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Estimating the Momentary Likelihood of Posttraumatic Stress Symptoms During and After Exposure to Potentially Traumatic Events
Estimating the Momentary Likelihood of Posttraumatic Stress Symptoms During and After Exposure to Potentially Traumatic Events
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20260202104833
- ISBN
- 9798293892525
- DDC
- 150
- 서명/저자
- Estimating the Momentary Likelihood of Posttraumatic Stress Symptoms During and After Exposure to Potentially Traumatic Events
- 발행사항
- [Sl] : University of California, Berkeley, 2025
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2025
- 형태사항
- 102 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 87-04, Section: A.
- 주기사항
- Advisor: Fisher, Aaron J.
- 학위논문주기
- Thesis (Ph.D.)--University of California, Berkeley, 2025.
- 초록/해제
- 요약Verbal theories of posttraumatic stress (PTS) symptom development and maintenance-i.e., theories operationalized verbally rather than numerically, such as emotional processing theory and cognitive theory-suggest that PTS symptoms occur in specific sequences within individuals over time and interact to perpetuate and intensify each other. While prior research has leveraged ecological momentary assessment (EMA) data to investigate how PTS symptoms behave within individuals over time, such work has not served as a quantitative evaluation of verbal theories of PTS, due in part to the use of continuous or Likert survey item response types and reliance on the general linear model. These methodological choices result in findings that elucidate how PTS symptoms behave in general over a given period (e.g., an EMA sampling period) but do not shed light on symptom sequences, such as those described in verbal theories. Accordingly, the present study offers a first step towards the quantitative assessment of symptom sequences via a novel probabilistic approach. Within this probabilistic approach, PTS symptom clusters from the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition are first identified as present or absent at each point in time for each person. Next, the marginal probability (i.e., base rate) of each symptom cluster is calculated, which provides information about each point in time: Each symptom cluster base rate indicates the likelihood of the given symptom cluster occurring at each point in time for each person. With information about each point in time rather than about the full sampling period, the sequential relationships described in verbal theories of PTS may then be tested.The present study focuses on the initial step in this probabilistic approach: investigating the base rates of PTS symptom clusters. In so doing, this study offers a map or momentary epidemiology of the frequency with which PTS symptom clusters occur over time in adults with PTS. Six archival data sets of EMA PTS symptom data collected from 612 adults were identified for the present analyses. These six studies varied in four key factors hypothesized to influence the course of PTS: baseline PTS symptom severity, the proximity of EMA data collection to potentially traumatic event (PTE) exposure, EMA sampling rate, and survey item response type. The present study examined patterns of PTS symptom cluster base rates across an analytic subsample of 513 adults, and between subsamples split along these four key factors. All data were either collected via dichotomous item response type or discretized prior to analysis to evaluate frequency separately from severity or distress ratings (see Method).Findings showed that adults with PTS were highly likely to experience one or more PTS symptoms at any given point in time and on any given day, and that hyperarousal symptoms occurred at the highest frequency, followed by negative alterations in cognition and mood (NACM), re-experiencing, and avoidance, in that order. These findings affirm existing theoretical and clinical conceptualizations of PTS symptoms as occurring frequently within each day, with variation in behavior between symptom clusters. These findings were consistent regardless of baseline PTS symptom severity, proximity to PTE, EMA sampling rate, and survey item response type, indicating that these frequency characteristics may be core signatures of PTS.When comparing symptom cluster base rates across baseline PTS symptom severity, proximity to PTE, EMA sampling rate, and survey item response type, three additional central findings emerged. First, symptom cluster base rates were consistent across levels of baseline PTS symptom severity. For example, the frequency of hyperarousal symptoms in individuals with low baseline PTS symptom severity was not significantly different from the frequency of hyperarousal symptoms in individuals with high baseline PTS symptom severity. As baseline PTS symptom severity scores were generated via popular assessment tools-tools that combine symptom frequency and distress into a single severity metric-this finding suggests that distress, not symptom frequency, may have driven baseline PTS symptom severity scores. Measuring symptom frequency and distress separately in future work may lead to a more nuanced understanding of PTS and to increased precision in diagnostic practices. Second, symptom cluster base rates varied as a function of PTE proximity. This finding aligns with research showing the experience of PTS is different when enduring ongoing PTE exposure, within 30 days of PTE exposure, and 31+ days after PTE exposure. This affirms the importance of considering PTE proximity when studying and intervening on PTS. Finally, symptom cluster base rates varied according to both EMA sampling rate and survey item response type. For example, symptom cluster base rates in data collected via continuous items were significantly lower than base rates in data collected via Likert or dichotomous items. Careful follow-up investigations are needed to understand the impact of these methodological choices on existing and future psychological science outcomes.Overall, the present study shows general feasibility for extracting meaningful information from PTS symptom cluster base rates, provides evidence for the rank order of symptom cluster base rates as a relatively stable feature of PTS, demonstrates the utility of isolating symptom frequency from distress ratings, and offers additional nuance to existing work on the impact of PTE proximity, EMA sampling rate, and survey item response type on PTS symptom behavior findings. Future research should build on this work using a probabilistic approach to identify the likelihood of each symptom cluster given the presence of all other symptom clusters at the same time point and the next, and compare findings to symptom sequences outlined in verbal theories of PTS.
- 일반주제명
- Psychology
- 일반주제명
- Epistemology
- 일반주제명
- Clinical psychology
- 키워드
- Cognitive theory
- 기타저자
- University of California, Berkeley Psychology
- 기본자료저록
- Dissertations Abstracts International. 87-04A.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■1001 ▼aHowe, Esther Stillman Head.
