| Literature DB >> 35710466 |
Danny Valdez1, Kristen N Jozkowski2, Katherine Haus1, Marijn Ten Thij3, Brandon L Crawford1, María S Montenegro4, Wen-Juo Lo5, Ronna C Turner5, Johan Bollen6.
Abstract
INTRODUCTION: Although much work has been done on US abortion ideology, less is known relative to the psychological processes that distinguish personal abortion beliefs or how those beliefs are communicated to others. As part of a forthcoming probability-based sampling designed study on US abortion climate, we piloted a study with a controlled sample to determine whether psychological indicators guiding abortion beliefs can be meaningfully extracted from qualitative interviews using natural language processing (NLP) substring matching. Of particular interest to this study is the presence of cognitive distortions-markers of rigid thinking-spoken during interviews and how cognitive distortion frequency may be tied to rigid, or firm, abortion beliefs.Entities:
Keywords: Abortion; Cognitive distortions; Natural language processing; Psychology; Qualitative
Year: 2022 PMID: 35710466 PMCID: PMC9200936 DOI: 10.1186/s40814-022-01078-0
Source DB: PubMed Journal: Pilot Feasibility Stud ISSN: 2055-5784
Participant demographic information and cognitive distortions spoken per interview
| Participant ID | Gender | Age | Abortion identity | Pol affiliation |
|---|---|---|---|---|
| 1 | Woman | 70 | Neither pro-choice nor pro life | Democrat |
| 2 | Woman | 46 | Strongly pro-choice | None |
| 3 | Woman | 65 | Strongly pro-choice | Democrat |
| 4 | Man | 44 | Strongly pro-choice | Libertarian |
| 5 | Man | 24 | Strongly pro-choice | Democrat |
| 6 | Man | 47 | Strongly pro-choice | Democrat |
| 7 | Man | 58 | Slightly pro-choice | Democrat |
| 8 | Woman | 61 | Equally pro-choice and pro-life | Democrat |
| 9 | Man | 35 | Equally pro-choice and pro-life | Democrat |
| 10 | Man | 35 | Equally pro-choice and pro-life | Independent |
| 11 | Man | 59 | Equally pro-choice and pro-life | Republican |
| 12 | Man | 52 | Slightly pro-life | Republican |
| 13 | Man | 47 | Moderately pro-life | Democrat |
| 14 | Man | 51 | Moderately pro-life | Republican |
| 15 | Man | 43 | Moderately pro-life | Democrat |
| 16 | Man | 49 | Strongly pro-life | Democrat |
Fig. 1A conceptual diagram of lexicon matching
List and definitions of cognitive distortions (CDS)a and select examples of terms in the CDSa lexicon
| Distortion | Definition | Select terms | Example sentence |
|---|---|---|---|
| Labeling and mislabeling | I am a | “ | |
| He is a | |||
| They are a | |||
| Catastrophizing | …Will go wrong | “If she has an abortion, | |
| …Will be terrible | |||
| …Will be a disaster | |||
| Dichotomous reasoning | Only | “I have | |
| Ever | |||
| Always | |||
| Emotional reasoning | But I feel | “Abortion are legal; | |
| Because I feel | |||
| Since it feels | |||
| Disqualifying the positive | …Great but | “Abortions are | |
| …Acceptable, yet | |||
| …. Not that good | |||
| Magnification and minimization | Worst | “Criminalizing abortion would be the | |
| Best | |||
| No matter | |||
| Mental filtering | All I see | “ | |
| …Can only think | |||
| If I only | |||
| Mind reading | Everyone knows | “ | |
| No one believes | |||
| They all know | |||
| Fortune-telling | I will not… | “ | |
| We will not… | |||
| He/she will… | |||
