DOI: 10.5061/dryad.5mkkwh7jp
title: Data from: The characteristics of patients’ medical care, living will, and signs of death by age and the place of death: A cross-sectional study using a questionnaire survey targeting physicians with expertise in end-of-life care

description: This dataset contains the complete, de-identified, participant-level data
 (n = 440) used for the analyses in the associated article. Records were
 obtained via a structured questionnaire survey and include age at death
 (years), sex, place of death, medical treatments received near the end of
 life, presence of a living will, and end-of-life signs observed by
 respondents. Data are provided as a tidy CSV (one row per patient) with an
 accompanying data dictionary and README describing variable definitions.
 The dataset enables replication of the published analyses and supports
 secondary reuse such as prevalence estimation, development of prognostic
 models for dying trajectories, and cross-setting comparisons. Direct
 identifiers have been removed, and quasi-identifiers have been generalized
 to reduce re-identification risk; only the minimally necessary data are
 included. Ethical considerations and consent procedures are described in
 the associated article; the Dryad deposit contains de-identified data
 suitable for public sharing.
description: # Data from: The characteristics of patients’ medical care, living will,
 and signs of death by age and the place of death: A cross-sectional study
 using a questionnaire survey targeting physicians with expertise in
 end-of-life care Dataset DOI:
 [10.5061/dryad.5mkkwh7jp](https://doi.org/10.5061/dryad.5mkkwh7jp) ##
 Description of the data and file structure These data were collected to
 characterize how demographic factors, place of death, and medical care
 relate to observed signs of dying. We conducted a cross-sectional
 questionnaire survey of physicians who had recently provided end-of-life
 care, asking each respondent to report on one decedent they had cared for
 within the past five years. The instrument captured age at death, sex,
 care setting/place of death, treatments and supportive or palliative
 measures provided, presence of a living will, and specific end-of-life
 signs observed in the final days or hours. Responses were entered via a
 secure web form and compiled into a tidy, participant-level dataset
 suitable for replication and secondary analyses. To reduce
 re-identification risk while preserving analytical value, the public
 dataset has been de-identified as follows: direct/pseudo-identifiers were
 removed, age was grouped into ranges, and selected categorical variables
 were numerically encoded. In addition, timing variables were collapsed
 into broader ordered categories and stored as ordinal codes. Consistent
 with de-identification practice, the code keys for selected sensitive
 variables are not provided in the public README or dataset documentation.
 ## Files in this deposit • Data.csv — De-identified participant-level
 dataset (UTF-8 CSV). The public version contains de-identification-safe
 encodings (e.g., grouped age ranges and numeric codes for selected
 categorical variables). Missing values are represented as empty cells. •
 data_dictionary.csv — Machine-readable data dictionary aligned with
 Data.csv (variable names, labels, data types, and notes). For selected
 sensitive variables, code meanings are intentionally not disclosed in the
 public documentation to reduce re-identification risk. • questionnaire.pdf
 — Full text of the self-developed questionnaire used in the study (item
 wording and response options; English translation if applicable). • code.R
 — Annotated R script that reads Data.csv and reproduces the main
 analyses/tables described in the manuscript (e.g., logistic regression,
 multiplicity control via FDR and Bonferroni). Uses base R functions; no
 proprietary software is required. ## Variables (Data.csv) Record
 identifier\ • ID is not included in the public dataset (removed during
 de-identification). Demographic and care-related variables\ • age: Age at
 death, grouped into ranges (e.g., 10-year bands, with a top-coded upper
 category). Type: categorical/ordinal string.\ • sex: Biological sex.
 Public file stores de-identified numeric code(s). Type: categorical
 (integer code).\ • place: Place of death (care setting). Public file
 stores de-identified numeric code(s). Type: categorical (integer code).\ •
 hot: Home oxygen therapy (HOT) before death. Public file stores
 de-identified numeric code(s). Type: binary indicator (integer code).\ •
 hot_when: If HOT was provided, time from initiation to death. Public file
 stores broader grouped timing categories as ordinal code(s). Type: ordinal
 (integer code).\ • pain: Use of pain management. Public file stores
 de-identified numeric code(s). Type: binary indicator (integer code).\ •
 pain_when: If pain management was provided, time from initiation to death.
