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. Author manuscript; available in PMC: 2022 Apr 1.
Published in final edited form as: J Adv Nurs. 2021 Jan 18;77(4):2073–2084. doi: 10.1111/jan.14742

Positive psychological states and stress responses in caregivers of adults receiving an allogeneic bone marrow transplant: A study protocol

Kelly R Tan 1, Sheila J Santacroce 1,2, William A Wood 2,3, Deborah K Mayer 1,2, Hudson Santos 1, Peter J Mucha 4, Todd A Schwartz 1,5, Barbara L Fredrickson 2,6
PMCID: PMC8284914  NIHMSID: NIHMS1654693  PMID: 33460207

Abstract

Aims:

This protocol directs a study that aims to: (a) describe the caregiver’s experience over 8–12 weeks after an index adult patient’s allogeneic bone marrow transplant (BMT) for advanced cancer using a case-oriented approach and mixed methods, with qualitative methods in the foreground; and (b) explore networks of relationships among psycho-neurological symptoms, positive psychological states and caregiver health.

Design:

Case-oriented longitudinal design using multiple data types and analytic approaches.

Methods:

Data will be collected from 10–12 caregivers. The sample will be recruited from a large public hospital in the southeastern United States using maximum variation sampling (e.g., caregiver race/ethnicity, relationship to patient, age, education, and number of caregiving roles). Participants will be asked to complete weekly surveys, have their blood drawn bi-weekly and participate in an interview each month during the study period (~100 days). Aim 1 analysis will include directed content analysis and case-oriented visual analysis. Aim 2 analysis will include symptom network estimation of psycho-neurological symptoms, positive psychological states, and caregiver health. Institutional review board approval was obtained August 2018.

Discussion:

Results will provide an in-depth description of caregivers’ experiences in the 100 days after BMT. Findings will inform generation of hypotheses and identification of targets for interventions to improve caregiver’s experiences after BMT.

Impact:

This in-depth multi-method longitudinal study to describe caregivers of adult patients receiving an allogeneic BMT is an essential step in understanding caregivers’ complex responses to chronic stress and the role of positive psychological states. The results from this study will inform future research on chronic stress processes, intense caregiving, and intervention development.

Keywords: caregiving, case-oriented analysis, emotions, network analysis, nursing, protocol, qualitative, quantitative, stress

1 |. INTRODUCTION

Family and friend caregivers are increasingly called on to care for patients undergoing an allogeneic bone marrow transplant (BMT) during the peri-transplant period (the approximately 100 days immediately preceding, during and following transplant). Evidence has shown that caregivers of patients undergoing BMT are at higher risk for stress related health problems including depression, anxiety, fatigue, and cardiovascular disease than non-caregivers (Schulz & Beach, 1999; Stenberg et al., 2010; Trevino et al., 2017). Earlier discharge of BMT patients to outpatient care, with the consequent shifting of clinical responsibilities to caregivers will further increase their burdens (Applebaum et al., 2016). Prior studies have not examined the experiences of caregivers during the peri-transplant period particularly during the transition from inpatient to outpatient care when caregiving demands and related stressors can be expected to heighten (Applebaum et al., 2016). This protocol describes a multi-method longitudinal study that seeks to describe caregivers’ experiences during the peri-transplant period and generate hypotheses using exploratory symptom network analysis. This study was guided by the Psychoneuroimmunological (PNI)-based paradigm (McCain et al., 2005; McCain & Smith, 1994) and the Broaden-and-Build Theory of Positive Emotions (Fredrickson, 2004, 2013).

2 |. BACKGROUND

Caregivers are vital to the care of patients receiving an allogeneic BMT, thus caregivers’ health status is an important contributor to their ability to provide care to maximize patient outcomes. Caregivers are so vital that BMT programs in the United States (US) typically require patients to identify at least one caregiver committed to providing care 24 hr a day, 7 days a week during the peri-transplant period (Applebaum et al., 2016; Foster et al., 2005). Discharge typically occurs 30 days after transplant, when there is evidence that the BMT has engrafted (peripheral blood cells are rising to normal levels). At that point, patients who reside distant from the BMT centre will move to a private room or other type of temporary housing for up to one year so they may have ready access to BMT specialists. Outpatient care consists of daily laboratory and clinical assessments by health professionals and round the clock monitoring by caregivers for transplant related toxicities (Atilla et al., 2017; Bergeron, 2017; Maffini et al., 2017). After discharge, responsibilities for transportation, medication management, monitoring and deciding when to contact a health professional lies with the caregiver (Von Ah et al., 2016; Williams, 2007). Nonetheless, little is known about how care transitions, that is, from hospital to outpatient care and changing caregiving demands affect indicators of caregiver health overtime.

Despite their caregiving burdens, caregivers are not systematically monitored and referred to resources as indicated during the peri-transplant period. They are, however, initially screened to ensure they are mentally and physically capable of providing the care that BMT patients are expected to need (Gemmill et al., 2011). Follow-up monitoring varies by treatment centre and ranges from informally asking caregivers how they are doing to formal monitoring through distress screening (Wulff-Burchfield et al., 2013). The later rarely occurs with the focus being primarily on the patients. As such, frequent screening for caregiver distress is needed to provide earlier intervention and support for caregivers. Supporting caregivers may in part increase their ability to care for the patient during the peri-transplant period and ultimately improve patient outcomes post-transplant.

Certain factors are known to place caregivers at higher risk for caregiving related stress including younger age (Kent, 2020; Simoneau et al., 2013), multiple caregiving roles (Bevans & Sternberg, 2012; Simoneau et al., 2013) and not having completed college (Kim & Carver, 2012). Younger caregivers (<age 35 years) may lack life experience managing caregiving demands (Kim & Carver, 2012; Simoneau et al., 2013). Moreover responsibilities for children (aged 0–17 years) and/or elderly family members compete for caregivers’ time and attention (Bevans & Sternberg, 2012; Simoneau et al., 2013). Caregivers who lack a college degree may have difficulty navigating the healthcare system and health insurance, understanding health-related information and communicating with healthcare and social workers (Kim & Carver, 2012). Each risk factor may have unique effects on caregiving related stress and the presence of multiple risk factors at initial screening may indicate a need for intensive caregiver monitoring and psychosocial support.

