
| | - Wendy E. Theobald
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin
- Corresponding Author: Wendy S. Slutske, UW Center for Tobacco Research and Intervention, 1930 Monroe Street #200, Madison, WI 53711. Phone: 608-262-8673; E-mail:
| | - Wendy S. Slutske
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin
- Department of Family Medicine and Community Health, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin
- Corresponding Author: Wendy S. Slutske, UW Center for Tobacco Research and Intervention, 1930 Monroe Street #200, Madison, WI 53711. Phone: 608-262-8673; E-mail:
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Bolt DM, Liao X. Item Complexity: A Neglected Psychometric Feature of Test Items? Psychometrika 2022; 87:1195-1213. [PMID: 35146596 DOI: 10.1007/s11336-022-09842-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Revised: 08/24/2021] [Indexed: 06/14/2023]
Abstract
Despite its frequent consideration in test development, item complexity receives little attention in the psychometric modeling of item response data. In this address, I consider how variability in item complexity can be expected to emerge in the form of item characteristic curve (ICC) asymmetry, and how such effects may significantly influence applications of item response theory, especially those that assume interval-level properties of the latent proficiency metric and groups that vary substantially in mean proficiency. One application is the score gain deceleration phenomenon often observed in vertical scaling contexts, especially in subject areas like math or second language acquisition. It is demonstrated how the application of symmetric IRT models in the presence of complexity-induced positive ICC asymmetry can be a likely cause. A second application concerns the positive correlation between DIF and difficulty commonly seen in verbal proficiency (and other subject area) tests where problem-solving complexity is minimal and proficiency-related guessing effects are likely pronounced. Here we suggest negative ICC asymmetry as a probable cause and apply sensitivity analyses to demonstrate the ease with which such correlations disappear when allowing for negative ICC asymmetry. Unfortunately, the presence of systematic forms of ICC asymmetry is easily missed due to the considerable flexibility afforded by latent trait metrics in IRT. Speculation is provided regarding other applications for which attending to ICC asymmetry may prove useful.
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Affiliation(s)
- Daniel M Bolt
- Department of Educational Psychology, University of Wisconsin, Madison, 1025 W. Johnson, Room 859, Madison, WI-, 53706, USA.
| | - Xiangyi Liao
- Department of Educational Psychology, University of Wisconsin, Madison, 1025 W. Johnson, Room 859, Madison, WI-, 53706, USA
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11
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Fiore MC, Smith SS, Adsit RT, Bolt DM, Conner KL, Bernstein SL, Eng OD, Lazuk D, Gonzalez A, Jorenby DE, D’Angelo H, Kirsch JA, Williams B, Nolan MB, Hayes-Birchler T, Kent S, Kim H, Piasecki TM, Slutske WS, Lubanski S, Yu M, Suk Y, Cai Y, Kashyap N, Mathew JP, McMahan G, Rolland B, Tindle HA, Warren GW, An LC, Boyd AD, Brunzell DH, Carrillo V, Chen LS, Davis JM, Dilip D, Ellerbeck EF, Iturrate E, Jose T, Khanna N, King A, Klass E, Newman M, Shoenbill KA, Tong E, Tsoh JY, Wilson KM, Theobald WE, Baker TB. The first 20 months of the COVID-19 pandemic: Mortality, intubation and ICU rates among 104,590 patients hospitalized at 21 United States health systems. PLoS One 2022; 17:e0274571. [PMID: 36170336 PMCID: PMC9518859 DOI: 10.1371/journal.pone.0274571] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 08/30/2022] [Indexed: 11/25/2022] Open
Abstract
Main objective There is limited information on how patient outcomes have changed during the COVID-19 pandemic. This study characterizes changes in mortality, intubation, and ICU admission rates during the first 20 months of the pandemic. Study design and methods University of Wisconsin researchers collected and harmonized electronic health record data from 1.1 million COVID-19 patients across 21 United States health systems from February 2020 through September 2021. The analysis comprised data from 104,590 adult hospitalized COVID-19 patients. Inclusion criteria for the analysis were: (1) age 18 years or older; (2) COVID-19 ICD-10 diagnosis during hospitalization and/or a positive COVID-19 PCR test in a 14-day window (+/- 7 days of hospital admission); and (3) health system contact prior to COVID-19 hospitalization. Outcomes assessed were: (1) mortality (primary), (2) endotracheal intubation, and (3) ICU admission. Results and significance The 104,590 hospitalized participants had a mean age of 61.7 years and were 50.4% female, 24% Black, and 56.8% White. Overall risk-standardized mortality (adjusted for age, sex, race, ethnicity, body mass index, insurance status and medical comorbidities) declined from 16% of hospitalized COVID-19 patients (95% CI: 16% to 17%) early in the pandemic (February-April 2020) to 9% (CI: 9% to 10%) later (July-September 2021). Among subpopulations, males (vs. females), those on Medicare (vs. those on commercial insurance), the severely obese (vs. normal weight), and those aged 60 and older (vs. younger individuals) had especially high mortality rates both early and late in the pandemic. ICU admission and intubation rates also declined across these 20 months. Conclusions Mortality, intubation, and ICU admission rates improved markedly over the first 20 months of the pandemic among adult hospitalized COVID-19 patients although gains varied by subpopulation. These data provide important information on the course of COVID-19 and identify hospitalized patient groups at heightened risk for negative outcomes. Trial registration ClinicalTrials.gov Identifier: NCT04506528 (https://clinicaltrials.gov/ct2/show/NCT04506528).
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Affiliation(s)
- Michael C. Fiore
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States of America
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
- * E-mail:
| | - Stevens S. Smith
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States of America
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Robert T. Adsit
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States of America
| | - Daniel M. Bolt
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States of America
- Department of Educational Psychology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Karen L. Conner
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States of America
| | - Steven L. Bernstein
- Department of Emergency Medicine, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire, United States of America
| | - Oliver D. Eng
- Institute for Clinical and Translational Research, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - David Lazuk
- Yale-New Haven Health System, New Haven, Connecticut, United States of America
| | - Alec Gonzalez
- BlueTree Network, a Tegria Company, Madison, Wisconsin, United States of America
| | - Douglas E. Jorenby
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States of America
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Heather D’Angelo
- Carbone Cancer Center, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Julie A. Kirsch
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States of America
- Department of Family Medicine and Community Health, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Brian Williams
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States of America
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
- Department of Pediatrics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Margaret B. Nolan
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States of America
| | - Todd Hayes-Birchler
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States of America
| | - Sean Kent
- Department of Statistics, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Hanna Kim
- Department of Educational Psychology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Thomas M. Piasecki
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States of America
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Wendy S. Slutske
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States of America
- Department of Family Medicine and Community Health, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Stan Lubanski
- United States Census Bureau, Washington, D.C., United States of America
| | - Menggang Yu
- Department of Biostatistics & Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Youmi Suk
- Department of Human Development, Teachers College, Columbia University, New York, New York, United States of America
| | - Yuxin Cai
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States of America
| | - Nitu Kashyap
- Yale-New Haven Health System, New Haven, Connecticut, United States of America
- Yale School of Medicine, New Haven, Connecticut, United States of America
| | - Jomol P. Mathew
- Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Gabriel McMahan
- Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Betsy Rolland
- Institute for Clinical and Translational Research, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
- Carbone Cancer Center, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Hilary A. Tindle
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
| | - Graham W. Warren
- Department of Radiation Oncology, Medical University of South Carolina, Charleston, South Carolina, United States of America
| | - Lawrence C. An
- Division of General Medicine, Rogel Cancer Center, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Andrew D. Boyd
- Department of Biomedical and Health Information Sciences, College of Applied Health Sciences, University of Illinois at Chicago, Chicago, Illinois, United States of America
| | - Darlene H. Brunzell
- Virginia Commonwealth University School of Medicine, Richmond, Virginia, United States of America
| | - Victor Carrillo
- Hackensack Meridian Health, Hackensack University Medical Center, Hackensack, New Jersey, United States of America
| | - Li-Shiun Chen
- Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA
| | - James M. Davis
- Duke Cancer Institute and Duke University Department of Medicine, Durham, North Carolina, United States of America
| | - Deepika Dilip
- Memorial Sloan Kettering Cancer Center, New York, New York, United States of America
| | - Edward F. Ellerbeck
- Department of Population Health, University of Kansas Medical Center, Kansas City, Missouri, United States of America
| | - Eduardo Iturrate
- New York University Langone Health, New York, New York, United States of America
| | - Thulasee Jose
- Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, Minnesota, United States of America
| | - Niharika Khanna
- University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - Andrea King
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago Comprehensive Cancer Center, Chicago, Illinois, United States of America
| | - Elizabeth Klass
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
| | - Michael Newman
- University of Utah, Salt Lake City, Utah, United States of America
| | - Kimberly A. Shoenbill
- Department of Family Medicine and Lineberger Comprehensive Cancer Center, University of North Carolina School of Medicine, Chapel Hill, North Carolina, United States of America
| | - Elisa Tong
- University of California Davis, Davis, California, United States of America
| | - Janice Y. Tsoh
- Department of Psychiatry and Behavioral Sciences, Hellen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, California, United States of America
| | - Karen M. Wilson
- Department of Pediatrics, University of Rochester School of Medicine, Rochester, New York, United States of America
| | - Wendy E. Theobald
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States of America
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Timothy B. Baker
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States of America
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
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Piasecki TM, Smith SS, Baker TB, Slutske WS, Adsit RT, Bolt DM, Conner KL, Bernstein SL, Eng OD, Lazuk D, Gonzalez A, Jorenby DE, D’Angelo H, Kirsch JA, Williams BS, Nolan MB, Hayes-Birchler T, Kent S, Kim H, Lubanski S, Yu M, Suk Y, Cai Y, Kashyap N, Mathew JP, McMahan G, Rolland B, Tindle HA, Warren GW, An LC, Boyd AD, Brunzell DH, Carrillo V, Chen LS, Davis JM, Deshmukh VG, Dilip D, Ellerbeck EF, Goldstein AO, Iturrate E, Jose T, Khanna N, King A, Klass E, Mermelstein RJ, Tong E, Tsoh JY, Wilson KM, Theobald WE, Fiore MC. Smoking Status, Nicotine Medication, Vaccination, and COVID-19 Hospital Outcomes: Findings from the COVID EHR Cohort at the University of Wisconsin (CEC-UW) Study. Nicotine Tob Res 2022; 25:1184-1193. [PMID: 36069915 PMCID: PMC9494410 DOI: 10.1093/ntr/ntac201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Revised: 07/05/2022] [Accepted: 08/17/2022] [Indexed: 11/14/2022]
Abstract
INTRODUCTION Available evidence is mixed concerning associations between smoking status and COVID-19 clinical outcomes. Effects of nicotine replacement therapy (NRT) and vaccination status on COVID-19 outcomes in smokers are unknown. METHODS Electronic health record data from 104 590 COVID-19 patients hospitalized February 1, 2020 to September 30, 2021 in 21 U.S. health systems were analyzed to assess associations of smoking status, in-hospital NRT prescription, and vaccination status with in-hospital death and ICU admission. RESULTS Current (n = 7764) and never smokers (n = 57 454) did not differ on outcomes after adjustment for age, sex, race, ethnicity, insurance, body mass index, and comorbidities. Former (vs never) smokers (n = 33 101) had higher adjusted odds of death (aOR, 1.11; 95% CI, 1.06-1.17) and ICU admission (aOR, 1.07; 95% CI, 1.04-1.11). Among current smokers, NRT prescription was associated with reduced mortality (aOR, 0.64; 95% CI, 0.50-0.82). Vaccination effects were significantly moderated by smoking status; vaccination was more strongly associated with reduced mortality among current (aOR, 0.29; 95% CI, 0.16-0.66) and former smokers (aOR, 0.47; 95% CI, 0.39-0.57) than for never smokers (aOR, 0.67; 95% CI, 0.57, 0.79). Vaccination was associated with reduced ICU admission more strongly among former (aOR, 0.74; 95% CI, 0.66-0.83) than never smokers (aOR, 0.87; 95% CI, 0.79-0.97). CONCLUSIONS Former but not current smokers hospitalized with COVID-19 are at higher risk for severe outcomes. SARS-CoV-2 vaccination is associated with better hospital outcomes in COVID-19 patients, especially current and former smokers. NRT during COVID-19 hospitalization may reduce mortality for current smokers. IMPLICATIONS Prior findings regarding associations between smoking and severe COVID-19 disease outcomes have been inconsistent. This large cohort study suggests potential beneficial effects of nicotine replacement therapy on COVID-19 outcomes in current smokers and outsized benefits of SARS-CoV-2 vaccination in current and former smokers. Such findings may influence clinical practice and prevention efforts and motivate additional research that explores mechanisms for these effects.
