
==== Front
Health Psychol Behav Med
Health Psychol Behav Med
Health Psychology and Behavioral Medicine
2164-2850
Routledge

2396137
10.1080/21642850.2024.2396137
Version of Record
Data Note
Data Note
The Seattle Amyotrophic Lateral Sclerosis (ALS) Patient Project Database: observational, longitudinal, dyadic characterization of people with ALS and their partners
HEALTH PSYCHOLOGY AND BEHAVIORAL MEDICINE
S. C. SEGERSTROM AND E. J. KASARSKIS
https://orcid.org/0000-0002-4020-111X
suzannecarrie
Segerstrom Suzanne C. ab
https://orcid.org/0000-0001-5584-7506
Kasarskis Edward J. c
a School of Human Development and Family Sciences, Oregon State University, Corvallis, OR, USA
b Department of Psychology, University of Kentucky, Lexington, KY, USA
c Department of Neurology, University of Kentucky College of Medicine, Lexington, KY, USA
CONTACT Suzanne C. Segerstrom suzanne.segerstrom@oregonstate.edu School of Human Development and Family Sciences, Oregon State University, 401 Waldo Hall, Corvallis, OR 97331, USA; Department of Psychology, University of Kentucky, 125 Kastle Hall, Lexington, KY 40506-0044, USA
Supplemental data for this article can be accessed online at https://doi.org/10.1080/21642850.2024.2396137.

4 9 2024
2024
4 9 2024
12 1 239613714 4 2024
16 8 2024
Nova techset22 8 2024
Converted to JATS 1.2 by Nova Techset22 8 2024
© 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group
2024
The Author(s)
https://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.

ABSTRACT

Introduction:

The median survival time in ALS is approximately 3 years, but survival times range from less than a year to more than 10 years and much variance in disease course remains to be explained. As is true for physical outcomes, there is considerable variance in QOL, which is influenced by psychological health, coping, and social support, among other psychosocial factors. The Seattle ALS Patient Project Database (SALSPPD) provides a unique opportunity for researchers to address established and novel hypotheses about disease progression and QOL in ALS.

Methods:

The SALSPPD is a longitudinal dataset of people with ALS (n = 143) and their partners (spouses, significant others, or caregivers; n = 123) from clinics and community-based ALS support groups. Participants were interviewed in their homes every 3 months for up to 18 months between March 1987 and August 1989. Follow-up phone calls were completed in 1990, 1994, and 2008, primarily to ascertain disease outcomes.

Results:

The provided data dictionary includes details of the over 500 variables measured in the study, which have been subsetted into domain datasets. Domains address physical, psychological, social, and behavioral status on the person with ALS and their partners. Missing data were coded according to their mechanism. Data are available in two formats: The person-level (wide) databases and the time-level (long) databases.

Discussion:

The SALSPPD will provide a rich resource to scientists interested in the natural history of ALS, psychosocial effects on ALS outcomes and vice versa, and psychosocial and disease outcomes of treatments.

KEYWORDS

Neurology
dyadic
longitudinal
quality of life
progression
The dataset used in this paper was collected by the Seattle ALS Patient Profile Project, an all-volunteer staff maintaining the rigor of a funded study. This research was funded in part by the University of Washington, The New Road Map Foundation, and Veterans Affairs, Seattle, Washington, USA. Preparation of the database was funded by the National Institute of Neurological Disorders and Stroke [R03-NS129748 to SCS].
==== Body
pmcIntroduction