The literature lacks in-depth examination of the effects of multiple factors on caregivers’ risk for caregiving-related stress, negative caregiving experiences, and poorer health outcomes during the peri-transplant period and beyond, for example, risk for onset of stress-related diseases (e.g., high-sensitivity (HS) c-reactive protein (CRP) level). In addition, few studies examine biological changes in response to stress such as changes in interleukin (IL)-6, IL-1B, IL-10, and BDNF levels, which can reflect inflammatory and immune responses to stress. Furthermore, few studies have followed caregivers as the index patient transitions to outpatient care. In addition to addressing the identified gaps, the proposed research will use symptom network analysis methodology to explore complex PNI mechanisms that account for individual level factors for higher levels of caregiving related stress and dynamic interactions among perceived stress, emotions, PNI symptoms, and quality of life (QOL) over time in a sample of 10–12 caregivers of patients who received an allogeneic BMT as part of their cancer treatment regimen.

3 |. THEORETICAL FRAMEWORK

The proposed study and subsequent analyses are guided by a synthesis (Tan et al., In Review) of the PNI-based paradigm (McCain et al., 2005; McCain & Smith, 1994) and the Broaden-and-Build Theory of Positive Emotions (Fredrickson, 2004, 2013). Caregiving related stressors perceived as stressful are appraised as being dangerous or beneficial (McCain et al., 2005; McCain & Smith, 1994). During and subsequent to these appraisals, caregivers experience psychological and physiological responses. Psychological responses may buffer the effects of stress on physiological changes. For example, positive emotions (joy, love, gratitude) may serve an adaptational role by enabling people to build resources that are key to survival, for example, social support (Fredrickson, 2004, 2013). In the context of caregiving, negative and positive emotions are both experienced despite the situation generally being viewed as burdensome (Autio & Rissanen, 2017; Li & Loke, 2013). Additionally, positive emotions enable individuals to broaden their mindsets, for example, by adopting perspectives that do not deny danger but allow a broader view the situation that includes potential benefits in situations such as caregiving and thus cope in more functional ways (Fredrickson, 2004, 2013). In contrast, negative emotions may exacerbate appraisals of the stressor as being dangerous, which activates the PNI axis to produce a cascade of responses including pro- and anti-inflammatory cytokines. While this cascade is initially advantageous when responding to acute stressors by making biological resources (glucose) more readily available, prolonged PNI axis activation can lead to inflammatory dysregulation and downstream new or worsened negative symptoms (anxiety, depression, fatigue, pain, sleep disturbance). Prolonged high levels of pro-inflammatory cytokines (e.g., IL-6, IL-1B), lower levers of anti-inflammatory cytokines (e.g., IL-10) and lower BDNF levels can worsen negative symptoms (e.g., anxiety depression) (Correa et al., 2015; Herbert & Cohen, 1993).

4 |. THE STUDY

The purpose of this study is to increase the richness of our understanding of stress processes during the peri-transplant period.

4.1 |. Aims

This research has two aims. Aim 1 is to describe the caregiver’s experience over 8–12 weeks after the index patient’s allogeneic BMT using a case-oriented approach and mixed methods, with qualitative methods in the foreground. Aim 2 is to explore networks of relationships among psycho-neurological symptoms, positive psychological states and caregiver health. A network systems approach shifts the focus from individual symptoms toward patterns of associations (Borsboom & Cramer, 2013) to identify influential symptoms that can be intervened on for maximal effects in future research. We will also explore the hypothesis that caregivers’ stress and PNI symptoms worsen after the patients are discharged from the hospital to outpatient.

4.2 |. Design/Methodology

The study is a case-oriented longitudinal design using multiple data types. A case-oriented approach allows for the synthesis of multiple data types and identification of emerging relationships and trends in change. Qualitative and quantitative methods allow for a rich description of the experiences of caregivers. Given the richness of the data, a small sample size is consistent with the design and methods.

4.3 |. Setting and Sample

The study setting will be an intermediate care BMT nursing unit and the linked outpatient clinic at a large academic public hospital in the southeastern USA. The sample will consist of between 10–12 index BMT patients and their identified caregivers. Recruitment of a sample this size within about 6 months seems feasible based on the number of allogeneic BMTs conducted in the last 3 years (approximately 70).

4.4 |. Measures

Demographics, caregiving factors, clinical descriptors, positive psychological states, appraisal of caregiving, perceived stress, stress response, and health will be measured using both survey and biological data (Table 1).

TABLE 1.