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Affiliation(s)
- Thomas M Piasecki
- Corresponding Author: Thomas M. Piasecki, PhD, Center for Tobacco Research and Intervention, University of Wisconsin School of Medicine and Public Health, 1930 Monroe St., Suite 200, Madison, WI 53711, USA. Telephone: +1 (608) 262-8673.
| | - Stevens S Smith
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, WI, USA
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, WI, USA
| | - Timothy B Baker
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, WI, USA
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, WI, USA
| | - Wendy S Slutske
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, WI, USA
- Department of Family Medicine and Community Health, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, WI, USA
| | - Robert T Adsit
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, WI, USA
| | - Daniel M Bolt
- Department of Educational Psychology, University of Wisconsin–Madison, Madison, WI, USA
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, WI, USA
| | - Karen L Conner
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, WI, USA
| | - Steven L Bernstein
- Department of Emergency Medicine, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | - Oliver D Eng
- Institute for Clinical and Translational Research, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, WI, USA
| | - David Lazuk
- Yale-New Haven Health System, New Haven, CT, USA
| | - Alec Gonzalez
- BlueTree Network, a Tegria Company, Madison, WI, USA
| | - Douglas E Jorenby
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, WI, USA
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, WI, USA
| | - Heather D’Angelo
- Carbone Cancer Center, University of Wisconsin–Madison, Madison, WI, USA
| | - Julie A Kirsch
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, WI, USA
- Department of Family Medicine and Community Health, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, WI, USA
| | - Brian S Williams
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, WI, USA
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, WI, USA
- Department of Pediatrics, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, WI, USA
| | - Margaret B Nolan
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, WI, USA
| | - Todd Hayes-Birchler
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, WI, USA
| | - Sean Kent
- Department of Statistics, University of Wisconsin–Madison, Madison, WI, USA
| | - Hanna Kim
- Department of Educational Psychology, University of Wisconsin–Madison, Madison, WI, USA
| | | | - Menggang Yu
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, USA
| | - Youmi Suk
- Department of Human Development, Teachers College Columbia University, New York, NY, USA
| | - Yuxin Cai
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, WI, USA
| | - Nitu Kashyap
- Yale-New Haven Health System, New Haven, CT, USA
- Yale School of Medicine, New Haven, CT, USA
| | - Jomol P Mathew
- Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Gabriel McMahan
- Department of Statistics, University of Wisconsin–Madison, Madison, WI, USA
| | - Betsy Rolland
- Institute for Clinical and Translational Research, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, WI, USA
- Carbone Cancer Center, University of Wisconsin–Madison, Madison, WI, USA
| | - Hilary A Tindle
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Graham W Warren
- Department of Radiation Oncology, Medical University of South Carolina, Charleston, SC, USA
| | - Lawrence C An
- Division of General Medicine, Rogel Cancer Center, University of Michigan, Ann Arbor, MI, USA
| | - Andrew D Boyd
- Department of Biomedical and Health Information Sciences, College of Applied Health Sciences, University of Illinois at Chicago, Chicago, IL, USA
| | | | - Victor Carrillo
- Hackensack Meridian Health, Hackensack University Medical Center, Hackensack, NJ, USA
| | - Li-Shiun Chen
- Washington University in St. Louis School of Medicine, St. Louis, MO, USA
| | - James M Davis
- Duke Cancer Institute and Duke University Department of Medicine, Durham, NC, USA
| | | | - Deepika Dilip
- Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Edward F Ellerbeck
- Department of Population Health, University of Kansas Medical Center, Kansas City, MO, USA
| | - Adam O Goldstein
- Department of Family Medicine and Lineberger Comprehensive Cancer Center, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | | | - Thulasee Jose
- Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN, USA
| | - Niharika Khanna
- University of Maryland School of Medicine, Baltimore, MD, USA
| | - Andrea King
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago Comprehensive Cancer Center, Chicago, IL, USA
| | - Elizabeth Klass
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Robin J Mermelstein
- Department of Psychology and Institute for Health Research and Policy, University of Illinois at Chicago, Chicago, IL, USA
| | - Elisa Tong
- Department of Internal Medicine, University of California Davis, Davis, CA, USA
| | - Janice Y Tsoh
- Department of Psychiatry and Behavioral Sciences, Hellen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA, USA
| | - Karen M Wilson
- Department of Pediatrics, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA
| | - Wendy E Theobald
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, WI, USA
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, WI, USA
| | - Michael C Fiore
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, WI, USA
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin–Madison, Madison, WI, USA
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Kim N, Bolt DM, Wollack J. Noncompensatory MIRT For Passage-Based Tests. Psychometrika 2022; 87:992-1009. [PMID: 35060012 DOI: 10.1007/s11336-021-09826-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/01/2020] [Revised: 11/12/2021] [Indexed: 06/14/2023]
Abstract
We consider a multidimensional noncompensatory approach for binary items in passage-based tests. The passage-based noncompensatory model (PB-NM) emphasizes two underlying components in solving passage-based test items: a passage-related component and a passage-independent component. An advantage of the PB-NM model over commonly applied compensatory models (e.g., bifactor model) is that the two components are parameterized in relation to difficulty as opposed to discrimination parameters. As a result, while simultaneously accounting for passage-related local item dependence, the model permits the assessment of how items based on the same passage may require varying levels of passage comprehension (as well as varying levels of passage-independent proficiency) to obtain a correct response. Through a simulation study, we evaluate the comparative fit of the PB-NM against the bifactor model and also illustrate the relationship between the difficulty parameters of the PB-NM and the discrimination parameters of the bifactor model. We further apply the PB-NM to an actual reading comprehension test to demonstrate the relevance of the model in understanding variation in the relative difficulty of the two components across different item types.
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Affiliation(s)
- Nana Kim
- University of Wisconsin-Madison, 1025 W. Johnson St, Madison, WI, 53706, USA.
| | - Daniel M Bolt
- University of Wisconsin-Madison, 1025 W. Johnson St, Madison, WI, 53706, USA
| | - James Wollack
- University of Wisconsin-Madison, 1025 W. Johnson St, Madison, WI, 53706, USA
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Huang Q(H, Bolt DM. The Potential for Interpretational Confounding in Cognitive Diagnosis Models. Appl Psychol Meas 2022; 46:303-320. [PMID: 35601265 PMCID: PMC9118932 DOI: 10.1177/01466216221084207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
Binary examinee mastery/nonmastery classifications in cognitive diagnosis models may often be an approximation to proficiencies that are better regarded as continuous. Such misspecification can lead to inconsistencies in the operational definition of "mastery" when binary skills models are assumed. In this paper we demonstrate the potential for an interpretational confounding of the latent skills when truly continuous skills are treated as binary. Using the DINA model as an example, we show how such forms of confounding can be observed through item and/or examinee parameter change when (1) different collections of items (such as representing different test forms) previously calibrated separately are subsequently calibrated together; and (2) when structural restrictions are placed on the relationships among skill attributes (such as the assumption of strictly nonnegative growth over time), among other possibilities. We examine these occurrences in both simulation and real data studies. It is suggested that researchers should regularly attend to the potential for interpretational confounding by studying differences in attribute mastery proportions and/or changes in item parameter (e.g., slip and guess) estimates attributable to skill continuity when the same samples of examinees are administered different test forms, or the same test forms are involved in different calibrations.
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Piper ME, Baker TB, Zwaga D, Bolt DM, Kobinsky K, Jorenby DE. Understanding contexts of smoking and vaping among dual users: analysis of ecological momentary assessment data. Addiction 2022; 117:1416-1426. [PMID: 34791744 PMCID: PMC9940410 DOI: 10.1111/add.15747] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Accepted: 10/29/2021] [Indexed: 11/29/2022]
Abstract
AIMS To understand dual users' cigarette and e-cigarette use patterns, including the contexts in which they vape versus smoke and to understand how environmental and internal contexts and smoking patterns differ between dual users and exclusive smokers. DESIGN Longitudinal observational trial. SETTING Research center in Wisconsin, USA. PARTICIPANTS Adult dual users (n = 162) and adults who exclusively smoked (n = 143), with no plans to quit smoking or vaping in the next 30 days. MEASUREMENTS Participants carried smartphones for 2 weeks at baseline to record each use event for the two products and report on the context of their product use. The percentage of mornings where participants vaped first versus smoked were used to compute e-cigarette dependence. FINDINGS Hierarchical linear regression models with random slopes and intercepts examined the within- and between-subject effects of context on the likelihood of vaping (versus smoking); significant fixed effects were tested for moderation by e-cigarette dependence. Dual users reported significantly more puffs/cigarette [mean = 13.1, standard deviation (SD) = 10.2] than puffs/vape event (mean = 11.7, SD = 11.5; P = 0.01). E-cigarette dependence moderated the influence of social cues (t-ratio = 2.4, P = 0.02) and smoking restrictions (t-ratio = 3.1, P = 0.003) on the likelihood of vaping versus smoking [odds ratio (OR) = 2.30, P = 0.02]. Context was more related to which product was used in those of low versus higher e-cigarette dependence. Reports of strong cravings to smoke and positive expectancies for cigarettes were associated with a reduced likelihood of vaping, whereas strong cravings to vape and positive vaping expectancies were related to increased likelihood of vaping. CONCLUSIONS Among dual users of cigarettes and e-cigarettes with no motivation to quit, vaping appears to be related to internal cues and more highly linked with social contexts and smoking restrictions (i.e. under stronger external stimulus control) among those with low to moderate e-cigarette dependence compared with high e-cigarette dependence. These findings illustrate the importance of contextual factors in tobacco product use among dual users with the influence of context being reduced at high levels of e-cigarette dependence.