Amyotrophic lateral sclerosis (ALS) is characterized by degeneration of upper and lower motor neurons initially resulting in weakness, rapid muscle twitches (fasciculations), and/or electromyogram (EMG) abnormalities and progressing to loss of respiratory and skeletal muscle function, with progressive paralysis and loss of ability to speak and ultimately to breathe. At that point, without mechanical ventilation, death ensues (Strong et al., 2017). The median survival time in ALS is approximately 3 years, but survival times range from less than a year to more than 10 years (Magnussen & Glass, 2017; Masrori & Damme, 2020). Some predictors of disease course have been identified, including bulbar (i.e. speaking, swallowing) onset, shorter time to diagnosis and faster decline, older age, lower respiratory function (i.e. forced vital capacity), and familial disease (Chiò et al., 2009; Magnussen & Glass, 2017; Masrori & Damme, 2020). However, much variance in disease course remains to be explained. A recent, good-performing prognostic model that used established predictors left both considerable unexplained variation from model-predicted survival and substantial overlap between prognostic groups (Westeneng et al., 2018). Therefore, validation of more prognostic factors is needed to more precisely predict outcomes in ALS.

In addition, people with ALS (pwALS) and their social networks are faced with adapting to extensive physical challenges and the reality of a markedly shortened life expectancy. There are also expectations of adherence to medical recommendations and possible participation in clinical research. As a consequence, quality of life (QOL) for both pwALS and their caregivers is affected by the disease. As is true for physical outcomes, there is considerable variance in QOL, which is influenced by pwALS’s and caregivers’ psychological health, coping, and social support, among other psychosocial factors (Averill et al., 2007; Caga et al., 2021; Edge et al., 2020; Segerstrom et al., 2019). Indeed, disease progression may not be the major contributor for pwALS, although it may be a contributor for caregivers (Roach et al., 2009). QOL may also interact with physical outcomes. Psychological health, social relationships, and other QOL indicators have been associated with longer survival in ALS (Chiò et al., 2009; Garcia-Willingham et al., 2018; McDonald et al., 1994; Spataro et al., 2017). Unfortunately, many studies of psychological health and QOL in ALS have small samples and cross-sectional designs (Benbrika et al., 2019).

Effects of interventions on survival and QOL are important for optimal care, recommendations, and decision-making (McDonald et al., 1996; Miller et al., 2009a; 2009b). Pharmacological, nutritional (e.g. feeding tube), and respiratory (e.g. noninvasive and invasive ventilation) interventions have survival benefits, leading to a recommendation for multidisciplinary care of ALS (Miller et al., 2009b). However, effects of these interventions on QOL are not as well characterized, nor are the joint effects (e.g. whether effects on QOL are related to effects on survival). Where an intervention extends lifespan but negatively affects QOL, ‘the cure can be worse than the disease’ (Chang et al., 2011, p. 97). Patient-reported outcomes are integral to assessing effects of interventions on health span above and beyond life span (Chang et al., 2011).

Psychosocial intervention trials for pwALS and caregivers had mixed results in terms of effects on QOL, perhaps due to small sample sizes, high dropout attributable to development of disability in pwALS, time demands in their caregivers, and rapidly changing psychosocial needs over the disease course (Averill et al., 2013; Oh et al., 2024). Due to these limitations, evidence for effectiveness in ‘real world’ conditions may, in this case, exceed evidence for efficacy in controlled trials, where treatment cannot be as nimble in responding to changing circumstances.

The Seattle ALS Patient Project Database (SALSPPD) provides a unique opportunity for researchers to address established and novel hypotheses about disease progression and QOL in ALS and to examine wide-ranging facets of the personal and clinical situation that could exert either a positive or a negative influence on the totality of ALS outcomes. The database contains a broad range of assessment domains on pwALS and their study partners (spouses, significant others, or caregivers), including health behavior, attitudes, beliefs, coping, family and social context, treatments, and physical and psychological health. Furthermore, these are longitudinal data with assessments every 3 months for up to 18 months. Many variables have not been examined, making this a rich resource for researchers. These data are innovative in that they are dyadic and longitudinal; cross traditional disciplinary boundaries; and provide opportunities to examine predictors of disease progression, QOL, and effects of clinical interventions on physical outcomes and on patient- and caregiver-reported outcomes. As of 2019, ‘there have been very few studies about the relationships between the cognitive (or psychological, or behavioral, for that matter) and physical profiles of patients’ (Benbrika et al., 2019, p. 17).