Measurement tools, reliabilities, and data collection weeks

Data collection visit week number
Variable Measure Citation # of items Reliability (Sensitivity) B 1 2 3 4 5 6 7 8 9 10 11 12
Caregiver–patient dyad demographics/clinical features
 Caregiver demographics Demographics – 8 – X
Context of caregiving – 3 – X
 Patient demographics Demographics – 4 – X
Clinical data – 3 – X
Positive psychological states
 Positive/negative emotions Modified Differential Emotions scale Cohn et al., 2009; Fredrickson et al., 2008 20 α = 0.82–0.94 X X X X X X X X X X X X X
 Meaning in caregiving Positive Aspects of Caregiving Scale Tarlow et al., 2004 9 α = 0.80–0.86 X X X X X X X X X X X X X
Caregiver stress/stress response
 Stress appraisal Appraisal of Caregiving Scale Lambert et al., 2015; Oberst et al., 1989 19 α = 0.83–0.90 X X X X
 Perceived stress Perceived stress survey Kupst et al., 2015 10 α = 0.91 X X X X X X X X X X X X X
Biological response Interleukin−1 (IL−1B)a – – 3.9–250 pg/ml (1.0 pg/mlb) X X X X X X X
Interleukin−6 (IL−6)a – – 7.8–500 pg/ml(2.0 pg/mlb) X X X X X X X
Interleukin−10 (IL−10)a – – 3.1–200 pg/ml(1.0 pg/mlb) X X X X X X X
BDNFa – – – 62.5–4.000 pg/ml(20 pg/mlb) X X X X X X X
Caregiver quality of life and health
 PN symptoms PROMIS®−29 profile: Anxiety, depression, fatigue, sleep disturbance Bjorner et al., 2014; Flynn et al., 2015; Merriwether et al., 2017 16 α = 0.85–0.95 X X X X X X X X X X X X X
 Affective well-being RAND SF−36: Affective well-being McHorney et al., 1993 36 α = 0.78–0.93 X X X X X X X X X X X X X
 Risk for disease onset C-Reactive Proteina – 1.9–150 ng/ml (0.12 ng/mlb) X X X X
Semi Structure Interview
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a

Enzyme-linked immune-absorbent assays (ELISA) using standard manufacturer (ALPCO and R&D) procedures.

b

Limit of detection for ELISA reported from manufacturer protocols.

4.4.1 |. Demographics, caregiving factors, and clinical descriptors

A demographic survey will be used to gather caregiver information (age, sex, race, ethnicity, highest degree received, marital status, income, usual employment status, current employment status, relationship to patient, duration of that relationship, if they were caring for others, if they had help caregiving) and patient information (age, sex, race, ethnicity, cancer diagnosis, cancer diagnosis date, date of transplant).

4.4.2 |. Positive psychological states

Positive emotions (10 items) and negative emotions (10 items) will be measured via the 20-item Modified Differential Emotions Scale (mDES Cohn et al., 2009; Fredrickson et al., 2008). Respondents are asked to use a 5-point response scale anchored by 0 = never and 4 = most of the time to indicate how frequently they felt a particular emotion in the past, responses to the positive items and the negative emotion items are summed separately. Higher scores indicate more emotion experienced.

Meaning in caregiving will be measured via the Positive Aspects of Caregiving (PAC), which includes 2 domains: self-affirmation (6 items) and outlook on life (3 items). Respondents are asked to use a 5-point scale anchored by 1 = strongly disagree and 5 = strongly agree to respond to statements about how providing help to the care recipient has made them feel in the last week Item responses are summed for a total score; higher scores indicate more positive feelings (Tarlow et al., 2004).

4.4.3 |. Appraisal of the caregiving experience

The Appraisal of Caregiving Scale (ACS) contains three domains two of which will be measured: threat (13 items) and benefit (6 items). Respondents are asked to indicate their response using a five-point scale anchored by 1 = strongly disagree and 5 = strongly agree (Lambert et al., 2015; Oberst et al., 1989). Scores are averaged by subscale. Higher mean scores represent greater threat or higher perceived benefits respectively.

4.4.4 |. Stress

Stress will be measured by the Perceived Stress Scale. Respondents are asked to use a 5-point scale anchored by 1 = never and 5 = very often to indicate how often they experienced stress in the past week. Reponses are summed for a total score; higher scores indicate higher levels of perceived stress (Kupst et al., 2015).

4.4.5 |. Stress response

Stress response will be measured using two types of measures: biomarkers and person reported. Biomarkers of the stress response will be IL-1B, IL-6, IL-10, and BDNF as measured in serum using enzyme linked immunosorbent assay (ELISA). The principal investigator (PI) will collect 5ml of blood in a serum separator tube via peripheral venipuncture from which serum will be derived. The person-reported measure of PN symptoms will be the 16-items from the PROMIS-29 profile that measure the domains of anxiety, depression, fatigue, and sleep disturbance (four items per domain). Respondents are asked to indicate how often they experienced a particular symptom in the last 7 days on a scale anchored by 1 = never −5 = always. Scores are averaged in each domain and higher average score indicates more symptoms experienced (Bjorner et al., 2014; Flynn et al., 2015; Merriwether et al., 2017). A single total PN symptom score will also be generated by summing the totals of each domain score.

4.4.6 |. Health

Two types of health will be measured in this study – person-reported QOL and a biomarker of risk for inflammation-related disease onset. Health in terms of person-reported QOL will be measured using the RAND SF-36 which measures eight QOL domains: General health, physical functioning, general psychological health, role limitations due to physical health, role limitations due to emotional health, energy/fatigue, social functioning and pain in the last four weeks. The items use various response formats including 5-point response scales anchored by 1 = not at all and 5 = excellent; 3-point scales with categorical responses anchored by 1 = limited a lot and 3 = not limited at all and 2-point categorical responses (1 = yes or 2 = no). Item scores are transformed to a 0–100 scale with 0 = ‘more disability’ −100 = ‘no disability’. Scores are then averaged by domain with higher scores indicating better quality of life state in that domain (McHorney et al., 1993). Health in terms of risk for inflammation-related disease onset will be HS CRP as measured in serum using high-sensitivity ELISA. The serum will be derived from the same 5 mls of whole blood from which the serum for the other biological assays will be derived.

4.4.7 |. Semi-structured interview

The semi-structured interviews will be guided by a set of questions that allows for the exploration of caregiving related experiences and perspectives on emotions felt while caring for the transplant recipient. The preliminary interview guide (Data S1) will be used for all interviews and refined as the data accumulate and further interview questions and probes are regarded as being important to gaining insight and understanding of the caregiving experience.