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Affiliation(s)
- Megan E. Piper
- University of Wisconsin, School of Medicine and Public Health, Center for Tobacco Research and Intervention, University of Wisconsin-Madison, Madison, WI,Correspondence concerning this article should be addressed to Megan E. Piper, Ph.D., Center for Tobacco Research and Intervention, University of Wisconsin, Madison, WI, 53711; Tel: 608-265-5472; Fax: 608-265-3102;
| | - Timothy B. Baker
- University of Wisconsin, School of Medicine and Public Health, Center for Tobacco Research and Intervention, University of Wisconsin-Madison, Madison, WI
| | - Deejay Zwaga
- University of Wisconsin, School of Medicine and Public Health, Center for Tobacco Research and Intervention, University of Wisconsin-Madison, Madison, WI
| | - Daniel M. Bolt
- Department of Educational Psychology, University of Wisconsin-Madison, Madison, WI
| | - Kate Kobinsky
- University of Wisconsin, School of Medicine and Public Health, Center for Tobacco Research and Intervention, University of Wisconsin-Madison, Madison, WI
| | - Douglas E. Jorenby
- University of Wisconsin, School of Medicine and Public Health, Center for Tobacco Research and Intervention, University of Wisconsin-Madison, Madison, WI
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Lyu W, Bolt DM. A psychometric model for respondent-level anchoring on self-report rating scale instruments. Br J Math Stat Psychol 2022; 75:116-135. [PMID: 34350978 DOI: 10.1111/bmsp.12251] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Revised: 07/14/2021] [Indexed: 06/13/2023]
Abstract
Among the various forms of response bias that can emerge with self-report rating scale assessments are those related to anchoring, the tendency for respondents to select categories in close proximity to the rating category used for the immediately preceding item. In this study we propose a psychometric model based on a multidimensional nominal model for response style that also simultaneously accommodates a respondent-level anchoring tendency. The model is estimated using a fully Bayesian estimation procedure. By applying this model to a real test data set measuring extraversion, we explore a theory that both response styles and anchoring might be viewed as evidence of a lack of effortful responding. Empirical results show that there is a positive correlation between the strength of midpoint response style and the anchoring effect; further, responses indicative of either anchoring or response style both negatively correlate with response time, consistent with a theory that both phenomena reflect reduced respondent effort. The results support attending to both anchoring and midpoint response style as ways of assessing respondent engagement.
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Affiliation(s)
- Weicong Lyu
- Department of Educational Psychology, University of Wisconsin-Madison, Wisconsin, USA
| | - Daniel M Bolt
- Department of Educational Psychology, University of Wisconsin-Madison, Wisconsin, USA
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17
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Bolt DM, Liao X. On the Positive Correlation between DIF and Difficulty: A New Theory on the Correlation as Methodological Artifact. Journal of Educational Measurement 2021. [DOI: 10.1111/jedm.12302] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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18
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Abstract
Meaningfully improved mental and behavioral health treatment is an unrealized dream. Across three factorial experiments, inferential tests in prior studies showed a pattern of negative interactions suggesting that better clinical outcomes are obtained when participants receive fewer rather than more intervention components. Further, relatively few significant main effects were found in these experiments. Modeling suggested that negative interactions amongst components may account for these patterns. This paper evaluates factors that may contribute to such declining benefit: increased attentional or effort burden; components that produce their effects via the same capacity limited mechanisms, making their effects subadditive; and a tipping point phenomenon in which those near a hypothesized "tipping point" for change will benefit markedly from weak intervention while those far from the tipping point will benefit little from even strong intervention. New research should explore factors that cause negative interactions amongst components and constrain the development of more effective treatments.
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Affiliation(s)
- Timothy B. Baker
- University of Wisconsin School of Medicine and Public Health, Center for Tobacco Research and Intervention, 1930 Monroe St., Suite 200, Madison, WI 53711
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, 1685 Highland Avenue, 5158 Medical Foundation Centennial Building, Madison, WI 53705
| | - Daniel M. Bolt
- University of Wisconsin, Department of Educational Psychology, 1025 W. Johnson St., Madison, WI 53706
| | - Stevens S. Smith
- University of Wisconsin School of Medicine and Public Health, Center for Tobacco Research and Intervention, 1930 Monroe St., Suite 200, Madison, WI 53711
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, 1685 Highland Avenue, 5158 Medical Foundation Centennial Building, Madison, WI 53705
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19
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Cook JW, Baker TB, Fiore MC, Collins LM, Piper ME, Schlam TR, Bolt DM, Smith SS, Zwaga D, Jorenby DE, Mermelstein R. Evaluating four motivation-phase intervention components for use with primary care patients unwilling to quit smoking: a randomized factorial experiment. Addiction 2021; 116:3167-3179. [PMID: 33908665 PMCID: PMC8492501 DOI: 10.1111/add.15528] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Revised: 10/15/2020] [Accepted: 04/14/2021] [Indexed: 11/27/2022]
Abstract
AIMS To assess the effectiveness of intervention components designed to increase quit attempts and promote abstinence in patients initially unwilling to quit smoking. DESIGN A four-factor, randomized factorial experiment. SETTING Sixteen primary care clinics in southern Wisconsin. PARTICIPANTS A total of 577 adults who smoke (60% women, 80% White) recruited during primary care visits who were currently willing to reduce their smoking but unwilling to try to quit. Interventions Four factors contrasted intervention components administered over a 1-year period: (i) nicotine mini-lozenge versus none; (ii) reduction counseling versus none; (iii) behavioral activation (BA) counseling versus none; and (iv) motivational 5Rs counseling versus none. Participants could request cessation treatment at any time. MEASUREMENTS The primary outcome was 7-day point-prevalence abstinence at 52 weeks post enrollment; secondary outcomes were point-prevalence abstinence at 26 weeks and making a quit attempt by weeks 26 and 52. FINDINGS No abstinence main effects were found but a mini-lozenge × reduction counseling × BA interaction was found at 52 weeks; P = 0.03. Unpacking this interaction showed that the mini-lozenge alone produced the highest abstinence rate (16.7%); combining it with reduction counseling produced an especially low abstinence rate (4.1%). Reduction counseling decreased the likelihood of making a quit attempt by 52 weeks relative to no reduction counseling (P = 0.01). CONCLUSIONS Nicotine mini-lozenges may increase smoking abstinence in people initially unwilling to quit smoking, but their effectiveness declines when used with smoking reduction counseling or other behavioral interventions. Reduction counseling decreases the likelihood of making a quit attempt in people initially unwilling to quit smoking.
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Affiliation(s)
- Jessica W Cook
- Center for Tobacco Research and Intervention, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- William S. Middleton Memorial Veterans Hospital, Madison, WI, USA
| | - Timothy B Baker
- Center for Tobacco Research and Intervention, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Michael C Fiore
- Center for Tobacco Research and Intervention, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Linda M Collins
- Department of Social and Behavioral Sciences, School of Global Public Health, New York University, New York, NY, USA
| | - Megan E Piper
- Center for Tobacco Research and Intervention, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Tanya R Schlam
- Center for Tobacco Research and Intervention, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Daniel M Bolt
- Department of Educational Psychology, University of Wisconsin, WI, USA
| | - Stevens S Smith
- Center for Tobacco Research and Intervention, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Deejay Zwaga
- Center for Tobacco Research and Intervention, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Douglas E Jorenby
- Center for Tobacco Research and Intervention, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Robin Mermelstein
- Institute for Health Research and Policy, University of Illinois at Chicago, Chicago, IL, USA
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20
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Baker TB, Piper ME, Smith SS, Bolt DM, Stein JH, Fiore MC. Effects of Combined Varenicline With Nicotine Patch and of Extended Treatment Duration on Smoking Cessation: A Randomized Clinical Trial. JAMA 2021; 326:1485-1493. [PMID: 34665204 PMCID: PMC8527361 DOI: 10.1001/jama.2021.15333] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Importance Smoking cessation medications are routinely used in health care. Research suggests that combining varenicline with the nicotine patch, extending the duration of varenicline treatment, or both, may increase cessation effectiveness. Objective To compare combinations of varenicline plus the nicotine or placebo patch vs combinations used for either 12 weeks (standard duration) or 24 weeks (extended duration). Design, Settings, and Participants Double-blind, 2 × 2 factorial randomized clinical trial conducted from November 11, 2017, to July 9, 2020, at 1 research clinic in Madison, Wisconsin, and at 1 clinic in Milwaukee, Wisconsin. Of the 5836 adults asked to participate in the study, 1251 who smoked 5 cigarettes/d or more were randomized. Interventions All participants received cessation counseling and were randomized to 1 of 4 medication groups: varenicline monotherapy for 12 weeks (n = 315), varenicline plus nicotine patch for 12 weeks (n = 314), varenicline monotherapy for 24 weeks (n = 311), or varenicline plus nicotine patch for 24 weeks (n = 311). Main Outcomes and Measures The primary outcome was carbon monoxide-confirmed self-reported 7-day point prevalence abstinence at 52 weeks. Results Among 1251 patients who were randomized (mean [SD] age, 49.1 [11.9] years; 675 [54.0%] women), 751 (60.0%) completed treatment and 881 (70.4%) provided final follow-up. For the primary outcome, there was no significant interaction between the 2 treatment factors of medication type and medication duration (odds ratio [OR], 1.03 [95% CI, 0.91 to 1.17]; P = .66). For patients randomized to 24-week vs 12-week treatment duration, the primary outcome occurred in 24.8% (154/622) vs 24.3% (153/629), respectively (risk difference, -0.4% [95% CI, -5.2% to 4.3%]; OR, 1.01 [95% CI, 0.89 to 1.15]). For patients randomized to varenicline combination therapy vs varenicline monotherapy, the primary outcome occurred in 24.3% (152/625) vs 24.8% (155/626), respectively (risk difference, 0.4% [95% CI, -4.3% to 5.2%]; OR, 0.99 [95% CI, 0.87 to 1.12]). Nausea occurrence ranged from 24.0% to 30.9% and insomnia occurrence ranged from 24.4% to 30.5% across the 4 groups. Conclusions and Relevance Among adults smoking 5 cigarettes/d or more, there were no significant differences in 7-day point prevalence abstinence at 52 weeks among those treated with combined varenicline plus nicotine patch therapy vs varenicline monotherapy, or among those treated for 24 weeks vs 12 weeks. These findings do not support the use of combined therapy or of extended treatment duration. Trial Registration ClinicalTrials.gov Identifier: NCT03176784.