Materials and methods

The SALSPPD is a longitudinal dataset of pwALS (n = 143) and their partners (spouses, significant others, or caregivers; n = 123) from clinics and community-based ALS support groups in Seattle, WA (n = 44); San Francisco, CA (n = 55); and Philadelphia, PA (n = 44). Table 1 gives the demographic and clinical characteristics of the sample. The purpose of the study was to characterize the psychosocial and physical natural histories of ALS and the interactions between them. Inclusion criteria were ALS diagnosis by a neurologist and ability to communicate in English. Exclusion criteria were diagnosed dementia or alcoholism. There were no inclusion or exclusion criteria related to disease severity, length of illness, or ventilator status (McDonald et al., 1994). The study was approved by the University of Washington Human Subjects Committee (number unknown); preparation of the database from identified data was approved by the University of Kentucky Institutional Review Board (#76660) and exemption for work on the de-identified data was provided the Oregon State University Institutional Review Board (#HE-2023-761). Table 1. Seattle ALS patient profile database baseline participant characteristics: M (SD) or n (per cent).

 	pwALS (n = 143)	Partners (n = 123)	
Age (years)	60.0 (12.0)	55.3 (14.3)	
Gender	 	 	
 Male	95 (66%)	33 (27%)	
 Female	48 (34%)	90 (73%)	
Ethnicity	 	 	
 White/Caucasian	135 (94%)	115 (93%)	
 Black/African-American	5 (4%)	5 (4%)	
 Hispanic/Latin@	1 (0.7%)	1 (0.8%)	
 Asian	1 (0.7%)	1 (0.8%)	
 Native American	1 (0.7%)	1 (0.8%)	
Education	 	 	
 No formal education	0	0	
 Grade 1–6	0	1 (0.8%)	
 Grade 7–9	8 (6%)	9 (7%)	
 Grade 10–12	44 (31%)	40 (33%)	
 Graduation equivalent (GED)	5 (4%)	3 (2%)	
 Some college	45 (31%)	40 (33%)	
 College degree	18 (13%)	11 (9%)	
 Some post-graduate study	6 (4%)	9 (7%)	
 Master’s degree	11 (8%)	6 (5%)	
 Doctoral degree	6 (4%)	4 (3%)	
Household annual income (1987 US$1 = 2023 US$2.68)	 	 	
 0–5000	15 (10%)	 	
 5001–10,000	16 (11%)	 	
 10,001–15,000	36 (25%)	 	
 15,001–20,000	28 (20%)	 	
 25,001–35,000	11 (8%)	 	
 35,001–50,000	14 (10%)	 	
 Over 50,000	12 (8%)	 	
 Missing	11 (8%)	 	
Length since first ALS diagnosis (months)	54.7 (63.1)	 	
Forced vital capacity (liters; n = 63)	2.36 (1.38)	 	
Ventilator status (hours per day)	 	 	
 0	125 (87%)	 	
 <8	4 (3%)	 	
 8–15	1 (1%)	 	
 16–19	0	 	
 20–24	13 (9%)	 	

Participants were interviewed in their homes every 3 months for up to 18 months between March 1987 and August 1989. Follow-up phone calls were completed in 1990, 1994, and 2008, primarily to ascertain disease outcomes.

Table 2 gives the major measurement domains included in the study. The provided data dictionary (Supplemental Online Material 1) includes details of the over 500 variables measured in the study, which have been subsetted into domain datasets: ALS Severity Scale (ALS), behavioral history (BHX), social cognition (COG), disease devices (DDV), demographics (DEM), disease history (DHX), disease treatments (DTX), family structure (FAM), family medical history (FHX), medical history (MHX), disease survival outcomes (OUT), psychiatric and psychological functions (PPF), psychological health (PSY), social role activity (SRA), social support (SSP), and study variables (STU). Table 2. Seattle ALS patient profile database domain-specific datasets: domain code and description with examples of measured constructs.

