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Data · dataset · 2025

The Impact of Financial Strain on Work-Family Conflict During COVID-19

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SAS data file used to produce results for article published in the Journal of Business and Psychology examining the impact of financial strain on work-family conflict during COVID-19. doi.org/10.1007/s10869-025-10063-2 Data were collected at seven time points between April 2020 and October 2020 using a longitudinal panel design. Participants were workers registered with Amazon's Mechanical Turk who were located in the United States

Abstract

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The announcements of pandemic lockdown measures across North America in mid-March 2020 marked the start of a chaotic period with extensive changes at work and at home. Because families experiencing financial strain had fewer resources to help manage work and family demands, the present study examined how financial strain at the within- and between-person levels influenced work interference with family (WIF) and family interference with work (FIW) and whether those experiences were moderated by childcare and eldercare responsibilities.

Using a longitudinal panel design, 538 workers recruited through Amazon’s Mechanical Turk responded to seven surveys between April and October 2020 asking about financial strain, WIF, and FIW. Multilevel modeling showed that an individual's average financial strain over the seven-month period was associated with higher WIF and FIW; however, a higher-than-usual level of financial strain was associated only with higher FIW.

Interactions of financial strain with childcare and eldercare were not significant. At the between-person level, financial strain was an important contributor to WIF and FIW, even after accounting for childcare and eldercare. Consistent with conservation of resources theory, these findings suggest that financial strain represents a perceived threat that actively draws on limited personal resources, thereby reducing capacity to manage work-family conflict.

This underscores the need for greater support for families experiencing financial strain. In addition to fair pay and benefits, organizations could consider novel approaches to reducing financial strain amongst employees such as financial counselling and emergency income replacement funds. This readme file was generated on 2025-07-25 by Christine Tulk -------------------- GENERAL INFORMATION -------------------- 1.

Title of Dataset: The Impact of Financial Strain on Work-Family Conflict During COVID-19 2. Author Information Name: Christine Tulk ORCID: 0000-0001-7312-7406 Institution: Carleton University Address: Ottawa, Canada Email: christine.tulk@carleton.ca 3. Date of data collection: 538 responses at Time 1 (April 17-18), 320 responses at Time 2 (May 4-11), 263 responses at Time 3 (June 6-13), 250 responses at Time 4 (July 9-16), 225 responses at Time 5 (Aug 17-24), 203 responses at Time 6 (Sept 26 - Oct 3), and 181 responses at Time 7 (Oct 28 - Nov 4) 4.

Geographic location of data collection: MTurk workers located in the United States 5. Dataset Description: The data are formatted in long format suitable for multilevel modeling with one row per time point per participant. ----------------------------------- SHARING/ACCESS INFORMATION ----------------------------------- Links to publications that cite or use the data: doi.org/10.1007/s10869-025-10063-2 ------------------------- DATA & FILE OVERVIEW ------------------------- 1.

File List: financial_strain.sas7bdat - SAS data file financial_strain.csv - Text file 3. Additional related data collected that was not included in the current data package: Additional variables were collected and are available upon reasonable request from the author. --------------------------- METHODOLOGICAL INFORMATION --------------------------- 1. Description of methods used for collection/generation of data: Collected by surveys administered at seven times between April 2020 and October 2020 2.

Methods for processing the data: Data were initially downloaded from the Qualtrics web site in Excel format and imported into SAS. ------------------------------------------- DATA-SPECIFIC INFORMATION FOR: financial_strain.csv/sas7bdat ------------------------------------------- 1. Number of variables: 2. Number of cases/rows: 1977 rows 3.

Variable List: id (Level 2): participant id Gender (Level 2): man = 0, woman = 1 BC_Emotion (Level 2): Measure of emotion-focused coping BC_Problem (Level 2): Measure of problem-focusing coping BC_Support (Level 2): Measure of support-focused coping FinM (Level 2): Person-averaged financial strain FinCM (Level 2): Person-averaged financial strain centered around group mean Child (Level 2): 0 = No childcare responsibilities 1 = Childcare responsibilities Elder (Level 2): 0 = No eldercare responsibilities 1 = Eldercare responsibilities Partner (Level 2): 0 = Not partnered (e.g., single, divorced) 1 = Partnered (e.g., married) wfcM (Level 2): Person-averaged work-to-family conflict fwcM (Level 2): Person-averaged family-to-work conflict HoursM (Level 2): Person-averaged average work hours per day TIME (Level 1): Time measure ranging from 0 (Time 1) to 6 (Time 7) WorkLocD ((Level 1): Work Location: 0 = outside the home 1 = inside the home Symp (Level 1): Symptoms of COVID: 0 = no 1 = yes SympOth (Level 1): Family members have symptoms of COVID: 0 = no 1 = yes Fin (Level 1): Financial strain ranging from 1 to 5.

FinC (Level 1): Deviation-from-average financial strain wfcC (Level 1): Deviation-from-average work-to-family conflict fwcC (Level 1): Deviation-from average family-to-work conflict wfc1 (Level 1): Item 1 for work-to-family conflict wfc2 (Level 1): Item 2 for work-to-family conflict fwc1 (Level 1): Item 1 for family-to-work conflict fwc2 (Level 1): Item 2 for family-to-work conflict ------------------------------------------- Description of Measures ------------------------------------------- Financial Strain Participants responded to a single item assessing the subjective perception of financial strain taken from Vinokur and Caplan (1987): “How difficult is it for you to live on your total household income right now?” Responses were measured on a 5-point scale from 1 (not at all difficult) to 5 (extremely difficult).

Work-Family Conflict Four items were taken from Frone et al.’s (1992) measure of time-based work-family conflict. Two items were averaged as a measure of WIF: “Over the past week, how often has your work interfered with your responsibility at home, such as child care, homeschooling, yard work, cooking, cleaning, repairs, shopping, or paying the bills?” and “Over the past week, how often has your work kept you from spending the amount of time you would like to spend with your family?” Two items were averaged as a measure of FIW: “Over the past week, how often has your homelife interfered with your responsibilities at work, such as getting to work on time, accomplishing daily tasks, or working overtime?” and “Over the past week, how often has your homelife kept you from spending the amount of time you would like to spend on work-related activities?" All responses were measured on 5-point scales from 1 (strongly disagree) to 5 (strongly agree).

Childcare and Eldercare Participants were asked “How many children are there currently in your home requiring care and/or homeschooling?” and “How many elderly family members in or outside your home are you providing care or services for?” We used dichotomous variables in the analyses to represent whether participants had childcare (yes/no) or eldercare (yes/no) responsibilities. Gender, Partner, Work Hours, Work Location, Symptoms of COVID-19 Control variables based on questions asked at Time 1 included gender [man, woman] and relationship partner status [partnered: living with partner and married; not partnered: single, separated/divorced, widowed].

Control variables based on questions asked at every time included average hours of work per day, working from home status [inside the home, outside the home], and whether the participant or their family members currently had symptoms or a diagnosis of COVID-19 as control variables to account for their role in work-family conflict.

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Social Sciences
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Banking, finance and investment 68% · Text 75%
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