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Affiliation(s)
- Timothy B Baker
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin, Madison
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin, Madison
| | - Megan E Piper
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin, Madison
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin, Madison
| | - Stevens S Smith
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin, Madison
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin, Madison
| | - Daniel M Bolt
- Department of Educational Psychology, University of Wisconsin, Madison
| | - James H Stein
- Division of Cardiovascular Medicine, Department of Medicine, School of Medicine and Public Health, University of Wisconsin, Madison
| | - Michael C Fiore
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin, Madison
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin, Madison
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21
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Goldberg SB, Bolt DM, Davidson RJ. Data Missing Not at Random in Mobile Health Research: Assessment of the Problem and a Case for Sensitivity Analyses. J Med Internet Res 2021; 23:e26749. [PMID: 34128810 PMCID: PMC8277392 DOI: 10.2196/26749] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 02/01/2021] [Accepted: 05/06/2021] [Indexed: 01/29/2023] Open
Abstract
Background Missing data are common in mobile health (mHealth) research. There has been little systematic investigation of how missingness is handled statistically in mHealth randomized controlled trials (RCTs). Although some missing data patterns (ie, missing at random [MAR]) may be adequately addressed using modern missing data methods such as multiple imputation and maximum likelihood techniques, these methods do not address bias when data are missing not at random (MNAR). It is typically not possible to determine whether the missing data are MAR. However, higher attrition in active (ie, intervention) versus passive (ie, waitlist or no treatment) conditions in mHealth RCTs raise a strong likelihood of MNAR, such as if active participants who benefit less from the intervention are more likely to drop out. Objective This study aims to systematically evaluate differential attrition and methods used for handling missingness in a sample of mHealth RCTs comparing active and passive control conditions. We also aim to illustrate a modern model-based sensitivity analysis and a simpler fixed-value replacement approach that can be used to evaluate the influence of MNAR. Methods We reanalyzed attrition rates and predictors of differential attrition in a sample of 36 mHealth RCTs drawn from a recent meta-analysis of smartphone-based mental health interventions. We systematically evaluated the design features related to missingness and its handling. Data from a recent mHealth RCT were used to illustrate 2 sensitivity analysis approaches (pattern-mixture model and fixed-value replacement approach). Results Attrition in active conditions was, on average, roughly twice that of passive controls. Differential attrition was higher in larger studies and was associated with the use of MAR-based multiple imputation or maximum likelihood methods. Half of the studies (18/36, 50%) used these modern missing data techniques. None of the 36 mHealth RCTs reviewed conducted a sensitivity analysis to evaluate the possible consequences of data MNAR. A pattern-mixture model and fixed-value replacement sensitivity analysis approaches were introduced. Results from a recent mHealth RCT were shown to be robust to missing data, reflecting worse outcomes in missing versus nonmissing scores in some but not all scenarios. A review of such scenarios helps to qualify the observations of significant treatment effects. Conclusions MNAR data because of differential attrition are likely in mHealth RCTs using passive controls. Sensitivity analyses are recommended to allow researchers to assess the potential impact of MNAR on trial results.
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Affiliation(s)
- Simon B Goldberg
- Department of Counseling Psychology, University of Wisconsin - Madison, Madison, WI, United States.,Center for Healthy Minds, University of Wisconsin - Madison, Madison, WI, United States
| | - Daniel M Bolt
- Department of Educational Psychology, University of Wisconsin - Madison, Madison, WI, United States
| | - Richard J Davidson
- Center for Healthy Minds, University of Wisconsin - Madison, Madison, WI, United States.,Department of Psychology, University of Wisconsin - Madison, Madison, WI, United States.,Department of Psychiatry, University of Wisconsin - Madison, Madison, WI, United States
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22
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Kent RD, Eichhorn J, Wilson EM, Suk Y, Bolt DM, Vorperian HK. Auditory-Perceptual Features of Speech in Children and Adults With Down Syndrome: A Speech Profile Analysis. J Speech Lang Hear Res 2021; 64:1157-1175. [PMID: 33789057 PMCID: PMC8608145 DOI: 10.1044/2021_jslhr-20-00617] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Revised: 01/02/2021] [Accepted: 01/03/2021] [Indexed: 05/17/2023]
Abstract
Purpose The aim of this study was to determine how the speech disorder profiles in Down syndrome (DS) relate to reduced intelligibility, atypical overall quality, and impairments in the subsystems of speech production (phonation, articulation, resonance, and prosody). Method Auditory-perceptual ratings of intelligibility, overall quality, and features associated with the subsystems of speech production were obtained from recordings of 79 children and adults with DS. Ratings were made for sustained vowels (62 of 79 speakers) and short sentences (79 speakers). The data were analyzed to determine the severity of the affected features in each speaking task and to detect patterns in the group data by means of principal components analysis. Results Reduced intelligibility was noted in 90% of the speakers, and atypical overall speech quality was noted in 100%. Affected speech features were distributed across the speech production subsystems. Principal components analysis revealed four components each for the vowel and sentence tasks, showing that individuals with DS are not homogeneous in the features of their speech disorder. Discussion The speech disorder in DS is complex in its perceptual features and reflects impairments across the subsystems of speech production, but the pattern is not uniform across individuals, indicating that attention must be given to individual variation in designing treatments.
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23
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Abstract
The assessment of tobacco withdrawal is important for both research and clinical purposes. This study describes the psychometric development of a revised version of the 28-item Wisconsin Smoking Withdrawal Scale (WSWS; Welsch et al., Experimental and Clinical Psychopharmacology, 1999, 7, p. 354). Because the different contexts of use sometimes permit only brief assessment, this revision has produced both a brief and longer form using an updated pool of candidate items. For the revised Wisconsin Smoking Withdrawal Scale 2 (WSWS2), a candidate pool of 37 items was developed to measure nine putative withdrawal constructs. The stem and wording of items were revised as was the response scale. Data for psychometric analyses were derived from three smoking cessation randomized clinical trials conducted at the University of Wisconsin Center for Tobacco Research and Intervention. Dimensionality, internal consistency, and item characteristic analyses of the candidate items were conducted in a derivation sample to ascertain the factor structure and to identify items that could be used in the WSWS2 scales. Confirmatory factor analyses (CFAs) of reduced item sets and factor structure were conducted in two validation samples along with reliability and validity analyses. Derivation and validation sample analyses yielded a longer version of the WSWS2 (WSWS2-L) with 19 items and six subscales (Craving, Negative Affect, Hunger, Sleep, Restlessness, and Concentration) and a brief 6-item version (WSWS2-B). In validation sample analyses, both the WSWS2-L and the WSWS2-B demonstrated good reliability and validity as well as good fit in CFAs. The WSWS2-L and WSWS2-B possess improved construct coverage, fewer items, and other enhancements relative to the WSWS. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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Affiliation(s)
- Stevens S. Smith
- Center for Tobacco Research and Intervention, University of Wisconsin School of Medicine and Public Health, Madison, WI
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI
| | - Megan E. Piper
- Center for Tobacco Research and Intervention, University of Wisconsin School of Medicine and Public Health, Madison, WI
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI
| | - Daniel M. Bolt
- Department of Educational Psychology, University of Wisconsin-Madison, Madison, WI
| | - Jesse T. Kaye
- Center for Tobacco Research and Intervention, University of Wisconsin School of Medicine and Public Health, Madison, WI
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI
- William S. Middleton Memorial Veterans Hospital, Madison, WI
| | - Michael C. Fiore
- Center for Tobacco Research and Intervention, University of Wisconsin School of Medicine and Public Health, Madison, WI
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI
| | - Timothy B. Baker
- Center for Tobacco Research and Intervention, University of Wisconsin School of Medicine and Public Health, Madison, WI
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI
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24
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Abstract
This paper presents a mixture item response tree (IRTree) model for extreme response style. Unlike traditional applications of single IRTree models, a mixture approach provides a way of representing the mixture of respondents following different underlying response processes (between individuals), as well as the uncertainty present at the individual level (within an individual). Simulation analyses reveal the potential of the mixture approach in identifying subgroups of respondents exhibiting response behavior reflective of different underlying response processes. Application to real data from the Students Like Learning Mathematics (SLM) scale of Trends in International Mathematics and Science Study (TIMSS) 2015 demonstrates the superior comparative fit of the mixture representation, as well as the consequences of applying the mixture on the estimation of content and response style traits. We argue that methodology applied to investigate response styles should attend to the inherent uncertainty of response style influence due to the likely influence of both response styles and the content trait on the selection of extreme response categories.
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Affiliation(s)
- Nana Kim
- University of Wisconsin–Madison, Madison, WI, USA
- Nana Kim, Department of Educational Psychology, University of Wisconsin–Madison, 1025 West Johnson Street, Madison, WI 53706, USA.
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25
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Ford JH, Kaur A, Rao D, Gilson A, Bolt DM, Garneau HC, Saldana L, McGovern MP. Improving Medication Access within Integrated Treatment for Individuals with Co-Occurring Disorders in Substance Use Treatment Agencies. Implement Res Pract 2021; 2. [PMID: 34988462 PMCID: PMC8726008 DOI: 10.1177/26334895211033659] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Background The best approach to provide comprehensive care for individuals with co-occurring disorders (CODs) related to substance use and mental health is to address both disorders through an integrated treatment approach. However, only 25% of behavioral health agencies offer integrated care and less than 7% of individuals who need integrated treatment receive it. A project used a cluster-randomized waitlist control group design to evaluate the effectiveness of Network for the Improvement of Addiction Treatment (NIATx) implementation strategies to improve access to addiction and psychotropic medications. Methods This study represents a secondary analysis of data from the NIATx project. Forty-nine agencies were randomized to Cohort1 (active implementation group, receiving the NIATx strategy [n=25]) or Cohort2 (waitlist control group [n=24]). Data were collected at three time points (Baseline, Year1 and Year2). A two-level (patient within agency) multinomial logistic regression model investigated the effects of implementation strategy condition on one of four medication outcomes: both medication types, only psychotropic medication, only addiction medication, or neither medication type. A per-protocol analysis included time, NIATx fidelity, and agency focus as predictors. Results The intent-to-treat analysis found a statistically significant change in access to addiction versus neither medication, but Cohort1 compared to Cohort2 at Year1 showed no differences. Changes were associated with the experimental intervention and occurred in the transition from Year 1 to Year 2, where greater increases were seen for agencies in Cohort2 versus Cohort1. The per-protocol analysis showed increased access to both medications and addiction medications from pre- to post-intervention for agencies in both cohorts; however, differences in change between high- and low-implementation agencies were not significant. Conclusions Access to integrated services for people with CODs is a long-standing problem. NIATx implementation strategies had limited effectiveness in improving medication access for individuals with CODs. Implementation strategy adherence is associated with increased medication access.