4.5 |. Procedures

The study has been reviewed and approved by the local Institutional Review Board (IRB# 18–1703). Index patients will be identified from the schedules for BMT nursing unit admissions and outpatient clinical visits. IRB-approved flyers and in-person methods will be used to recruit participants to the study. Patients and their caregivers who express interest will have their eligibility confirmed and informed consent will be obtained by the PI from the patient and caregiver separately. Patients will also be asked to provide written authorization for a specific set of clinical data to be abstracted from their electronic health record (EHR). Data collection will not be initiated until the patient and the caregiver has signed the required documents.

The eligibility criteria for index patients are: (a) scheduled to receive an allogeneic BMT in the next month; (b) aged 18 years or older; and (c) ability to use the English language well enough to provide informed consent and authorization for abstraction of a limited set of demographic and clinical data from their electronic health record (EHR). Caregiver eligibility criteria are: (a) Identified as a designated caregiver of an index patient; (b), aged 18 years or more; and (c) ability to use the English language well enough to provide informed consent, complete online study surveys and participate in study interviews. Caregiver participants will be recruited to the study from among those who are eligible using maximum variation sampling, a type of purposive sampling (Patton, 2002) and screened for fear of blood or history of fainting at the sight of blood; caregivers who screen positive for either of these will be excluded from the study.

4.5.1 |. Data collection

Index patient data will be extracted from the EHR by the PI, after which the index patient’s participation in the study will end. Caregivers will be asked to participate in weekly data collections for 8–12 weeks following enrolment (Figure 1). Caregiver data will include weekly surveys, bi-weekly venipunctures and monthly semi-structured interviews. Their data will be collected during face-to-face meetings with the PI in a private agreed on location. Caregivers will be asked to complete the online study surveys using an electronic device. The study survey comprises measures that ask participants about their demographics, psychological states, perceived stress, psychoneurological symptoms, and perceived health.

FIGURE 1.

FIGURE 1

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Study progression plan [Colour figure can be viewed at wileyonlinelibrary.com]

Bi-weekly venipunctures will be conducted by the PI at the end of the data collection visit. Universal precautions and biohazard handling procedures will be followed when collecting and transporting the blood specimen. Venipuncture procedures are as follows: (a) prepare supplies; (b) don gloves; (c) apply tourniquet; (d) identify vein; (e) clean site; (f) insert phlebotomy needle; (g) attach vacutainer serum separator tube to collect 5ml of blood; (h) withdraw needle, apply pressure and bandage; (i) dispose of phlebotomy devices into sharps biohazard container; and (j) invert SST tube, put on ice and transport to the laboratory where the sample will be processed and stored.

Monthly, after completing the weekly survey, participants will be asked to engage in a semi-structured interview. The interviews will be digitally recorded on both the electronic pad device and a back-up digital audio recorder. The participant will be shown how to pause both recording devices such that they are in control halting the interview process for any reason. The PI will write a post interview field note documenting any occurrences during the interview, interviewer emotions or reactions and observations not able to be captured by audio recording.

4.5.2 |. Data management

Survey’s completed on an electronic tablet device will be directly uploaded to ta secure server. After the interview is completed, the digital file and back up recording will be uploaded named by study identifier number (SN) and data collection visit number (DN) (SN_DN_Interview) to the School of Nursing’s secure server. As interviews are uploaded, they will be transcribed verbatim by the PI to a Microsoft® word document and saved on the School of Nursing secure server (SN_DN_Interview_transcription). The verbatim interview transcripts will be uploaded to Dedoose ® (Scientific Software Development, Berlin Germany) for coding and analysis. The PIs field notes will also be entered onto a word document, saved securely (SN_DN_Interview_Fieldnote) and uploaded to Dedoose®. Blood samples will be processed in the laboratory using standard serum separation procedures. Standard serum separation procedures are as follows: (a) allow specimen to sit at room temperature for 30 min; (b) centrifuge sample at 1100–1300 rpm for 15 min; (c) aliquot 210 uL of serum into labelled tubes; and (d) freeze tubes of serum at −80°C for storage. After 38 serum samples have amassed, the samples will be thawed and a full 96-well ELISA plate run for each biological indicator per manufacturer protocol in duplicate against two controls (negative, company positive control) and company provided standard dilution series.

4.6 |. Data analysis

4.6.1 |. General statistical analyses

Descriptive statistics will be conducted for all variables using R-statistical software (R Core Team, 2020). For continuous variables, means, standard deviations (SD), and ranges will be estimated for pooled data and individual cases. For each standardized measure, the Cronbach alpha for the measure at each data collection time point will be calculated to estimate internal consistency. For the categorical variables, frequencies and percentages will be calculated.

4.6.2 |. Aim 1 analytic plan

Directed content analysis of the transcripts; the study framework will direct the analysis (Elo & Kyngas, 2008; Hsieh & Shannon, 2005). A code book will guide the coding. First, a codebook will be developed that includes codes and definitions for codes that reflect themes in the study framework. The first transcript will be read in its entirety and then deductively coded using the codes for the study framework themes using Atlas.ti ®. Next, inductive in vivo coding will be performed on the first transcript to identify themes not captured by the study framework (Braun & Clarke, 2014). Codes identified from inductive in-vivo coding will be added to the working code book and conceptually defined. The same coding methods will be used for each subsequent interview within a case. One case will be analysed at a time. In-vivo coding (codes from participants own words) will also be used to generate a list of codes that will be examined for recurring codes within cases and across cases. New codes with their conceptual and operational definitions will be added to the code book as interviews transcripts are analysed. Subsequent analyses will use the latest version of the code book, that is, the version that includes all in vivo codes. Themes will be created by reviewing the recurring codes based on within and across case similarities and differences (Ayres et al., 2003).

