Health and Illness Over Time

Henly, Susan J.; Wyman, Jean F.; Findorff, Mary J.

doi:10.1097/nnr.0b013e318216dfd3

Cited by 51 publications

(20 citation statements)

References 29 publications

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“…As hypothesised, health information behaviour in the Suomi24 discussion forum shows clear and robust rhythmicity on seasonal and daily level. This is most evident for the themes analysed in this study, and endorses the notion that well-being, health and illness are dynamic processes, as suggested by earlier research (Eriksson, 1993;Henly et al, 2011;Mogilner et al, 2018;Reinberg et al, 2017;Roenneberg, 2012;Svalastog et al, 2017). Analysing digital traces of health information also provides evidence for understanding when people make sense of their health, as exemplified here by the Suomi24 data.…”

Section: Discussionsupporting

confidence: 86%

“…Rhythmicity and temporal patterns related to sleeping, breathing, eating, thinking and issues of health and illness are universal phenomena (Adam, 1990;Mogilner et al, 2018;Reinberg et al, 2017;Roenneberg, 2012;). Especially well-being, health and illness are all dynamic processes that change over time, placing individuals on a discontinuous and cyclical spectrum ranging from health, well-being and optimal function on one end to illness and death on the other end (Eriksson, 1993;Henly et al, 2011;Svalastog et al, 2017). This discontinuous nature is closely associated with health information behaviour or how people seek, obtain, evaluate, categorise, use and share health-related information in regards to their health and illness (Ek, 2013).…”

Section: Introductionmentioning

confidence: 99%

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The aspect of time in online health information behaviour

Tana

Eirola

Eriksson‐Backa

2019

INF

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Temporal structures and rhythmicity are universal phenomena and affect all aspects of life, including dynamic processes like health and well-being that change over time. Health related issues and threats trigger health information behaviour, a majority of which happens online and thus leaves digital traces behind. This study analyses the temporal variations and rhythmicity of health information behaviour through the action of online posting in a large Finnish discussion forum, Suomi24. The findings in this study show that health information behaviour follow clear and robust rhythmicity on both a seasonal and daily level. This endorses the notion that well-being, health and illness are dynamic processes that change with time and can help provide a more holistic picture of health and well-being, including aspects that fall outside professional healthcare settings. Studying when health information behaviour happens can thus have wide-ranging consequences.

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Section: Discussionsupporting

confidence: 86%

Section: Introductionmentioning

confidence: 99%

The aspect of time in online health information behaviour

Tana

Eirola

Eriksson‐Backa

2019

INF

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“…In addition, acute pain is a dynamic process that changes over time and can be influenced by a number of factors. An analysis of predictors of acute postoperative pain trajectories [ 10 ] acknowledges pain as a dynamic process, takes inter-individual variability into account, and may identify modifiable risk factors for more severe pain.…”

Section: Introductionmentioning

confidence: 99%

The Impact of Demographic, Clinical, Symptom and Psychological Characteristics on the Trajectories of Acute Postoperative Pain After Total Knee Arthroplasty

et al. 2016

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Objective. Total knee arthroplasty is a painful procedure. No studies have evaluated modifiable predictors of acute postoperative pain trajectories during hospitalization.Methods. Consecutive patients (N = 188) were enrolled in a longitudinal cohort study and completed a demographic questionnaire, as well as the Brief Pain Inventory, Hospital Depression and Anxiety Scale, Lee Fatigue Scale, Fatigue Severity Scale, and Brief Illness Perception Questionnaire on the day before surgery. Clinical data were extracted from medical records.Setting and Patients. Each patient completed a pain diary that assessed pain at rest and with activity, and hours per day in pain every evening from day of surgery until postoperative day 3. Using hierarchical linear modeling, we investigated which demographic, clinical, symptom, and psychological characteristics predicted initial levels as well as the trajectories of acute pain at rest and with activity, and hours per day in pain.Results. Higher levels of all three acute pain characteristics on the day of surgery resulted in worse trajectories. Higher pain scores with rest and with activity on the day of surgery were associated with more days with femoral block, higher average dose of opioids, and higher emotional response to osteoarthritis. Higher number of comorbidities, higher average dose of opioids, and lower perceived control predicted more hours per day in pain on the day of surgery.Conclusions. This study identified several potentially modifiable predictors of worsening pain trajectories following total knee arthroplasty. Optimal pain management warrants identification of these high-risk patients and treatment of modifiable risk factors.

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“…A symptom trajectory is defined as a pattern of symptoms over time (Henly, Wyman, & Gaugler, 2011). Focusing research on individuals’ symptom trajectories, rather than on symptoms at a single point in time, is a patient-centered approach and is highly relevant to clinical situations (Henly, Wyman, & Findorff, 2011). …”

Section: Introductionmentioning

confidence: 99%

Symptom Trajectories After an Emergency Department Visit for Potential Acute Coronary Syndrome

Knight

Shea²,

Rosenfeld

et al. 2016

Nursing Research

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Background Many patients evaluated for acute coronary syndrome (ACS) in emergency departments (EDs) continue to experience troubling symptoms after discharge—regardless of their ultimate medical diagnosis. However, comprehensive understanding of common postED symptom trajectories is lacking. Objectives To identify common trajectories of symptom severity in the six months after an ED visit for potential ACS. Methods This was a secondary analysis of data from a larger observational, prospective study conducted in five U.S. emergency departments. Patients (N = 1005) who had electrocardiogram and biomarker testing ordered, and were identified by the triage nurse as potentially having ACS, were enrolled. Symptom severity was assessed in the hospital after initial stabilization and by telephone at 30 days and six months using the validated 13-item ACS Symptom Checklist. Growth mixture modeling was used for the secondary analysis. The eight most commonly reported symptoms (chest discomfort, chest pain, chest pressure, lightheadedness, shortness of breath, shoulder pain, unusual fatigue, and upper back pain) were modeled across the three study timepoints. Models with increasing numbers of classes were compared, and final model selection was based on a combination of interpretability, theoretical justification, and statistical fit indices. Results The sample was 62.6% male with a mean age of 60.2 years (SD = 14.17), and 57.1% ruled out for ACS. Between two and four distinct trajectory classes were identified for each symptom. The seven different types of trajectories identified across the eight symptoms were labeled “tapering off,” “mild/persistent,” “moderate/persistent,” “moderate/worsening,” “moderate/improving,” “late onset, “and “severe/improving.” Trajectories differed on age, sex, and diagnosis. Discussion Research on the individual nature of symptom trajectories can contribute to patient-centered, rather than disease-centered, care. Further research is needed to verify the existence of multiple symptoms trajectories in diverse populations, and to assess the antecedents and consequences of individual symptom trajectories.

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Health and Illness Over Time

Cited by 51 publications

References 29 publications

The aspect of time in online health information behaviour

The aspect of time in online health information behaviour

The Impact of Demographic, Clinical, Symptom and Psychological Characteristics on the Trajectories of Acute Postoperative Pain After Total Knee Arthroplasty

Symptom Trajectories After an Emergency Department Visit for Potential Acute Coronary Syndrome

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