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Affiliation(s)
- James H Ford
- School of Pharmacy, Social and Administrative Sciences Division, University of Wisconsin - Madison
| | - Arveen Kaur
- School of Pharmacy, Social and Administrative Sciences Division, University of Wisconsin - Madison
| | - Deepika Rao
- School of Pharmacy, Social and Administrative Sciences Division, University of Wisconsin - Madison
| | - Aaron Gilson
- School of Pharmacy, Social and Administrative Sciences Division, University of Wisconsin - Madison
| | - Daniel M Bolt
- School of Education, Educational Psychology Division, University of Wisconsin - Madison
| | - Helene Chokron Garneau
- Center for Behavioral Health Services and Implementation Research, Division of Public Health & Population Sciences, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine
| | | | - Mark P McGovern
- Center for Behavioral Health Services and Implementation Research, Division of Public Health & Population Sciences, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine.,Division of Primary Care and Population Health, Department of Medicine, Stanford University School of Medicine
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26
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Goldberg SB, Imhoff-Smith T, Bolt DM, Wilson-Mendenhall CD, Dahl CJ, Davidson RJ, Rosenkranz MA. Testing the Efficacy of a Multicomponent, Self-Guided, Smartphone-Based Meditation App: Three-Armed Randomized Controlled Trial. JMIR Ment Health 2020; 7:e23825. [PMID: 33245288 PMCID: PMC7732708 DOI: 10.2196/23825] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Revised: 10/23/2020] [Accepted: 10/26/2020] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND A growing number of randomized controlled trials (RCTs) suggest psychological benefits associated with meditation training delivered via mobile health. However, research in this area has primarily focused on mindfulness, only one of many meditative techniques. OBJECTIVE This study aims to evaluate the efficacy of 2 versions of a self-guided, smartphone-based meditation app-the Healthy Minds Program (HMP)-which includes training in mindfulness (Awareness), along with practices designed to cultivate positive relationships (Connection) or insight into the nature of the self (Insight). METHODS A three-arm, fully remote RCT compared 8 weeks of one of 2 HMP conditions (Awareness+Connection and Awareness+Insight) with a waitlist control. Adults (≥18 years) without extensive previous meditation experience were eligible. The primary outcome was psychological distress (depression, anxiety, and stress). Secondary outcomes were social connection, empathy, compassion, self-reflection, insight, rumination, defusion, and mindfulness. Measures were completed at pretest, midtreatment, and posttest between October 2019 and April 2020. Longitudinal data were analyzed using intention-to-treat principles with maximum likelihood. RESULTS A total of 343 participants were randomized and 186 (54.2%) completed at least one posttest assessment. The majority (166/228, 72.8%) of those assigned to HMP conditions downloaded the app. The 2 HMP conditions did not differ from one another in terms of changes in any outcome. Relative to the waitlist control, the HMP conditions showed larger improvements in distress, social connectedness, mindfulness, and measures theoretically linked to insight training (d=-0.28 to 0.41; Ps≤.02), despite modest exposure to connection- and insight-related practice. The results were robust to some assumptions about nonrandom patterns of missing data. Improvements in distress were associated with days of use. Candidate mediators (social connection, insight, rumination, defusion, and mindfulness) and moderators (baseline rumination, defusion, and empathy) of changes in distress were identified. CONCLUSIONS This study provides initial evidence of efficacy for the HMP app in reducing distress and improving outcomes related to well-being, including social connectedness. Future studies should attempt to increase study retention and user engagement. TRIAL REGISTRATION ClinicalTrials.gov NCT04139005; https://clinicaltrials.gov/ct2/show/NCT04139005.
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Affiliation(s)
- Simon B Goldberg
- Center for Healthy Minds, University of Wisconsin, Madison, WI, United States
- Department of Counseling Psychology, University of Wisconsin-Madison, Madison, WI, United States
| | | | - Daniel M Bolt
- Department of Educational Psychology, University of Wisconsin-Madison, Madison, WI, United States
| | | | - Cortland J Dahl
- Center for Healthy Minds, University of Wisconsin, Madison, WI, United States
- Healthy Minds Innovations Inc, Madison, WI, United States
| | - Richard J Davidson
- Center for Healthy Minds, University of Wisconsin, Madison, WI, United States
- Department of Psychology, University of Wisconsin-Madison, Madison, WI, United States
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, United States
| | - Melissa A Rosenkranz
- Center for Healthy Minds, University of Wisconsin, Madison, WI, United States
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, United States
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Schlam TR, Baker TB, Smith SS, Bolt DM, McCarthy DE, Cook JW, Hayes-Birchler T, Fiore MC, Piper ME. Electronically Monitored Nicotine Gum Use Before and After Smoking Lapses: Relationship With Lapse and Relapse. Nicotine Tob Res 2020; 22:2051-2058. [PMID: 32598468 DOI: 10.1093/ntr/ntaa116] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2020] [Accepted: 06/22/2020] [Indexed: 11/14/2022]
Abstract
INTRODUCTION Greater use of nicotine replacement therapy (NRT) is related to smoking cessation success, but the causal direction is unclear. This study characterized the relationship between NRT use and smoking lapse and relapse. METHODS Participants (N = 416 smokers; 57% female, 85% White) were recruited from primary care for a smoking cessation factorial experiment and analyzed if abstaining ≥1 day in the first 2 weeks post-target quit day (TQD). Participants were randomized to counseling and 8 versus 26 weeks of nicotine patch plus nicotine gum post-TQD. Participants carried electronic dispensers that timestamped each gum use. Participants who lapsed (smoked after abstaining) within 6 weeks post-TQD were matched with nonlapsers (n = 146 pairs) on multiple variables. We compared lapsers' versus matched nonlapsers' gum use in the 5 days before and after the lapsers' first lapse. RESULTS By week 6 post-TQD, 63% of participants lapsed. Compared with nonlapsers, lapsers used less gum 1 and 2 days pre-"lapse" and on the 5 days post-lapse. Lapsers used less gum during the 5 days post-lapse than the 5 days pre-lapse. Univariate survival analyses with lapsers showed greater gum use during both pre- and post-lapse periods predicted longer latency to relapse in the first 6 weeks. CONCLUSIONS In a smoking cessation attempt using nicotine patch plus gum, lapsers versus matched nonlapsers used less gum immediately preceding and following their first lapse. Lower mean gum use before and after lapses predicted a more rapid escalation to relapse. Decreased nicotine gum use both precedes and follows returns to smoking during cessation attempts. IMPLICATIONS This research examined electronically monitored nicotine gum use collected in real time and found that among smokers engaged in a quit attempt, lapsers (vs. matched nonlapsers) tended to decrease their gum use 1-2 days prior to lapsing and to further decrease their gum use from pre- to post-lapse. Decreased gum use pre-lapse may signal heightened lapse risk in 1-2 days, with lower level of gum use predicting a more precipitous course of relapse. These results encourage further exploration of objective measures of smoking medication use patterns to examine their signaling properties and to inform understanding of cessation failure. CLINICAL TRIAL REGISTRATION ClinicalTrials.gov NCT01120704.
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Affiliation(s)
- Tanya R Schlam
- Center for Tobacco Research and Intervention, University of Wisconsin School of Medicine and Public Health, Madison, WI.,Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI
| | - Timothy B Baker
- Center for Tobacco Research and Intervention, University of Wisconsin School of Medicine and Public Health, Madison, WI.,Division of General Internal Medicine, Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI
| | - Stevens S Smith
- Center for Tobacco Research and Intervention, University of Wisconsin School of Medicine and Public Health, Madison, WI.,Division of General Internal Medicine, Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI
| | - Daniel M Bolt
- Department of Educational Psychology, University of Wisconsin-Madison, Madison, WI
| | - Danielle E McCarthy
- Center for Tobacco Research and Intervention, University of Wisconsin School of Medicine and Public Health, Madison, WI.,Division of General Internal Medicine, Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI
| | - Jessica W Cook
- Center for Tobacco Research and Intervention, University of Wisconsin School of Medicine and Public Health, Madison, WI.,Division of General Internal Medicine, Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI.,William S. Middleton Memorial Veterans Hospital, Madison, WI
| | - Todd Hayes-Birchler
- Center for Tobacco Research and Intervention, University of Wisconsin School of Medicine and Public Health, Madison, WI
| | - Michael C Fiore
- Center for Tobacco Research and Intervention, University of Wisconsin School of Medicine and Public Health, Madison, WI.,Division of General Internal Medicine, Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI
| | - Megan E Piper
- Center for Tobacco Research and Intervention, University of Wisconsin School of Medicine and Public Health, Madison, WI.,Division of General Internal Medicine, Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI
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Bolt DM, Kim N, Wollack J, Pan Y, Eckerly C, Sowles J. A Psychometric Model for Discrete-Option Multiple-Choice Items. Appl Psychol Meas 2020; 44:33-48. [PMID: 31853157 PMCID: PMC6906389 DOI: 10.1177/0146621619835499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Discrete-option multiple-choice (DOMC) items differ from traditional multiple-choice (MC) items in the sequential administration of response options (up to display of the correct option). DOMC can be appealing in computer-based test administrations due to its protection of item security and its potential to reduce testwiseness effects. A psychometric model for DOMC items that attends to the random positioning of key location across different administrations of the same item is proposed, a feature that has been shown to affect DOMC item difficulty. Using two empirical data sets having items administered in both DOMC and MC formats, the variability in key location effects across both items and persons is considered. The proposed model exploits the capacity of the DOMC format to isolate both (a) distinct sources of item difficulty (i.e., related to the identification of keyed responses versus the ruling out of distractor options) and (b) distinct person proficiencies related to the same two components. Practical implications in terms of the randomized process applied to schedule item key location in DOMC test administrations are considered.
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Affiliation(s)
| | - Nana Kim
- University of Wisconsin–Madison,
USA
| | | | - Yiqin Pan
- University of Wisconsin–Madison,
USA
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Bolt DM, Ysseldyke J, Patterson MJ. Students, Teachers, and Schools as Sources of Variability, Integrity, and Sustainability in Implementing Progress Monitoring. School Psychology Review 2019. [DOI: 10.1080/02796015.2010.12087746] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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Vorperian HK, Kent RD, Lee Y, Bolt DM. Corner vowels in males and females ages 4 to 20 years: Fundamental and F1-F4 formant frequencies. J Acoust Soc Am 2019; 146:3255. [PMID: 31795713 PMCID: PMC6850954 DOI: 10.1121/1.5131271] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2019] [Revised: 09/06/2019] [Accepted: 10/08/2019] [Indexed: 05/29/2023]
Abstract
The purpose of this study was to determine the developmental trajectory of the four corner vowels' fundamental frequency (fo) and the first four formant frequencies (F1-F4), and to assess when speaker-sex differences emerge. Five words per vowel, two of which were produced twice, were analyzed for fo and estimates of the first four formants frequencies from 190 (97 female, 93 male) typically developing speakers ages 4-20 years old. Findings revealed developmental trajectories with decreasing values of fo and formant frequencies. Sex differences in fo emerged at age 7. The decrease of fo was larger in males than females with a marked drop during puberty. Sex differences in formant frequencies appeared at the earliest age under study and varied with vowel and formant. Generally, the higher formants (F3-F4) were sensitive to sex differences. Inter- and intra-speaker variability declined with age but had somewhat different patterns, likely reflective of maturing motor control that interacts with the changing anatomy. This study reports a source of developmental normative data on fo and the first four formants in both sexes. The different developmental patterns in the first four formants and vowel-formant interactions in sex differences likely point to anatomic factors, although speech-learning phenomena cannot be discounted.