The multiple data types (surveys and biological indicators) will be plotted across time (days since transplant) and examined for trends. Plotting will be done by using a case-oriented visual analysis to describe trends in the person reported data over the 8–12 weeks post-transplant informed by qualitative themes by graphically assembling the multiple types of quantitative data along a timeline and then visually searching for patterns (Docherty et al., 2016). Themes from the interview data will provide contextual grounding for the cases and insights into factors influencing caregiver stress, psychological states and QOL.

4.6.3 |. Aim 2 Analytic Plan

Because the sample size for this study is small (10–12 caregivers), the number of nodes will be reduced by using subscale scores or total scores, depending on the measure, instead of individual item scores. Subscale scores will be calculated for the following measures: (a) mDES subscale scores for positive and negative emotions; (b) PROMIS-29 profile domain scores for anxiety, depression, fatigue, and sleep disturbance; and (c) SF-36 subscale scores for role limitations due to emotional health and social functioning.

4.6.4 |. Pre-analysis

The raw caregiver stress and PN symptom data will be plotted on a timeline for each caregiver and visually examined for changes over time. Particular attention will be made to caregiver scores before and after discharge from the hospital to explore whether caregiver stress and PN symptoms worsen following patients’ discharge from the hospital to outpatient care. If the expected worsening is noted, this observation suggests that two network models are needed to describe the stress response network (network 1 prior to discharge, network 2 post discharge). In the case that the raw data does not indicate the expected worsening, a single network model will be generated by pooling all data.

4.6.5 |. Network estimation

Network analysis will be conducted by using the following tutorial paper: Estimating networks and their stability (Epskamp et al., 2018). Gaussian Graphical Model (GGM) will be used to estimate regularized partial correlation networks for each weekly time point for pooled and individual data. First, the PI will estimate the network structure by computing and constructing network models using the R-package qgraph and graphicalVAR (GVAR) (Epskamp et al., 2012), which estimates associations between variables and forms network models that will provide a graphic representation of the linkages between variables. Using terminology from graph theory (Bondy & Murty, 2008), the network model will depict variables as nodes (circles) and associations between those variables as edges (lines connecting circles in the graphic image). The strength of an association edge (line) will be indicated by the thickness of the line. The coloration of the edge will be such that green lines represent positive associations and red lines negative associations between sets of variables. To generate parsimonious models, a least absolute shrinkage and selection operator (LASSO) estimation network will be used (Epskamp et al., 2012). The literature suggests that LASSO estimations are able to account for small samples with a large number of nodes by applying a penalty that reduces small correlations to zero (Epskamp et al., 2018). However, the built-in shrinkage operation may need to be adjusted to fit the network. Adjustments to the network model will be considered in the case that too many relationships are found (e.g. more stringent shrinkages). If no relationships are found, the default shrinkage will be adjusted by using a less strict shrinkage.

4.6.6 |. Centrality

Important nodes in the network will be identified by quantifying their importance through centrality measures. Degree, strength, betweenness, and closeness centrality will be calculated for each network model. The interpretation of these centrality measures will take into consideration the issues surrounding the use of centrality measures in psychological networks including that they may be unstable and unreliable in psychological networks (Bringmann et al., 2019). Centrality measures in psychological networks should be interpreted skeptically; some researchers suggest abandoning them all together in psychological networks (Bringmann et al., 2019). However, centrality measures will still be calculated and interpreted to gain insight into potential nodes of interest.

4.6.7 |. Robustness

Robustness of the networks will be examined by exploring the accuracy of edge weights and centrality indices using the R package bootnet (Epskamp, Borsboom, et al., 2018). Accuracy of edge weights will be estimated by calculating bootstrapped 95% confidence intervals (CI) around the edge weights and centrality indices. The estimated CI will contain the true edge weight parameter in 95% of the cases. Non-parametric bootstrapping, where the data will be resampled with replaced, will be used to create new datasets for testing. Smaller CIs denote more accuracy in the estimation of edges (Epskamp, Borsboom, et al., 2018). Smaller sample sizes and greater numbers of nodes have a negative impact on the robustness of a network (Epskamp, Borsboom, et al., 2018).

4.7 |. Ethical considerations

To protect both caregiver and index patient participants, the study underwent three separate reviews including by the local National Cancer Institute-funded comprehensive cancer center protocol review committee (PRC # 1831) which focuses on the science of the proposed research, local IRB (IRB # 18–1703) which focuses on risks to human subjects and adequacy of protections to minimize risk and the hospital’s Nursing Research Council which focuses on study demands on nursing resources. To reduce burden on caregivers, all meeting places and data collection scheduling will be made based on convenience to the participant.

All study materials will be de-identified. Informed consent documents and field notes will be stored in a locked document box in the PI’s secure office. Computerized form of the name-study number list will be kept separate from the study database. Random three-digit study numbers will be used to identify the participant’s study forms, specimen tube labels, audio files, and transcripts. Since this study is a small sample case-oriented study collecting details about intimate life events, additional precautions will be taken to protect privacy and confidentiality during dissemination. The precautions include only reporting de-identified aggregated data and reporting of generalized demographics when directly quoting from a case.

In addition, the study has ethical risks associated with the results of the analyses of biological data and returning these results to the participants. In particular, serum high sensitivity CRP levels of 3.0 mg/L or more indicate high risk for future cardiovascular disease and levels over 10.0 mg/L is indicative of acute bacterial or fungal infection (Emerging Risk Factors et al., 2010). Thus, lab assays will not be completed until all samples are collected. Once assays are completed, when a participant’s serum high sensitivity CRP is between 3.0 and 10 mg/L the participant will notified of the result and told to follow up with a primary health care provider Caregivers with CRPs > 10 will be strongly encouraged to see a PCP as soon as possible.