| Overgeneralizing | Completely | “Regretting an abortion? It will | |
| Always happens | |||
| Every single time | |||
| Personalizing | All me | “I tend to not have many friends | |
| Because of my | |||
| My responsibility | |||
| Normative statements | Should [not] | “We | |
| Ought [not] | |||
| Must |
aCDS is an acronym for the cognitive distortion schemata. Please also note terms listed per CDS are non-exhaustive
Breakdown of included LIWCa variables (2015 Dictionary)
| Indicator | Definition | Select terms | Example sentence |
|---|---|---|---|
| Authenticity | ‘Please be aware that the views about abortion I am expressing are | ||
| Clout | “ | ||
| Analytic thinking | “ | ||
| Perceptiveness | I see… | “ | |
| I hear… | |||
| I feel… |
aThe Linguistic Inquiry and Word Count (LIWC) is a proprietary algorithm and does not disclose the precise words used to calculate authenticity, clout, and analytic thinking scores. However, a detailed description of each variable and how the variable was calibrated can be found at https://liwc.wpengine.com/interpreting-liwc-output/
Participant ID and CDSa spoken per interview
| Participant ID | CDS total | CDS per minute | Abortion Identity |
|---|---|---|---|
| 1 | 122 | 1.91 | Neither pro-choice nor pro-life |
| 2 | 308 | 4.46 | Strongly pro-choice |
| 3 | 90 | 1.38 | Strongly pro-choice |
| 4 | 226 | 5.65 | Strongly pro-choice |
| 5 | 152 | 4.22 | Strongly pro-choice |
| 6 | 327 | 5.19 | Strongly pro-choice |
| 7 | 259 | 4.80 | Strongly pro-choice |
| 8 | 144 | 1.92 | Equally pro-choice and pro-life |
| 9 | 122 | 1.85 | Equally pro-choice and pro-life |
| 10 | 130 | 1.66 | Equally pro-choice and pro-life |
| 11 | 236 | 2.95 | Equally pro-choice and pro-life |
| 12 | 126 | 2.26 | Slightly pro-life |
| 13 | 157 | 2.53 | Moderately pro-life |
| 14 | 78 | 0.81 | Moderately pro-life |
| 15 | 134 | 2.13 | Moderately pro-life |
| 16 | 303 | 3.33 | Strongly pro-life |
aCDS is an acronym for cognitive distortion schemata
Total CDSa by category and percent of CDSa by category
| Labeling and mislabeling | Catastrophizing | Dichotomous reasoning | Emotional reasoning | Disqualifying the positive | Magnification | Mental filtering | Mind reading | Fortune-telling | Overgeneralizing | Personalizing | Normative thinking | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| SUM | 204 | 3 | 5 | 16 | 64 | 2 | 11 | 36 | 33 | |||
| %total | 7% | 0% | 0% | 1% | 2% | 0% | 0% | 1% | 1% |
aCDS is an acronym for cognitive distortion schemata
Fig. 2Standardized CDS per interview by abortion identity
Participant ID and LIWCa indicators
| Participant ID | Authenticity | Analytic | Clout | Perceptiveness |
|---|---|---|---|---|
| 1 | 40.81 | 7.84 | 67.92 | 1.59 |
| 2 | 71.15 | 6.72 | 64.34 | 2.10 |
| 3 | 51.12 | 1.99 | 33.74 | 1.49 |
| 4 | 89.67 | 8.65 | 74.59 | 1.73 |
| 5 | 68.28 | 6.13 | 52.44 | 1.47 |
| 6 | 86.97 | 6.62 | 70.28 | 1.41 |
| 7 | 77.47 | 8.86 | 74.78 | 3.48 |
| 8 | 41.93 | 15.91 | 88.37 | 1.90 |
| 9 | 64.35 | 8.12 | 55.04 | 2.29 |
| 10 | 52.68 | 9.07 | 56.06 | 2.20 |
| 11 | 69.57 | 13.29 | 58.90 | 1.82 |
| 12 | 85.73 | 2.49 | 45.25 | 1.98 |
| 13 | 62.80 | 5.10 | 59.16 | 2.25 |
| 14 | 62.89 | 18.54 | 57.41 | 3.03 |
| 15 | 40.19 | 25.33 | 79.35 | 2.95 |
| 16 | 68.67 | 13.37 | 59.06 | 1.37 |
aLIWC is an acronym for Linguistic Inquiry and Word Count. Please also note numeric LIWC values are expressed as percentages