 Public file stores broader grouped timing categories as ordinal code(s).
 Type: ordinal (integer code).\ • palli: Receipt of palliative care. Public
 file stores de-identified numeric code(s). Type: binary indicator (integer
 code).\ • palli_when: If palliative care was provided, time from
 initiation to death. Public file stores broader grouped timing categories
 as ordinal code(s). Type: ordinal (integer code).\ • will: Presence of a
 living will. Public file stores de-identified numeric code(s). Type:
 binary indicator (integer code). End-of-life signs (s1–s18)\ All
 end-of-life sign variables are binary indicators and are stored in the
 public file as de-identified numeric code(s) rather than human-readable
 labels. • s1: Lower level of consciousness and uttering incoherent
 statements.\ • s2: Spending extended periods sleeping.\ • s3: Experiencing
 difficulty consuming meals.\ • s4: Struggling with drinking, with
 increased risk of aspiration.\ • s5: Displaying agitation and heightened
 limb movement.\ • s6: Decreased verbal communication, with diminished
 auditory clarity.\ • s7: Appearing dazed and devoid of expression.\ • s8:
 Experiencing urinary and fecal incontinence, with inability to reach the
 bathroom.\ • s9: Diminished responsiveness to calls.\ • s10: Impaired
 speech clarity.\ • s11: Exhibiting distress due to shallow breathing.\ •
 s12: Difficulty in detecting pulse or experiencing a drop in blood
 pressure.\ • s13: Limbs becoming cold.\ • s14: Development of cyanosis on
 the face or extremities.\ • s15: Sensation of warmth and reluctance to
 wear clothing.\ • s16: Experiencing agitation or delirium.\ • s17: Slight
 limb movements despite being bedridden.\ • s18: Tremors or shivering of
 coverings draped over the body. ## Missing data Missing values are
 represented as empty cells (no “NA” literal). For timing variables
 (hot_when, pain_when, palli_when), empty cells occur in two situations:
 (i) the corresponding care was not provided (not applicable), or (ii) care
 was provided but the timing is unknown. The former can be inferred from
 the corresponding parent indicator variable. Notes on de-identification
 and interpretation The public dataset is designed to preserve analytical
 utility while reducing re-identification risk. Accordingly, some original
 response detail (e.g., exact age in years and fine-grained timing
 categories) has been coarsened in the public release. Numeric encodings
 are used for selected categorical variables, and the corresponding code
 keys are intentionally not disclosed in the public files. ##
 **Code/software** **Software needed to view the data** The dataset is
 supplied as UTF-8–encoded CSV files that can be opened with any
 spreadsheet or text editor, or analyzed with the free, open-source R
 environment. **Analysis software** All statistical analyses reported in
 the associated article were performed using R version 3.3.3 (R Foundation
 for Statistical Computing, Vienna, Austria). Two-sided P &lt; 0.05 was
 considered statistically significant. Only base R functionality (e.g.,
 stats, utils) was used; no proprietary software is required. **Code
 availability** This deposit includes code.R, which reproduces the main
 analyses and tables from the manuscript using Data.csv. Researchers may
 also re-implement the models described in the Methods in R 3.3.3 or later,
 using the variable definitions provided in data_dictionary.csv and
 questionnaire.pdf. **Typical workflow (for reuse)** 1. Open Data.csv. 2.
 Consult data_dictionary.csv and questionnaire.pdf for variable definitions
 and item mapping. 3. Run code.R to reproduce the main analyses and output
 tables/figures; alternatively, re-implement the models (e.g., logistic
 regression via glm(family = binomial)). 4. Export tables/figures as
 needed. ## Human subjects data This dataset contains de-identified human
 subjects data derived from a questionnaire survey of 440 decedents’ cases
 reported by physicians. We obtained explicit consent from participants
 (via the Japan Society for Dying with Dignity, JSDD) to deposit the
 de-identified dataset in a public repository upon publication. All direct
 identifiers were removed (e.g., names, addresses, contact details, medical
 record numbers), and free-text fields were deleted.