Domain	Contents	Examples	
ALS	ALS Severity Scale Scores	lower extremities, upper extremities	
BHX	Behavioral History	alcohol and tobacco use	
COG	Social Cognition	attitudes, beliefs, personality from informant	
DDV	Disease Devices	feeding tube, respirator	
DEM	Demographics	age, education	
DHX	Disease History	symptom onsets, forced vital capacity	
DTX	Disease Treatments	providers, treatments	
FAM	Family Structure	marital status, number of children	
FHX	Family Medical History	neurological diseases, cancer, CVD	
MHX	Medical History	infections, hospitalizations, surgeries	
OUT	Outcomes	vital status	
PPF	Psychiatric and Psychological Functions	appraisals, coping	
PSY	Psychological Health	anger, depression, body appraisal	
SRA	Social Role Activity	hours in different activities, social roles	
SSP	Social Support	support group attendance, social support	
STU	Study Variables	completion, time to visits, study site	

Ethics statement

The Seattle ALS Patient Project was approved by the University of Washington Human Subjects Committee; preparation of the database was approved by the University of Kentucky Institutional Review Board and the Oregon State University Institutional Review Board. Institutional Review Board Statement: The study was conducted in accordance with the Declaration of Helsinki and was approved by an Institutional Review Board/Ethics committee (University of Washington, number unknown; University of Kentucky, #76660). See details under Methods. The study received an exemption from an Institutional Review Board/Ethics committee (Oregon State University, #HE-2023-761). See details under Methods.

Dataset validation and description

From the original dataset, variables were grouped by domain (see above) and renamed, according to explicit conventions, by domain, variable meaning, and indicators (where applicable), for example, BHXalcOZ is alcohol use in ounces. Data were de-identified by replacing the original study ID with a new, random ID number and by expressing all dates including dates of birth and death as number of days before or after the first interview.

Missing data were coded according to their mechanism: death, dropout, unmeasured, not applicable, or no partner in study. If data were missing for another, unknown reason, a generic missing data code was applied. The values of all variables were checked using the R (4.2.0) package validate (van der Loo & de Jonge, 2021). There were a handful of recorded values out of the possible range, and these values were replaced with a specific missing data code.

People are identified by the dyad-level variable ID. In some data, variables were only assessed on or were only relevant to the pwALS (e.g. ALS Severity Scale scores). In some data, variables were also assessed on the partner/significant other. Finally, some variables were assessed by asking the partner/significant other to report on the pwALS. These sources of data have their own records, identified by the person-level variable PERSON. Therefore, in the person-level databases, records are identified by ID and PERSON.

Data are available in two formats. The person-level (wide) database contains variables measured only once as well as variables measured repeatedly, indicated by _x, where x is the visit number. For example, ALSlower_3 is the ALSS lower extremities score at Visit 3. Visits 1–7 are the full interviews, and Visits 8–10 are the vital status follow-ups (1990, 1994, and 2008). The time-level (long) database contains variables measured repeatedly, where each visit has its own record, identified by the variable TIME. Therefore, in the time-level databases, records are identified by ID, PERSON, and TIME.

For each variable, the data dictionary indicates variable type (e.g. ordinal) and range, variable definition, whether variables were measured once or repeatedly, whether the data source was the pwALS or partner (reporting on self and/or reporting on pwALS), any interviews at which the variable was not assessed, and suggested code groupings by the original study investigators. Coding information is included in the data dictionary and in the accompanying study codes document (Supplemental Online Material 2).