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Affiliation(s)
- Houri K Vorperian
- Vocal Tract Development Laboratory, Waisman Center, University of Wisconsin-Madison, 1500 Highland Avenue, Madison, Wisconsin 53705, USA
| | - Raymond D Kent
- Vocal Tract Development Laboratory, Waisman Center, University of Wisconsin-Madison, 1500 Highland Avenue, Madison, Wisconsin 53705, USA
| | - Yen Lee
- Department of Educational Psychology, University of Wisconsin-Madison, 1086 Educational, Sciences Building, 1025 West Johnson Street, Madison, Wisconsin 53706, USA
| | - Daniel M Bolt
- Department of Educational Psychology, University of Wisconsin-Madison, 1086 Educational, Sciences Building, 1025 West Johnson Street, Madison, Wisconsin 53706, USA
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Adams DJ, Bolt DM, Deng S, Smith SS, Baker TB. Using multidimensional item response theory to evaluate how response styles impact measurement. Br J Math Stat Psychol 2019; 72:466-485. [PMID: 30919943 PMCID: PMC6765459 DOI: 10.1111/bmsp.12169] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2018] [Revised: 02/21/2019] [Indexed: 05/25/2023]
Abstract
Multidimensional item response theory (MIRT) models for response style (e.g., Bolt, Lu, & Kim, 2014, Psychological Methods, 19, 528; Falk & Cai, 2016, Psychological Methods, 21, 328) provide flexibility in accommodating various response styles, but often present difficulty in isolating the effects of response style(s) from the intended substantive trait(s). In the presence of such measurement limitations, we consider several ways in which MIRT models are nevertheless useful in lending insight into how response styles may interfere with measurement for a given test instrument. Such a study can also inform whether alternative design considerations (e.g., anchoring vignettes, self-report items of heterogeneous content) that seek to control for response style effects may be helpful. We illustrate several aspects of an MIRT approach using real and simulated analyses.
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Affiliation(s)
- Daniel J Adams
- Department of Educational Psychology, University of Wisconsin, Madison, Wisconsin, USA
| | - Daniel M Bolt
- Department of Educational Psychology, University of Wisconsin, Madison, Wisconsin, USA
| | | | - Stevens S Smith
- Department of Medicine, University of Wisconsin, Madison, Wisconsin, USA
| | - Timothy B Baker
- Department of Medicine, University of Wisconsin, Madison, Wisconsin, USA
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Plate RC, Bloomberg Z, Bolt DM, Bechner AM, Roeber BJ, Pollak SD. Abused Children Experience High Anger Exposure. Front Psychol 2019; 10:440. [PMID: 30890983 PMCID: PMC6411659 DOI: 10.3389/fpsyg.2019.00440] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2018] [Accepted: 02/13/2019] [Indexed: 11/13/2022] Open
Abstract
Childhood maltreatment is a critical problem in the United States. Much attention has been paid to the negative outcomes suffered by victims of abuse. Less attention has been devoted to understanding the emotional environments of maltreated children. One assumption, which has stood without empirical test, is that abused children encounter a high degree of anger in their home environments. Anger exposure is thought to be a source of stress for children in abusive environments and a potential link between the experience of abuse and the development of health and behavioral problems. We tested this notion by assessing data on over 1,000 parents and guardians of 3- to 17-year-old children who were participants in child development studies. Abuse was measured via records from Child Protective Services regarding substantiated and unsubstantiated claims of abuse as well as parent/guardian report. We compared self-reported experiences of anger from parents/guardians of children who have experienced abuse with those who have not. We found support for the claim that caregivers of abused children experience and express high levels of anger. Better characterization of the emotional environments in which abused children develop is critical for understanding how and why abuse affects children and has important implications for informing interventions.
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Affiliation(s)
- Rista C Plate
- Department of Psychology, University of Wisconsin-Madison, Madison, WI, United States.,Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
| | - Zachary Bloomberg
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
| | - Daniel M Bolt
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
| | - Anna M Bechner
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
| | - Barbara J Roeber
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
| | - Seth D Pollak
- Department of Psychology, University of Wisconsin-Madison, Madison, WI, United States.,Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
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Bolt DM, Lee S, Wollack J, Eckerly C, Sowles J. Application of Asymmetric IRT Modeling to Discrete-Option Multiple-Choice Test Items. Front Psychol 2018; 9:2175. [PMID: 30483187 PMCID: PMC6240662 DOI: 10.3389/fpsyg.2018.02175] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2018] [Accepted: 10/22/2018] [Indexed: 11/13/2022] Open
Abstract
Asymmetric IRT models have been shown useful for capturing heterogeneity in the number of latent subprocesses underlying educational test items (Lee and Bolt, 2018a). One potentially useful practical application of such models is toward the scoring of discrete-option multiple-choice (DOMC) items. Under the DOMC format, response options are independently and randomly administered up to the (last) keyed response, and thus the scheduled number of distractor response options to which an examinee may be exposed (and consequently the overall difficulty of the item) can vary. In this paper we demonstrate the applicability of Samejima's logistic positive exponent (LPE) model to response data from an information technology certification test administered using the DOMC format, and discuss its advantages relative to a two-parameter logistic (2PL) model in addressing such effects. Application of the LPE in the context of DOMC items is shown to (1) provide reduced complexity and a superior comparative fit relative to the 2PL, and (2) yield a latent metric with reduced shrinkage at high proficiency levels. The results support the potential use of the LPE as a basis for scoring DOMC items so as to account for effects related to key location.
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Affiliation(s)
- Daniel M Bolt
- Department of Educational Psychology, University of Wisconsin-Madison, Madison, WI, United States
| | - Sora Lee
- Department of Educational Psychology, University of Wisconsin-Madison, Madison, WI, United States
| | - James Wollack
- Department of Educational Psychology, University of Wisconsin-Madison, Madison, WI, United States
| | - Carol Eckerly
- Educational Testing Service, Princeton, NJ, United States
| | - John Sowles
- Ericsson, Inc., Santa Clara, CA, United States
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Fink JT, Magnan EM, Johnson HM, Bednarz LM, Allen GO, Greenlee RT, Bolt DM, Smith MA. Blood Pressure Control and Other Quality of Care Metrics for Patients with Obesity and Diabetes: A Population-Based Cohort Study. High Blood Press Cardiovasc Prev 2018; 25:391-399. [PMID: 30328045 DOI: 10.1007/s40292-018-0284-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2018] [Accepted: 10/03/2018] [Indexed: 10/28/2022] Open
Abstract
INTRODUCTION There are no population-level estimates in the United States for achievement of blood pressure goals in patients with diabetes and hypertension by obesity weight class. AIM We sought to examine the relationship between the extent of obesity and the achievement of guideline-recommended blood pressure goals and other quality of care metrics among patients with diabetes. METHODS We conducted an observational population-based cohort study of electronic health data of three large health systems from 2010-2012 in rural, urban and suburban settings of 51,229 adults with diabetes. Outcomes were achievement of diabetes quality of care metrics: blood pressure, A1c, and LDL control, and A1c and LDL testing. Two blood pressure goals were examined given the recommendation for adults with diabetes of 130/80 mmHg from JNC7 and the recommendation of 140/90 mmHg from JNC8 in 2014. RESULTS Patients in obesity classes I, II, and III with diagnosed hypertension were less likely to achieve blood pressure control at both the 140/90 mmHg and 130/80 mmHg control levels. The patients from obesity class III had the lowest likelihood of achieving control at the 130/80 mmHg goal, and control was markedly worse for the 130/80 mmHg threshold in all weight classes. There were minimal to no differences by weight class in LDL and A1c control and LDL and A1c testing. CONCLUSIONS Although the cardiovascular risk for patients with obesity and diabetes is greater than for non-obese patients with diabetes, we found that patients with obesity are even further behind in achieving blood pressure control.
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Affiliation(s)
- Jennifer T Fink
- Department of Health Informatics and Administration, College of Health Sciences, University of Wisconsin-Milwaukee, Milwaukee, WI, USA.,Aurora Research Institute, Aurora Health Care, Milwaukee, WI, USA
| | - Elizabeth M Magnan
- Department of Family and Community Medicine, University of California, Davis, Sacramento, CA, USA
| | - Heather M Johnson
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Lauren M Bednarz
- Health Innovation Program, University of Wisconsin School of Medicine and Public Health, 800 University Bay Dr., Suite 210-31, Madison, WI, 53705, USA.,Department of Population Health Sciences, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Glenn O Allen
- Department of Urology, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Robert T Greenlee
- Center for Clinical Epidemiology and Population Health, Marshfield Clinic Research Institute, Marshfield, WI, USA
| | - Daniel M Bolt
- Department of Educational Psychology, University of Wisconsin School of Education, Madison, WI, USA
| | - Maureen A Smith
- Health Innovation Program, University of Wisconsin School of Medicine and Public Health, 800 University Bay Dr., Suite 210-31, Madison, WI, 53705, USA. .,Department of Population Health Sciences, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA. .,Department of Family Medicine and Community Health, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
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Schlam TR, Cook JW, Baker TB, Hayes-Birchler T, Bolt DM, Smith SS, Fiore MC, Piper ME. Can we increase smokers' adherence to nicotine replacement therapy and does this help them quit? Psychopharmacology (Berl) 2018; 235:2065-2075. [PMID: 29696311 PMCID: PMC6141024 DOI: 10.1007/s00213-018-4903-y] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2017] [Accepted: 04/10/2018] [Indexed: 12/01/2022]
Abstract
OBJECTIVE To examine the effects of five intervention components on smokers' adherence to combined nicotine patch and nicotine gum during a quit attempt and assess whether adherence is related to cessation. METHOD Smokers interested in quitting (N = 513; 59% female; 87% White) received nicotine patch plus nicotine gum and participated in a 2x2x2x2x2 randomized factorial experiment (i.e., 32 treatment conditions) evaluating five intervention components: (1) medication adherence counseling versus none; (2) automated medication adherence calls versus none; (3) electronic medication monitoring with feedback and counseling versus e-monitoring alone; (4) 26 versus 8 weeks of nicotine patch plus nicotine gum; and (5) maintenance counseling versus none. Adherence was assessed over the first 6 weeks post-target quit day via timeline follow-back (nicotine patch) and electronic medication dispenser (gum). RESULTS In the first 6 weeks post-quit day, 12% of participants used no patches or gum, and 40% used the patch every day. Only 1.4% used both patch and gum adherently every day in the 6 weeks post-target quit day. E-monitoring counseling increased gum use (from 1.9 to 2.6 pieces/day; p < .001) but did not increase abstinence. More adherent patch and gum use in the first 6 weeks were each associated with higher point-prevalence abstinence rates through 1 year. CONCLUSIONS This large experiment with electronic monitoring of nicotine gum adherence showed that e-monitoring counseling increased gum use but not abstinence. Adherence to nicotine patch and to gum were each strongly related to abstinence, but it is unclear whether adherence increases abstinence, or relapse causes medication discontinuation. CLINICAL TRIAL REGISTRATION ClinicalTrials.gov NCT01120704.