4.8 |. Validity and reliability/Rigour

The rigour and reproducibility of the laboratory methods and their results will be ensured by running all biological assays specimens in duplicate at a minimum, use of manufacturer-provided standards to generate standardized dilution curves for sample analysis and use of negative and positive controls for all assays. The rigour and trustworthiness of the qualitative methods and their results are addressed through strategies such as use of dual coders (thus enhancing credibility and authenticity), post-interview reflection to identify biases affecting conduct of the interview and conscientious recording of generated codes and identified themes, thus ensuring auditability. The PI will record variations in survey administration, biological specimen collection/processing, qualitative field notes and audit trail in field and lab notebooks.

5 |. Discussion

The purpose of the study outlined in this protocol was to describe the caregiver’s experience over 8–12 weeks after the index patient’s allogeneic BMT and explore networks of relationships among psycho-neurological symptoms, positive psychological states, and caregiver health. Previous research has demonstrated the negative effects of caregiving related stress on health (Schulz & Beach, 1999; Stenberg et al., 2010; Trevino et al., 2017), described the intensity of caregiving for a patient receiving an allogeneic BMT and highlighted the potential for positive psychological states in reducing negative stress effects. This study seeks to increase the richness of our understanding of stress processes during these uniquely intense times and to guide future research on targeted intervention development.

The coronavirus pandemic began while the study was well underway. Its spread to the United States halted all non-essential in-person research. Under the guidance of the IRB several changes to the study’s procedures were made. All in-person data collection was stopped in March of 2020 and participants were messaged about the change in study procedures and asked if they would like to continue. If interested in continuing, participants indicated whether they wanted survey’s by e-mail of text message. Interviews were conducted via telephone and all blood collections were stopped. The decision to stop all in-person data collection was made to reduce risk of spread of COVID-19 to the participant and caregiver. We maintain the original study aims and analytic plans but note that the pandemic may have altered the stress experiences of caregivers of these high-risk patients.

5.1 |. Limitations

A case-oriented longitudinal qualitative and quantitative approach was selected over a single method approach to gain a richer understanding of stress response and experiences of caregivers of patients receiving an allogeneic BMT. A cross-sectional design was also considered; however, the complex nature of stress response (biological and psychological) over time in allogeneic BMT caregiving over 8–12 weeks post-transplant cannot be examined through this design. The small sample size is appropriate given the study aims, design, methods and projected index patient population. As a descriptive study of a small group of caregivers, the findings may not be generalizable. Even so, the proposed research is a critical first step in generating hypotheses for future intervention research.

6 |. Conclusion

Caregivers of patients receiving an allogeneic BMT are at high risk for stress. Our understanding of their experiences has been limited by study design and the complex and intense nature of transplant. The study described in this protocol, will further enrich our understanding through in-depth longitudinal data collected from a diverse but small sample of caregivers.

Supplementary Material

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ACKNOWLEDGEMENTS

The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or the Hillman Foundation. The first author thanks her current and past members of her writing group (Martha Grace Cromeens, BSN, RN and Leah Morgan, BSN, RN, Laura Britton, PhD, RN, Elizabeth Myers, BSN, RN, Rebecca Salomon, PhD, RN), the UNC School of Nursing Research Support & Consultation Office (Gregory Workman, Ruth Anderson, PhD, RN, FAAN, Barbara Mark, PhD, RN, FAAN) and so many others (Ashley Bryant, PhD, RN-BC, Lixin Song, PhD, RN, FAAN), for their feedback, support, and critical comments.

FUNDING INFORMATION

National Institutes of Health/National Institute of Nursing Research Grant Number: F31NR018098 (PI: K. R. Tan, Sponsors: B. L. Fredrickson and S. J. Santacroce).

National Institutes of Health/National Institute of Nursing Research Grant Number: T32NR007091 (MPIs: S. J. Santacroce/contact and J. Leeman).

Rita and Alex Hillman Foundation Hillman Scholars of Nursing Innovation Program (PI: C. Jones).

Funding information

National Institutes of Health/National Institute of Nursing Research, Grant/Award Number: F31NR018098 and T32NR007091

Footnotes

SUPPORTING INFORMATION

Additional supporting information may be found online in the Supporting Information section.

PEER REVIEW

The peer review history for this article is available at https://publons.com/publon/10.1111/jan.14742.

CONFLICT OF INTEREST

The authors declare that there are no conflicts of interest.