Discussion

The SALSPPD represents an extremely rich, longitudinal description of a relatively large sample of pwALS and their study partners. As such, it can be used to test many kinds of hypotheses about the interactions among psychological, social, functional, and physical changes during ALS progression. Relatively few papers have been published using these data. Published results include the effect of pwALS composite psychosocial health on survival through 1990 (1994 and 2008 survival outcomes were not included) (McDonald et al., 1994), pwALS psychological health as it relates to ventilator status (McDonald et al., 1996), psychosocial correlates of pwALS hopelessness (Plahuta et al., 2002), pwALS-caregiver dyadic similarity and dissimilarity in purpose in life and quality of life (Garcia et al., 2017), and pwALS-spouse differences in the effect of financial and social resources on psychological health (Segerstrom et al., 2019). These investigations, while addressing important questions, only scratch the surface of the dataset.

At the time the SALSPPD data were collected, it was believed that ‘dementia in ALS is undoubtedly rare’ (Montgomery & Erickson, 1987, p. 69). It is now recognized that ALS can include cognitive decline and frontotemporal dementia (Phukan et al., 2007). Current diagnostic criteria identify subtypes of ALS with behavioral impairment (e.g. apathy, reduced empathy, difficulties in self-regulation); with cognitive impairment (e.g. neuropsychological deficits, typically verbal and executive); and with frontotemporal dementia, including behavioral variant (e.g. emotional blunting, loss of insight, changes in social conduct) (Strong et al., 2017). Behavioral impairments occur in 30–40% of pwALS, and behavioral variant frontotemporal dementia occurs in 7–13% (Garcia-Willingham, 2018; Raaphorst et al., 2012). These features are associated with lower QOL for pwALS and their caregivers (de Wit et al., 2018; Radakovic et al., 2024) and shorter survival in pwALS (e.g. Garcia-Willingham et al., 2018).

Due to the era in which they were collected, the data are not rich in measures of behavioral impairment. However, partner ratings of the pwALS provide relevant measures, including apathy (‘motivation to achieve goals’, ‘motivation to win’, ‘hard worker’); emotional blunting (‘moody’, ‘sharing thoughts and feelings’, ‘emotionally expressive’); mental rigidity/inflexibility (‘immoveable’, ‘flexible’); diminished social interest/personal warmth (‘nice’, ‘loving’); and pwALS reports of regulation of social conduct (expressing emotion by ‘yelling’, ‘physical violence’, and ‘cursing’).

The longitudinal structure of the data also lends itself to identification of critical periods for pwALS and their caregivers. Psychosocial intervention trials had mixed results in terms of effects on QOL (Oh et al., 2024). Targeting critical periods could result in better efficacy. For example, in the SALSPPD, the steepest declines in purpose in life and quality of life for pwALS and spouses occurred shortly after diagnosis and nearing end of life (Garcia et al., 2017), suggesting critical periods for psychological intervention. Likewise, effects of nutritional and respiratory interventions may be optimal at particular points in the disease course. Because this sample represents the entire disease course (with disease duration at enrollment ranging from 1.8 months after diagnosis to 3 years after diagnosis), preliminary identification of critical periods is possible.

Among the myriad future directions one could pursue with these data are hypotheses about specific psychosocial influences on longer-term survival (Chiò et al., 2009; Garcia-Willingham et al., 2018; McDonald et al., 1994; Spataro et al., 2017); determinants of QOL for pwALS and their spouses or caregivers (Averill et al., 2007; Caga et al., 2021; de Wit et al., 2018; Edge et al., 2020; Radakovic et al., 2024; Segerstrom et al., 2019); and the effects of interventions on psychosocial health and QOL (Chang et al., 2011; Oh et al., 2024). The dyadic element of the data allows one to ask questions about dyadic relationships, dyad similarity and dissimilarity, and their effects on psychosocial health, QOL, disease progression, and survival (Reed et al., 2013; Weitkamp et al., 2021). The longitudinal element of the data further allows questions about how pwALS, spouses or caregivers, and dyads change over time (e.g. Garcia et al., 2017). The SALSPPD will provide a rich resource to scientists interested in the natural history of ALS, psychosocial effects on ALS outcomes and vice versa, and psychosocial and disease outcomes of treatments.