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Affiliation(s)
- Tanya R Schlam
- Center for Tobacco Research and Intervention, Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, 1930 Monroe Street, Suite 200, Madison, WI, 53711, USA.
| | - Jessica W Cook
- Center for Tobacco Research and Intervention, Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, 1930 Monroe Street, Suite 200, Madison, WI, 53711, USA
- Division of General Internal Medicine, Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
- William S. Middleton Memorial Veterans Hospital, Madison, WI, USA
| | - Timothy B Baker
- Center for Tobacco Research and Intervention, Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, 1930 Monroe Street, Suite 200, Madison, WI, 53711, USA
- Division of General Internal Medicine, Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Todd Hayes-Birchler
- Center for Tobacco Research and Intervention, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Daniel M Bolt
- Department of Educational Psychology, University of Wisconsin-Madison, Madison, WI, USA
| | - Stevens S Smith
- Center for Tobacco Research and Intervention, Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, 1930 Monroe Street, Suite 200, Madison, WI, 53711, USA
- Division of General Internal Medicine, Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Michael C Fiore
- Center for Tobacco Research and Intervention, Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, 1930 Monroe Street, Suite 200, Madison, WI, 53711, USA
- Division of General Internal Medicine, Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Megan E Piper
- Center for Tobacco Research and Intervention, Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, 1930 Monroe Street, Suite 200, Madison, WI, 53711, USA
- Division of General Internal Medicine, Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
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Bryant HA, Dixon JJ, Weller R, Bolt DM. Use of positive contrast radiography to identify synovial involvement in horses with traumatic limb wounds. Equine Vet J 2018; 51:20-23. [PMID: 29931725 DOI: 10.1111/evj.12985] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2018] [Accepted: 06/18/2018] [Indexed: 11/29/2022]
Abstract
BACKGROUND The diagnostic value of positive contrast radiography in the work-up of suspected synovial infection in horses with limb wounds near synovial structures has yet to be systematically evaluated. OBJECTIVES To determine the specificity, sensitivity and positive and negative predictive values of positive contrast radiography for identification of synovial infection in a population of horses with limb wounds. STUDY DESIGN Retrospective case study comparing the performance of positive contrast radiography to the gold standard of synovial fluid cytology in horses presenting with limb wounds in the vicinity of synovial structures. METHODS Case records of horses presenting to the Royal Veterinary College Equine Hospital between 2010 and 2015 with limb wounds that may have compromised adjacent synovial structures were analysed. Synovial fluid cytology results were used to categorise synovial structures in infected and noninfected groups. Positive contrast radiography results were compared between infected and noninfected groups and sensitivity, specificity, positive and negative predictive values were calculated. RESULTS Fifty horses with 66 synovial structures were included in the study. Positive contrast radiography had a high specificity (86.4%), but only a moderate sensitivity (59.1%) for the identification of synovial infection. In addition, a low positive predictive value (68.4%) and high negative predictive value (80.9%) were observed in this population of horses. MAIN LIMITATIONS Sensitivity, specificity and predictive values may differ between different synovial structures and cases. Different conclusions may be drawn from the results in a single population. Sensitivity and specificity of positive contrast radiography may also be influenced by different techniques used by examiners and by inherent characteristics of individual cases. CONCLUSIONS Positive contrast radiography should be used for the investigation of potential synovial infection in horses with limb wounds, particularly if no synovial fluid sample for laboratory analysis can be obtained. However, it appears that positive contrast radiography is best used in combination with other tests to ensure that a correct and timely diagnosis is made.
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Affiliation(s)
- H A Bryant
- Department of Clinical Science & Services, Royal Veterinary College, Hatfield, Hertfordshire, UK
| | - J J Dixon
- Rainbow Equine Hospital, Malton, North Yorkshire, UK
| | - R Weller
- Department of Clinical Science & Services, Royal Veterinary College, Hatfield, Hertfordshire, UK
| | - D M Bolt
- Department of Clinical Science & Services, Royal Veterinary College, Hatfield, Hertfordshire, UK
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Lee S, Bolt DM. Asymmetric Item Characteristic Curves and Item Complexity: Insights from Simulation and Real Data Analyses. Psychometrika 2018; 83:453-475. [PMID: 28948426 DOI: 10.1007/s11336-017-9586-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/23/2016] [Revised: 08/23/2017] [Indexed: 06/07/2023]
Abstract
While item complexity is often considered as an item feature in test development, it is much less frequently attended to in the psychometric modeling of test items. Prior work suggests that item complexity may manifest through asymmetry in item characteristics curves (ICCs; Samejima in Psychometrika 65:319-335, 2000). In the current paper, we study the potential for asymmetric IRT models to inform empirically about underlying item complexity, and thus the potential value of asymmetric models as tools for item validation. Both simulation and real data studies are presented. Some psychometric consequences of ignoring asymmetry, as well as potential strategies for more effective estimation of asymmetry, are considered in discussion.
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Affiliation(s)
- Sora Lee
- University of Wisconsin, Madison, WI, USA.
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Deng S, E McCarthy D, E Piper M, B Baker T, Bolt DM. Extreme Response Style and the Measurement of Intra-Individual Variability in Affect. Multivariate Behav Res 2018; 53:199-218. [PMID: 29324049 PMCID: PMC6240342 DOI: 10.1080/00273171.2017.1413636] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Extreme response style (ERS) has the potential to bias the measurement of intra-individual variability in psychological constructs. This paper explores such bias through a multilevel extension of a latent trait model for modeling response styles applied to repeated measures rating scale data. Modeling responses to multi-item scales of positive and negative affect collected from smokers at clinic visits following a smoking cessation attempt revealed considerable ERS bias in the intra-individual sum score variances. In addition, simulation studies suggest the magnitude and direction of bias due to ERS is heavily dependent on the mean affect level, supporting a model-based approach to the study and control of ERS effects. Application of the proposed model-based adjustment is found to improve intra-individual variability as a predictor of smoking cessation.
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Affiliation(s)
- Sien Deng
- a Department Educational Psychology , University of Wisconsin Madison , Madison , USA
| | - Danielle E McCarthy
- b Department of Medicine , University of Wisconsin Madison School of Medicine and Public Health , Madison , USA
| | - Megan E Piper
- b Department of Medicine , University of Wisconsin Madison School of Medicine and Public Health , Madison , USA
| | - Timothy B Baker
- b Department of Medicine , University of Wisconsin Madison School of Medicine and Public Health , Madison , USA
| | - Daniel M Bolt
- a Department Educational Psychology , University of Wisconsin Madison , Madison , USA
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Lee S, Bolt DM. An Alternative to the 3PL: Using Asymmetric Item Characteristic Curves to Address Guessing Effects. Journal of Educational Measurement 2018. [DOI: 10.1111/jedm.12165] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Wild A, Vorperian HK, Kent RD, Bolt DM, Austin D. Single-Word Speech Intelligibility in Children and Adults With Down Syndrome. Am J Speech Lang Pathol 2018; 27:222-236. [PMID: 29214307 PMCID: PMC5968330 DOI: 10.1044/2017_ajslp-17-0002] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/06/2017] [Accepted: 10/11/2017] [Indexed: 05/06/2023]
Abstract
PURPOSE A single-word identification test was used to study speech production in children and adults with Down syndrome (DS) to determine the developmental pattern of speech intelligibility with an emphasis on vowels. METHOD Speech recordings were collected from 62 participants with DS aged 4-40 years and 25 typically developing participants aged 4-7 years. Panels of 5 adult lay listeners transcribed the speech recordings orthographically, and their responses were scored in comparison with the speakers' target words. RESULTS Speech intelligibility in persons with DS improved with age, especially between the ages of 4 and 16 years. Whereas consonants contribute to intelligibility, vowels also played an important role in reduced intelligibility with an apparent developmental difference in low versus high vowels, where the vowels /æ/ and/ɑ/ developed at a later age than /i/ and /u/. Interspeaker variability was large, with male individuals being generally less intelligible than female individuals and some adult men having very low intelligibility. CONCLUSION Results show age-related patterns in speech intelligibility in persons with DS and identify the contribution of dimensions of vowel production to intelligibility. The methods used clarify the phonetic basis of reduced intelligibility, with implications for assessment and treatment.
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Affiliation(s)
- Alyssa Wild
- 433 Waisman Center, University of Wisconsin-Madison
| | | | - Ray D. Kent
- 433 Waisman Center, University of Wisconsin-Madison
| | - Daniel M. Bolt
- Department of Educational Psychology, University of Wisconsin-Madison
| | - Diane Austin
- 433 Waisman Center, University of Wisconsin-Madison
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Baker TB, Smith SS, Bolt DM, Loh WY, Mermelstein R, Fiore MC, Piper ME, Collins LM. Implementing Clinical Research Using Factorial Designs: A Primer. Behav Ther 2017; 48:567-580. [PMID: 28577591 PMCID: PMC5458623 DOI: 10.1016/j.beth.2016.12.005] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/24/2016] [Revised: 12/12/2016] [Accepted: 12/26/2016] [Indexed: 10/20/2022]
Abstract
Factorial experiments have rarely been used in the development or evaluation of clinical interventions. However, factorial designs offer advantages over randomized controlled trial designs, the latter being much more frequently used in such research. Factorial designs are highly efficient (permitting evaluation of multiple intervention components with good statistical power) and present the opportunity to detect interactions amongst intervention components. Such advantages have led methodologists to advocate for the greater use of factorial designs in research on clinical interventions (Collins, Dziak, & Li, 2009). However, researchers considering the use of such designs in clinical research face a series of choices that have consequential implications for the interpretability and value of the experimental results. These choices include: whether to use a factorial design, selection of the number and type of factors to include, how to address the compatibility of the different factors included, whether and how to avoid confounds between the type and number of interventions a participant receives, and how to interpret interactions. The use of factorial designs in clinical intervention research poses choices that differ from those typically considered in randomized clinical trial designs. However, the great information yield of the former encourages clinical researchers' increased and careful execution of such designs.
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Affiliation(s)
- Timothy B. Baker
- Center for Tobacco Research and Intervention, University of Wisconsin School of Medicine and Public Health, 1930 Monroe St., Suite 200, Madison, WI 53711
| | - Stevens S. Smith
- Center for Tobacco Research and Intervention, University of Wisconsin School of Medicine and Public Health, 1930 Monroe St., Suite 200, Madison, WI 53711,University of Wisconsin School of Medicine and Public Health, Department of Medicine, 1025 W. Johnson St., Madison, WI 53706
| | - Daniel M. Bolt
- University of Wisconsin, Department of Educational Psychology, 1025 W. Johnson St., Madison, WI 53706
| | - Wei-Yin Loh
- University of Wisconsin, Department of Statistics, 1300 University Ave., Madison, WI 53706
| | - Robin Mermelstein
- University of Illinois at Chicago, Institute for Health Research and Policy, 544 Westside Research Office Bldg., 1747 West Roosevelt Rd., Chicago, IL 60608
| | - Michael C. Fiore
- Center for Tobacco Research and Intervention, University of Wisconsin School of Medicine and Public Health, 1930 Monroe St., Suite 200, Madison, WI 53711,University of Wisconsin School of Medicine and Public Health, Department of Medicine, 1025 W. Johnson St., Madison, WI 53706
| | - Megan E. Piper
- Center for Tobacco Research and Intervention, University of Wisconsin School of Medicine and Public Health, 1930 Monroe St., Suite 200, Madison, WI 53711,University of Wisconsin School of Medicine and Public Health, Department of Medicine, 1025 W. Johnson St., Madison, WI 53706
| | - Linda M. Collins
- The Methodology Center and Department of Human Development & Family Studies, The Pennsylvania State University, 404 Health and Human Development Building, University Park, PA 16802
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Bolt DM, Adams DJ. Exploring Rubric-Related Multidimensionality in Polytomously Scored Test Items. Appl Psychol Meas 2017; 41:163-177. [PMID: 29881086 PMCID: PMC5978550 DOI: 10.1177/0146621616677715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Test items scored as polytomous have the potential to display multidimensionality across rating scale score categories. This article uses a multidimensional nominal response model (MNRM) to examine the possibility that the proficiency dimension/dimensional composite best measured by a polytomously scored item may vary by score category, an issue not generally considered in multidimensional item response theory (MIRT). Some practical considerations in exploring rubric-related multidimensionality, including potential consequences of not attending to it, are illustrated through simulation examples. A real data application is applied in the study of item format effects using the 2007 administration of Trends in Mathematics and Science Study (TIMSS) among eighth graders in the United States.