■24510▼aEstimating the Momentary Likelihood of Posttraumatic Stress Symptoms During and After Exposure to Potentially Traumatic Events
■260 ▼a[Sl]▼bUniversity of California, Berkeley▼c2025
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2025
■300 ▼a102 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 87-04, Section: A.
■500 ▼aAdvisor: Fisher, Aaron J.
■5021 ▼aThesis (Ph.D.)--University of California, Berkeley, 2025.
■520 ▼aVerbal theories of posttraumatic stress (PTS) symptom development and maintenance-i.e., theories operationalized verbally rather than numerically, such as emotional processing theory and cognitive theory-suggest that PTS symptoms occur in specific sequences within individuals over time and interact to perpetuate and intensify each other. While prior research has leveraged ecological momentary assessment (EMA) data to investigate how PTS symptoms behave within individuals over time, such work has not served as a quantitative evaluation of verbal theories of PTS, due in part to the use of continuous or Likert survey item response types and reliance on the general linear model. These methodological choices result in findings that elucidate how PTS symptoms behave in general over a given period (e.g., an EMA sampling period) but do not shed light on symptom sequences, such as those described in verbal theories. Accordingly, the present study offers a first step towards the quantitative assessment of symptom sequences via a novel probabilistic approach. Within this probabilistic approach, PTS symptom clusters from the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition are first identified as present or absent at each point in time for each person. Next, the marginal probability (i.e., base rate) of each symptom cluster is calculated, which provides information about each point in time: Each symptom cluster base rate indicates the likelihood of the given symptom cluster occurring at each point in time for each person. With information about each point in time rather than about the full sampling period, the sequential relationships described in verbal theories of PTS may then be tested.The present study focuses on the initial step in this probabilistic approach: investigating the base rates of PTS symptom clusters. In so doing, this study offers a map or momentary epidemiology of the frequency with which PTS symptom clusters occur over time in adults with PTS. Six archival data sets of EMA PTS symptom data collected from 612 adults were identified for the present analyses. These six studies varied in four key factors hypothesized to influence the course of PTS: baseline PTS symptom severity, the proximity of EMA data collection to potentially traumatic event (PTE) exposure, EMA sampling rate, and survey item response type. The present study examined patterns of PTS symptom cluster base rates across an analytic subsample of 513 adults, and between subsamples split along these four key factors. All data were either collected via dichotomous item response type or discretized prior to analysis to evaluate frequency separately from severity or distress ratings (see Method).Findings showed that adults with PTS were highly likely to experience one or more PTS symptoms at any given point in time and on any given day, and that hyperarousal symptoms occurred at the highest frequency, followed by negative alterations in cognition and mood (NACM), re-experiencing, and avoidance, in that order. These findings affirm existing theoretical and clinical conceptualizations of PTS symptoms as occurring frequently within each day, with variation in behavior between symptom clusters. These findings were consistent regardless of baseline PTS symptom severity, proximity to PTE, EMA sampling rate, and survey item response type, indicating that these frequency characteristics may be core signatures of PTS.When comparing symptom cluster base rates across baseline PTS symptom severity, proximity to PTE, EMA sampling rate, and survey item response type, three additional central findings emerged. First, symptom cluster base rates were consistent across levels of baseline PTS symptom severity. For example, the frequency of hyperarousal symptoms in individuals with low baseline PTS symptom severity was not significantly different from the frequency of hyperarousal symptoms in individuals with high baseline PTS symptom severity. As baseline PTS symptom severity scores were generated via popular assessment tools-tools that combine symptom frequency and distress into a single severity metric-this finding suggests that distress, not symptom frequency, may have driven baseline PTS symptom severity scores. Measuring symptom frequency and distress separately in future work may lead to a more nuanced understanding of PTS and to increased precision in diagnostic practices. Second, symptom cluster base rates varied as a function of PTE proximity. This finding aligns with research showing the experience of PTS is different when enduring ongoing PTE exposure, within 30 days of PTE exposure, and 31+ days after PTE exposure. This affirms the importance of considering PTE proximity when studying and intervening on PTS. Finally, symptom cluster base rates varied according to both EMA sampling rate and survey item response type. For example, symptom cluster base rates in data collected via continuous items were significantly lower than base rates in data collected via Likert or dichotomous items. Careful follow-up investigations are needed to understand the impact of these methodological choices on existing and future psychological science outcomes.Overall, the present study shows general feasibility for extracting meaningful information from PTS symptom cluster base rates, provides evidence for the rank order of symptom cluster base rates as a relatively stable feature of PTS, demonstrates the utility of isolating symptom frequency from distress ratings, and offers additional nuance to existing work on the impact of PTE proximity, EMA sampling rate, and survey item response type on PTS symptom behavior findings. Future research should build on this work using a probabilistic approach to identify the likelihood of each symptom cluster given the presence of all other symptom clusters at the same time point and the next, and compare findings to symptom sequences outlined in verbal theories of PTS.
■590 ▼aSchool code: 0028.
■650 4▼aPsychology
■650 4▼aEpistemology
■650 4▼aClinical psychology
■653 ▼aPosttraumatic stress
■653 ▼aCognitive theory
■653 ▼aEcological momentary assessment
■690 ▼a0621
■690 ▼a0622
■690 ▼a0393
■71020▼aUniversity of California, Berkeley▼bPsychology.
■7730 ▼tDissertations Abstracts International▼g87-04A.
■790 ▼a0028
■791 ▼aPh.D.
■792 ▼a2025
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17359095▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