Supplementary Material

Supplemental Material

Supplemental Material

ALSPPD_DataDictionary_HPBM.pdf

Acknowledgements

The authors acknowledge the principal investigator of the Seattle ALS Patient Project, Allen D. Hillel, MD, and project manager Rhoda Walter, MS. Suzanne C. Segerstrom: Conceptualization, Data curation, Funding acquisition, Methodology, Validation, Writing – original draft, and Writing – review & editing. Edward J. Kasarskis: Conceptualization, Methodology, and Writing – review & editing.

Open Scholarship

This article has earned the Center for Open Science badge for Open Data. The data are openly accessible at https://data.mendeley.com/datasets/stcztggnnp.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data referenced in this manuscript are openly available in Mendeley Data at 10.17632/stcztggnnp.1
. The data are licensed CC BY NC 3.0: You are free to adapt, copy or redistribute the material, providing you attribute appropriately and do not use the material for commercial purposes. The dataset authors have made every effort to ensure the accuracy of the data, syntax, and accompanying information. However, they make no guarantee about such accuracy. If an inaccuracy is found, please contact alspatientprofiledatabase@gmail.com.
==== Refs
References

Averill, A. J., Kasarskis, E. J., & Segerstrom, S. C. (2007). Psychological health in patients with amyotrophic lateral sclerosis. Amyotrophic Lateral Sclerosis, 8 (4 ), 243–254. 10.1080/17482960701374643 17653923
Averill, A. J., Kasarskis, E. J., & Segerstrom, S. C. (2013). Expressive disclosure to improve well-being in patients with amyotrophic lateral sclerosis: A randomised, controlled trial. Psychology & Health, 28 (6 ), 701–713. 10.1080/08870446.2012.754891 23289543
Benbrika, S., Desgranges, B., Eustache, F., & Viader, F. (2019). Cognitive, emotional and psychological manifestations in amyotrophic lateral sclerosis at baseline and overtime: A review. Frontiers in Neuroscience, 13 , 951. 10.3389/fnins.2019.00951 31551700
Caga, J., Zoing, M. C., Foxe, D., Ramsey, E., D’Mello, M., Mioshi, E., Ahmed, R. M., Kiernan, M. C., & Piguet, O. (2021). Problem-focused coping underlying lower caregiver burden in ALS-FTD: Implications for caregiver intervention. Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration, 22 (5–6 ), 434–441. 10.1080/21678421.2020.1867180 33438449
Chang, S., Gholizadeh, L., Salamonson, Y., DiGiacomo, M., Betihavas, V., & Davidson, P. M. (2011). Health span or life span: The role of patient-reported outcomes in informing health policy. Health Policy, 100 (1 ), 96–104. 10.1016/j.healthpol.2010.07.001 20813420
Chiò, A., Logroscino, G., Hardiman, O., Swingler, R., Mitchell, D., Beghi, E., & Traynor, B. G. (2009). Prognostic factors in ALS: A critical review. Amyotrophic Lateral Sclerosis, 10 (5/6 ), 310–323. 10.3109/17482960802566824 19922118
de Wit, J., Bakker, L. A., van Groenestijn, A. C., van den Berg, L. H., Schröder, C. D., Visser-Meily, J. M., & Beelen, A. (2018). Caregiver burden in amyotrophic lateral sclerosis: A systematic review. Palliative Medicine, 32 (1 ), 231–245. 10.1177/0269216317709965 28671483