R EFER EN CE S

  1. Applebaum AJ, Bevans M, Son T, Evans K, Hernandez M, Giralt S, & DuHamel K. (2016). A scoping review of caregiver burden during allogeneic HSCT: Lessons learned and future directions. Bone Marrow Transplantation, 51(11), 1416–1422. 10.1038/bmt.2016.164 [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Atilla E, Atilla PA, Toprak SK, & Demirer T. (2017). A review of late complications of allogeneic hematopoietic stem cell transplantations. Clinical Transplant, 31(10), e13062. 10.1111/ctr.13062 [DOI] [PubMed] [Google Scholar]
  3. Ayres L, Kavanaugh K, & Knafl KA (2003). Within-case and across-case approaches to qualitative data analysis. Qualitative Health Research, 13(6), 871–883. 10.1007/s11136-012-0122-x [DOI] [PubMed] [Google Scholar]
  4. Bergeron A. (2017). Late-onset noninfectious pulmonary complications after allogeneic hematopoietic stem cell transplantation. Clinics in Chest Medicine, 38(2), 249–262. 10.1016/j.ccm.2016.12.013 [DOI] [PubMed] [Google Scholar]
  5. Bevans MF, & Sternberg EM (2012). Caregiving burden, stress and health effects among family caregivers of adult cancer patients. JAMA, 307(4), 398–403. 10.1001/jama.2012.29 [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Bjorner JB, Rose M, Gandek B, Stone AA, Junghaenel DU, & Ware JE Jr (2014). Method of administration of PROMIS scales did not significantly impact score level, reliability, or validity. Journal of Clinical Epidemiology, 67(1), 108–113. 10.1016/j.jclinepi.2013.07.016 [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Bondy JA, & Murty USR (2008). Graph theory. : Springer. http://www.loc.gov/catdir/enhancements/fy0825/2007940370-d.html [Google Scholar]
  8. Borsboom D, & Cramer AO (2013). Network analysis: An integrative approach to the structure of psychopathology. Annu Rev Clin Psychol, 9, 91–121. 10.1146/annurev-clinpsy-050212-185608 [DOI] [PubMed] [Google Scholar]
  9. Braun V, & Clarke V. (2014). What can “thematic analysis” offer health and wellbeing researchers? International Journal of Qualitative Studies on Health and Well-being, 9, 26152. 10.3402/qhw.v9.26152 [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Bringmann LF, Elmer T, Epskamp S, Krause RW, Schoch D, Wichers M, Wigman J, & Snippe E. (2019). What do centrality measures measure in psychological networks? Journal of Abnormal Psychology, 128(8), 892–903. 10.1037/abn0000446 [DOI] [PubMed] [Google Scholar]
  11. Cohn MA, Fredrickson BL, Brown SL, Mikels JA, & Conway AM (2009). Happiness unpacked: Positive emotions increase life satisfaction by building resilience. Emotion, 9(3), 361–368. 10.1037/a0015952 [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Corrêa MS, Vedovelli K, Giacobbo BL, de Souza C, Ferrari P, de Lima Argimon II, Walz JC, Kapczinski F, & Bromberg E. (2015). Psychophysiological correlates of cognitive deficits in family caregivers of patients with Alzheimer Disease. Neuroscience, 286, 371–382. 10.1016/j.neuroscience.2014.11.052 [DOI] [PubMed] [Google Scholar]
  13. Docherty SL, Vorderstrasse A, Brandon D, & Johnson C. (2016). Visualization of multidimensional data in nursing science. Western Journal of Nursing Research, 10.1177/0193945916672448 [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Elo S, & Kyngas H. (2008). The qualitative content analysis process. Journal of Advanced Nursing, 62(1), 107–115. 10.1111/j.1365-2648.2007.04569.x [DOI] [PubMed] [Google Scholar]
  15. Emerging Risk Factors C, Kaptoge S, Di Angelantonio E, Lowe G, Pepys MB, Thompson SG, Collins R, & Danesh J. (2010). C-reactive protein concentration and risk of coronary heart disease, stroke and mortality: An individual participant meta-analysis. Lancet, 375(9709), 132–140. 10.1016/S0140-6736(09)61717-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Epskamp S, Borsboom D, & Fried EI (2018). Estimating psychological networks and their accuracy: A tutorial paper. Behavioral Research Methods, 50(1), 195–212. 10.3758/s13428-017-0862-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Epskamp S, Cramer AOJ, Waldorp LJ, Schmittmann VD, & Borsboom D. (2012). qgraph: Network Visualizations of Relationships in Psychometric Data. Journal of Statistical Software, 48(4), 1–18. 10.18637/jss.v048.i04. [DOI] [Google Scholar]
  18. Epskamp S, Waldorp LJ, Mottus R, & Borsboom D. (2018). The gaussian graphical model in cross-sectional and time-series data. Multivariate Behavioral Research, 53(4), 453–480. 10.1080/00273171.2018.1454823 [DOI] [PubMed] [Google Scholar]
  19. Flynn KE, Dew MA, Lin L, Fawzy M, Graham FL, Hahn EA, Hays RD, Kormos RL, Liu H, McNulty M, & Weinfurt KP (2015). Reliability and construct validity of PROMIS(R) measures for patients with heart failure who undergo heart transplant. Quality of Life Research, 24(11), 2591–2599. 10.1007/s11136-015-1010-y [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Foster LW, McLellan LJ, Rybicki LA, Dabney J, Welsh E, & Wolwell BJ (2005). Allogeneic BMT and patient eligibility based on psychosocial criteria: A survey of BMT professionals. Bone Marrow Transplantation, 37, 223–228. 10.1038/sj.bmt.1705219 [DOI] [PubMed] [Google Scholar]
  21. Fredrickson BL (2004). The broaden-and-build theory of positive emotions. Philosophical Transactions of the Royal Society B Biological Scienxes, 359(1449), 1367–1378. 10.1098/rstb.2004.1512 [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Fredrickson BL (2013). Positive emotions broaden and build. In Devine P & Plant A. (Eds.), Advances on experimental social psychology, Vol. 47 (pp. 1–53). Cambridge, MA: Academic Press. [Google Scholar]
  23. Fredrickson BL, Cohn MA, Coffey KA, Pek J, & Finkel SM (2008). Open hearts build lives: Positive emotions, induced through loving-kindness meditation, build consequential personal resources. Journal of Personality and Social Psychology, 95(5), 1045–1062. 10.1037/a0013262 [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Gemmill R, Cooke L, Williams AC, & Grant M. (2011). Informal caregivers of hematopoietic cell transplant patients: A review and recommendations for interventions and research. Cancer Nursing, 34(6), E13–21. 10.1097/NCC.0b013e31820a592d [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Herbert TB, & Cohen S. (1993). Stress and immunity in humans: A meta-analytic review. Psychosomatic Medicine, 55(4), 364–379. 10.1097/00006842-199307000-00004 [DOI] [PubMed] [Google Scholar]