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46
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Asmus JM, Carter EW, Moss CK, Biggs EE, Bolt DM, Born TL, Bottema-Beutel K, Brock ME, Cattey GN, Cooney M, Fesperman ES, Hochman JM, Huber HB, Lequia JL, Lyons GL, Vincent LB, Weir K. Efficacy and Social Validity of Peer Network Interventions for High School Students With Severe Disabilities. Am J Intellect Dev Disabil 2017; 122:118-137. [PMID: 28257242 DOI: 10.1352/1944-7558-122.2.118] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
This randomized controlled trial examined the efficacy of peer network interventions to improve the social connections of 47 high school students with severe disabilities. School staff invited, trained, and supported 192 peers without disabilities to participate in individualized social groups that met throughout one semester. Compared to adolescents in the "business-as-usual" control group (n = 48), students receiving peer networks gained significantly more new social contacts and friendships. Although many peer relationships maintained one and two semesters later, their spill over beyond the school day was limited. Students and staff affirmed the social validity of the interventions. We offer recommendations for research and practice aimed at improving the implementation and impact of peer network interventions in secondary schools.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Katie Weir
- Katie Weir, University of Wisconsin-Madison
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Piper ME, Schlam TR, Cook JW, Smith SS, Bolt DM, Loh WY, Mermelstein R, Collins LM, Fiore MC, Baker TB. Toward precision smoking cessation treatment I: Moderator results from a factorial experiment. Drug Alcohol Depend 2017; 171:59-65. [PMID: 28013098 PMCID: PMC5263119 DOI: 10.1016/j.drugalcdep.2016.11.025] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/14/2016] [Revised: 11/08/2016] [Accepted: 11/15/2016] [Indexed: 12/28/2022]
Abstract
BACKGROUND The development of tobacco use treatments that are effective for all smokers is critical to improving clinical and public health. The Multiphase Optimization Strategy (MOST) uses highly efficient factorial experiments to evaluate multiple intervention components for possible inclusion in an optimized tobacco use treatment. Factorial experiments permit analyses of the influence of patient characteristics on main and interaction effects of multiple, relatively discrete, intervention components. This study examined whether person-factor and smoking characteristics moderated the main or interactive effects of intervention components on 26-week self-reported abstinence rates. METHODS This fractional factorial experiment evaluated six smoking cessation intervention components among primary care patients (N=637): Prequit Nicotine Patch vs. None, Prequit Nicotine Gum vs. None, Preparation Counseling vs. None, Intensive Cessation In-Person Counseling vs. Minimal, Intensive Cessation Telephone Counseling vs. Minimal, and 16 vs. 8 Weeks of Combination Nicotine Replacement Therapy (NRT; nicotine patch+nicotine gum). RESULTS Both psychiatric history and smoking heaviness moderated intervention component effects. In comparison with participants with no self-reported history of a psychiatric disorder, those with a positive history showed better response to 16- vs. 8-weeks of combination NRT, but a poorer response to counseling interventions. Also, in contrast to light smokers, heavier smokers showed a poorer response to counseling interventions. CONCLUSIONS Heavy smokers and those with psychiatric histories demonstrated a differential response to intervention components. This research illustrates the use of factorial designs to examine the interactions between person characteristics and relatively discrete intervention components. Future research is needed to replicate these findings.
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Affiliation(s)
- Megan E Piper
- Center for Tobacco Research and Intervention, University of Wisconsin School of Medicine and Public Health, United States; University of Wisconsin School of Medicine and Public Health, Department of Medicine, Division of General Internal Medicine, United States.
| | - Tanya R Schlam
- Center for Tobacco Research and Intervention, University of Wisconsin School of Medicine and Public Health, United States; University of Wisconsin School of Medicine and Public Health, Department of Medicine, Division of General Internal Medicine, United States
| | - Jessica W Cook
- Center for Tobacco Research and Intervention, University of Wisconsin School of Medicine and Public Health, United States; University of Wisconsin School of Medicine and Public Health, Department of Medicine, Division of General Internal Medicine, United States; William S. Middleton Memorial Veterans Hospital, United States
| | - Stevens S Smith
- Center for Tobacco Research and Intervention, University of Wisconsin School of Medicine and Public Health, United States; University of Wisconsin School of Medicine and Public Health, Department of Medicine, Division of General Internal Medicine, United States
| | - Daniel M Bolt
- University of Wisconsin, Department of Educational Psychology, United States
| | - Wei-Yin Loh
- University of Wisconsin, Department of Statistics, United States
| | - Robin Mermelstein
- University of Illinois at Chicago, Institute for Health Research and Policy, United States
| | - Linda M Collins
- The Methodology Center and Department of Human Development and Family Studies, The Pennsylvania State University, United States
| | - Michael C Fiore
- Center for Tobacco Research and Intervention, University of Wisconsin School of Medicine and Public Health, United States; University of Wisconsin School of Medicine and Public Health, Department of Medicine, Division of General Internal Medicine, United States
| | - Timothy B Baker
- Center for Tobacco Research and Intervention, University of Wisconsin School of Medicine and Public Health, United States; University of Wisconsin School of Medicine and Public Health, Department of Medicine, Division of General Internal Medicine, United States
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Magnan EM, Bolt DM, Greenlee RT, Fink J, Smith MA. Stratifying Patients with Diabetes into Clinically Relevant Groups by Combination of Chronic Conditions to Identify Gaps in Quality of Care. Health Serv Res 2016; 53:450-468. [PMID: 27861829 DOI: 10.1111/1475-6773.12607] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
OBJECTIVE To find clinically relevant combinations of chronic conditions among patients with diabetes and to examine their relationships with six diabetes quality metrics. DATA SOURCES/STUDY SETTING Twenty-nine thousand five hundred and sixty-two adult patients with diabetes seen at eight Midwestern U.S. health systems during 2010-2011. STUDY DESIGN We retrospectively evaluated the relationship between six diabetes quality metrics and patients' combinations of chronic conditions. We analyzed 12 conditions that were concordant with diabetes care to define five mutually exclusive combinations of conditions ("classes") based on condition co-occurrence. We used logistic regression to quantify the relationship between condition classes and quality metrics, adjusted for patient demographics and utilization. DATA COLLECTION We extracted electronic health record data using a standardized algorithm. PRINCIPAL FINDINGS We found the following condition classes: severe cardiac, cardiac, noncardiac vascular, risk factors, and no concordant comorbidities. Adjusted odds ratios and 95 percent confidence intervals for glycemic control were, respectively, 1.95 (1.7-2.2), 1.6 (1.4-1.9), 1.3 (1.2-1.5), and 1.3 (1.2-1.4) compared to the class with no comorbidities. Results showed similar patterns for other metrics. CONCLUSIONS Patients had distinct quality metric achievement by condition class, and those in less severe classes were less likely to achieve diabetes metrics.
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Affiliation(s)
- Elizabeth M Magnan
- Department of Family and Community Medicine, University of California, Davis, 4860 Y Street, Suite 2320, Sacramento, CA, 95817.,Health Innovation Program, University of Wisconsin School of Medicine and Public Health, Madison, WI
| | - Daniel M Bolt
- Department of Educational Psychology, University of Wisconsin-Madison, Madison, WI
| | - Robert T Greenlee
- Center for Clinical Epidemiology and Population Health, Marshfield Clinic Research Foundation, Marshfield, WI
| | - Jennifer Fink
- Department of Health Informatics and Administration, College of Health Sciences, University of Wisconsin-Milwaukee, Milwaukee, WI.,Center for Urban Population Health, Milwaukee, WI.,Aurora Research Institute, Aurora Health Care, Milwaukee, WI
| | - Maureen A Smith
- Health Innovation Program, University of Wisconsin School of Medicine and Public Health, Madison, WI.,Department of Population Health Sciences, University of Wisconsin School of Medicine and Public Health, Madison, WI.,Department of Family Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI.,Department of Surgery, University of Wisconsin School of Medicine and Public Health, Madison, WI
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Derdemezis E, Vorperian HK, Kent RD, Fourakis M, Reinicke EL, Bolt DM. Optimizing Vowel Formant Measurements in Four Acoustic Analysis Systems for Diverse Speaker Groups. Am J Speech Lang Pathol 2016; 25:335-54. [PMID: 26501214 PMCID: PMC5270637 DOI: 10.1044/2015_ajslp-15-0020] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/25/2015] [Revised: 06/23/2015] [Accepted: 09/18/2015] [Indexed: 05/21/2023]
Abstract
PURPOSE This study systematically assessed the effects of select linear predictive coding (LPC) analysis parameter manipulations on vowel formant measurements for diverse speaker groups using 4 trademarked Speech Acoustic Analysis Software Packages (SAASPs): CSL, Praat, TF32, and WaveSurfer. METHOD Productions of 4 words containing the corner vowels were recorded from 4 speaker groups with typical development (male and female adults and male and female children) and 4 speaker groups with Down syndrome (male and female adults and male and female children). Formant frequencies were determined from manual measurements using a consensus analysis procedure to establish formant reference values, and from the 4 SAASPs (using both the default analysis parameters and with adjustments or manipulations to select parameters). Smaller differences between values obtained from the SAASPs and the consensus analysis implied more optimal analysis parameter settings. RESULTS Manipulations of default analysis parameters in CSL, Praat, and TF32 yielded more accurate formant measurements, though the benefit was not uniform across speaker groups and formants. In WaveSurfer, manipulations did not improve formant measurements. CONCLUSIONS The effects of analysis parameter manipulations on accuracy of formant-frequency measurements varied by SAASP, speaker group, and formant. The information from this study helps to guide clinical and research applications of SAASPs.
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Affiliation(s)
| | | | - Ray D. Kent
- Waisman Center, University of Wisconsin–Madison
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Bolt DM, Hare RD, Neumann CS. Score Metric Equivalence of the Psychopathy Checklist–Revised (PCL-R) Across Criminal Offenders in North America and the United Kingdom. Assessment 2016; 14:44-56. [PMID: 17314179 DOI: 10.1177/1073191106293505] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
David Cooke and colleagues have published a series of item response theory (IRT) studies investigating the equivalence of the Psychopathy Checklist-Revised (PCL-R) for European versus North American (NA) male criminal offenders. They have consistently concluded that PCL-R scores are not equivalent, with European offenders receiving scores up to five points lower than those in NA when matched according to the latent trait. In this article, the authors critique the Cooke et al. analyses and demonstrate how their anchor item selection method is responsible for their final conclusions concerning the apparent lack of equivalence. The authors provide a competing IRT analysis using an iterative purification strategy for anchor item selection and show how this more justifiable approach leads to very different conclusions regarding the equivalence of the PCL-R. More generally, it is argued that strong interpretations of IRT analyses in the presence of uncorroborated anchor items can be highly misleading when evaluating score metric equivalence.
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