Edge, R., Mills, R., Tennant, A., Diggle, P. J., & Young, C. A. (2020). Do pain, anxiety and depression influence quality of life for people with amyotrophic lateral sclerosis/motor neuron disease? A national study reconciling previous conflicting literature. Journal of Neurology, 267 (3 ), 607–615. 10.1007/s00415-019-09615-3 31696295
Garcia-Willingham, N. E. (2018). Neurobehavioral impairments in the amyotrophic lateral sclerosis continuum: A systematic review of prevalence and profile features [Preprint]. 10.31234/osf.io/yj5k8
Garcia-Willingham, N. E., Roach, A. R., Kasarskis, E. J., & Segerstrom, S. C. (2018). Self-regulation and executive functioning as related to survival in motor neuron disease: Preliminary findings. Psychosomatic Medicine, 80 (7 ), 665–672. 10.1097/PSY.0000000000000602 29771729
Garcia, N. E., Morey, J. N., Kasarskis, E. J., & Segerstrom, S. C. (2017). Purpose in life in ALS patient–caregiver dyads: A multilevel longitudinal analysis. Health Psychology, 36 (11 ), 1092–1104. 10.1037/hea0000507 28541074
Magnussen, M. J., & Glass, J. D. (2017). Natural history of amyotrophic lateral sclerosis. In N. Boulis, D. O’Connor, & A. Donsante (Eds.), Molecular and cellular therapies for motor neuron diseases (pp. 25–41). Academic Press.
Masrori, P., & Damme, P. V. (2020). Amyotrophic lateral sclerosis: A clinical review. European Journal of Neurology, 27 (10 ), 1918–1929. 10.1111/ene.14393 32526057
McDonald, E. R., Hillel, A., & Wiedenfeld, S. A. (1996). Evaluation of the psychological status of ventilatory-supported patients with ALS/MND. Palliative Medicine, 10 (1 ), 35–41. 10.1177/026921639601000106 8821186
McDonald, E. R., Wiedenfeld, S. A., Hillel, A., Carpenter, C. L., & Walter, R. A. (1994). Survival in amyotrophic lateral sclerosis: The role of psychological factors. Archives of Neurology, 51 (1 ), 17–23. 10.1001/archneur.1994.00540130027010 8274106
Miller, R. G., Jackson, C. E., Kasarskis, E. J., England, J. D., Forshew, D., Johnston, W., Kalra, S., Katz, J. S., Mitsumoto, H., Rosenfeld, J., Shoesmith, C., Strong, M. J., & Woolley, S. C. (2009a). Practice parameter update: The care of the patient with amyotrophic lateral sclerosis: Drug, nutritional, and respiratory therapies (an evidence-based review): Report of the quality standards subcommittee of the American Academy of Neurology. Neurology, 73 (15 ), 1218–1226. 10.1212/WNL.0b013e3181bc0141 19822872
Miller, R. G., Jackson, C. E., Kasarskis, E. J., England, J. D., Forshew, D., Johnston, W., Kalra, S., Katz, J. S., Mitsumoto, H., Rosenfeld, J., Shoesmith, C., Strong, M. J., & Woolley, S. C. (2009b). Practice parameter update: The care of the patient with amyotrophic lateral sclerosis: Multidisciplinary care, symptom management, and cognitive/behavioral impairment (an evidence-based review): Report of the quality standards subcommittee of the American Academy of Neurology. Neurology, 73 (15 ), 1227–1233. 10.1212/WNL.0b013e3181bc01a4 19822873
Montgomery, G. K., & Erickson, L. M. (1987). Neuropsychological perspectives in amyotrophic lateral sclerosis. Neurologic Clinics, 5 (1 ), 61–81. 10.1016/S0733-8619(18)30935-6 3104753
Oh, J., An, J., Park, K., & Park, Y. (2024). Psychosocial interventions for people with amyotrophic lateral sclerosis and motor neuron disease and their caregivers: A scoping review. BMC Nursing, 23 (1 ), 75. 10.1186/s12912-024-01721-6 38287331