  26. Hsieh HF, & Shannon SE (2005). Three approaches to qualitative content analysis. Qualitative Health Research, 15(9), 1277–1288. 10.1177/1049732305276687 [DOI] [PubMed] [Google Scholar]
  27. Kent EE (2020). Time to Recognize and Support Emerging Adult Caregivers in Public Health. American Journal of Public Health, 110, (12), 1720–1721. 10.2105/ajph.2020.305951 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Kim Y, & Carver CS (2012). Recognizing the value and needs of the caregiver in oncology. Current Opinion in Supportive and Palliative Care, 6(2), 280–288. 10.1097/SPC.0b013e3283526999 [DOI] [PubMed] [Google Scholar]
  29. Kupst MJ, Butt Z, Stoney CM, Griffith JW, Salsman JM, Folkman S, & Cella D. (2015). Assessment of stress and self-efficacy for the NIH Toolbox for Neurological and Behavioral Function. Anxiety Stress & Coping, 28(5), 531–544. 10.1080/10615806.2014.994204 [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Lambert SD, Yoon H, Ellis KR, & Northouse L. (2015). Measuring appraisal during advanced cancer: Psychometric testing of the appraisal of caregiving scale. Patient Education and Counseling, 98(5), 633–639. 10.1016/j.pec.2015.01.009 [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Li Q, & Loke AY (2013). The positive aspects of caregiving for cancer patients: a critical review of the literature and directions for future research. Psycho-oncology, 22(11), 2399–2407. 10.1002/pon.3311 [DOI] [PubMed] [Google Scholar]
  32. Maffini E, Festuccia M, Brunello L, Boccadoro M, Giaccone L, & Bruno B. (2017). Neurologic complications after allogeneic hematopoietic stem cell transplantation. Biology of Blood Marrow Transplantation, 23(3), 388–397. 10.1016/j.bbmt.2016.12.632 [DOI] [PubMed] [Google Scholar]
  33. McCain NL, Gray DP, Walter JM, & Robins J. (2005). Implementing a comprehensive approach to the study of health dynamics using the psychoneuroimmunology paradigm. Advances in Nursing Scienxe, 28(4), 320–332. 10.1097/00012272-200510000-00004 [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. McCain NL, & Smith JC (1994). Stress and coping in the context of psychoneuroimmunology: A holistic framework for nursing practice and research. Archives of Psychiatric Nursing, 8(4), 221–227. 10.1016/0883-9417(94)90063-9 [DOI] [PubMed] [Google Scholar]
  35. McHorney CA, Ware JE Jr, & Raczek AE (1993). The MOS 36-Item Short-Form Health Survey (SF-36): II. Psychometric and clinical tests of validity in measuring physical and mental health constructs. Medical Care, 31(3), 247–263. https://www.ncbi.nlm.nih.gov/pubmed/8450681. [DOI] [PubMed] [Google Scholar]
  36. Merriwether EN, Rakel BA, Zimmerman MB, Dailey DL, Vance CGT, Darghosian L, Golchha M, Geasland KM, Chimenti R, Crofford LJ, & Sluka KA (2017). Reliability and construct validity of the Patient-Reported Outcomes Measurement Information System (PROMIS) instruments in women with fibromyalgia. Pain Medicine, 18(8), 1485–1495. 10.1093/pm/pnw187 [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Oberst MT, Thomas SE, Gass KA, & Ward SE (1989). Caregiving demands and appraisal of stress among family caregivers. Cancer Nursing, 12(4), 209–215. 10.1097/00002820-198908000-00003 [DOI] [PubMed] [Google Scholar]
  38. Patton MQ (2002). Qualitative research and evaluation methods., 3rd.ed. Sage Publications. [Google Scholar]
  39. R Core Team. (2020). R: A language and environment for statistical computing. In R Foundation for Statistical Computing. https://www.R-project.org/ [Google Scholar]
  40. Schulz R, & Beach SR (1999). Caregiving as a risk factor for mortality: The Caregiver Health Effects Study. JAMA, 282(23), 2215–2219. 10.1001/jama.282.23.2215 [DOI] [PubMed] [Google Scholar]
  41. Simoneau TL, Mikulich-Gilbertson SK, Natvig C, Kilbourn K, Spradley J, Grzywa-Cobb R, Philips S, McSweeney P, & Laudenslager ML (2013). Elevated peri-transplant distress in caregivers of allogeneic blood or marrow transplant patients. Psychooncology, 22(9), 2064–2070. 10.1002/pon.3259 [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Stenberg U, Ruland CM, & Miaskowski C. (2010). Review of the literature on the effects of caring for a patient with cancer. Psychooncology, 19(10), 1013–1025. 10.1002/pon.1670 [DOI] [PubMed] [Google Scholar]
  43. Tan KR, Santacroce SJ, Mayer DK, & Fredrickson BL (In Review). Synthesis of theories for studying positive emotions, stress, and health in caregivers of adults with advanced cancer. [Google Scholar]
  44. Tarlow BJ, Wisniewski SR, Belle SH, Rubert M, Ory MG, & Gallagher-Thompson D. (2004). Positives aspects of caregiving. Research on Aging, 26(4), 429–453. 10.1177/0164027504264493 [DOI] [Google Scholar]
  45. Trevino KM, Prigerson HG, & Maciejewski PK (2017). Advanced cancer caregiving as a risk for major depressive episodes and generalized anxiety disorder. Psychooncology, 27(1), 243–249. 10.1002/pon.4441 [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Von Ah D, Spath M, Nielsen A, & Fife B. (2016). The Caregiver’s Role Across the Bone Marrow Transplantation Trajectory. Cancer Nursing, 39(1), E12–E19. 10.1097/NCC.0000000000000242 [DOI] [PubMed] [Google Scholar]
  47. Williams LA (2007). Whatever it takes: Informal caregiving dynamics in blood and marrow transplantation. Oncology Nursing Forum, 34(2), 379–387. 10.1188/07.ONF.379-387 [DOI] [PubMed] [Google Scholar]
  48. Wulff-Burchfield EM, Jagasia M, & Savani BN (2013). Long-term follow-up of informal caregivers after allo-SCT: A systematic review. Bone Marrow Transplantion, 48(4), 469–473. 10.1038/bmt.2012.123 [DOI] [PubMed] [Google Scholar]

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