🛌 slumbR

Sleep Diaries helper package for R — import, compute, and score.

[!WARNING] slumbR is in early development and has not been formally tested. The API may change without notice, scoring algorithms have not yet been validated against reference implementations, and the package has not undergone peer review. Use with caution and verify outputs independently before using in any research context.

📖 What is slumbR?

slumbR is the official R companion to the Sleep Diaries app. When a study ends, participants export their data as a JSON file. slumbR reads those files — one per participant or a whole directory at once — and hands you a clean, analysis-ready data frame in seconds.

It computes standard sleep variables (TIB, TST, SE, SOL, WASO) directly from the raw diary answers, re-scores all eight validated questionnaires bundled in the app (ESS, ISI, DBAS-16, MEQ, PSQI, RU-SATED, STOP-BANG, MCTQ), and assembles both long and wide study-level frames ready for downstream statistics or visualisation.

✨ Features

📥 read_export() — parse a single participant's JSON export into a structured slumbr_export object
📂 read_study() — batch-read a whole directory of exports into a slumbr_study with long, wide, and scores frames
📐 compute_sleep_vars() — derive TIB, TST, SE, and clinical flags from raw morning diary answers
🔀 diary_wide() — pivot to one row per participant × night with m_ / e_ prefixed columns
📊 study_summary() — participant-level summary table (mean TST, SE, SOL, quality, etc.)
🧮 score_questionnaire() — re-score any of the 8 instruments from raw answers; algorithms match the app exactly
✅ score_all_questionnaires() — re-score an entire questionnaire data frame in one call

🗂️ Project Structure

slumbR/
├── R/
│   ├── slumbR-package.R      # package-level docs and imports
│   ├── import.R              # read_export(), read_study(), compute_sleep_vars()
│   ├── tidy.R                # diary_long(), diary_wide(), study_summary()
│   └── questionnaires.R      # score_questionnaire(), score_all_questionnaires()
├── inst/extdata/             # bundled example exports (3 simulated participants)
├── man/figures/
│   └── logo.svg              # hex sticker
├── man/                      # roxygen2-generated documentation
├── vignettes/
│   └── getting-started.Rmd  # end-to-end worked example
├── tests/testthat/
│   ├── test-questionnaires.R
│   └── test-import.R
├── .github/workflows/
│   └── R-CMD-check.yaml
├── DESCRIPTION
├── LICENSE
└── slumbR.Rproj

🚀 Getting Started

Prerequisites

R ≥ 4.1
The following packages (installed automatically): jsonlite, dplyr, lubridate, purrr, rlang, cli

Installation

# Install from GitHub (requires remotes)
# remotes::install_github("circadia-bio/slumbR")
install.packages("slumbR", repos = c('https://circadia-bio.r-universe.dev', 'https://cloud.r-project.org'))

Basic usage

library(slumbR)

# ── Single participant ──────────────────────────────────────────────────────
p <- read_export("exports/P001.json")

p$diary          # long-format: one row per diary entry
p$questionnaires # questionnaire results with raw answers

# ── Whole study ─────────────────────────────────────────────────────────────
study <- read_study("exports/")

study$diary   # long-format, all participants combined
study$wide    # wide-format: one row per participant × night
study$scores  # questionnaire scores, one row per participant × instrument

# ── Participant-level summary ───────────────────────────────────────────────
study_summary(study)
#>   participant_id n_morning n_evening n_nights mean_tst_h mean_se_pct ...

# ── Re-score a questionnaire ────────────────────────────────────────────────
score_questionnaire("ess", answers = list(
  ess1 = 2, ess2 = 1, ess3 = 0, ess4 = 3,
  ess5 = 1, ess6 = 0, ess7 = 2, ess8 = 1
))
#> $score
#> [1] 10
#> $label
#> [1] "Excessive"

Try it with the bundled example data

[!NOTE] The bundled dataset is entirely simulated. The three participants (Sarah Chen, James Okonkwo, Priya Mehta) and all their diary entries and questionnaire responses are artificially generated for demonstration purposes. They do not represent real people or real study data.

extdata <- system.file("extdata", package = "slumbR")
study   <- read_study(extdata)
study_summary(study)

See vignette("getting-started", package = "slumbR") for a full worked example.

🛏️ Computed sleep variables

Morning diary entries are automatically enriched with the following derived variables when using read_export() or read_study():

Variable	Definition	Reference threshold
`tib_min`	Time in bed (rise − bed), minutes	—
`tst_min`	Total sleep time (TIB − SOL − WASO), minutes	≥ 420 min (7 h)
`se_pct`	Sleep efficiency (TST / TIB × 100), %	≥ 85%
`sol_flag`	`TRUE` if SOL > 30 min	Ohayon et al. (2017)
`se_flag`	`TRUE` if SE < 85%	Morin (1993)
`waso_flag`	`TRUE` if WASO > 30 min	Ohayon et al. (2017)
`tst_flag`	`TRUE` if TST < 7 h	Hirshkowitz et al. (2015)

🧮 Supported questionnaires

ID	Full name	Score range	Reference
`ess`	Epworth Sleepiness Scale	0–24	Johns (1991)
`isi`	Insomnia Severity Index	0–28	Morin et al. (2011)
`dbas16`	Dysfunctional Beliefs and Attitudes about Sleep	0–10 (mean)	Morin et al. (2007)
`meq`	Morningness–Eveningness Questionnaire	16–86	Horne & Östberg (1976)
`psqi`	Pittsburgh Sleep Quality Index	0–21	Buysse et al. (1989)
`rusated`	RU-SATED Sleep Health Scale	0–24	Buysse (2014)
`stopbang`	STOP-BANG Questionnaire	0–8	Chung et al. (2016)
`mctq`	Munich Chronotype Questionnaire	MSFsc + SJL	Roenneberg et al. (2003)

Note: Some instruments require institutional permission for research use. Please verify licensing before use. The app's Settings → Questionnaire Credits screen lists the relevant permissions for each instrument.

📦 Dependencies

Package	Version	Purpose
jsonlite	≥ 1.8.0	JSON parsing
dplyr	≥ 1.1.0	Data manipulation
lubridate	≥ 1.9.0	Date/time handling
purrr	≥ 1.0.0	Functional iteration
rlang	≥ 1.1.0	Error/warning infrastructure
cli	≥ 3.6.0	Progress and messages

👥 Authors

Role	Name	Affiliation
Author, maintainer	Lucas França	Northumbria University, Circadia Lab
Author	Mario Leocadio-Miguel	Northumbria University, Circadia Lab

🤝 Related Tools

🌙 SleepDiaries — the cross-platform Sleep Diaries app that generates the exports slumbR reads
🔬 circadia-bio — the Circadia Lab GitHub organisation

📄 Licence

Released under the MIT License.