Phukan, J., Pender, N. P., & Hardiman, O. (2007). Cognitive impairment in amyotrophic lateral sclerosis. The Lancet Neurology, 6 (11 ), 994–1003. 10.1016/S1474-4422(07)70265-X 17945153
Plahuta, J. M., McCulloch, B. J., Kasarskis, E. J., Ross, M. A., Walter, R. A., & McDonald, E. R. (2002). Amyotrophic lateral sclerosis and hopelessness: Psychosocial factors. Social Science & Medicine, 55 (12 ), 2131–2140. 10.1016/S0277-9536(01)00356-2 12409126
Raaphorst, J., Beeldman, E., De Visser, M., De Haan, R. J., & Schmand, B. (2012). A systematic review of behavioural changes in motor neuron disease. Amyotrophic Lateral Sclerosis, 13 (6 ), 493–501. 10.3109/17482968.2012.656652 22424127
Radakovic, R., Radakovic, C., Abrahams, S., Simmons, Z., & Carroll, A. (2024). Quality of life, cognitive and behavioural impairment in people with motor neuron disease: A systematic review. Quality of Life Research, 33 (6 ), 1469–1480. 10.1007/s11136-024-03611-5 38345764
Reed, R. G., Butler, E. A., & Kenny, D. A. (2013). Dyadic models for the study of health. Social and Personality Psychology Compass, 7 (4 ), 228–245. 10.1111/spc3.12022
Roach, A. R., Averill, A. J., Segerstrom, S. C., & Kasarskis, E. J. (2009). The dynamics of quality of life in ALS patients and caregivers. Annals of Behavioral Medicine, 37 (2 ), 197–206. 10.1007/s12160-009-9092-9 19350337
Segerstrom, S. C., Kasarskis, E. J., Fardo, D. W., & Westgate, P. M. (2019). Socioemotional selectivity and psychological health in amyotrophic lateral sclerosis patients and caregivers: A longitudinal, dyadic analysis. Psychology & Health, 34 (10 ), 1179–1195. 10.1080/08870446.2019.1587441 30907138
Spataro, R., Volanti, P., Coco, D. L., & Bella, V. L. (2017). Marital status is a prognostic factor in amyotrophic lateral sclerosis. Acta Neurologica Scandinavica, 136 (6 ), 624–630. 10.1111/ane.12771 28470818
Strong, M. J., Abrahams, S., Goldstein, L. H., Woolley, S., Mclaughlin, P., Snowden, J., Mioshi, E., Roberts-South, A., Benatar, M., HortobáGyi, T., Rosenfeld, J., Silani, V., Ince, P. G., & Turner, M. R. (2017). Amyotrophic lateral sclerosis – frontotemporal spectrum disorder (ALS-FTSD): Revised diagnostic criteria. Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration, 18 (3–4 ), 153–174. 10.1080/21678421.2016.1267768 28054827
van der Loo, M. P. J., & de Jonge, E. (2021). Data validation infrastructure for R. Journal of Statistical Software, 97 , 1–31.
Weitkamp, K., Feger, F., Landolt, S. A., Roth, M., & Bodenmann, G. (2021). Dyadic coping in couples facing chronic physical illness: A systematic review. Frontiers in Psychology, 12 , Article 722740. 10.3389/fpsyg.2021.722740
Westeneng, H. J., Debray, T. P. A., Visser, A. E., van Eijk, R. P. A., Rooney, J. P. K., Calvo, A., Martin, S., McDermott, C. J., Thompson, A. G., Pinto, S., Kobeleva, X., Rosenbohm, A., Stubendorff, B., Sommer, H., Middelkoop, B. M., Dekker, A. M., van Vugt, J. J. F. A., van Rheenen, W., Vajda, A., … van den Berg, L. H. (2018). Prognosis for patients with amyotrophic lateral sclerosis: Development and validation of a personalised prediction model. The Lancet Neurology, 17 (5 ), 423–433. 10.1016/S1474-4422(18)30089-9 29598923
